ABOUT MONTHLY AND QUARTERLY DATA - Euromonitor … · ABOUT MONTHLY AND QUARTERLY DATA Click on table of contents to be taken to your section of interest. CONTENTS About Monthly and

ABOUT MONTHLY AND QUARTERLY DATA

Click on table of contents to be taken to your section of interest.

CONTENTS

About Monthly and Quarterly Data ............................................................................................... 8 1. Frequently Asked Questions ..................................................................................................... 8 How often do you update the data? .............................................................................................. 8 Why is data often revised? ........................................................................................................... 9 Why are some datasets only available quarterly? ........................................................................ 9 What does seasonally adjusted mean? ........................................................................................ 9 Should I choose seasonally adjusted or non-seasonally adjusted? .............................................. 9 Not all of the data I select is displayed. Why? .............................................................................. 9 How do you forecast the data? ..................................................................................................... 9

2. Methodology ........................................................................................................................... 10 3. Definitions & Sources ............................................................................................................. 11 Agricultural Raw Materials Index ................................................................................................ 11 Almond Price .............................................................................................................................. 11 Aluminium Price ......................................................................................................................... 11 Apple Price ................................................................................................................................. 11 Banana Price .............................................................................................................................. 11 Bank Nonperforming Loans to Total Gross Loans ...................................................................... 12 Barley Price ................................................................................................................................ 12 Beef Price ................................................................................................................................... 12 Beverages Index ........................................................................................................................ 12 Business Confidence Index ........................................................................................................ 12 Capital to Assets ........................................................................................................................ 13 Cardamom Price ........................................................................................................................ 13 Central Bank Policy Rate............................................................................................................ 13 Chicken Price ............................................................................................................................. 13 Coal Price ................................................................................................................................... 14 Cocoa Price ................................................................................................................................ 14 Coconut Oil Price ....................................................................................................................... 14 Coffee Price ................................................................................................................................ 14 Commodity Fuel (Energy) Index ................................................................................................. 14 Consumer Confidence Index ...................................................................................................... 15 Copper Price .............................................................................................................................. 15 Coriander Price .......................................................................................................................... 15 Corn Price .................................................................................................................................. 15 Cotton Price ................................................................................................................................ 15 Crude Oil (Europe Brent) Spot Price .......................................................................................... 16 Crude Oil (WTI Cushing) Spot Price ........................................................................................... 16

Cumin Price ................................................................................................................................ 16 Current Account Balance............................................................................................................ 16 Customer Deposits to Total Non-Interbank Loans ...................................................................... 17 Employed/Unemployed/Economically Active Population ............................................................ 17 Exchange Rates Against US Dollar ............................................................................................ 17 Export Price Index ...................................................................................................................... 18 Exports ....................................................................................................................................... 18 Exports of Goods and Services .................................................................................................. 18 Food Index ................................................................................................................................. 18 Foreign Currency Denominated Loans to Total Loans ............................................................... 18 Foreign Exchange Reserves ...................................................................................................... 19 GDP ........................................................................................................................................... 19 Gold Price ................................................................................................................................... 19 Government Expenditure............................................................................................................ 19 Government Final Consumption Expenditure ............................................................................. 20 Government Net Lending/Borrowing .......................................................................................... 20 Government Revenue ................................................................................................................ 20 Grapefruit Price .......................................................................................................................... 20 Gross Fixed Capital Formation ................................................................................................... 20 Gross Loans to Nonfinancial Corporations ................................................................................. 21 Hard Logs Price .......................................................................................................................... 21 Hard Sawnwood Price ................................................................................................................ 21 House Price Index ...................................................................................................................... 21 House Price to Income Ratio ...................................................................................................... 22 House Price to Rent Ratio .......................................................................................................... 22 House Rent Price Index.............................................................................................................. 22 Household Debt .......................................................................................................................... 22 Housing Completions ................................................................................................................. 22 Housing Permits ......................................................................................................................... 23 Import Price Index ...................................................................................................................... 23 Imports ....................................................................................................................................... 23 Imports of Goods and Services .................................................................................................. 23 Increases in Stocks .................................................................................................................... 24 Index of Consumer Prices .......................................................................................................... 24 Industrial Production Index ......................................................................................................... 24 Inflation ....................................................................................................................................... 25 International Reserves................................................................................................................ 25 Iron Ore Price ............................................................................................................................. 25 Lamb Price ................................................................................................................................. 25 Lead Price .................................................................................................................................. 25 Lemon Price ............................................................................................................................... 26 Lime Price .................................................................................................................................. 26 Long-Term Interest Rates........................................................................................................... 26 Market Capitalisation .................................................................................................................. 26 Mean Maximum Temperature .................................................................................................... 26 Mean Minimum Temperature ..................................................................................................... 27 Mean Temperature ..................................................................................................................... 27

Metals Index ............................................................................................................................... 27 Milk Price, European Union ........................................................................................................ 27 Milk Price, New Zealand ............................................................................................................. 27 Milk Price, USA .......................................................................................................................... 28 Money Supply ............................................................................................................................. 28 Natural Gas Price, Europe .......................................................................................................... 28 Natural Gas Price, Japan ........................................................................................................... 28 Natural Gas Price, USA .............................................................................................................. 28 Nickel Price ................................................................................................................................ 29 Non-Residential Building Completions ....................................................................................... 29 Non-Residential Building Permits ............................................................................................... 29 Number of Job Vacancies .......................................................................................................... 29 Orange Juice Price ..................................................................................................................... 30 Orange Price .............................................................................................................................. 30 Overnight Interbank Rate ........................................................................................................... 30 Palm Oil Price ............................................................................................................................. 30 Peanut Price ............................................................................................................................... 30 Pepper Price ............................................................................................................................... 31 Pork Price ................................................................................................................................... 31 Private Final Consumption Expenditure ..................................................................................... 31 Producer Price Index, Manufacturing ......................................................................................... 31 Pulp Price ................................................................................................................................... 31 Real GDP Growth ....................................................................................................................... 32 Red Chili Price ............................................................................................................................ 32 Regulatory Tier 1 Capital to Risk-Weighted Assets .................................................................... 32 Residential Real Estate Loans to Total Loans ............................................................................ 32 Retail Sales Index ...................................................................................................................... 32 Rice Price ................................................................................................................................... 33 Rubber Price .............................................................................................................................. 33 Salmon Price .............................................................................................................................. 33 Silver Price ................................................................................................................................. 33 Soft Logs Price ........................................................................................................................... 33 Soft Sawnwood Price ................................................................................................................. 34 Soybeans Price .......................................................................................................................... 34 Steel Price, China ....................................................................................................................... 34 Steel Price, USA ......................................................................................................................... 34 Steel Price, Western Europe ...................................................................................................... 34 Stock Market Index ..................................................................................................................... 35 Strawberry Price ......................................................................................................................... 35 Sugar Price, European Union ..................................................................................................... 35 Sugar Price, USA ....................................................................................................................... 35 Sugar Price, World ..................................................................................................................... 35 Tea Price .................................................................................................................................... 36 Tin Price ..................................................................................................................................... 36 Tobacco Price ............................................................................................................................ 36 Total Gross Loans ...................................................................................................................... 36 Total Precipitation ....................................................................................................................... 36

Trade Balance ............................................................................................................................ 37 Turmeric Price ............................................................................................................................ 37 Unemployment Rate ................................................................................................................... 37 Unit Labour Cost Index ............................................................................................................... 37 Usual/Actual Weekly Working Hours .......................................................................................... 38 Wage per Hour ........................................................................................................................... 38 Wheat Price ................................................................................................................................ 38 Wool Price .................................................................................................................................. 38 Zinc Price ................................................................................................................................... 39 Seasonal Adjustment ................................................................................................................. 39 Point Increase ............................................................................................................................ 39 Growth Rates ............................................................................................................................. 39

4. Forecasting Methodology ....................................................................................................... 40 I. Euromonitor Macro Model ....................................................................................................... 40 II. Vector Error Correction Model ................................................................................................ 41 III. ARIMA Models ...................................................................................................................... 41

Data pre-processing ............................................................................................................... 41 Model selection ....................................................................................................................... 42 Forecast validation.................................................................................................................. 42 Data post-processing .............................................................................................................. 43

IV. Commodity Forecasts ........................................................................................................... 43

Some specific economic ideas applied in the model............................................................... 43 Basic modelling framework ..................................................................................................... 43 Outcomes of model solution ................................................................................................... 44

5. Business Confidence Indices: Methodology & Sources .......................................................... 45 Australia ..................................................................................................................................... 45 Austria ........................................................................................................................................ 45 Belgium ...................................................................................................................................... 46 Brazil .......................................................................................................................................... 47 Bulgaria ...................................................................................................................................... 48 Canada ....................................................................................................................................... 49 Chile ........................................................................................................................................... 49 China .......................................................................................................................................... 50 Colombia .................................................................................................................................... 51 Costa Rica .................................................................................................................................. 51 Croatia ........................................................................................................................................ 52 Czech Republic .......................................................................................................................... 53 Denmark ..................................................................................................................................... 53 Ecuador ...................................................................................................................................... 54 Estonia ....................................................................................................................................... 55 Finland........................................................................................................................................ 56 France ........................................................................................................................................ 57 Georgia....................................................................................................................................... 58 Germany ..................................................................................................................................... 58 Greece........................................................................................................................................ 59 Hong Kong, China ...................................................................................................................... 60

Hungary ...................................................................................................................................... 61 India ........................................................................................................................................... 62 Indonesia .................................................................................................................................... 63 Ireland ........................................................................................................................................ 63 Israel........................................................................................................................................... 64 Italy ............................................................................................................................................. 64 Japan.......................................................................................................................................... 65 Latvia .......................................................................................................................................... 65 Lithuania ..................................................................................................................................... 66 Macedonia .................................................................................................................................. 68 Malaysia ..................................................................................................................................... 69 Mexico ........................................................................................................................................ 69 Netherlands ................................................................................................................................ 70 New Zealand .............................................................................................................................. 70 Nigeria ........................................................................................................................................ 71 Norway ....................................................................................................................................... 72 Peru ............................................................................................................................................ 72 Philippines .................................................................................................................................. 73 Poland ........................................................................................................................................ 73 Portugal ...................................................................................................................................... 74 Qatar .......................................................................................................................................... 75 Romania ..................................................................................................................................... 76 Russia ........................................................................................................................................ 77 Saudi Arabia ............................................................................................................................... 78 Singapore ................................................................................................................................... 78 Slovakia ...................................................................................................................................... 79 Slovenia...................................................................................................................................... 80 South Africa ................................................................................................................................ 81 South Korea ............................................................................................................................... 81 Spain .......................................................................................................................................... 82 Sweden ...................................................................................................................................... 83 Switzerland ................................................................................................................................. 83 Thailand...................................................................................................................................... 84 Turkey ........................................................................................................................................ 85 United Arab Emirates ................................................................................................................. 86 United Kingdom .......................................................................................................................... 86 USA ............................................................................................................................................ 87

6. Consumer Confidence Indices: Methodology & Sources ........................................................ 89 Algeria ........................................................................................................................................ 89 Argentina .................................................................................................................................... 89 Australia ..................................................................................................................................... 90 Austria ........................................................................................................................................ 91 Belgium ...................................................................................................................................... 91 Brazil .......................................................................................................................................... 92 Bulgaria ...................................................................................................................................... 93 Canada ....................................................................................................................................... 94 Chile ........................................................................................................................................... 94

China .......................................................................................................................................... 95 Colombia .................................................................................................................................... 96 Costa Rica .................................................................................................................................. 97 Croatia ........................................................................................................................................ 97 Czech Republic .......................................................................................................................... 98 Denmark ..................................................................................................................................... 99 Dominican Republic ................................................................................................................... 99 Ecuador .................................................................................................................................... 100 Egypt ........................................................................................................................................ 101 Estonia ..................................................................................................................................... 101 Finland...................................................................................................................................... 102 France ...................................................................................................................................... 103 Georgia..................................................................................................................................... 104 Germany ................................................................................................................................... 105 Greece...................................................................................................................................... 105 Hungary .................................................................................................................................... 106 Indonesia .................................................................................................................................. 107 Ireland ...................................................................................................................................... 108 Israel......................................................................................................................................... 109 Italy ........................................................................................................................................... 109 Japan........................................................................................................................................ 110 Jordan ...................................................................................................................................... 110 Kuwait....................................................................................................................................... 111 Latvia ........................................................................................................................................ 112 Lithuania ................................................................................................................................... 112 Malaysia ................................................................................................................................... 113 Mexico ...................................................................................................................................... 114 Netherlands .............................................................................................................................. 114 New Zealand ............................................................................................................................ 115 Nigeria ...................................................................................................................................... 116 Norway ..................................................................................................................................... 116 Peru .......................................................................................................................................... 117 Philippines ................................................................................................................................ 117 Poland ...................................................................................................................................... 118 Portugal .................................................................................................................................... 119 Qatar ........................................................................................................................................ 119 Romania ................................................................................................................................... 120 Russia ...................................................................................................................................... 121 Saudi Arabia ............................................................................................................................. 122 Slovakia .................................................................................................................................... 122 Slovenia.................................................................................................................................... 123 South Africa .............................................................................................................................. 124 South Korea ............................................................................................................................. 125 Spain ........................................................................................................................................ 125 Sweden .................................................................................................................................... 126 Switzerland ............................................................................................................................... 127 Taiwan ...................................................................................................................................... 127

Thailand.................................................................................................................................... 128 Tunisia ...................................................................................................................................... 129 Turkey ...................................................................................................................................... 130 Ukraine ..................................................................................................................................... 130 United Arab Emirates ............................................................................................................... 131 United Kingdom ........................................................................................................................ 132 Uruguay .................................................................................................................................... 132 USA .......................................................................................................................................... 133 Vietnam .................................................................................................................................... 134

7. House Price Indices: Methodology & Sources ...................................................................... 136 Argentina .................................................................................................................................. 136 Australia ................................................................................................................................... 136 Austria ...................................................................................................................................... 137 Belarus ..................................................................................................................................... 137 Belgium .................................................................................................................................... 138 Brazil ........................................................................................................................................ 138 Bulgaria .................................................................................................................................... 139 Canada ..................................................................................................................................... 139 Chile ......................................................................................................................................... 140 China ........................................................................................................................................ 141 Colombia .................................................................................................................................. 141 Croatia ...................................................................................................................................... 142 Czech Republic ........................................................................................................................ 142 Denmark ................................................................................................................................... 142 Estonia ..................................................................................................................................... 143 Finland...................................................................................................................................... 143 France ...................................................................................................................................... 144 Georgia..................................................................................................................................... 145 Germany ................................................................................................................................... 145 Greece...................................................................................................................................... 146 Hong Kong, China .................................................................................................................... 147 Hungary .................................................................................................................................... 147 India ......................................................................................................................................... 148 Indonesia .................................................................................................................................. 148 Ireland ...................................................................................................................................... 149 Israel......................................................................................................................................... 150 Italy ........................................................................................................................................... 150 Japan........................................................................................................................................ 151 Kazakhstan ............................................................................................................................... 151 Latvia ........................................................................................................................................ 152 Lithuania ................................................................................................................................... 152 Macedonia ................................................................................................................................ 153 Malaysia ................................................................................................................................... 154 Mexico ...................................................................................................................................... 154 Netherlands .............................................................................................................................. 155 New Zealand ............................................................................................................................ 155 Norway ..................................................................................................................................... 156

Peru .......................................................................................................................................... 156 Philippines ................................................................................................................................ 157 Poland ...................................................................................................................................... 157 Portugal .................................................................................................................................... 158 Qatar ........................................................................................................................................ 158 Romania ................................................................................................................................... 159 Russia ...................................................................................................................................... 159 Serbia ....................................................................................................................................... 160 Singapore ................................................................................................................................. 160 Slovakia .................................................................................................................................... 161 Slovenia.................................................................................................................................... 162 South Africa .............................................................................................................................. 163 South Korea ............................................................................................................................. 163 Spain ........................................................................................................................................ 163 Sweden .................................................................................................................................... 164 Switzerland ............................................................................................................................... 165 Taiwan ...................................................................................................................................... 165 Thailand.................................................................................................................................... 165 Turkey ...................................................................................................................................... 166 Ukraine ..................................................................................................................................... 166 United Arab Emirates ............................................................................................................... 167 United Kingdom ........................................................................................................................ 167 USA .......................................................................................................................................... 168

8. Stock Market Indices ............................................................................................................ 170

ABOUT MONTHLY AND QUARTERLY DATA

Euromonitor International’s high frequency database incorporates a wide range of short-term

economic indicators across 80 countries including short-term forecasts, enabling analysis of

economic trends and developments in real time.

1. FREQUENTLY ASKED QUESTIONS

HOW OFTEN DO YOU UPDATE THE DATA? Our data is updated two times per month, with our analysts closely monitoring the release

schedules of statistical offices and central banks to ensure that our database always contains the

latest available data. The forecasts are also updated twice a month by our expert macroeconomic

modelling team.

WHY IS DATA OFTEN REVISED? Statistical offices frequently revise their data as more information becomes available or as they

find better methods to capture trends. We constantly review the entire time series of data to ensure

that we capture these changes to historical data.

WHY ARE SOME DATASETS ONLY AVAILABLE QUARTERLY? GDP, Real GDP Growth, Government Final Consumption Expenditure, Private Final Consumption

Expenditure, Exports of Goods and Services, Imports of Goods and Services, Gross Fixed Capital

Formation, Increases in Stocks are all only available quarterly. These datasets are major

components of National Accounts data. The international methodology, which most economies

follow, only requires quarterly data. In addition, some indicators for which monthly data availability is

low are available quarterly.

WHAT DOES SEASONALLY ADJUSTED MEAN? Data is often seasonally adjusted to remove the effects of seasonal calendar influences impacting

on a series. Seasonal effects usually reflect the influence of the seasons themselves either directly

(e.g. there is less construction in winter) or through social conventions (e.g. moving holidays such as

Easter and Eid have an impact on working days and Christmas has a huge impact on retail sales).

For the datasets that include countries with missing seasonally adjusted data, we model the missing

series using STL/X-12 seasonal decomposition procedures. To correctly detect and remove the

seasonal component, the decomposition procedures are not implemented if the time series is

shorter than 3 years.

SHOULD I CHOOSE SEASONALLY ADJUSTED OR NON-SEASONALLY ADJUSTED?

Seasonally adjusted data removes “noise” from the time series allowing for a more thorough

understanding of trends. Many analysts prefer seasonally adjusted data because they want to see

those characteristics that seasonal movements tend to mask, especially changes in the direction of

the series.

NOT ALL OF THE DATA I SELECT IS DISPLAYED. WHY? Data is not always available for all countries and all indicators; nor are they always available in

both seasonally adjusted and non-seasonally adjusted form. If the data you choose is unavailable,

change the frequency and/or the seasonal adjustment and try again.

HOW DO YOU FORECAST THE DATA? To arrive at short-term forecasts for our set of monthly and quarterly data, we use econometric

models developed by our expert macroeconomic modelling team as well as judgemental input.

Country-specific indicators are forecasted using Euromonitor Macro Model, Vector Error Correction

Model (VECM) and ARIMA methods, while commodities are considered a separate group and thus

are forecasted using an econometric model reflecting both common and specific factors that affect

commodity markets. The model based forecasts are then revised by imposing certain restrictions

that ensure internal consistency of the forecasts and supplementing them with additional economic

information from a network of in-country experts. For more detailed information see section 4

“Forecasting methodology”.

2. METHODOLOGY

Euromonitor International’s team of economic analysts research part-year economic data from a

range of national and international sources. Our data is updated two times per month, with our

analysts closely monitoring the release schedules of statistical offices and central banks to ensure

that our database always contains the latest available data.

The time series runs from January 2000 (where available) until the latest month.

Statistical offices frequently revise their data backwards – we capture these changes and revise

the entire time series as necessary.

All indices (with the exception of consumer and business confidence) have been re-based to 2010

= 100 to facilitate cross-country comparisons.

Wherever possible, both seasonally adjusted and non-seasonally adjusted data has been

researched. For the datasets that include countries with missing seasonally adjusted data, we model

the missing series using STL/X-12 seasonal decomposition procedures. To correctly detect and

remove the seasonal component, the decomposition procedures are not implemented if the time

series is shorter than 3 years.

Business confidence, consumer confidence and house price data are not strictly cross country

comparable due to varying methodology across countries. For cross-country comparison of business

confidence and consumer confidence, we calculate a standardised index (z-score) indicating the

number of standard deviations each observation is above or below the long-term mean. The further

the index is from zero the better/worse the confidence is compared to the long-term average. Full

information regarding the source, scope and compilation of consumer and business confidence

surveys used can be found in the Methodology & Sources sections 5 and 6.

To arrive at short-term forecasts for our set of monthly and quarterly data, we use econometric

models developed by our expert macroeconomic modelling team as well as judgemental input.

Country-specific indicators are forecasted using Euromonitor Macro Model, Vector Error Correction

Model (VECM) and ARIMA methods, while commodities are considered a separate group and thus

are forecasted using an econometric model reflecting both common and specific factors that affect

commodity markets. The model based forecasts are then revised by imposing certain restrictions

that ensure internal consistency of the forecasts and supplementing them with additional economic

information from a network of in-country experts. For more detailed information see section 4

“Forecasting methodology”.

3. DEFINITIONS & SOURCES

AGRICULTURAL RAW MATERIALS INDEX The index is compiled using the nominal prices of the following commodities: timber (logs and

sawnwood) 52.2%, cotton 11.8%, natural rubber 22.3%, tobacco 13.7%. Data is not country specific,

so in “Geographies selection” select “World” to view data.

Source: World Bank

Frequency: Monthly and quarterly

Seasonal adjustment: Only NSA data is available

ALMOND PRICE Average spot price of Nonpareil variety of Californian or Australian origin, 22/27 pieces/ounce,

light-medium brown coloured kernels, ex-Delhi (exclusive of VAT, other taxes and levies). The price

is in nominal US dollars. Data is not country specific, so in “Geographies selection” select “World” to

view data.

Source: MCX India (Multi Commodity Exchange of India Limited)



ALUMINIUM PRICE London Metal Exchange, unalloyed primary ingots, high grade, minimum 99.7% purity, settlement

price beginning 2005; previously cash price. The price is in nominal US dollars. Data is not country

specific, so in “Geographies selection” select “World” to view data.

Source: World Bank



APPLE PRICE USA, fresh market, FOB price. The price is in nominal US dollars. Data is not country specific, so

in “Geographies selection” select “World” to view data.

Source: United States Department of Agriculture



BANANA PRICE Central & South America, major brands, US import price, free on truck (f.o.t.) US Gulf ports. The

price is in nominal US dollars. Data is not country specific, so in “Geographies selection” select

“World” to view data.

Source: World Bank



BANK NONPERFORMING LOANS TO TOTAL GROSS LOANS Bank nonperforming loans to total gross loans are the value of nonperforming loans divided by the

total value of the loan portfolio (including nonperforming loans before the deduction of specific loan-

loss provisions). The loan amount recorded as nonperforming should be the gross value of the loan

as recorded on the balance sheet, not just the amount that is overdue. The last figure in time series

refers to the last available data of the corresponding year.

Source: International Monetary Fund

Frequency: Quarterly

Seasonal adjustment: Both SA and NSA data is available

BARLEY PRICE Barley (US) feed, No. 2, spot, 20 days To-Arrive, delivered Minneapolis from May 2012 onwards;

previously April Canadian, feed, Western No. 1, Winnipeg Commodity Exchange, spot, wholesale

farmers' price. The price is in nominal US dollars. Data is not country specific, so in “Geographies

selection” select “World” to view data.

Source: World Bank



BEEF PRICE Australia/New Zealand, chucks and cow forequarters, frozen boneless, 85% chemical lean, c.i.f.

U.S. port (East Coast), ex-dock, beginning November 2002; previously cow forequarters. The price


view data.

Source: World Bank



BEVERAGES INDEX The index is compiled using the nominal prices of the following commodities: coffee 45.7%, cocoa

beans 36.9%, tea 17.4%. Data is not country specific, so in “Geographies selection” select “World”

to view data.

Source: World Bank



BUSINESS CONFIDENCE INDEX Business confidence index measures the amount of optimism or pessimism that business

managers have with regard to current situation and the prospects of their organizations. Survey

design and methodology vary from country to country depending on the source. Please see section

5 for further information. For cross-country comparison, a standardised business confidence index is

calculated, indicating the number of standard deviations each observation is above or below the

long-term mean. The further the index is from zero the better/worse the confidence is compared to

the long-term average.

Sources: Central Banks, National Statistics Offices, European Commission, trade sources



CAPITAL TO ASSETS The ratio provides an indication of financial leverage—that is, the extent to which assets are

funded by other than own funds—and another measure of capital adequacy of the deposit-taking

sector. The ratio is calculated by taking capital and reserves as the numerator, and all nonfinancial

and financial assets as the denominator.




CARDAMOM PRICE Average spot price of Cardamom 6-7mm bold bulk with minimum of 375-385 grams per litre

density, Ex-Vandanmedu, Dist. Idukki, Kerala. The price is in nominal US dollars. Data is not country


Source: MCX India (Multi Commodity Exchange of India Limited)



CENTRAL BANK POLICY RATE Central bank policy rate is the rate that is used by central bank to implement or signal its monetary

policy stance. It is most commonly set by the central banks’ policy making committees.

Sources: Central Banks, National Statistics Offices, IMF



CHICKEN PRICE United States, broiler/fryer, whole birds, 2.5 to 3 pounds, USDA grade "A", ice-packed, Georgia

Dock preliminary weighted average, wholesale. The price is in nominal US dollars. Data is not

country specific, so in “Geographies selection” select “World” to view data.

Source: World Bank



COAL PRICE Australia, thermal GAR, f.o.b. piers, Newcastle/Port Kembla from 2002 onwards , 6,300 kcal/kg

(11,340 btu/lb), less than 0.8% sulphur, 13% ash; previously 6,667 kcal/kg (12,000 btu/lb), less than

1.0% sulphur, 14% ash. The price is in nominal US dollars. Data is not country specific, so in

“Geographies selection” select “World” to view data.

Source: World Bank



COCOA PRICE International Cocoa Organization daily price, average of the first three positions on the terminal

markets of New York and London, nearest three future trading months. The price is in nominal US

dollars. Data is not country specific, so in “Geographies selection” select “World” to view data.

Source: World Bank



COCONUT OIL PRICE Philippines/Indonesia coconut oil, bulk, CIF Rotterdam. The price is in nominal US dollars. Data is

not country specific, so in “Geographies selection” select “World” to view data.

Source: World Bank



COFFEE PRICE International Coffee Organization indicator price, other mild Arabicas, average New York and

Bremen/Hamburg markets, ex-dock. The price is in nominal US dollars. Data is not country specific,

so in “Geographies selection” select “World” to view data.

Source: World Bank



COMMODITY FUEL (ENERGY) INDEX The index is compiled using the nominal prices of the following commodities: coal 4.7%, natural

gas 10.8%, crude oil 84.6%. Data is not country specific, so in “Geographies selection” select


Source: World Bank



CONSUMER CONFIDENCE INDEX Consumer confidence index measures consumers’ optimism or pessimism about their current and

future situations. Survey design and methodology vary substantially from country to country

depending on the source. Please see section 6 for further information. For cross-country

comparison, a standardised consumer confidence index is calculated, indicating the number of

standard deviations each observation is above or below the long-term mean. The further the index is

from zero the better/worse the confidence is compared to the long-term average.

Sources: Central Banks, National Statistics Offices, European Commission, trade sources



COPPER PRICE London Metal Exchange, grade A, minimum 99.9935% purity, cathodes and wire bar shapes,

settlement price. The price is in nominal US dollars. Data is not country specific, so in “Geographies


Source: World Bank



CORIANDER PRICE Average spot price of dried mature seeds of Coriandrum sativum L of Indian origin, machine

cleaned with acceptable level of moisture up to 9%, foreign matter up to 0.9%, damaged seeds up to

1.9%, shrivelled seeds up to 1.5%, weevil seeds up to 0.5% and Coriander splits (Dal) up to 9.5%

with prohibited live infestation, Badami Whole Dhaniya ex warehouse Kota exclusive of sales

tax/VAT. The price is in nominal US dollars. Data is not country specific, so in “Geographies


Source: NCDEX (National Commodity and Derivatives Exchange Limited)



CORN PRICE United States, no. 2, yellow, f.o.b. US Gulf ports. The price is in nominal US dollars. Data is not


Source: World Bank



COTTON PRICE Cotton (Cotton Outlook "Cotlook A index"), middling 1-3/32 inch, traded in Far East, C/F beginning

2006; previously Northern Europe, c.i.f. The price is in nominal US dollars. Data is not country


Source: World Bank



CRUDE OIL (EUROPE BRENT) SPOT PRICE Brent crude is a major classification of oil, used to price two thirds of the world's internationally

traded crude oil supplies. A spot price is the price for a one-time open market transaction for near-

term delivery of a specific quantity of product at a specific location where the commodity is

purchased “on the spot” at current market rates. A barrel is the standard unit of price for oil, and is

equal to 42 US gallons. The price is in nominal US dollars. Data is not country specific, so in


Source: U.S. Energy Information Administration



CRUDE OIL (WTI CUSHING) SPOT PRICE West Texas Intermediate, also known as Texas Light Sweet, is a type of crude oil used as a

benchmark in oil pricing. A spot price is the price for a one-time open market transaction for near-

term delivery of a specific quantity of product at a specific location where the commodity is

purchased “on the spot” at current market rates. A barrel is the standard unit of price for oil, and is

equal to 42 US gallons. The price is in nominal US dollars. Data is not country specific, so in


Source: U.S. Energy Information Administration



CUMIN PRICE Average spot price of dried mature fruits of Cuminum Cyminum L of Indian origin, machine

cleaned with acceptable level of moisture up to 9%, foreign matter up to 1%, damaged seeds up to

2%, seeds with stalks up to 8% and insect damaged seeds up to 0.5%, ex-warehouse Unjha

exclusive of sales tax/VAT. The price is in nominal US dollars. Data is not country specific, so in





CURRENT ACCOUNT BALANCE A constituent part of the Balance of Payments (BoP) which consists of the balance of trade in

goods and services between countries, the balance of income and the balance of current transfers.

Trade balance is the difference between exports and imports of goods and services. Income balance

includes the flows of compensations to employees and investment income. Current transfers consist

of all transfers that are not transfers of capital.

Sources: Central Banks, National Statistics Offices, OECD



CUSTOMER DEPOSITS TO TOTAL NON-INTERBANK LOANS The ratio is a measure of liquidity, in that it compares the “stable” deposit base with gross loans

(excluding interbank activity). When stable deposits are low relative to loans, there is a greater

dependence on more volatile funds to cover the illiquid assets in deposit takers’ portfolios. Customer

deposits is the numerator and includes deposits considered to be more “stable” and less volatile

types of deposits that can be employed to fund long-term lending. Non-interbank loans are the

denominator and incorporate loans excluding interbank activity.




EMPLOYED/UNEMPLOYED/ECONOMICALLY ACTIVE POPULATION Employed population comprises all persons above a specific age who during a specified brief

period, either one week or one day, were in the following categories: (A) "paid employment": (i) "at

work": persons who during the reference period performed some work for wage or salary, in cash or

in kind; (ii) "with a job but not at work": persons who, having already worked in their present job,

were temporarily not at work during the reference period and had a formal attachment to their job.

(B) "self-employment": (i) "at work": persons who during the reference period performed some work

for profit or family gain, in cash or in kind: (ii) "with an enterprise but not at work": persons with an

enterprise, which may be a business enterprise, a farm or a service undertaking, who were

temporarily not at work during the reference period for any specific reason.

Unemployed population comprises all persons above a specific age who during the reference

period were simultaneously: (a) "without work", i.e. were not in paid employment or self-employed;

(b) "currently available for work", i.e. were available for paid employment or self-employment during

the reference period, and (c) "seeking work", i.e. had taken specific steps in a specified reference

period to seek paid employment or self-employment.

Economically active population comprises all persons who furnish the supply of labour for the

production of economic goods and services (employed and unemployed, including those seeking

work for the first time) during a specified time reference period.

Sources: National Statistics Offices, OECD, Eurostat



EXCHANGE RATES AGAINST US DOLLAR

The exchange rate is defined as the price in a given currency at which bills drawn in another

currency may be bought. The data is the monthly average of market rates.

Sources: Central Banks, National Statistics Offices, OECD, IMF



EXPORT PRICE INDEX Export price index measures changes in the value of one unit of actual exported merchandise

goods. In case unit values are not available, the index measures changes in the value of a certain

fixed basket of exported merchandise goods. The index represents prices at national currency.

Sources: Customs Departments, National Statistics Offices, Eurostat



EXPORTS Data refer to merchandise exports. Exports consist of goods leaving a country’s economic

territory. Goods simply being transported through a country (goods in transit) or temporarily admitted

or withdrawn (except for goods for inward or outward processing) are not included. Exports of goods

are valued f.o.b. (free on board); the costs of transportation and insurance up to the border of the

exporting country are included in exports of goods.

Sources: Customs Departments, National Statistics Offices, OECD, IMF



EXPORTS OF GOODS AND SERVICES Exports of goods and services consist of transactions of all goods and services from residents to

non-residents of a country. They include the value of merchandise, goods sent for processing and

repairs, nonmonetary gold, and services such as transportation, construction, information, financial,

business and other services.

Sources: National Statistics Offices, Eurostat, OECD



FOOD INDEX The index is compiled using the nominal prices of the following commodities: bananas 4.9%,

cereals (maize, rice, wheat, barley) 28.2%, meat (beef, chicken) 12.8%, vegetable oils and protein

meals (coconut oil, groundnuts, groundnut oil, palm oil, soybeans, soybean meal, soybean oil)

40.8%, oranges 3.6%, sugar 9.8%. Data is not country specific, so in “Geographies selection” select


Source: World Bank



FOREIGN CURRENCY DENOMINATED LOANS TO TOTAL LOANS Foreign currency denominated loans to total loans is calculated by using the foreign currency and

foreign-currency-linked part of gross loans to residents and non-residents as the numerator and total

gross loans as the denominator. It is an asset quality indicator, which measures the relative size of

foreign currency loans within gross loans and therefore monitors exposures to both credit and

currency risk.




FOREIGN EXCHANGE RESERVES Foreign exchange reserves comprise a part of international reserves and are stocks of foreign

currency denominated assets held by central banks and monetary authorities. Foreign exchange

includes monetary authorities’ claims on non-residents in the forms of currency bank deposits,

government securities, other bonds and notes, money market instruments, financial derivatives,

equity securities, and nonmarketable claims arising from arrangements between central banks or

governments.

Sources: Central Banks, IMF



GDP Gross domestic product is an aggregate measure of production equal to the sum of the gross

values added of all resident institutional units engaged in production (plus any taxes, and minus any

subsidies, on products not included in the value of their outputs). The sum of the final uses of goods

and services (all uses except intermediate consumption) measured in purchasers' prices, less the

value of imports of goods and services, or the sum of primary incomes distributed by resident

producer units.

Sources: National Statistics Offices, Eurostat, OECD, IMF



GOLD PRICE 99.5% fine (995 parts of pure gold per thousand), London, afternoon fixing, nominal US dollars

per troy ounce. Afternoon fixing refers to the price determined at 3PM London time each business

day on the London market by the five members of The London Gold Market Fixing Ltd. Data is not


Source: World Bank



GOVERNMENT EXPENDITURE Government expenditure refers to total general government finance devoted for different purposes

financed by government. It covers all non-repayable payments – whether capital or current, requited

or not – by government. Total expenditure consists of total expense and the net acquisition of

nonfinancial assets.

Sources: National Statistics Offices, Eurostat



GOVERNMENT FINAL CONSUMPTION EXPENDITURE Government final consumption expenditure consists of expenditure, including imputed

expenditure, incurred by general government on both individual consumption goods and services

and collective consumption services.




GOVERNMENT NET LENDING/BORROWING Net lending (+)/ borrowing (–) is calculated as revenue minus total expenditure. This is a core

government finance balance that measures the extent to which general government is either putting

financial resources at the disposal of other sectors in the economy and non-residents (net lending),

or utilizing the financial resources generated by other sectors and non-residents (net borrowing).

This balance may be viewed as an indicator of the financial impact of general government activity on

the rest of the economy and non-residents.




GOVERNMENT REVENUE General government revenue consists of taxes, social contributions, grants receivable, and other

revenue. Revenue increases government’s net worth, which is the difference between its assets and

liabilities.




GRAPEFRUIT PRICE USA, fresh market, FOB price. The price is in nominal US dollars. Data is not country specific, so





GROSS FIXED CAPITAL FORMATION Gross fixed capital formation consists of resident producers’ investments, deducting disposals, in

fixed assets during a given period. It also includes certain additions to the value of non-produced

http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Glossary:Asset

assets realised by producers or institutional units. Fixed assets are tangible or intangible assets

produced as outputs from production processes that are used repeatedly, or continuously, for more

than one year.




GROSS LOANS TO NONFINANCIAL CORPORATIONS Gross loans to nonfinancial corporations are loans to institutional entities whose principal activity

is the production of goods or nonfinancial services for sale at prices that are economically

significant. They include nonfinancial corporations, nonfinancial quasi corporations, and non-profit

institutions that are producers of goods or nonfinancial services for sale at prices that are

economically significant.




HARD LOGS PRICE Malaysia, meranti, Sarawak, sale price charged by importers in Tokyo, Japan. The price is in

nominal US dollars. Data is not country specific, so in “Geographies selection” select “World” to view

data.

Source: World Bank



HARD SAWNWOOD PRICE Malaysia, dark red seraya/meranti, select and better quality, average 7 to 8 inches; length

average 12 to 14 inches; thickness 1 to 2 inch(es); kiln dry, c. & f. UK ports, with 5% agents

commission including premium for products of certified sustainable forest beginning January 2005;

previously excluding the premium. The price is in nominal US dollars. Data is not country specific, so


Source: World Bank



HOUSE PRICE INDEX House price index reflects changes in the prices of residential dwellings in a country. Survey

design and methodology vary substantially from country to country. For further information, see

section 7.

Sources: Central Banks, National Statistics Offices, trade sources



HOUSE PRICE TO INCOME RATIO House price to income ratio is given by the ratio of nominal house prices to nominal household

disposable income per capita. This is a measure of the affordability of purchasing a house.

Source: OECD


Seasonal adjustment: Only SA data is available

HOUSE PRICE TO RENT RATIO House price to rent ratio is given by the ratio of nominal house prices to rental prices. This is a

measure of the profitability of owning a house.

Source: OECD


Seasonal adjustment: Only SA data is available

HOUSE RENT PRICE INDEX House rent price index measures the level of rent prices for residential dwellings in a geographical

area over time.

Sources: National Statistics Offices



HOUSEHOLD DEBT Household debt comprises debt incurred by resident households of the economy only.




HOUSING COMPLETIONS Housing completion is an agreement on a local government or other regulatory body that a

completed construction work of housing unit or a part thereof conforms to the requirements

prescribed for such construction work and that it may be used for the intended purpose. A housing

unit is defined as a house, an apartment, a group of rooms or a single room intended for occupancy

as separate living quarters. Separate living quarters are those in which the occupants live separately

from any other individuals in the building and which have a direct access from the outside of the

building or through a common hall.




HOUSING PERMITS Housing permit is a type of authorization that must be granted by a local government or other

regulatory body before the construction of a new or existing housing unit can legally occur. A

housing unit is defined as a house, an apartment, a group of rooms or a single room intended for

occupancy as separate living quarters. Separate living quarters are those in which the occupants

live separately from any other individuals in the building and which have a direct access from the

outside of the building or through a common hall.




IMPORT PRICE INDEX Import price index measures changes in the value of one unit of actual imported merchandise

goods. In case unit values are not available, the index measures changes in the value of a certain

fixed basket of imported merchandise goods. The index represents prices at national currency.

Sources: Customs Departments, National Statistics Offices, Eurostat



IMPORTS Data refer to merchandise imports. Imports consist of goods entering a country’s economic

territory. Goods simply being transported through a country (goods in transit) or temporarily admitted

or withdrawn (except for goods for inward or outward processing) are not included. Imports of goods

are valued c.i.f. (cost, insurance, freight). Import values reflect the price of a good delivered at the

frontier of the importing country, including any insurance and freight charges incurred to that point,

before the payment of any import duties or other taxes on imports or trade and transport margins

within the country.




IMPORTS OF GOODS AND SERVICES Imports of goods and services consist of transactions of all goods and services from non-residents

to residents of a country. They include the value of merchandise, goods sent for processing and

repairs, nonmonetary gold, and services such as transportation, construction, information, financial,

business and other services.




INCREASES IN STOCKS Stocks are holdings of assets and liabilities at a point in time. They include:

stocks of inputs intended to be used later as intermediate consumption in a production process;

stocks of finished goods that have not yet been sold;

stocks of merchandise purchased for resale (mainly in wholesale and retail distribution);

strategic stocks (food, oil, stocks for intervention on agricultural markets) managed by government

authorities;

work in progress, which consists of goods being processed but which cannot yet be delivered to

the user at the end of the accounting period.

Stocks are recorded for all assets within the system’s boundaries; that is, for financial assets and

liabilities and for non-financial assets, both produced and non-produced. However, the coverage is

limited to those assets that are used in economic activity and that are subject to ownership rights.

Thus, stocks are not recorded for assets such as human capital and natural resources that are not

owned.




INDEX OF CONSUMER PRICES The index of consumer prices measures changes over time in the general level of prices of goods

and services that a reference population acquires, uses or pays for consumption. A consumer price

index is estimated as a series of summary measures of the period-to-period proportional change in

the prices of a fixed set of consumer goods and services of constant quantity and characteristics,

acquired, used or paid for by the reference population. Each summary measure is constructed as a

weighted average of a large number of elementary aggregate indices. Each of the elementary

aggregate indices is estimated using a sample of prices for a defined set of goods or services

obtained in, or by residents of, a specific region from a given set of outlets or other sources of

consumption goods or services.




INDUSTRIAL PRODUCTION INDEX Industrial production Index refers to the volume of output generated by production units classified

under the industrial sectors B (Mining), C (Manufacturing), D and E (Electricity, gas and water) of the

International Standard Industrial Classification of all Economic Activities (ISIC Rev. 4). Data is

generally presented in indices of industrial production, which measure volume changes of output.

Initially, partial indices for production groups at a low level of the Industrial classification are

calculated from the production of each group's representatives using weights determined by the

representatives' gross output. These partial indices are then further aggregated. Weights used to

aggregate data at branch and product level are based on variables measuring the relative shares of

the products and branches in the value added of industry, in the base year.

Sources: National Statistics Offices, OECD



INFLATION Inflation measures the average changes in the Index of consumer prices.




INTERNATIONAL RESERVES International reserves consist of those external assets that are readily available to and controlled

by monetary authorities for direct financing of payments imbalances. International reserves comprise

of monetary gold, SDRs, reserve position in the Fund, foreign exchange assets (consisting of foreign

currency and deposits and securities) and other claims.

Sources: Central Banks, OECD, IMF



IRON ORE PRICE For years 2008 (December) to present: spot, any origin fines, 62% Fe, c.f.r. China; during 2006 to

2008 (November): spot, 63.5% Fe. Earlier data refer to annual contract prices (Brazil for Europe,)

VALE Carajas mines sinter feed, f.o.b. Ponta da Madeira. The price is in nominal US dollars. Data is


Source: World Bank



LAMB PRICE New Zealand, frozen whole carcasses Prime Medium (PM) wholesale, Smithfield, London

beginning January 2006; previously Prime Light (PL). The price is in nominal US dollars. Data is not


Source: World Bank



LEAD PRICE London Metal Exchange, refined, 99.97% purity, settlement price. The price is in nominal US


Source: World Bank



LEMON PRICE USA, fresh market, FOB price. The price is in nominal US dollars. Data is not country specific, so

in “Countries selection” select “World” to view data. Data is not country specific, so in “Geographies





LIME PRICE Market price of first class lime fruits in Michoacán, Mexico. The price is in nominal US dollars.

Data is not country specific, so in “Geographies selection” select “World” to view data.

Source: Mexico National System of Information and Integration of Markets



LONG-TERM INTEREST RATES Long term interest rate is the secondary market yield on long term government bonds, which in

most cases is 10 years. Generally the yield is calculated at the pre-tax level and before deductions

for brokerage costs and commissions and is derived from the relationship between the present

market value of the bond and that at maturity, taking into account also interest payments paid

through to maturity.

Sources: Central Banks, OECD



MARKET CAPITALISATION Market capitalisation is an estimation of the value of a business that is obtained by multiplying the

number of shares outstanding by the current price of a share.

Sources: National Statistics, Central Banks, World Federation of Exchanges



MEAN MAXIMUM TEMPERATURE Average daily maximum air temperature in Celsius.

Sources: NOAA NCEI (National Oceanic and Atmospheric Administration's National Centers for

Environmental Information), Weatherbase



MEAN MINIMUM TEMPERATURE Average daily minimum air temperature in Celsius.





MEAN TEMPERATURE Average daily air temperature in Celsius.





METALS INDEX The index is compiled using the nominal prices of the following commodities: aluminium 26.7%,

copper 38.4%, iron ore 18.9%, lead 1.8%, nickel 8.1%, tin 2.1%, zinc 4.1%. Data is not country


Source: World Bank



MILK PRICE, EUROPEAN UNION The price a dairy farmer receives if milk of specific (standard) composition, quality and quantity is

delivered to the different European dairy companies. The price (nominal US dollars per 100 kg) is

exclusive of VAT, ex-farm and inclusive of supplementary payments. Select “World” in “Geographies

selection” to view data.

Source: LTO Nederland



MILK PRICE, NEW ZEALAND The price a dairy farmer receives if milk of specific (standard) composition, quality and quantity is

delivered to Fonterra, the largest New Zealand dairy company. The price (nominal US dollars per

100 kg) is exclusive of VAT, ex-farm and inclusive of supplementary payments. Select “World” in

“Geographies selection” to view data.

Source: LTO Nederland



MILK PRICE, USA All milk price received by producers, nominal US dollars per 100 kg; before deductions for hauling;

includes quality, quantity and other premiums; excludes hauling subsidies. All milk includes fluid

grade milk (milk produced under sanitary conditions that qualify it for fluid consumption) and

manufacturing grade milk (milk not meeting the fluid grade standards). Select “World” in




Seasonal adjustment: Both SA and NSA data is available.

MONEY SUPPLY Money supply is defined as narrow money (M1) that includes currency in circulation, i.e.

banknotes and coins, as well as balances which can immediately be converted into currency or used

for cashless payments, i.e. overnight deposits.




NATURAL GAS PRICE, EUROPE Europe, average import border price and a spot price component, beginning April 2010 including

UK; during June 2000 - March 2010 prices excludes UK. The price is in nominal US dollars. Select

“World” in “Geographies selection” to view data.

Source: World Bank



NATURAL GAS PRICE, JAPAN Liquefied Natural Gas (Japan), import price, cif, recent two months' averages are estimates. The

price is in nominal US dollars. Select “World” in “Geographies selection” to view data.

Source: World Bank



NATURAL GAS PRICE, USA Natural gas spot price at the Henry Hub terminal in Louisiana. The price is in nominal US dollars.

Select “World” in “Geographies selection” to view data.

Source: World Bank



NICKEL PRICE London Metal Exchange, cathodes, minimum 99.8% purity, settlement price beginning 2005;

previously cash price. The price is in nominal US dollars. Data is not country specific, so in


Source: World Bank



NON-RESIDENTIAL BUILDING COMPLETIONS Building completion is an agreement on a local government or other regulatory body that a

completed construction work conforms to the requirements prescribed for such construction work

and that it may be used for the intended purpose. Non-residential buildings include all buildings

other than dwellings: warehouse and industrial buildings, commercial buildings, buildings for public

entertainment, hotels, restaurants, educational buildings, health buildings and other.




NON-RESIDENTIAL BUILDING PERMITS Building permit is a type of authorization that must be granted by a local government or other

regulatory body before the construction of a new or existing unit can legally occur. Non-residential

buildings include all buildings other than dwellings: warehouse and industrial buildings, commercial

buildings, buildings for public entertainment, hotels, restaurants, educational buildings, health

buildings and other.




NUMBER OF JOB VACANCIES A job vacancy is a post, either newly created, unoccupied or about to become vacant, which the

employer actively seeks to fill with a suitable candidate from outside the enterprise (including any

further necessary steps) immediately or in the near future. Although the definition states that a job

vacancy should be open to candidates from outside the enterprise, this does not exclude the

possibility of appointing an internal candidate to the post. A post that is open to internal candidates

only, however, is not considered a job vacancy.

Sources: National Statistics Offices, OECD, Eurostat



ORANGE JUICE PRICE Intercontinental Exchange (ICE), Frozen Concentrated Orange Juice (FCOJ-A) futures contract,

nearby position, monthly average of close prices. The price is in nominal US dollars. Data is not


Source: Intercontinental Exchange



ORANGE PRICE Mediterranean exporters, navel, European Union indicative import price, c.i.f. Paris. The price is in


data.

Source: World Bank



OVERNIGHT INTERBANK RATE Overnight interbank rate is the rate at which banks lend money to each other in domestic currency

for the duration of one night. Official discount rates are used in some cases where official interbank

rates are not calculated by national authorities. The official discount rate is the rate at which central

banks make advances to, or discount eligible bills of exchange for, selected banks and other

financial intermediaries. Overnight loans usually serve to balance temporary surpluses and

shortages of liquidity in banks, and are usually considered the lowest cost of money in the market.

Sources: Central Banks, OECD



PALM OIL PRICE Palm oil (Malaysia), 5% bulk, c.i.f. North-West Europe market. The price is in nominal US dollars.


Source: World Bank



PEANUT PRICE United States, Runners 40/50, shelled basis, c.i.f. Rotterdam. The price is in nominal US dollars.


Source: World Bank



PEPPER PRICE Average spot price of dried mature fruits of black pepper (Piper nigrum) with acceptable level of

moisture up to 11.5%, foreign matter up to 0.5% and light pepper up to 2%, Malabar Garbled 1 ex

accredited warehouse Kochi exclusive of all taxes. The price is in nominal US dollars. Data is not





PORK PRICE United States, price received by farmers for live hogs. The price is in nominal US dollars. Data is





PRIVATE FINAL CONSUMPTION EXPENDITURE Consists of the expenditure, including imputed expenditure, incurred by resident households on

individual consumption goods and services, including those sold at prices that are not economically

significant. It also includes imputed expenditure (such as rent payments that householders would

pay if they rented their dwelling, instead of owning it) and the expenditures of Non Profit Institutions

Serving Households (NPISH).




PRODUCER PRICE INDEX, MANUFACTURING Producer Price Indices (PPIs) are indices designed to measure the average change in the price of

goods and services either as they leave the place of production or as they enter the production

process. Data refer to goods and services produced for domestic market.

Sources: National Statistics Offices, OECD



PULP PRICE Woodpulp from Sweden, softwood, sulphate, bleached, air-dry weight, CIF North Sea ports. The

price is in nominal US dollars. Data is not country specific, so in “Geographies selection” select


Source: World Bank



REAL GDP GROWTH Percentage change in GDP at constant prices.




RED CHILI PRICE Average spot price of dried ripe fruits or pods of the Capsicum annum L & Capsicum frutescens L

of bright red colour, not less than 4 cm in length with acceptable level of moisture up to 11%, foreign

matter up to 1%, damaged fruits up to 3.5%, loose seeds 0.9%, unripe fruits up to 1.9% and insect

damaged matter up to 1%, Chilli Teja Guntur exclusive of Sales Tax/VAT. The price is in nominal US





REGULATORY TIER 1 CAPITAL TO RISK-WEIGHTED ASSETS The ratio measures the capital adequacy of deposit takers based on the core capital concept of

the Basel Committee on Banking Supervision. Tier 1 capital is the numerator and comprises paid-up

shares and common stock—issued and fully paid ordinary shares/common stock and perpetual

noncumulative preference shares—and disclosed reserves created or increased by appropriations of

retained earnings or other surplus. Sector-wide risk-weighted assets are the denominator and

include currency and deposits, loans, securities, and other on-balance-sheet assets. Assets are

weighted by factors representing their credit riskiness and potential for default.




RESIDENTIAL REAL ESTATE LOANS TO TOTAL LOANS Residential Real Estate Loans to Total Loans is an asset quality ratio, which is intended to identify

deposit takers’ exposure to the residential real estate sector, with the focus on household borrowers.

A high concentration of the loan portfolio in real estate signals the potential existence of an important

vulnerability in the financial system.




RETAIL SALES INDEX Retail trade represents a form of trade in which the goods are purchased in small quantities for

direct consumption by the purchaser. Retail sales index measures the turnover of the country’s retail

trade industry. Retail trade includes the activities of ISIC Rev. 4 Division 47 (Retail trade, except of

motor vehicles and motorcycles). This corresponds to the NACE Rev. 2 Division 47 (Retail trade,

except of motor vehicles and motorcycles). The index is available in both nominal and real terms.




RICE PRICE Thailand, 5% broken, white rice (WR), milled, indicative price based on weekly surveys of export

transactions, government standard, f.o.b. Bangkok. The price is in nominal US dollars. Data is not


Source: World Bank



RUBBER PRICE Rubber (any origin), Ribbed Smoked Sheet (RSS) no. 1, in bales, Rubber Traders Association

(RTA), spot, New York. The price is in nominal US dollars. Data is not country specific, so in


Source: World Bank



SALMON PRICE Fresh Norwegian salmon, farm bred, export price. The price is in nominal US dollars. Data is not


Source: Statistics Norway



SILVER PRICE UK, 99.9% refined, London afternoon fixing. Data is not country specific, so in “Geographies


Source: World Bank



SOFT LOGS PRICE Average export price of Douglas-fir, Western hemlock and other softwoods exported from

Washington, Oregon, Northern California and Alaska. The price is in nominal US dollars. Data is not





SOFT SAWNWOOD PRICE Soft sawnwood, average export price of Douglas Fir, U.S. Price. The price is in nominal US





SOYBEANS PRICE Soybeans (United States), c.i.f. Rotterdam. The price is in nominal US dollars. Data is not country


Source: World Bank



STEEL PRICE, CHINA 5mm thick x 1200-1500mm wide hot-rolled band with a carbon component of 0.08% to 0.13%

price in China, ex-works. The price is in nominal US dollars. Select “World” in “Geographies


Source: SteelBenchmarker



STEEL PRICE, USA 5mm thick x 1200-1500mm wide hot-rolled band with a carbon component of 0.08% to 0.13%

price in the USA, FOB mill. The price is in nominal US dollars. Select “World” in “Geographies





STEEL PRICE, WESTERN EUROPE 5mm thick x 1200-1500mm wide hot-rolled band with a carbon component of 0.08% to 0.13%

price in Germany/France, ex-works. The price is in nominal US dollars. Select “World” in





STOCK MARKET INDEX Stock market index is a hypothetical basket of securities designed to summarize the performance

of stocks market. Usually all indexes are chain-linked, meaning that they are always calculated

based on the price level of the previous trading day. The indexes are market weighted, calculated

based on the change in the total market value from one point in time to another of all the shares

included in the index. The figure for a certain time period refers to an average of daily data for that

period. For country-specific index names see section 8.

Source: national stock exchanges, OECD



STRAWBERRY PRICE USA, fresh market, FOB price. The price is in nominal US dollars. Data is not country specific, so





SUGAR PRICE, EUROPEAN UNION European Union negotiated import price for raw unpackaged sugar from African, Caribbean and

Pacific (ACP) under Lome Conventions, c.I.f. European ports. The price is in nominal US dollars.

Select “World” in “Geographies selection” to view data.

Source: World Bank



SUGAR PRICE, USA United States, nearby futures contract, c.i.f. The price is in nominal US dollars. Select “World” in


Source: World Bank



SUGAR PRICE, WORLD International Sugar Agreement (ISA) daily price, raw, f.o.b. and stowed at greater Caribbean

ports. The price is in nominal US dollars. Select “World” in “Geographies selection” to view data.

Source: World Bank



TEA PRICE Mombasa/Nairobi auctions, African origin, all tea, arithmetic average of weekly quotes. The price


view data.

Source: World Bank



TIN PRICE London Metal Exchange, refined, 99.85% purity, settlement price. The price is in nominal US


Source: World Bank



TOBACCO PRICE Tobacco of any origin, unmanufactured, general import price in the USA, CIF. The price is in


data.

Source: World Bank



TOTAL GROSS LOANS Total gross loans include those financial assets created through the direct lending of funds by a

creditor to a debtor through an arrangement in which the lender either receives no security

evidencing the transactions or receives a non-negotiable document or instrument. Collateral, in the

form of either a financial asset (such as a security) or nonfinancial asset (such as land or a building),

may be provided under a loan transaction, though it is not an essential feature. Loans include

commercial loans, instalment loans, hire-purchase credit, loans to finance trade credit and

advances, financial leases, repurchase agreements not classified as a deposit, and overdrafts.




TOTAL PRECIPITATION Total precipitation amount for the period in millimetres.





TRADE BALANCE Exports of goods minus Imports of goods.




TURMERIC PRICE Average spot price of primary or secondary rhizomes of Curcuma Longa L of minimum length of 3

cm, which were soaked in boiling water and dried, with acceptable level of moisture up to 12%,

damage from moisture or over boiling up to 1.2%, not boiled matter up to 0.3%, foreign matter up to

0.75%, bulbs up to 3% and free of fungus, ex warehouse Nizamabad exclusive of Sales Tax/VAT.

The price is in nominal US dollars. Data is not country specific, so in “Geographies selection” select





UNEMPLOYMENT RATE The number of unemployed persons expressed as a percentage of the total economically active

population (the total number of people employed plus unemployed). The ILO international standard

definition of unemployment is based on the following three criteria which should be satisfied

simultaneously: "without work", "currently available for work" and "seeking work". Accordingly: The

unemployed comprise all persons above a specific age who during the reference period were: (a)

"without work", i.e. were not in paid employment or self-employed; (b) "currently available for work",

i.e. were available for paid employment or self-employment during the reference period, and (c)

"seeking work", i.e. had taken specific steps in a specified reference period to seek paid employment

or self-employment.




UNIT LABOUR COST INDEX Unit labour costs measure the average cost of labour per unit of output and are calculated as the

ratio of total labour costs to labour productivity. Unit labour costs represent a direct link between

productivity and the cost of labour used in generating output. A rise in an economy’s unit labour

costs represents an increased reward for labour’s contribution to output. However, a rise in labour

costs higher than the rise in labour productivity may be a threat to an economy's cost

competitiveness, if other costs are not adjusted in compensation.

Sources: OECD



USUAL/ACTUAL WEEKLY WORKING HOURS Actual weekly working hours are the number of hours actually worked during the reference week,

including overtime but excluding meal breaks and hours paid for but not worked (e.g. paid annual

leave, paid sick leave, public holidays etc.). Usual weekly working hours are the modal value of

hours actually worked per week over a long reference period.

The difference between the concepts of usual and actual working hours is that usual hours refer to

the typical hours worked over a week, while actual hours represent the exact number of hours

worked over a week. Both usual and actual working hours refer to total employment (both full-time

and part-time) in all the industry sectors.




WAGE PER HOUR Wages per hour refer to remuneration paid per hour worked to employees, together with overtime

payments, premiums, bonuses, allowances and remuneration for time not worked, such as for

annual vacation, other paid leave or holidays. Wage data exclude employers’ contributions in

respect of their employees paid to social security and pension schemes and also the benefits

received by employees under these schemes. Wages also exclude severance and termination pay.

Wages relate to employees’ gross remuneration, i.e. the total before any deductions are made by

the employer in respect of taxes, contributions of employees to social security and pension

schemes, life insurance premiums, union dues and other obligations of employees. Data for total

economy and manufacturing sector is available.

Sources: National Statistics Offices, ILOSTAT



WHEAT PRICE United States, no. 1, hard red winter, ordinary protein, export price delivered at the US Gulf port

for prompt or 30 days shipment. The price is in nominal US dollars. Data is not country specific, so in


Source: World Bank



WOOL PRICE Australian Wool Exchange, Eastern Market Indicator monthly average. The price is in nominal US


Source: Australian Wool Innovation Limited



ZINC PRICE London Metal Exchange, high grade, minimum 99.95% purity, settlement price. The price is in


data.

Source: World Bank



SEASONAL ADJUSTMENT Seasonal adjustment is a statistical technique to remove the effects of seasonal calendar

influences impacting on a series. Seasonal effects usually reflect the influence of the seasons

themselves either directly (e.g. there is less construction in winter) or through social conventions

(e.g. moving holidays such as Easter and Eid have an impact on working days and Christmas has a

huge impact on retail sales). For the datasets that include countries with missing seasonally

adjusted data, we model the missing series using STL/X-12 seasonal decomposition procedures. To

correctly detect and remove the seasonal component, the decomposition procedures are not

implemented if the time series is shorter than 3 years.

POINT INCREASE Simple arithmetic increase over previous period, or same period of previous year.

GROWTH RATES Growth rates and indices for the following datasets are calculated in national currency and in

current/nominal terms: Current Account Balance; Exports; Exports of Goods and Services; Foreign

Exchange Reserves; GDP; Government Expenditure; Government Final Consumption Expenditure;

Government Net Lending/Borrowing; Government Revenue; Gross Fixed Capital Formation; Gross

Loans to Nonfinancial Corporations; Household Debt; Imports; Imports of Goods and Services;

Increases in Stocks; International Reserves; Market Capitalisation; Money Supply; Private Final

Consumption Expenditure; Total Gross Loans; Trade Balance; Wage per Hour and Wage per Hour,

Manufacturing. Growth rates and indices for all commodity prices are calculated in current/nominal

US$.

4. FORECASTING METHODOLOGY

Our short-term forecasts are a combination of model-based projections and qualitative input.

Depending on the series, the country-specific forecasts are produced using either the Euromonitor

Macro Model, Vector Error Correction Model or univariate time series methods. The commodity

prices are forecasted using a semi-structural econometric model. The obtained results are then

checked against the additional economic information gathered from a network of our in-country

experts. In addition, certain restrictions are imposed to ensure internal consistency of the forecasts.

I. EUROMONITOR MACRO MODEL Euromonitor Macro Model (EMM) is a small generic open economy model that describes the joint

determination of output, unemployment, inflation, short-term interest rate and exchange rate for a

group of economies. The model is fundamentally a gap model, in which the gaps of the variables

from their equilibrium values play the crucial role in the functioning of the system. A number of

definitions and identities are used to complete the model. There could be some specific differences

in model structure for various countries, e.g. incorporation of the US Bank Lending Tightening

variable to the US output gap equation, fixed exchange rate policy structures, etc., however the

basic model equations are the same for all covered countries.

Country coverage:

Africa and Middle East: Egypt, Iran, Israel, Saudi Arabia, South Africa, Vietnam;

Asia Pacific: China, Hong Kong, India, Indonesia, Japan, Kazakhstan, Malaysia, Pakistan,

Singapore, South Korea, Taiwan, Thailand;

Australasia: Australia, New Zealand;

Eastern Europe: Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland,

Romania, Russia, Slovakia, Ukraine;

Western Europe: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy,

Netherlands, Norway, Portugal, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom;

Latin America: Argentina, Brazil, Chile, Colombia, Mexico, Peru;

North America: Canada, USA.

Forecasted indicators:

Real GDP growth;

Index of consumer prices/inflation;

Unemployment rate;

Central bank policy rate.

II. VECTOR ERROR CORRECTION MODEL Many economic variables exhibit persistent upward or downward movement. This feature can be

generated by stochastic trends in integrated variables. If the same stochastic trend is driving a set of

integrated variables jointly, they are called cointegrated. In this case certain linear combinations of

integrated variables are stationary. Such linear combinations that link the variables to a common

trend path are called cointegrating relationships. They sometimes may be interpreted as equilibrium

relationships in economic models.

Cointegrating relationships can be imposed by reparameterizing the VAR model as a vector error

correction model (VECM). We use the VECM approach to forecast a set of variables with a long-

term equilibrium relationship: GDP expenditure components. In addition, several auxiliary indicators

are forecasted in the same framework.

The VECM approach forecasts all GDP expenditure components simultaneously, including the

relations between variables and making an assumption that there is a long-term equilibrium equation

which insures short-term shocks will be eliminated in the long run. Subsequently, Government

Expenditure is forecasted using an autoregressive model with exogenous regressors. The main

regressor is Government Final Consumption Expenditure from GDP expenditure component model.

Next, Government Net Lending/Borrowing is forecasted as % of GDP using time series models with

quarter-on-quarter growth. Finally, Government Revenue is calculated from Government

Expenditure and Government Net Lending/Borrowing. In addition, Actual Weekly Working Hours are

calculated using time series models; Usual Weekly Working Hours are forecasted as a ratio of

Actual Weekly Working Hours using linear regression.

III. ARIMA MODELS We use ARIMA forecasting method to find the most appropriate models for the rest of economic

indicators (not forecasted under EMM or VECM frameworks), forecast them and check whether the

obtained forecasts are reliable.

For each country-economic indicator combination, a suitable ARIMA model is selected and the

forecasts are generated using the selected model.

Data pre-processing

Each economic indicator usually has several units (level, growth, index etc.). All these units can

be derived from each other. We forecast only one unit and forecasts for all other units (of the same

economic indicator) are derived accordingly. Some economic indicators are derived from other

indicators (e.g. Trade Balance); in that case, we derive the forecast for such indicators from

corresponding indicators using the original relationships. This way data integrity is ensured.

To improve the reliability of forecasts, the indicators starting after Q1 2008 (for quarterly time

series)/M1 2010 (for monthly time series) are not forecasted.

Model selection

ARIMA models are very flexible and particularly suitable for short-term forecasting of economic

indicators. For each country-economic indicator combination multiple ARIMA models are fitted and

then one model is chosen according to the following criteria:

The model has to have high AIC and BIC value. AIC and BIC are correspondingly Akaike

and Bayesian information criteria. These criteria are measures of the relative goodness of fit of a

statistical model.

The model must reasonably satisfy the theoretical assumptions of the ARIMA model.

The model must be non-trivial, simple random walks are not used for forecasting.

Forecast validation Checking model and forecast reliability

The selected model is tested to ensure reliability. First, the model coefficient stability is tested.

This is done by sequentially dropping observations from the end of the data sample and re-

estimating the model. The idea is that if we selected the true model which represents the data,

removal of few observations should not result in major changes in the coefficients.

We also test model forecasting performance. This is done by dividing the available data for

economic indicator into test and train parts. The model is estimated using only the test data, then

forecasts are generated and they are compared to the train data. The division is done to simulate

real forecasting exercise, i.e. the splitting of the data is done at some time period. The train data is

the data before that period and the test data is the data after the period. If, for example, the

economic indicator is of monthly frequency, then the test data covers up to 12 last months. Having

calculated the forecasts for the test data we calculate MAPE – mean average percentage error and

MASE – mean average scaled error. In case where the original data is measured in percent, MAE –

mean average absolute error – is used instead of MAPE.

For some economic indicators, the long-run averages and ranges are known from economic

theory or from research. In these cases we check whether long-term forecasts of chosen models

conform to these averages and ranges.

Finally, we check our forecasts against the economic evidence gathered by a team of in-country

experts in order to see the range of our predictions in the context of other sources.

Iterative procedure

All model selection and validation procedures are done iteratively. If selected model fails any of

the checks, the data is investigated for outliers and other irregularities. Then depending on the

situation, measures are taken to fix it. Usually a failure to pass one or another criterion is unique to

each separate case. The most effective fixes are changing the historical period for model selection,

changing the unit of the indicator which is used for forecasting and changing seasonality modelling.

Note on seasonality

When data indicates the presence of seasonality, it is either directly modelled via an extension of

ARIMA, SARIMA, or the seasonal component is removed using industry-standard algorithms

(STL/X-12 seasonal decomposition procedures). To correctly detect and remove the seasonal

component, the decomposition procedures are not implemented if the time series is shorter than 3

years.

Data post-processing

It is common that some economic indicators are interrelated. After producing forecasts, we

calculate pairwise correlations of all the economic indicators for all countries for historical data and

for historical data coupled with forecasts, and check the results to ensure that the correlations did

not change drastically.

IV. COMMODITY FORECASTS In order to forecast commodity prices and price indices, we have developed an economic model

that is useful for assessing and quantifying major economic drivers behind commodity price trends:

We develop an economic model in a sense that the model consists of a coherent system of

economic relationships among commodity price indices and explanatory economic variables.

Our analysis focuses on development of a structural econometric model for a group of commodity

indices (namely energy, metals, food, agricultural raw materials and beverages) compiled and

published on a monthly basis by the World Bank.

The purpose of the model is its use for short-term commodity price forecasts. The forecasting

process requires making projections of explanatory macroeconomic and financial variables and

running the current model to obtain conditional commodity price forecasts.

The model explains in-sample dynamics and produces forecasts of several quite broad commodity

price indices. The output of the model is further used in ARIMA statistical models designed

specifically for individual commodities.

Some specific economic ideas applied in the model

A number of economic ideas are utilised in developing the model:

Relative prices of different commodity groups exhibit certain regularities that could be successfully

exploited in commodity price modelling. There is a well-known economic rationale behind the

correlation among different commodity prices.

Given the recently increased correlation among price movements of different commodity groups, it

is clear that commodity groups are strongly affected by common (systemic) factors emanating from

the macroeconomic and financial sphere.

Commodity groups are also affected by specific (idiosyncratic) factors, such as supply or demand

indicators for a specific commodity group. Some of such factors are conveniently included in

regressions for certain commodity groups. However, in many cases such factors cannot be easily

incorporated in the quantitative analysis due to lack of timely data of sufficient regularity.

Indicators obtained from commodity futures markets reflect market expectations and in some

cases contain useful information content that can improve regressions for some commodity groups.

Commodity groups are explicitly modelled as constituents of the commodity complex (the broad

index), which is thus an endogenous variable in the model but also impacts prices of constituent

commodity groups. This bi-directional relation enhances internal consistency of the model.

Basic modelling framework

In creating the model, we try to exploit the existing correlations among different commodity prices.

In order to avoid modelling an excessive number of pair-wise correlations, we examine the

relationship between each commodity group and the broad commodity index (thus we have only 5

pair-wise relationships in our case).

We find the standard econometric error-correction modelling technique particularly useful for

modelling fundamentals of commodity prices. Error-correction models are usually estimated in two

phases: at first the long-term, or equilibrium, relationships among variables are determined and then

short term deviations from long-term trends are examined.

The basic structure of the current error-correction type model is as follows:

Long-run relationship for commodity group i:

Long-run trend for commodity price index i is a function of:

Broad index excluding commodity index i

Systemic factors

Idiosyncratic factors

Short-run relationship for commodity group i:

Change in commodity price index i is a function of:

Last period’s deviation from the long-run trend

Changes in systemic factors

Changes in idiosyncratic factors

Slopes of the futures curve from earlier periods

Broad commodity price index is sum of individual weighted indices i.

In the above description i stands for energy, metal, food, agricultural materials, and beverages. All

of the equations are included in a unified model, which predicts endogenous commodity indices for

given values of exogenous variables.

Outcomes of model solution

The relationships outlined above are estimated for each commodity index over the sample from

1992M01 to the latest month by simple ordinary least squares estimation method. They are

combined together in one econometric model, which is then dynamically solved.

After the forecasts for each commodity index are obtained, individual commodity prices are

predicted by running a suitable ARIMAX model with 5 commodity indices used as regressors.

Estimated paths for commodity price indices can be interpreted as commodity fundamentals based

on the current model, and large positive deviations of actual commodity prices from estimated

fundamentals may be indicative of commodity bubble formation.

5. BUSINESS CONFIDENCE INDICES: METHODOLOGY & SOURCES

AUSTRALIA

Name of survey

Monthly Business Survey

Source

National Australia Bank

Frequency

Monthly

Scope

The sample consists of 400-500 firms in non-farm sector.

Survey questions

Not available

Index construction

The index values range from -100 (when all respondents have negative confidence) to +100

(when all respondents have positive confidence).

AUSTRIA

Name of survey

Joint Harmonised EU Programme of Business and Consumer Surveys

Source

European Commission; Directorate-General for Economic and Financial Affairs (DG ECFIN)

Frequency

Monthly

Scope

Random sample of 925 firms in manufacturing sector. Firms on the frame list are contacted on a

regular basis and are asked whether they are willing to participate.

Survey questions

The industry survey is largely qualitative. The main questions refer to an assessment of recent

trends in production, of the current levels of order books and stocks, as well as expectations about

production, selling prices and employment. For qualitative questions, answers are usually given

according to a three-option ordinal scale: “increase” (+), “remain unchanged” (=), “decrease” (-); or

“more than sufficient” (+), “sufficient” (=), “not sufficient” (-); or “too large” (+), “adequate” (=), “too

small” (-). In some cases, respondents have the choice between four, five or six options.

Index construction

On the basis of the distribution of the various options for each question, aggregate balances are

calculated for each question. Balances are the difference between positive and negative answering

options, measured as percentage points of total answers. In particular, if a question has three

alternative options, “positive” (“up”, “more”, “more than sufficient”, “good”, “too large”, “increase”,

“improve”, etc.), “neutral” (“unchanged”, “as much”, “sufficient”, “satisfactory”, “adequate”, etc.) and

“negative” (“down”, “less”, “not sufficient”, “too small”, “decline”, etc.), and if P, E and M (with P+E+M

= 100) denote the percentages of respondents having chosen respectively the option positive,

neutral, and negative, the balance is calculated as

B = P - M

In the case of questions with six options, i.e. the three options above plus “very positive” (“got/get

a lot better”, “very much higher”, “increase sharply”, etc.), “very negative” (“got/get a lot worse”, “very

unfavourable”, “fall sharply”, etc.) and “don’t know”, the balances are calculated on the basis of

weighted averages. If P, E and M have the same meaning as in the previous paragraph, while PP

denotes the percentage of respondents having chosen the option “very positive”, MM the percentage

of respondents having chosen the option “very negative” and N is the percentage of respondents

without any opinion (so that PP+P+E+M+MM+N=100), balances are calculated as

B = (PP + 1⁄2 P) - (1⁄2 M + MM)

The balance values range from -100, when all respondents choose the negative option (or the

most negative one in the case of six option questions) to +100, when all respondents choose the

positive (or the most positive) option.

The industrial confidence indicator is the arithmetic average of the balances (in percentage points)

of the answers to the questions on production expectations, order books and stocks of finished

products (the last with inverted sign).

BELGIUM

Name of survey

Business Survey

Source

National Bank of Belgium

Frequency

Monthly

Scope

The sample consists of the same 6000 firms in industry, building, trade and business-related

services.

Survey questions

The qualitative questions concern subjects such as production, order books, employment and

prices. They centre on three main aspects. Businesses are first questioned about the latest

developments: has there been an increase, a decrease, or no change? Next, businesses are asked

to assess each reported change: is it normal, greater than normal or less than normal? Finally,

business leaders indicate what trend they expect to see in the next three months.

Index construction

The responses of each firm form the basis for calculating, for each question, the percentage of

business leaders reporting improvement (positive responses), the percentage reporting deterioration

(negative responses) and the percentage stating that there has been no change. In calculating these

three percentages, account is taken of the relative importance of each firm within each activity

covered by the surveys. The results for each firm (individual results) are then aggregated on the

basis of the value added of each activity. For each aggregation level, a balance is determined for

each question: this is the difference between the percentage of firms reporting improvement

(positive responses) and the percentage reporting deterioration (negative responses). For example,

if the number of positive responses equals the number of negative responses the balance for the

question is zero; conversely, a balance of +10 means that positive responses outnumbered negative

responses by 10 percentage points.

Each balance is then adjusted for seasonal variations. After that, a synthetic indicator is calculated

for each sector and for each branch of activity by finding the arithmetical mean of the seasonally

adjusted balances of the responses to all the questions, except those concerning prices. The overall

synthetic curve is the weighted average of the synthetic indicators for industry, building and trade.

Weights are: 65% - manufacturing industry, 15% - building industry, 5% - trade, 15 - business-

related services.



BRAZIL

Name of survey

Industrial Confidence Survey

Source

National Confederation of Industry Brazil

Frequency

Monthly

Scope

Random sample of firms in industrial sector

Survey questions

The index is built on four basic questions concerning current and expected conditions of the

general economy and current and expected conditions of the company.

Index construction

The ICEI is an indicator of diffusion ranging from 0 to 100, with 50 representing neutral

confidence. For each industry sector, initial indicators for each of the four basic questions are

calculated. Each question allows five exclusive alternatives. Each alternative is given a weight of

0.0, 0.25, 0.50, 0.75, and 1.0 (from the most negative to the most positive respectively). The

indicator for each question is the average of these scores, weighted by the relative frequency of

response. The total confidence index is a weighted average of all the indicators, with weights based

on the company size.

BULGARIA

Name of survey

Business Survey in Industry

Source

National Statistical Institute of Bulgaria

Frequency

Monthly

Scope

Stratified sample of the enterprises in the industry sector

Survey questions

The first type of questions of business surveys is related to the present or expected direction of

change of economic variables such as production, competitive position on the market, selling prices,

etc. The replies are presented in a three-option ordinal scale formulated as follows: “Increase”, “No

change”, “Decrease” or “Improve”, “No change”, “Deteriorate”.

The second type of questions is related to the level of the economic variable compared to an ideal

level called “normal”, “sufficient”, “satisfying for the season”. In the same manner are formulated the

replies: “Above normal”, “Normal”, “Below normal” or “More than sufficient”, “Sufficient”, “Not

sufficient”, etc.

The third type of questions as an exception requires quantitative information as for example the

percent of the enterprise’s capacity utilization, where the replies are tabulated as “from” and “to” a

certain percent. Another quantitative question is related to the production assurance with orders

measured in number of months. The investment inquiry in industry also gathers quantitative

information about the investment plans of industrial enterprises.

Index construction

In order to use the variables from the business survey as short-term economic indicators, it is

necessary to transform the qualitative replies into quantitative indicators. The indicator which is

perceived as the most appropriate is called the balance of opinions. This indicator is a function of the

shares (percentages) of different variants of replies (P – positive (+), E – neutral (=), and M –

negative (-)), i.e.:

B = 1 x (P)% + 0 x (E)% - 1 x (M)%



CANADA

Name of survey

Index of Business Confidence

Source

The Conference Board of Canada

Frequency

Quarterly

Scope

Approximately 1,500 Canadian business organizations

Survey questions

1. Do you expect overall economic conditions in Canada six months from now to be better, same or worse?

2. Do you expect prices, in general, in Canada to increase over the next six months at an annual rate of how many percent?

3. Over the next six months, do you expect your firm's financial position to improve, worsen or remain the same?

4. Over the next six months, do you expect your firm's profitability to improve, worsen or remain the same?

5. Would you say the present is a good or a bad time to undertake expenditures to expand your plant or add to your stock of machinery and equipment?

6. What change in the level of your capital investment expenditures do you expect over the next 6 months?

7. In which region(s) of the country do you expect the bulk of your planned investment expenditures for the next six months to take place?

8. How do you assess your current level of operations relative to optimal capacity?

Index construction

Not available

CHILE

Name of survey

Business Confidence Survey

Source

Instituto Chileno de Administración Racional de Empresas (ICARE)

Frequency

Monthly

Scope

A panel of approximately 600 business executives from manufacturing, mining, construction and

trade industries

Survey questions

The questions include present and future view on general business conditions, production trend,

demand, inventory levels and employment situation.

Index construction

Confidence indicator generated by the survey is constructed from the response balances based

on the percentage of answers ("favourable", "unfavourable" and "neutral"). The balance of

responses is constructed as the difference between the percentage of favourable and unfavourable

responses, so that such balances are contained in the interval [-100; 100]. The balances are

presented in the form of diffusion rates, adding 100 to each balance and dividing the result by two.

This transformation allows all indicators to have positive values in the range [0; 100], with 50 being

the "neutral barrier." The total index is a weighted average of four sector-specific confidence

indicators (manufacturing, mining, construction, trade), with the weights corresponding to the share

of each sector in GDP.

CHINA

Name of survey

Business Climate Index

Source

National Bureau of Statistics of China

Frequency

Quarterly

Scope

The survey covers eight sectors: industry, construction, wholesale and retail trade, transportation,

storage and postal services, hotel and catering industry, information transmission, software and IT

services, real estate, and social services. The national total sample size is approximately 21,000

enterprises.

Survey questions

Survey involves questions on the business running, enterprises operation, profitability,

employment, investment, financing, inventory and other production and management problems.

Index construction

Business Climate Index = 0.4 × Current BCI + 0.6 × Expected BCI

Current BCI = the proportion of “positive” answers regarding the operating conditions in the

current quarter - the proportion of “negative” answers + 100

Expected BCI = the proportion of “positive” answers regarding the operating conditions in the next

quarter - the proportion of “negative” answers + 100

The index values range from 0 (when all respondents have negative confidence) to 200 (when all

respondents have positive confidence).

COLOMBIA

Name of survey

Business Opinion Survey

Source

Centro de Investigacion Economica y Social

Frequency

Monthly

Scope

Not available

Survey questions

Not available

Index construction



COSTA RICA

Name of survey

Pulso Empresial

Source

Unión Costarricense de Camaras y Asociaciones del Sector Empresial Privado (UCCAEP)

Frequency

Quarterly

Scope

Covers companies in agriculture, services, tourism, commerce, construction, industry and

financial sectors

Survey questions

The questionnaires contain questions regarding the expected and running business tendencies:

assessment of economic situation, demand, stocks, expected development of activity and

employment. Questions are put in the form of evaluation scales, mostly with five possible

alternatives of answers such as improvement, constancy, worsening, and the like.

Index construction

Each response for each variable in each sector is assigned a value. The minimum value is equal

to 0 (the answer “worse”); the maximum value is equal to 10 (the answer “better”). After that the

weighted average is calculated in each sector. Business Confidence Index is calculated for separate

sectors and the whole economy as well.

CROATIA

Name of survey


Source


Frequency

Monthly

Scope

A panel of 400 firms in manufacturing sector

Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







CZECH REPUBLIC

Name of survey

Business Cycle Surveys

Source

Czech Statistical Office

Frequency

Monthly

Scope

Covers companies in industry, construction, trade and selected services sectors

Survey questions

The questionnaires contain questions regarding the expected and running business tendencies:

assessment of economic situation, demand, stocks, expected development of activity and

employment. Questions are put in the form of evaluation scales, mostly with three possible

alternatives of answers such as improvement, constancy, worsening, and the like.

Index construction

Evaluation of the results is made as a summary of the questions in individual alternatives; a clear

expression of tendencies is business cycle balance, which is the difference between the answers

“improvement” and “worsening” expressed in percent. The higher the positive balance of answers

the more optimistic is the evaluation of the answer obtained.

The business confidence indicator is a weighted average of seasonally adjusted confidence

indicators in industry, construction, trade and in selected services. The confidence indicator for

industry is the average of seasonally adjusted balances of three indicators (the assessment of total

demand, assessment of stocks of final production (with inverted sign) and the expected

development of production activity). The confidence indicator for construction is the average of two

indicators (the assessment of total demand and the expected development of employment). The

confidence indicator for trade is the average of three indicators (the assessment of economic

situation, assessment of stocks (with inverted sign) and the expected development of economic

situation). The confidence indicator for selected services is the average of three indicators (the

assessment of economic situation, the assessment of demand and expected demand).



DENMARK

Name of survey

Industry Tendency Survey

Source

Statistics Denmark

Frequency

Monthly

Scope

The survey is based on returns from about 500 major manufacturing enterprises, representing just

over 50% of total employment in the sector and covering about 1,000 establishments (local units).

Survey questions

It is a characteristic feature of the method used that the management of the responding

enterprises should be able to answer the questions without any elaborate analysis, since they are

primarily requested to indicate by a checkmark whether a given economic variable, e.g. production is

up, largely unchanged or down for the survey period, compared to the preceding period. The

questions concern both future expectations and current judgment over the preceding period.

In answering other questions the responding enterprises are asked to measure, e.g. their stocks

of unfilled orders at the end of the period in relation to the normal situation. The respondents are

also requested to indicate any limits to total production activities, and if so, indicate the causes of

these.

Index construction

The results from each establishment are being weighted in relation to the size of employment of

the establishments. In distributing information over the groups of industries, the results are first

aggregated for establishments in the same industry group. Calculations are first made for some 35

industry groups. These are then weighted in relation to total employment for the groups and are then

distributed over 14 industry groups, 4 sectors and the total manufacturing industry.



ECUADOR

Name of survey

Business Opinion Survey

Source

Banco Central del Ecuador

Frequency

Monthly

Scope

The survey covers a sample of companies in trade, construction, industrial and service sectors.

Survey questions

The questions cover present and expected situation with regard to business conditions, sales

volume, employment situation, selling prices, new orders etc.

Index construction

For each sector, the sum of the responses for each question is calculated, with each company’s

answer weighted by its share in total industry revenue. The total index is calculated as a weighted

average of all sector indicators, with weights assigned according to the share of each sector in the

Gross Domestic Product for year 2005.

ESTONIA

Name of survey


Source


Frequency

Monthly

Scope

A panel of 275 firms in manufacturing sector

Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







FINLAND

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 700 firms in manufacturing sector

Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







FRANCE

Name of survey

Business Climate Survey

Source

National Institute of Statistics and Economics Studies

Frequency

Monthly

Scope

The survey covers manufacturing, construction, retail, wholesale and services industries in

metropolitan France.

Survey questions

The 26 balances of opinion that compose confidence index are:

• Manufacturing industry survey: general prospects, past production trend, expected production

trend, stock levels, foreign order books, overall order books

• Services survey: past turnover trend, expected turnover trend, general prospects, expected

demand, past operating income trend, expected operating income trend

• Building survey: past activity trend, expected activity trend, level of order books, past workforce

trends, production capacity utilization

• Retail survey: overall order books, general prospects, past sales trend, expected staffing trend

• Wholesale trade survey: past sales trend, past foreign sales trend, ordering intentions, general

prospects, deliveries received from abroad

Index construction

The business climate indicator describes the common component of the selected balances of

opinion in a single variable. It is constructed using factor analysis techniques. This makes it possible

to summarise the concomitant trends of several variables whose movements are highly correlated.

Changes in the business climate composite indicator summarize the cyclical phase affecting the

different balances of opinion from the tendency surveys: the higher its value, the more industrialists

consider the outlook to be favourable.

The methodology used is based on a representation in the form of an unobserved components

model: in each month t, each balance of opinion is expressed as the sum of two unobserved

components, a term proportional to the common factor and a component specific to the balance of

opinion considered, also known as the residual. The index is standardized to have a mean of 100

and a standard deviation of 10.

GEORGIA

Name of survey

ISET Business Confidence Survey

Source

ISET Policy Institute

Frequency

Quarterly

Scope

Business confidence for Georgia is measured by seven sector-specific indices focusing on 1)

services, 2) retail trade, 3) agriculture, 4) manufacturing industry, 5) financial service 6) construction

and 7) other sectors. For each sector, confidence is measured through a simple survey instrument

targeted at top business executives.

Survey questions

Business confidence index is calculated as a weighted average of the balances induced from all

the answers about production/sales/turnover, competition, order books, volume of stock, demand

evaluation, operation costs, profit, employment, and sales price setting.

Index construction

Answers obtained from the surveys are aggregated in the form of "balances". Balances are

constructed as the difference between the percentages of respondents giving positive and negative

replies. Using this method, a Confidence Index of +100 would indicate that all survey respondents

were much more confident about future prospects, while -100 would indicate that all survey

respondents were much less confident about future prospects.

The methodology of compiling the indices is based on the Joint Harmonised EU Programme of

Business and Consumer Surveys.

GERMANY

Name of survey

Business Climate Survey

Source

CESifo Group Munich

Frequency

Monthly

Scope

The Ifo Business Climate Index is based on about 7,000 monthly survey responses of firms in

manufacturing, construction, wholesaling and retailing.

Survey questions

The firms are asked to assess their current business situation and their expectations for the next

six months. They can characterize their situation as "good", "satisfactory" or "poor" and their

business expectations for the next six months as "more favourable", "unchanged" or "more

unfavourable".

Index construction

The balance value of the current business situation is the difference of the percentages of the

responses "good" and "bad"; the balance value of the expectations is the difference of the

percentages of the responses "more favourable" and "unfavourable". The Business Climate Index is

the mean of the balances of business situation and expectations.



GREECE

Name of survey


Source


Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







HONG KONG, CHINA

Name of survey

Business Tendency Survey

Source

Census and Statistics Department of Hong Kong

Frequency

Quarterly

Scope

The survey gathers views on short-term business performance from the senior management of

about 500 to 600 prominent establishments in ten major sectors in Hong Kong: manufacturing,

construction, import/export trade and wholesale, retail, accommodation and food services (mainly

covering services rendered by hotels and restaurants), transportation, storage and courier services,

information and communications, financing and insurance, real estate and professional and

business services sectors.

Survey questions

The survey solicits views from respondents regarding expected changes of a number of economic

variables (including business situation, volume of business/output, number of persons engaged and

selling price/service charge), situation regarding orders and inventories, as well as factors limiting

increase in business activities. Views collected refer only to those of respondents on their own

establishments rather than those on the respective sectors they are engaged in; and are limited to

the expected direction of quarter-to-quarter change (e.g. "up", "same" or "down") but not the

magnitude of change. In collecting views on the quarter-to-quarter changes, if the variable in

question is subject to seasonal variations, respondents are asked to provide the expected changes

after excluding the normal seasonal variations.

Index construction

In compiling the survey results, the percentages of establishments choosing individual response

categories within each stratum, which is mainly at industry grouping level, are first computed to

arrive at stratum estimates. These stratum estimates are then weighted and summed up to give the

percentages of establishments choosing individual responses for the corresponding sectors. Overall

estimates are weighted averages of all sectorial estimates. Weights for the variable on employment

are "number of persons engaged" of various strata, while weights for all other variables are "value

added".

Survey results are presented as "net balance", i.e. the difference between the percentage of

respondents choosing "up" and that choosing "down". The percentage distribution of respondents

among various response categories (e.g. "up", "same" and "down") reflects how varied their

business expectations are. The "net balance", with its appropriate sign, indicates the direction of

expected change in the variable concerned. A positive sign indicates a likely upward trend while a

negative sign, a likely downward trend. However, the magnitude of the "net balance" reflects only

the prevalence of optimism or pessimism but not the magnitude of expected change, since

information relating to such magnitude is not collected in the survey.



HUNGARY

Name of survey

Business Cycle Survey

Source

GKI Economic Research Co.

Frequency

Monthly

Scope

Based on 1,300 questionnaires, GKI Co. prepares surveys on the business cycle in industry, retail

trade, construction and services sectors.

Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)






products (the last with inverted sign). Balances are seasonally adjusted.

INDIA

Name of survey

Business Outlook Survey

Source

Confederation of Indian Industry

Frequency

Quarterly

Scope

Business Outlook Survey is based on a large sample size of 250 companies covering all industry

sectors, including small, medium and large enterprises from different regions. The survey also

enumerated responses across industry groups both in public and private sectors engaged in

manufacturing and services sector.

Survey questions

Indices are based on three questions on the performance of the economy, respondent’s industry

and respondent’s company. Respondents are asked to rate the current and expected performance

on a scale of 0 to 100. A score above 50 indicates positive confidence while a score above 75

indicates strong positive confidence.

Index construction

Business confidence index is calculated as a weighted average of the Current Situation Index

(CSI) and the Expectation Index (EI), with greater weight given to EI as compared to CSI. In the

construction of the two sub-indices, the highest weight is given to the questions related to the

performance of the individual company, and the lowest weight is assigned to the questions on the

economy. The weights are assigned on the basis of the premise that the average respondent would

possess more detailed and accurate knowledge on the current and expected performance of their

own company than the economy as a whole.

INDONESIA

Name of survey

Business & Consumer Tendency Survey

Source

Badan Pusat Statistik (Statistics Indonesia)

Frequency

Quarterly

Scope

Not available

Survey questions

Not available

Index construction

Business Tendency Index consists of two types of indicators: Current Situation Index and Future

Expectations Index.



IRELAND

Name of survey

SME Business Trends

Source

Irish Small and Medium Enterprises Association

Frequency

Quarterly

Scope

Not available

Survey questions

Not available

Index construction



ISRAEL

Name of survey


Source

Central Bureau of Statistics of Israel

Frequency

Monthly

Scope

Covers businesses in the industry, construction, retail trade, hotels and services sectors.

Survey questions

Questionnaires include questions on present and expected view on business conditions, financial

situation, capacity utilization, volume of sales/production, stocks, employment situation, order books

etc.

Index construction



ITALY

Name of survey

Business Confidence Survey

Source

The Italian National Institute of Statistics

Frequency

Monthly

Scope

The survey conducted on a panel that currently includes about 4,000 companies. It covers

industry, construction, services and retail trade sectors.

Survey questions

The survey questionnaire includes questions designed to obtain qualitative information on the

current status and short-term expectations in terms of orders, production and stocks of finished

goods, cash, employment, prices, and an assessment of the general trend of the Italian economy.

Index construction

The indicator of confidence is developed as the average of seasonally adjusted data related to

questions regarding opinions on the level of total orders, the level of stocks (with inverted sign) and

the short-term expectations on production. The index is rebased to 2010=100.

JAPAN

Name of survey

Short-Term Economic Survey of Enterprises in Japan

Source

Bank of Japan

Frequency

Quarterly

Scope

The population of the survey is approximately 210 thousand private enterprises (excluding

financial institutions) in Japan with at least 20 million yen in capital.

Survey questions

The survey covers topics such as business conditions, domestic and foreign supply and demand,

inventory levels, production capacity, employment conditions, financial position, credit conditions.

Index construction

Responses are aggregated into Diffusion Index (DI) as follows:

DI (percent points) = Percentage share of enterprises responding positively – Percentage share of

enterprises responding negatively.



LATVIA

Name of survey


Source


Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







LITHUANIA

Name of survey


Source


Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







MACEDONIA

Name of survey


Source


Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







MALAYSIA

Name of survey

Business Conditions Survey

Source

Malaysian Institute of Economic Research

Frequency

Quarterly

Scope

The survey covers a sample of over 350 manufacturing businesses incorporated locally and

foreign manufacturing concerns operating in Malaysia, covering 11 industries.

Survey questions

Questions posed in the survey questionnaire are based on key determinants such as production

level, new order bookings, sales performance, inventory build-up and new job openings.

Index construction



MEXICO

Name of survey

Monthly Survey of Business Opinion

Source

Instituto Nacional de Estadística, Geografía e Informática (INEGI)

Frequency

Monthly

Scope

The sample is a stratified random selection of a number of companies in the manufacturing

sector.

Survey questions

The questionnaire includes questions that measure the economic activity through five exclusive

response alternatives for each variable: much higher, somewhat higher, equal, somewhat lower and

much lower, while those related to the economic environment are captured by the response options

much better, somewhat better, same, somewhat worse and much worse.

Information is collected for the following variables: production; use of plant and equipment; total

orders; domestic demand; external demand (exports); inventories of supplies; delivery of inputs;

timeliness of delivery of inputs; inventories of finished goods; sales prices; input prices; investment;

employed personnel; expectations of the exchange rate and inflation; situation of the country today,

compared to twelve months ago; situation of the country within twelve months, compared to the

current; status of the company today, compared to twelve months ago; status of the company within

twelve months, compared to the current.

Index construction

For each question, a response rate is calculated, which is then multiplied by the weighting

assigned. The total index is a simple average of all component indicators.



NETHERLANDS

Name of survey

Producer Confidence Survey

Source

Statistics Netherlands

Frequency

Monthly

Scope

The sample covers companies in the manufacturing industry.

Survey questions

The questions concern the expected activity in the next three months, opinion on order books and

opinion on stocks of finished products.

Index construction

The indicator is a weighted arithmetic average of three component indicators from the Business

sentiment survey of the manufacturing industry. Before the Producer confidence is calculated,

seasonal and bias effects are removed from the three component indicators.



NEW ZEALAND

Name of survey

Business Outlook Survey

Source

ANZ Bank New Zealand

Frequency

Monthly

Scope

The Business Outlook is a monthly survey with around 500 respondents. Each firm self-selects its

business sector, region of residence, and firm size.

Survey questions

The survey covers questions on the present and expected future situation regarding the general

business conditions, employment, selling prices, investment activities, capacity utilization, credit

conditions etc.

Index construction

Although the survey itself is qualitative in nature, the reported statistic for each question is a single

net balance number. That is, for each question the respondent is asked to indicate ‘improved’ or

‘increased’, ‘deteriorated’ or ‘decreased’, or ‘remain the same’. The responses are then converted

into a net balance statistic via the calculation:

where i is the number of ‘improved’ responses; d is the number of ‘deteriorated’ responses; rts is

the number of ‘remain the same’ responses.



NIGERIA

Name of survey

Business Expectations Survey

Source

Central Bank of Nigeria

Frequency

Quarterly

Scope

Respondents are drawn from the companies in the industrial, construction, wholesale/retail trade

and services sectors.

Survey questions

Not available

Index construction

The Confidence Index is computed as the percentage of firms that answered affirmatively less the

percentage of firms that answered negatively with respect to their view on a given indicator. A

positive Confidence Index indicates a favourable view, except for the average inflation rate and the

average naira borrowing rate, while a negative Confidence Index indicates the opposite.



NORWAY

Name of survey


Source

Statistics Norway

Frequency

Quarterly

Scope

The gross sample includes about 800 units and represents about 3.5 per cent of the total

population of branch units. The sample units cover about 40 per cent of the total level of

employment for the industries covered by the survey. The sample includes all branch units with 300

employees or more. The remaining units are drawn by methods based on stratification and optimal

allocation with probability proportional to the size of the unit measured by the number of employees.

The sample does not include establishments with fewer than 10 employees. The survey covers all

branch units in mining, quarrying and manufacturing.

Survey questions

Not available

Index construction

Employment weighted results (response distribution) are calculated for each question. The

sample units are classified in different strata depending on the number of employees in the branch

unit and in which industry they belong to (3-digit NACE). For each question by stratum a response

distribution is estimated using employment data as weights. The response for each branch unit is

given a weight equal to the number of employees. For aggregation to the industrial group level and

totals, the stratum results carry a weight equal to the stratum population employment.



PERU

Name of survey

Índice de confianza empresarial (Business Confidence Index)

Source

Banco Central de Reserva del Perú

Frequency

Monthly

Scope

Not available

Survey questions

Not available

Index construction

The index is constructed as a diffusion index, with values above 50 indicating positive confidence

and values below 50 – negative confidence. The index reflects the business managers’ expectations

about the state of economy in the next three months.

PHILIPPINES

Name of survey


Source

Central Bank of Philippines

Frequency

Quarterly

Scope

The Business Expectations Survey uses the stratified random sampling design covering

corporations from the SEC’s Top 7000 Corporations (ranked based on gross revenues) as sampling

units.

Survey questions

Not available

Index construction

The Confidence Index is computed as the percentage of firms that answered affirmatively less the

percentage of firms that answered negatively with respect to their views on a given indicator. A

positive Confidence Index indicates a favourable view, except for the inflation rate and the peso-

borrowing rate, while a negative Confidence Index indicates the opposite.



POLAND

Name of survey


Source

Central Statistical Office of Poland

Frequency

Monthly

Scope

3,500 manufacturing entities pertaining to C section according to the Polish Classification of

Activities (PKD 2007) compiled on the basis of NACE Rev.2; 5,000 entities carrying out construction

and assembly activities pertaining to F section according to PKD 2007 compiled on the basis of

NACE Rev.2.; 5,200 entities representing retail trade activities pertaining to G section (divisions 45

and 47) according to PKD 2007 compiled on the basis of NACE Rev.2.; 5,000 entities carrying out

service activities pertaining to sections from H to S (without O section ) according to PKD 2007

compiled on the basis of NACE Rev.2.

Survey questions

The questionnaires cover questions related to the basic features of economic situation in

manufacturing, construction, retail trade and services:

• Manufacturing – current overall order books, current stock of finished products, expected

production;

• Construction – current overall order books, expected employment;

• Retail trade – business activity (sales) in the past 3 months, volume of stock, expected business

activity;

• Services – business situation in the past 3 months, demand in the past 3 months, expected

demand.

Index construction

Indicators for each economy sector are calculated as a standardized arithmetic average of

selected (seasonally adjusted) two (construction) or three balances of answers (other business

tendency surveys). For computation of the synthetic indicator particular weights are allocated to the

different sectors – manufacturing industry (50%), services (38%), retail trade (6%), construction

(6%).

PORTUGAL

Name of survey

Business and Consumer Survey

Source

National Institute of Statistics of Portugal

Frequency

Monthly

Scope

All enterprises with over 200 employed persons are included in the sample; companies with below

200 employed persons are stratified by size of companies with the Neyman (optimum) allocation.

Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







QATAR

Name of survey

Dun & Bradstreet’s Business Optimism Index – Qatar

Source

Dun & Bradstreet

Frequency

Quarterly

Scope

A random sample is selected from Dun & Bradstreet’s commercial database for conducting this

survey. This sample is divided into hydrocarbon and non-hydrocarbon segments to eliminate the

dominance of the former over the latter and understand their dynamics individually. The hydrocarbon

segment includes Qatar’s mining, oil and gas companies whereas the non-hydrocarbon segment

encapsulates in its purview the following sectors:

• Manufacturing (90 units)

• Construction (110 units)

• Trade & Hospitality (80 units)

• Transport & Communications (65 units)

• Finance, Real Estate & Business Services (115 units)

Survey questions

The survey respondents are asked if they expect an increase, decrease or no change regarding

the following parameters: volume of sales, net profits, level of selling prices, new orders received,

level of stock, and number of employees.

Additional poll questions are asked relating to the current economic scenario and are aimed at

gauging the business sentiments with regards to several key current issues.



Index construction

Not available

ROMANIA

Name of survey


Source


Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







RUSSIA

Name of survey

Business Confidence Index

Source

Federal State Statistics Service

Frequency

Monthly

Scope

A sample of over 4,000 companies (except for small enterprises) in the manufacturing, mining and

quarrying, electricity, gas and water supply industries

Survey questions

The questions cover the expected output, actual demand and stocks of production on hand.

Index construction

The total index is an arithmetic average of balances of all the survey questions. The balance is

calculated as the difference between positive (“up”, “better” etc.) and negative (“down”, “worse” etc.)

answers.



SAUDI ARABIA

Name of survey

Business Optimism Index

Source

Dun & Bradstreet

Frequency

Quarterly

Scope

A sample of companies in non-hydrocarbon sector (manufacturing, construction, trade and

hospitality, transportation, finance and business services)

Survey questions

The questions cover the expected volume of sales, net profit, level of selling prices, new orders

received, level of stock and number of employees.

Index construction

The individual indices for each of the parameters (volume of sales, net profit, level of selling

prices, new orders received, level of stock and number of employees) are calculated by subtracting

the percentage of respondents expecting decrease from those expecting increase. A composite

index is then calculated, capturing the aggregate weighted behaviour of all the six individual indices

in the non-hydrocarbon sector.

SINGAPORE

Name of survey


Source

Statistics Singapore

Frequency

Quarterly

Scope

A sample of companies in the manufacturing sector

Survey questions

Surveyed establishments are asked to indicate their expectation of general business conditions

and other indicators such as output and employment. Their views are expressed in terms of

directional change (i.e. “up”, “same” or “down).

Index construction

Individual responses provided by the establishments are weighted by their contribution to

employment and value added. These responses are then aggregated at cluster, sub-cluster and

overall manufacturing level, and presented in terms of weighted percentages. The net weighted

balance is commonly used to reflect the direction and extent of the business sentiments. It is the

difference between the weighted percentage of 'up' responses and the weighted percentage of

'down' responses. For example, if weighted responses for overall manufacturing output yields a net

weighted balance of +30 per cent, the plus sign before the percentage figure indicates a positive

balance or net upward movement, and not a 30 per cent increase in output. Similarly, a minus sign

before the percentage indicates a downward trend and not a decline by that amount.



SLOVAKIA

Name of survey

The Economic Sentiment Indicator

Source

Statistical Office of the Slovak Republic

Frequency

Monthly

Scope


Survey questions







Index construction









B = P - M








B = (PP + 1⁄2 P) - (1⁄2 M + MM)







SLOVENIA

Name of survey


Source

Statistical Office of the Republic of Slovenia

Frequency

Monthly

Scope

The panel includes all large enterprises and share of medium and small enterprises in

manufacturing sector.

Survey questions

The questions cover the present and expected situation on order books, production pace, stocks,

selling prices, employment situation, demand, capacity utilization.

Index construction

The results are shown as the balance of individual questions. The balance is the difference

between positive and negative answers expressed in percentage. The balance shows the movement

of observed economic variables (present situation and future expectations).

The confidence indicator in manufacturing is defined as the arithmetic mean of the balances to the

questions on production expectation, assessment of overall order books and assessment of stocks

of finished products (the latter with inverted sign).



SOUTH AFRICA

Name of survey

RMB/BER Business Confidence Index

Source

Bureau for Economic Research

Frequency

Quarterly

Scope

The survey results are obtained from questionnaires completed by senior executives in the trade,

manufacturing and building sector. Questionnaires are sent to 1,400 senior executives in the

building sector, 1,400 in the trade sector and 1,000 in manufacturing.

Survey questions

The business survey questionnaire contains a small number of questions. These questions are

qualitative in nature, e.g. “Compared to the same quarter a year ago, are the volume of sales up, the

same or down?”. No figures are requested.

Index construction



SOUTH KOREA

Name of survey

Business Survey Index

Source

The Bank of Korea

Frequency

Monthly

Scope

The survey covers 2,862 corporations in various industries which are selected using stratified

systematic sampling

Survey questions

Items surveyed: business conditions (overall conditions), inventories, facilities investment,

production facilities, labour force situation, new orders, production, sales (domestic and exports),

capacity utilization, sales prices, raw material purchase prices, profitability, financial situation,

operational difficulties.

Index construction

The survey responses are translated into indices in accordance with the following formulas:

Where:

ωi – each sub-sector’s GDP weight

BSIi – each sub-sector’s BSI

SPAIN

Name of survey

Business Confidence Indicator

Source

National Statistics Institute of Spain

Frequency

Quarterly

Scope

The sample is comprised of about 8,000 establishments.

Survey questions

Not available

Index construction

The following indicators are published from the question regarding performance of business in the

establishment:

1. Harmonised situation indicator: Situation balance (difference between the % of positive and negative responses). This is abbreviated as "Situation”.

2. Harmonised expectation indicator: Balance of expectations (difference between the % of positive and negative responses). This is abbreviated as "Expectations”.

3. Harmonised Business Confidence Index (HBCI): Geometric average of the situation balance and expectations, suitably standardising the results.

Details of the calculation for each quarter would be specifically as follows:

Confidence may, therefore, fluctuate between the extremes of -100 and +100. When rebased to

Q1 2013=100 according to the source methodology, the index ranges are approximately [66; 198].

SWEDEN

Name of survey

Monthly Business Tendency Survey

Source

National Institute of Economic Research of Sweden

Frequency

Monthly

Scope

Each month, around 6,000 firms are interviewed. Sampling of firms takes place through the

Business Register of Statistics Sweden and is renewed each year. This is done by replacing some

firms while all firms are assigned new weights. Firms with more than 100 employees are used

permanently for all surveys. Samples are stratified by size and industry.

Survey questions

The survey covers the present and expected future situation in business conditions, including

demand, output volume, new orders, inventories, selling prices, employment situation.

Index construction

Survey responses are processed by the sample's industry and stratum (size category) by

weighing the response of each firm by company size. The weights vary depending on the question

and industry. For the manufacturing industry, value added is the main weight used, but the number

of employees is also used for questions referring to employment. For the construction industry, the

retail trade and service sectors, the number of employees is used. The weights for the various

response alternatives are subsequently totalled for each stratum. Before the responses are totalled

by industry, the different size categories are weighted relative to the population. While calculating

the confidence indicators, the net balances for the questions are seasonally adjusted and

transformed (standardised) so that they have the same mean and standard deviation. In the next

step, these seasonally-adjusted and standardised net balances are averaged. This standardisation

process avoids movements in the confidence indicators being dominated by the questions that

historically vary the most. Finally, the confidence indicators are standardised to a mean of 100 and a

standard deviation of 10.

SWITZERLAND

Name of survey

Switzerland Business Tendency Survey in Manufacturing

Source

OECD

Frequency

Monthly

Scope

The sample comprises 1600 enterprises and the response rate is 80%. The manufacturing

industries are covered by the survey. The survey covers 22% of total employment in the

manufacturing sector.

Survey questions

Not available

Index construction

Data is presented as the balance of positive ("will increase", "increased", "too large") over

negative ("will decrease", "decreased", "too small") replies expressed as a percentage of total

replies. Responses are weighted according to the number of persons engaged in the production

process. The replies to questions relating to economic activity on the domestic market or abroad are

weighted by the corresponding shares of enterprises on each of these two markets. The indicator for

the whole industry is obtained by weighting each industry branch indicator, the weight being the

share of the branch in the total value added.



THAILAND

Name of survey

Business Expectation Index

Source

Bureau of Trade and Economic Indices of Thailand

Frequency

Quarterly

Scope

Sample includes companies from various business branches, 30 samples per province.

Survey questions

Topics covered in the survey include:

• General business situation

• Business situation in the same sector

• Results of business operations

• Cost per unit of goods or services

• Employment situation

• Expansion of organization

In each topic, there are three types of questions:

• Compare present quarter of this year with the same quarter last year

• Compare present quarter with previous quarter of the present year

• Forecast next quarter

Index construction

Calculation steps:

1. Raw data is translated to quantity data. For answers “better/increase”, score is 1; for “unchanged”, score is 0.5; for “worse/decrease”, score is 0.

2. The estimated percentage is used to calculate the index according to the formula:

Index = % of answers “better” + (% of answers “unchanged” / 2)

The index can vary from 0 to 100, with the score of 50 meaning that the business is expected to

remain unchanged.

TURKEY

Name of survey

Real Sector Confidence Index

Source

Central Bank of the Republic of Turkey

Frequency

Monthly

Scope

The survey covers opinions of senior managers of the major private sector firms.

Survey questions

The questions cover topics on the present and expected situation of production, demand,

investment, sales, employment, capacity utilization and inflation expectations.

Index construction

The responses which are in the form of “more optimistic, the same, more pessimistic” or “up, the

same, down” are coded. The responses indicating improvement (better off) for a particular variable

are scored 1, while the responses showing no change are scored 0, and the responses showing a

worsening condition are scored -1. The questions affecting the industrial production index positively

are coded in the same direction, while those affecting adversely are coded in the reverse direction.

The diffusion index is then constructed by summing up the related encoded responses obtained

from the respondent firms.

There is no need for trend adjustment since the diffusion indexes formed by the survey data

display cyclical patterns. While choosing the appropriate questions, the economic significance is

considered, as well as the statistical methods such as the performance for leading the industrial

production index, low volatility and cross correlation. The composite index is calculated as the

equally weighted average of the sub-indices in line with the applications in the EU countries. No

base-year adjustment has been made to the index.



UNITED ARAB EMIRATES

Name of survey

Dubai Business Survey

Source

Department of Economic Development

Frequency

Quarterly

Scope

The sample includes a mix of small, medium and large enterprises in the Emirate of Dubai,

ensuring adequate representation from manufacturing, trading and services, proportionately to their

respective contributions to Dubai’s GDP.

Survey questions

In order to tap “business outlook” or expectations, the survey focuses on key indicators, such as

sales, selling prices, volumes sold, profits and number of employees. Respondents are asked to

indicate if they expected an “increase”, “decrease” or “no change” in these indicators.

Index construction

The Business Confidence Index (BCI) is calculated as a weighted average score of the following

“business outlook” indicators:

1. Selling Prices 2. Volumes Sold 3. Number of Employees 4. Profits

For each indicator, “resulting scores” are calculated using the net balance method: (% of positive

responses - % of negative responses) + 100. For the Composite Business Confidence Index, the

resulting scores are multiplied with their corresponding weights to arrive at a weighted average

Index score. This index is finally rebased so that Q2, 2011 = 100. Taking account of the economy’s

composition by firm size, the index is weighted by the relative contributions of SMEs and large

businesses to Dubai’s GDP. The final result is the following index:

Overall Index = 60% x (Large enterprise Index) + 40% x (SME Index).

UNITED KINGDOM

Name of survey

BDO Monthly Business Trends

Source

BDO

Frequency

Monthly

Scope

Over 4,000 different respondents from companies in a range of different industries

Survey questions

Not available

Index construction

The indices are calculated by taking a weighted average of the results of the UK main business

surveys. It incorporates the results of the quarterly CBI Industrial Trends Survey (and the CBI

Monthly Trends Enquiry which is carried out in the intervening months); the Bank of England Agents’

summary of business conditions; and the Chartered Institute of Purchasing and Supply’s Surveys of

Manufacturing and of Services.

The surveys are weighted together by a three-stage process. First, the results of each individual

survey are correlated against the relevant economic cycles for manufacturing and services. This

determines the extent of the correlations between each set of survey results and the relevant timing

relationships. Then the surveys are weighted together based on their scaling, on the extent of these

correlations and the timing of their relationships with the relevant reference cycles. Finally, the

weighted total is scaled into an index with 100 as the mean, the average of the past two cyclical

peaks as 110 and the average of the past two cyclical troughs as 90.

USA

Name of survey

Small Business Economic Trends

Source

National Federation of Independent Business

Frequency

Monthly

Scope

Survey respondents are drawn from NFIB's membership

Survey questions

• Do you think the next three months will be a good time for small business to expand

substantially? Why?

• About the economy in general, do you think that six months from now general business

conditions will be better than they are now, about the same, or worse?

• Were your net earnings or “income” (after taxes) from your business during the last calendar

quarter higher, lower, or about the same as they were for the quarter before?

• If higher or lower, what is the most important reason?

• During the last calendar quarter, was your dollar sales volume higher, lower, or about the same

as it was for the quarter before?

• Overall, what do you expect to happen to real volume (number of units) of goods and/or services

that you will sell during the next three months?

• How are your average selling prices compared to three months ago?

• In the next three months, do you plan to change the average selling prices of your goods and/or

services?

• During the last three months, did the total number of employees in your firm increase, decrease,

or stay about the same?

• If you have filled or attempted to fill any job openings in the past three months, how many

qualified applicants were there for the position(s)?

• Do you have any job openings that you are not able to fill right now?

• In the next three months, do you expect to increase or decrease the total number of people

working for you?

• Over the past three months, did you change the average employee compensation?

• Do you plan to change average employee compensation during the next three months?

• Are loans easier or harder to get than they were three months ago?

• During the last three months, was your firm able to satisfy its borrowing needs?

• Do you expect to find it easier or harder to obtain your required financing during the next three

months?

• If you borrow money regularly (at least once every three months) as part of your business

activity, how does the rate of interest payable on your most recent loan compare with that paid three

months ago?

• If you borrowed within the last three months for business purposes, and the loan maturity

(payback period) was 1 year or less, what interest rate did you pay?

• During the last three months, did you increase or decrease your inventories?

• At the present time, do you feel your inventories are too large, about right, or inadequate?

• Looking ahead to the next three months to six months, do you expect, on balance, to add to your

inventories, keep them about the same, or decrease them?

• During the last six months, has your firm made any capital expenditures to improve or purchase

equipment, buildings, or land?

• If [your firm made any capital expenditures], what was the total cost of all these projects?

• Looking ahead to the next three to six months, do you expect to make any capital expenditures

for plant and/or physical equipment?

• What is the single most important problem facing your business today?

• Please classify your major business activity, using one of the categories of example below

• How many employees do you have full and part-time, including yourself?

Index construction

Not available

6. CONSUMER CONFIDENCE INDICES: METHODOLOGY & SOURCES

ALGERIA

Name of survey

Bayt.com Middle East Consumer Confidence Index

Source

Bayt.com

Frequency

Quarterly

Scope

Adult males and females aged 18 plus years

Survey questions

The survey questions include topics such as current and future views on personal financial

situation, country’s economy, business conditions, job availability and satisfaction.

Index construction



ARGENTINA

Name of survey

Consumer Confidence Index (Indice de Confianza del Consumidor)

Source

Universidad Torcuato di Tella

Frequency

Monthly

Scope

Households from Capital Federal, Interior and Gran Buenos Aires.

Survey questions

1. How is your personal economic situation in relation to the past year: would you say it got

better, stayed equal or got worse?

2. What do you think would happen to your economic situation one year from now: will it get

better, stay equal or get worse?

3. What will the economic situation of the country be one year from now: better, stay equal or

be worse than now?

4. What will the economic situation of the country be three years from now: better, stay equal

or be worse than now?

5. Do you think this is a good time to make purchases let's say of white goods: yes/no/don’t

know?

6. Do you think this is a good time to make more important purchases like cars, or to move

home: yes/no/don’t know?

Index construction

For each question, the options Better/Yes are considered "positive" answers, and the options

Worse/No are considered "negative" answers. The Index for each question is based on the

proportion of "positive" answers (p) and "negative" answers (n) out of the total number of individuals

surveyed. According to the formula below, a "positive" answer takes a value of 100 and a "negative"

answer takes a value of 0:

Partial Index = 50 * {p - n + 1}

Once the Partial Index is calculated, the results for the two questions of each category are

averaged and the three results are averaged again to obtain a regional average, which are

compounded to obtain a national average according to the following formula:

National Index = IndexCapital * 0.1667 + IndexInterior * 0.3666 + IndexGBA * 0.4667



AUSTRALIA

Name of survey

Consumer Sentiment Index

Source

Melbourne Institute of Applied Economic and Social Research

Frequency

Monthly

Scope

In most months the survey covers 1,200 people stratified by sex and location. In the third month of

each quarter, ie March, June, September and December, 1,410 people are surveyed.

Survey questions

The five questions include people’s assessment of:

1. Current family finances compared to a year ago;

2. Family finances over the coming 12 months;

3. Economic conditions in Australia over the coming 12 months;

4. Economic conditions in Australia over the next five years;

5. Whether it is a good or bad time to buy major household items.

Index construction

Each question can be represented by an index that is equal to the per cent of optimists minus per

cent of pessimists plus 100. The Consumer Sentiment Index is an average of the five component

indices. The index is transformed so that its average since 1980 is 100. The data are seasonally

adjusted.

AUSTRIA

Name of survey

The Joint Harmonized EU Consumer Confidence Indicator

Source


Frequency

Monthly

Scope

Random sample of 1,500 Austrian households

Survey questions

The Joint Harmonized EU Consumer Confidence Indicator is based on answers to four questions:

1. How do you expect the financial position of your household to change over the next 12

months?

2. How do you expect the general economic situation in this country to develop over the

next 12 months?

3. How do you expect the number of people unemployed in this country to change over the

next 12 months?

4. Over the next 12 months, how likely is it that you will save any money?

Index construction

The Joint Harmonized EU Consumer Confidence Indicator is based on answers to four questions

with five answer alternatives to each question (a lot better, a little better, the same, a little worse, a

lot worse). The index is constructed with double weights on the extremes. Responses “a lot better”

and “a lot worse” get the weight 1 and “a little better” and “a little worse” get the weight 1/2, and “the

same” has zero weight. Values range from −100, when all respondents choose the most negative

option, to +100, when all respondents choose the most positive answers.

BELGIUM

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,600 Belgian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







BRAZIL

Name of survey

Consumer Confidence Index (Indice de Confiança do Consumidor)

Source

Fundação Getulio Vargas

Frequency

Monthly

Scope

Households in the main urban centres.

Survey questions

Current Situation:

1. Situation of the local economy;

2. Financial situation of the family.

Expectations:

3. Situation of the local economy;

4. Purchase intention;

5. Financial situation of the family.

Index construction

The Consumer Confidence Index comprises 1) the Index of the Current Situation and 2) the Index

of Expectations, for the respective timeframe.

The formula for the calculation is the following:

Where:

i =1,....,5 represents each of the 5 questions

RFi = Favourable responses to the question "i"

RDi = Unfavourable responses to the question "i"

This number is rebased to 2005=100.

BULGARIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,000 Bulgarian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







CANADA

Name of survey

Index of Consumer Confidence

Source

The Conference Board of Canada

Frequency

Monthly

Scope

Random sample of Canadian households across provinces.

Survey questions

Data is collected on each respondent's age, sex, marital status, occupation and geographic

location of residence. The four questions are:

1. Considering everything, would you say that your family is better or worse off financially

than six months ago?

2. Again, considering everything, do you think that your family will be better off, the same

or worse off financially six months from now?

3. How do you feel the job situation and overall employment will be in this community six

months from now?

4. Do you think that right now is a good or bad time for the average person to make a

major outlay for items such as a home, car or other major item?

Index construction

The percentage of respondents who stated positive and negative opinions is calculated by

question for each of the socio-economic and regional classifications as well as for the national

aggregate. Positive (negative) opinions are beliefs that a consumer's financial situation improved

(worsened) over the past six months or will improve (get worse) over the next six months, that more

(less) jobs will be available over the near term or that it is a good (bad) time to make a major

purchase.

Each Index of Consumer Confidence is then derived by adding the percentage of positive

responses, subtracting the percentage of negative responses, adding a scalar equal to 400 and

indexing the resulting series to a base year of 2002. The scalar is introduced to force the value of

the Index to zero if all responses are negative.

CHILE

Name of survey

Index of Economy Perception (Índice de Percepción de la Economía)

Source

Adimark GfK

Frequency

Monthly

Scope

Random sample of over 1,000 households living in the major cities of Chile

Survey questions

1. Would you say that the economic situation of you and your family is better, worse or the

same as a year ago?

2. Speaking of the country as a whole, would you say that the current economic situation of

the country is good, fair or poor?

3. Within the next 12 months, do you think that the economic situation of the country will be

good, fair or poor?

4. What do you think will most likely happen with the economic situation of the country in the

next five years?

5. Would you say that we are currently in a good time or a bad time to buy household items?

Index construction

The percentage of "positive" and "negative" answers for each question is counted. A score for

each question is calculated with the following procedure: the percentage of negative responses is

subtracted from the percentage of positive responses, and 100 are added to the result. This is in

order to avoid negative numbers occurring when the negative response rate is higher than the

percentage of positive responses. Then the scores to the 5 questions of the questionnaire are added

up and the result is divided by 10. This operation allows the rate to vary between a minimum of 0

and a maximum of 100 points. Finally, in order to adjust the rate to methodological changes that

were made in the year 2002, a "joint factor" or correction consisting of a constant of –2 points is

applied. This factor was decreasing at a rate of two-tenths per month to disappear completely in May

2006.

The final value of IPEC is the sum of scores calculated for each of the five questions in the

manner described above. The index values range from 0 (when all respondents have negative

confidence) to 100 (when all respondents have positive confidence).

CHINA

Name of survey

Consumer Confidence Index

Source

National Bureau of Statistics of China

Frequency

Monthly

Scope

Based on a survey of 700 individuals over 15 years old from 20 cities all over the country.

Survey questions

The index measures the consumers' degree of satisfaction about the current economic situation

and expectation on the future economic trend. The index values range from 0 (when all respondents

have negative confidence) to 200 (when all respondents have positive confidence).

Index construction

Not available

COLOMBIA

Name of survey


Source

Fedesarrollo

Frequency

Monthly

Scope

600 adults are interviewed, with the sample structured to be nationally representative of all adults

in term of age, sex and socio-economic group.

Survey questions

The topics asked in the survey include:

1. Household’s financial situation, present and future

2. The economic situation of the country, present and future

3. The expected changes in prices

4. The expected change in the number of unemployed

5. The expected change in the interest in loans

6. Conditions for major purchases and savings

Index construction

The index values range from -100 (when all respondents have negative confidence) to 100 (when

all respondents have positive confidence).

COSTA RICA

Name of survey


Source

Universidad de Costa Rica

Frequency

Quarterly

Scope

About 700 households with fixed telephone line are interview throughout the country.

Survey questions

The question block for CCI calculation consists of five questions: two relating to current economic

conditions and three relating to economic expectations.

Index construction

The CCI is calculated considering two dimensions: the first is the Current Economic Conditions

Index (ICEA) and the second is the Index of Economic Expectations (IEE).

To calculate the index value 100 is assigned if the answer is positive, 50 neutral or "do not know"

and zero to unfavourable responses. Then the average of five scores is calculated. The minimum is

zero, the lowest value of the CCI, i.e. the more pronounced pessimism. The maximum is reached at

100, the highest degree of optimism. The intermediate position (neither optimistic nor pessimistic,

neutral, undecided or uncertainty) is at 50.

CROATIA

Name of survey

The CNB Consumer Confidence Indicator

Source

The Croatian National Bank

Frequency

Monthly

Scope

Not available

Survey questions

The CNB Consumer Confidence Survey is carried out in accordance with the methodology of the

European Commission, the Joint Harmonized EU Programme of Business and Consumer Surveys.

Consumer Confidence Indicator is based on answers to four questions:


months?


next 12 months?


next 12 months?


Index construction







CZECH REPUBLIC

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,000 Czech households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







DENMARK

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Danish households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







DOMINICAN REPUBLIC

Name of survey

Consumer Confidence Survey (Encuesta de Confianza de los Consumidores)

Source

Ministerio de Economía, Planificación y Desarrollo (MEPyD)

http://economia.gob.do/mepyd/

Frequency

Semiannual

Scope

A sample of about 2,000 individuals

Survey questions

The survey includes questions about the economic situation in the last 12 months and the

expectations about the next 12 months.

Index construction

Consumer Confidence Index assesses consumer opinion on the current state and future

expectations of personal and country economic situation. The index calculation is done in three

stages. Firstly, the answers to each question are transformed into a balance measure (S). For

questions with three possible answers (positive (P), neutral (R) and negative (N)) the balance is

calculated as the difference between the proportion of people who gave a positive answer less the

proportion of people who were negative: S = P – N. For questions with five possible answers (very

positive (PP), positive (P), neutral (R), negative (N), very negative (NN)), the balance is calculated

as: S = (PP + 0.5P) – (0.5N + NN). Secondly, the balance S is multiplied by 100 and added to 100

so that the possible ranges would fall in the interval [0; 200]. Thirdly, the overall index is calculated

as the arithmetic average of the balances.



ECUADOR

Name of survey

Indice de Confianza del Consumidor ICC-BCE

Source

Banco Central del Ecuador

Frequency

Monthly

Scope

Monthly sample of approximately 3800 households in the cities of Quito, Guayaquil, Ambato,

Cuenca and Machala

Survey questions

The Present Situation Index is based on three questions:

1. Household economic situation in the previous month

2. Household consumption on entertainment in the previous month

3. Country's economic situation in the previous month

The Future Expectations Index is based on three questions:

1. Household economic situation in the next three months

2. Household consumption on entertainment in the next three months

3. Country’s economic situation in the next 3 months

Index construction

The Consumer Confidence Index is constructed as a weighted average of the Present Situation

Index and the Future Expectations Index. This index is bounded between 0 and 100 points.

EGYPT

Name of survey


Source

Bayt.com

Frequency

Quarterly

Scope


Survey questions


situation, country’s economy, business conditions, job availability and satisfaction. The index values

range from 0 (when all respondents have negative confidence) to 200 (when all respondents have

positive confidence).

Index construction

Not available

ESTONIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 800 Estonian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







FINLAND

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 2,200 Finnish households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







FRANCE

Name of survey

Household Confidence Indicator (Indicateur synthétique de confiance des ménages)

Source

Institut National de la Statistique et des Études Économiques (INSEE)

Frequency

Monthly

Scope

Sample of around 2,000 households.

Survey questions

1. How do you think the general economic situation in your country has changed over the past

12 months?

2. How do you expect the general economic situation in your country to develop over the next

12 months?

3. How do you expect the number of people unemployed (unemployment) in your country to

change over the next 12 months?

4. How do you think the consumer prices have developed over the last 12 months?

5. By comparison with the past 12 months, how do you expect the consumer prices will

develop in the next 12 months?

6. In view of the general economic situation, do you think now it is the right moment for people

to make major purchases such as furniture, electrical / electronic devices, etc.?

7. In view of the general economic situation, do you think that now is a good moment to save?

8. Which of these statements best describes the current financial situation of your household?

We are saving a lot (+) / we are saving a little (+) / we are just managing to make ends

meet on our income / we have to draw on our savings (-) / we are running into debt (-) /

don’t know.

9. How has the financial situation of your household changed over the last 12 months?


months?

11. Over the next 12 months, how likely is it that you will save money?

Index construction

The Household Confidence Indicator consists of eight indicators:

1. Living standards in France – past change;

2. Living standards in France – outlook;

3. Personal financial position – past change;

4. Personal financial position – outlook;

5. Prospects of unemployment;

6. Opportunity to make major purchases;

7. Ability to save in the present;

8. Ability to save in the months to come.

Each indicator is calculated by subtracting the percentage of negative responses from the

percentage of positive responses. “Don’t know” responses are ignored. The Household Confidence

indicator unites the eight balances of opinion into a single variable, which is calculated using the

technique of factor analysis. The result is a weighted average of the selected balances of opinion,

with the weights re-estimated in January each year. The indicator is normalized to have a mean of

100 and a standard error of 10 over the estimation period of 1987-2010. The data are seasonally

adjusted.

GEORGIA

Name of survey

ISET Consumer Confidence Survey

Source


Frequency

Monthly

Scope

Random sample of 300-350 individuals

Survey questions

The survey includes questions on the financial situation of households, the general economic

situation, unemployment expectations (with inverted sign) and savings, all over the next 12 months.

Index construction

The ISET Consumer Confidence Survey follows the standard EU methodology.

The consumer confidence indicator is the arithmetic average of the balances (in percentage

points) of the answers to the survey questions. On the basis of the distribution of the various options

for each question, aggregate balances are calculated for each question. Balances are the difference

between positive and negative answering options, measured as percentage points of total answers.

In particular, if a question has three alternative options: "positive", "neutral" and "negative", and if P,

E and M (with P+E+M=100) denote the percentages of respondents having chosen respectively the

option positive, neutral, and negative, the balance is calculated as: B = P – M.

In the case of questions with six options, i.e. the three options above plus "very positive", "very

negative" and "don’t know", the balances are calculated on the basis of weighted averages. If P, E

and M have the same meaning as in the previous paragraph, while PP denotes the percentage of

respondents having chosen the option "very positive", MM the percentage of respondents having

chosen the option “very negative” and N is the percentage of respondents without any opinion (so

that PP+P+E+M+MM+N=100), balances are calculated as: B = (PP + 0.5P) − (0.5M + MM).

It is clear from the expressions above that balance values range from −100, when all respondents

choose the negative option (or the most negative one in the case of five-option questions) to +100,

when all respondents choose the positive (or the most positive) option.

GERMANY

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 2,000 German households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







GREECE

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Greek households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







HUNGARY

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Hungarian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







INDONESIA

Name of survey


Source

Bank Indonesia

Frequency

Monthly

Scope

Stratified and random sample of around 4,600 households in 18 cities: Jakarta, Bandung,

Semarang, Surabaya, Medan, Makassar, BandarLampung, Palembang, Banjarmasin, Padang,

Pontianak, Samarinda, Manado, Denpasar, Mataram, Pangkal Pinang, Ambon, and Banten.

Survey questions

Main characteristics of the variables collected include:

1. Current Economic Condition Index: - Current income, Buying durable goods conditions,

Employment conditions;

2. Consumer Expectation Index: - Income, Economic conditions, Employment conditions,

Prices, Economic Indicators (availability of goods and services, interest rate, savings). All

the variables of the Consumer Expectation Index are surveyed as to what the situation will

be six months into the future; prices are additionally surveyed for three months into the

future.

Index construction

The Balance Score Method (net balance + 100) has been adopted to construct the index, where

the index is above 100 points indicate optimism (positive responses) and vice versa.

The sample has a significance level of 99% and a sampling error of 2%.

Components of Consumer Confidence Index are calculated by a weighted average method, i.e.

with adding city weight based on the number of households and contribution of Gross Regional

Domestic Product household consumptions per province. The index values range from 0 (when all

respondents have negative confidence) to 200 (when all respondents have positive confidence).

IRELAND

Name of survey

KBC Bank Ireland/ESRI Irish consumer sentiment survey

Source

KBC Bank Ireland; Economic and Social Research Institute

Frequency

Monthly

Scope

Random sample of a minimum of 1,100 Irish households

Survey questions

The questionnaire used in the monthly survey contains a series of questions that record

respondents’ perceptions on recent and likely future trends in the economy. The areas addressed

include the following:

1. assessment of changes in the general economy in the previous 12 months as well as

expectations about likely future trends in the next 12 months;

2. perceptions of recent trends in unemployment;

3. views on recent trends and likely future outturns in terms of consumer prices;

4. recent trends and likely future trends in the financial situation of the respondent’s

household;

5. views on whether or not the respondent thinks it is currently a good or bad time to incur

expenditure on a number of major household items;

6. likely future outturns in terms of the respondent’s ability to save.

Index construction

The data is obtained during the first two weeks of the month. The data is re-weighted in line with

gender, age and level of educational attainment to ensure the data is fully representative of the

national population of adults. Each index is calculated by computing the relative scores (the percent

giving favourable replies minus the percent giving unfavourable replies (the balance), plus 100) for

each question used in the different indices. Those who reply “Don’t Know”, “Remain the same” are

excluded from the index calculations. Each relative score is rounded to the nearest whole number.

The sum of the relative scores is then divided by the base period total (Q4 1995 = 100).

ISRAEL

Name of survey

Bank Hapoalim and TNS Teleseker Israeli Consumer Confidence Index

Source

Bank Hapoalim and TNS Teleseker

Frequency

Monthly

Scope

Random sample of 1,000 Israeli households

Survey questions

The survey questions about:

1. Current Economic Conditions.

2. Current Employment situation in the country.

3. Economic Condition expectations in 6 months.

4. Employment expectations in 6 months.

5. Income expectations in 6 months.

6. Shopping Climate.

7. Public feeling regarding the nation’s general direction.

Index construction

Index is expressed as the balance of positive minus negative answers with the base April 2002 =

100. Three answer choices are given: positive, neutral and negative.

ITALY

Name of survey

Consumer Confidence Climate Indicator (Indicatore del Clima di Fiducia dei Consumatori)

Source

Istituto di Studi e Analisi Economica (Isae)

Frequency

Monthly

Scope

Random sample of households across four regions: North West, North East, Centre and

Mezzogiorno.

Survey questions

The categories include:

1. General and households' economic situations;

2. Unemployment forecast;

3. Present ability and future opportunity to save;

4. Propensity to purchase consumer durables;

5. Households' budget.

Index construction

The Italian consumer confidence indicator is an overall synthetic indicator of the consumer survey.

It is elaborated on the basis of nine questions considered most suitable to evaluate consumers'

optimism/pessimism about the economy. (Net balance + 100) has been adopted to construct the

index. The index is rebased to 2010=100.

JAPAN

Name of survey


Source

Economic and Social Research Institute of the Cabinet Office of the Government of Japan

Frequency

Monthly

Scope

6,720 households (4,704 households with more than two-persons, 2,016 one-person households)

are sampled using a three-level stratified random sampling method of city/town/village, local unit and

household.

Survey questions

Consumer perceptions of the following four categories are surveyed: overall livelihood, income

growth, employment and willingness to buy durable goods. Respondents are asked to evaluate on a

scale of one to five what they consider the prospects to be for the subjects over the next six months.

Index construction

The consumer confidence index is then calculated by simply averaging the four consumer

perception indexes (original figures). The index values range from 0 (when all respondents have

negative confidence) to 100 (when all respondents have positive confidence).

JORDAN

Name of survey


Source

Bayt.com

Frequency

Quarterly

Scope


Survey questions



Index construction



KUWAIT

Name of survey

ARA Consumer Confidence Index

Source

ARA Marketing Research & Consultancy

Frequency

Monthly

Scope

Not available

Survey questions

Not available

Index construction

The general Consumer Confidence Index is based on six indices which the researchers at ARA

use to measure the level of the consumer satisfaction and optimism. These are:

1. Current Economic Situation Index

2. Expected Economic Situation Index

3. Current Personal Income Index

4. Expected Personal Income Index

5. Current Employment Opportunities Index

6. Purchase of Durables Index

LATVIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,000 Latvian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







LITHUANIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,200 Lithuanian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







MALAYSIA

Name of survey

Consumer Sentiments Index

Source

Malaysian Institute of Economic Research

Frequency

Quarterly

Scope

Sample of over 1,200 households in Peninsular Malaysia

Survey questions

Respondents are asked about perceptions on their household's current and expected financial

positions and their employment outlook. The survey also seeks to uncover general economic

conditions such as inflation as seen from the consumers' perspective. Questions relating to their

plans to buy houses, new or used cars and other major consumer durables are also asked.

Index construction



MEXICO

Name of survey


Source

Instituto Nacional de Estadistica y Geografia (Inegi)

Frequency

Monthly

Scope

2,336 urban households at national level.

Survey questions

1. Compared to the economic situation that the members of the household had 1 year ago,

how do you rate your economic situation today?

2. How do you consider the economic situation of the members of the household will be 12

months from now, compared to the current situation?

3. How do you think the economic situation of the country is today compared to 12 months

ago?

4. How do you consider the economic situation of the country will be 12 months from now,

compared to the current situation?

5. Comparing your current economic situation with that one year ago, how do you rate the

possibility that you or one of the members of the household make purchases like furniture,

TV set, washing machine, other white goods, etc.?

Index construction

In each of the first four questions, consumers have five options to choose an answer from: Much

better, Better, The same, Worse and Much worse. In the fifth question the options are: Higher, Equal

and Lower. The monthly value of the indicator for a given question results of the monthly average of

the (expanded) percentages of the answers of households to that question. The overall index

averages all five indicators.

NETHERLANDS

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Dutch households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







NEW ZEALAND

Name of survey

The Westpac McDermott Miller survey of consumer confidence

Source

Westpac McDermott Miller

Frequency

Quarterly

Scope

Random sample of 1,500 New Zealand households

Survey questions

The following questions are asked:

1. Are you better or worse off financially now than a year ago?

2. Do you expect to be better or worse off financially this time next year?

3. Do you expect good or bad economic times over the next 12 months in New Zealand?

4. Do you expect good or bad economic times over the next 5 years in New Zealand?

5. Is this a good or bad time to buy a major household item?

Index construction

Index is expressed as percentage of “positive” responses minus the percentage of “negative”

responses, plus 100. Neutral responses are counted as zero. Values range from 0, when all

respondents choose the negative option to +200, when all respondents choose the positive option.

NIGERIA

Name of survey

Consumer Expectations Survey

Source

Central Bank of Nigeria

Frequency

Quarterly

Scope

Random sample of about 1,800 Nigerian households

Survey questions

The survey questions cover the expectations of macroeconomic conditions, family financial

situation (level of savings, investments, other assets including cash at hand and outstanding debts)

and family income.

Index construction

The total index is determined as the average of three measures (macroeconomic conditions,

family financial situation and family income). Each of the three sub-indices is computed as the

percentage share of respondents that answered affirmatively less the percentage share of

respondents that answered negatively for a given indicator. The index values range from -100 (when

all respondents have negative confidence) to 100 (when all respondents have positive confidence).

NORWAY

Name of survey

Forventningsbarometeret (Expectations Survey)

Source

TNS Gallup; Finance Norway

Frequency

Quarterly

Scope

Sample of about 1,100 Norwegian households

Survey questions

The following questions are asked:

1. Would you say that the economy of your household is better or worse than a year ago, or is

there no difference?

2. Do you think that the economy of your household is going to be better or worse in a year or

will there be no difference?

3. If we look at the economic situation in Norway, would you say that the economy of the

country in general is better or worse than a year ago, or is there no difference?

4. Do you think that the economic situation in Norway is going to be better or worse in a year,

or will there be no difference?

5. Do you think that now is a good time for the population to buy large household items or do

you think it is a bad time?

Index construction

The index is the difference between the percentage of optimistic and pessimistic responses for

each question divided by 5. The index values range from -100 (when all respondents have negative

confidence) to 100 (when all respondents have positive confidence). The data are seasonally

adjusted.

PERU

Name of survey

Apoyo Consultoria Consumer Confidence Index (Indice de Confianza del Consumidor de Apoyo

Consultoria)

Source

Apoyo Consultoria

Frequency

Monthly

Scope

Not available

Survey questions

Not available

Index construction

Not available

PHILIPPINES

Name of survey

Consumer Expectations Survey

Source

Bangko Sentral ng Pilipinas; National Statistics Office

Frequency

Quarterly

Scope

Sample of over 5,000 households

Survey questions

Survey questions are based on three topics concerning the present situation and future

expectations of the households: overall conditions of the economy, household finances and

household income.

Index construction

The index is computed as the percentage of households that answered affirmatively less the

percentage of households that answered negatively with respect to their views on a given indicator.



POLAND

Name of survey


Source


Frequency

Monthly

Scope

Sample of 1,000 households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







PORTUGAL

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 2,100 Portuguese households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







QATAR

Name of survey


Source

Ministry of Development Planning and Statistics

Frequency

Monthly

Scope

Not available

Survey questions

The index is based on five questions of which two sub-indices are composed as follows:

1. The present situation index, which is composed of: a. The respondents’ evaluation of the present economic situation; b. The respondents’ evaluation of the present job opportunities.

2. The future expectations index, which is composed of: a. The respondents’ expectations of the future situation of the economy (12 months in

the future); b. The respondents’ expectations of the future job opportunities (12 months in the

future); c. The respondents’ expectations of the future financial status for them and for their

households (12 months in the future).

Index construction

The index is calculated based on the balance of assessments of the responses of the relevant

questions. The index value ranges from 0 to 200 points. It reaches its maximum if all the

respondents’ opinions are positive. The index becomes neutral (100) when the positive and negative

opinions are equal. If it is lower than 100 points, then it corresponds to a negative evaluation of the

economic situation of Qatar.

ROMANIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,000 Romanian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







RUSSIA

Name of survey

Index of Consumer Confidence

Source


Frequency

Quarterly

Scope

Territorial multistage sample of 5,000 people aged 16 and over living in private households in all

the regions of Russia.

Survey questions


1. The economic situation of Russia (current status and expected changes in the short

and long term)

2. The economic situation of the administrative division where the household lives

3. The expected changes in prices

4. The expected change in the number of unemployed

5. The personal financial situation (current, past and expected changes)

6. Conditions for major purchases and savings

The specific answers to the questions are provided by the following options:

1. Definitely positive/negative (very good, very favourable/very bad, very unfavourable)

2. Rather positive/negative (good, rather good/bad, rather bad)

3. Neutral (average, about the same)

Index construction

Individual indexes are calculated based on the balance of assessments of the responses (in

percentages) of the relevant questions. Definitely positive/negative responses are weighted by 1;

rather positive/negative by 1/2; and neutral responses are disregarded.

The Index of Consumer Confidence is the arithmetic mean of five Individual Indexes covering Past

and Current (1) and Expected Changes (2) to the personal financial situation; Past and Current (3)

and Expected Changes (4) to the economic situation in Russia; and Conditions for major purchases

(5).



SAUDI ARABIA

Name of survey


Source

Bayt.com

Definition

Consumer confidence is a measure of the economic well-being of a country. It is a reflection of

consumer satisfaction levels and expectations based on various factors in the economy - inflation,

stock market performance, job opportunities/salary structures, unemployment, investment

avenues/returns, business growth, state economic policies, infrastructure, cost of living, interest

rates, exchange rates etc.

Frequency

Quarterly

Scope


Reporting method

Online data collection

Survey questions



Index construction



SLOVAKIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,400 Slovak households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







SLOVENIA

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Slovenian households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







SOUTH AFRICA

Name of survey


Source

Bureau for Economic Research (BER)

Frequency

Quarterly

Scope

Area-stratified probability sample of 2,500 households

Survey questions

1. How do you expect the general economic position in South Africa to develop during the

next 12 months? Will it improve considerably, improve slightly, deteriorate slightly,

deteriorate considerably or don’t know?

2. How do you expect the financial position in your household to develop in the next 12

months? Will it improve considerably, improve slightly, deteriorate slightly, deteriorate

considerably or don’t know?

3. What is your opinion of the suitability of the present time for the purchase of domestic

appliances such as furniture, washing machines, refrigerators etc? Do you think that for

people in general it is the right time, neither a good nor a bad time or the wrong time?

Index construction

The net balance is derived as the percentage of respondents expecting an improvement less the

percentage expecting a deterioration. The answers of the first and second question are weighted as

follows: improve considerably (+10), improve slightly (+5), deteriorate slightly (-5) and deteriorate

considerably (-10). The responses of the third question are weighted in the following manner: right

time to buy (+10) and wrong time to buy (-10). The composite consumer confidence index is the

average of the results of the above three questions.



SOUTH KOREA

Name of survey

Consumer Survey Index

Source

The Bank of Korea

Frequency

Monthly (Quarterly from 3Q 1995 to 2Q 2008)

Scope

Covers 2,200 from a total of about 12 million urban households

Survey questions

Consumer Survey asks consumers about domestic economic situations, living standards,

valuation of assets, etc. (the current situation and expectation for next six months or a year).

Categories included are:

1. Domestic economic situations

2. Living standards

3. Total family income

4. Spending plans

Index construction

Individual consumer indices are calculated according to the formula:

Individual CSI = (very positive x 1.0 + somewhat positive x 0.5 + similar x 0.0 – somewhat

negative x 0.5 – very negative x 1.0) / (total number of households surveyed) x 100 + 100

The composite index is calculated as the sum of the six individual indices standardised so that the

historical average is equal to 100 and the standard deviation is equal to 10.

SPAIN

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 2,000 Spanish households

Survey questions



months?


next 12 months?


next 12 months?


Index construction







SWEDEN

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 1,500 Swedish households

Survey questions



months?

2. How do you expect the general economic situation in this country to develop over the next

12 months?


next 12 months?


Index construction







SWITZERLAND

Name of survey

Index of Consumer Sentiment

Source

Swiss Institute for Business Cycle Research

Frequency

Quarterly

Scope

Not available

Survey questions

Not available

Index construction

Data for each question are expressed as the balance of positive over negative answers. The

Consumer Sentiment Index is then calculated as an average of three separate indexes: economic

development in the past, financial situation in the past, expected financial situation.



TAIWAN

Name of survey


Source

Research Center for Taiwan Economic Development, National Central University

Frequency

Monthly

Scope

Random sample of over 2,000 individuals aged 20+.

Survey questions

The questions cover topics such as expectations about the domestic price level, household

economic conditions, domestic employment, overall economic conditions, investing in stocks and

buying durable goods.

Index construction

The index is calculated as an average of 6 sub-indices related to 6 various topics. Each of the

sub-indices is calculated according to the following formulas:

Domestic price level over the next 6 months:

Sub-index = 100 + [(100 × % of answers “expected to fall”) + (50 × % of answers “expected to be

stable”) – (50 × % of answers “expected to rise slightly”) – (100 × % of answers “expected to rise

sharply”)]

Household economic conditions over the next 6 months; domestic employment over the next 6 months; overall economic conditions over the next 6 months:

Sub-index = 100 + [(100 × % of answers “much better”) + (50 × % of answers “slightly better”) + (0

× % of answers “unchanged”) – (50 × % of answers “slightly worse”) – (100 × % of answers “much

worse”)]

Are the next 6 months good for investing in stocks:

Sub-index = 100 + [(100 × % of answers “good”) + (0 × % of answers “do not know”) – (100 × %

of answers “bad”)]

Are the next 6 months good for buying durable goods:

Sub-index = 100 + [(100 × % of answers “very good”) + (50 × % of answers “good”) + (0 × % of

answers “neutral”) – (50 × % of answers “bad”) – (100 × % of answers “very bad”)]

The overall index can range between 0 and 200, with 100 indicating a neutral confidence level.

THAILAND

Name of survey


Source

Bureau of Trade and Economic Indices

Frequency

Monthly

Scope

Sample of about 1,100 households in Thailand

Survey questions


1. Information about the general situation (present and future economic conditions,

expected future revenue, present and future opportunity to find work)

2. Information about the purchasing power of consumers (present and future cost of

consumer goods, future plans to buy consumer durables)

3. Information about factors that affect the economy (feedback about the factors that

affect the economy, opinion on possible solutions)

Index construction

The percentage proportion of each answer (better, worse, no change) is calculated. Consumer

Confidence Index is calculated using the formula:



TUNISIA

Name of survey


Source

Bayt.com

Definition

Consumer confidence is a measure of the economic well-being of a country. It is a reflection of

consumer satisfaction levels and expectations based on various factors in the economy - inflation,

stock market performance, job opportunities/salary structures, unemployment, investment

avenues/returns, business growth, state economic policies, infrastructure, cost of living, interest

rates, exchange rates etc.

Frequency

Quarterly

Scope


Reporting method

Online data collection

Survey questions



Index construction



TURKEY

Name of survey


Source

Central Bank of Turkey

Frequency

Monthly

Scope

2,000 individuals at the age of 15 and above who have an income from economic activity.

Survey questions

Categories included:

1. General Economic Situation: Consumers’ assessments on current general economic

situation in Turkey compared to past 3 months and their expectations for the general

economic

2. Situation in Turkey over the next 3 months, their expectations for job opportunities in

Turkey over the next 6 months, their assessments on timing of setting aside savings

and buying durable consumption goods.

3. Expenditures: Consumers’ expenditure plans for buying durable and semi-durable

goods, car, house and spending on house renovation.

4. Price Expectations: Consumers’ expectations for the direction of changes in prices

over the next 12 months.

Index construction

Indices are compiled in accordance with the balance method of European Union. The balance is

calculated as the difference between the percentages of positive and negative responses and 100 is

added to this difference, thus forming a separate diffusion index for each question. Then, the general

index is calculated by taking arithmetic means of diffusion indices of the questions included in

consumer confidence index.

The index is evaluated between 0 and 200. If it is above 100, it means consumer confidence is

optimistic. If it is below 100, consumer confidence is pessimistic. 100 refer to neutral opinion in

consumer confidence.

UKRAINE

Name of survey

GfK Ukraine Consumer Confidence Survey

Source

GfK Ukraine

Frequency

Monthly

Scope

Random survey of 1,000 individuals aged 15-59

Survey questions

1. How has the financial standing of your family changed over the last six months?

2. How do you think your family’s financial standing will change in the next six months?

3. Looking at economic conditions in the country as a whole, do you think the next 12 months

will be good or bad?

4. Looking at the next five years, will they be good ones or bad ones for the country’s

economy?

5. In terms of large purchases for your home, do you think now is generally a good time or a

bad time to make such purchases?

Index construction

For each of the five questions, an index is calculated: the share of negative answers is deducted

from the share of positive answers, and 100 is added to this difference in order to eliminate negative

values. Consumer Confidence Index is calculated as the arithmetic average of these five indices.

The index value can range from 0 to 200.


Name of survey


Source

Bayt.com

Frequency

Quarterly

Scope


Survey questions



Index construction



UNITED KINGDOM

Name of survey


Source


Frequency

Monthly

Scope

Random sample of 2,000 households

Survey questions



months?

2. How do you expect the general economic situation in this country to develop over the next

12 months?


next 12 months?


Index construction







URUGUAY

Name of survey

Indice de Confianza del Consumidor (Consumer Confidence Index)

Source

Universidad Catolica del Uruguay - Departamento de Economia

Frequency

Monthly

Scope

A sample of 400 individuals aged 18 years or more living in the country’s urban areas

Survey questions

1. What do you think will be the country’s economic situation in a year: better, the same or

worse than currently?

2. What do you think will be the country’s economic situation in 3 years: better, the same or


3. What is your current personal economic situation compared to a year ago: better, the same

or worse?

4. What do you think will be your personal economic situation in a year: better, the same or


5. Do you think it is a good time to make purchases such as household appliances?

6. Do you think it is a good time to make major purchases such as cars, or to change a

house?

Index construction

The survey questions form three sub-indices: questions 1 and 2 – the index of country economic

situation; questions 3 and 4 – the index of personal economic situation index; questions 5 and 6 –

the index of predisposition to purchase durable goods. The Consumer Confidence Index is a simple

average of the three sub-indices.



USA

Name of survey

University of Michigan Index of Consumer Sentiment (ICS)

Source

University of Michigan

Frequency

Monthly

Scope

Random sample of 500 households across states, excluding Alaska and Hawaii.

Survey questions

5 questions are asked:

1. Would you say that you (and your family living there) are better off or worse off financially

than you were a year ago?

2. Looking ahead – do you think that a year from now you (and your family living there) will be

better off financially, or worse off, or just about the same as now?

3. Turning to business conditions in the country as a whole – do you think that during the next

twelve months we will have good times financially, or bad times, or what?

4. Looking ahead, which would you say is more likely – that in the country as a whole we will

have continuous good times during the next five years or so, or that we will have periods of

widespread unemployment or depression, or what?

5. About the big things people buy for their homes – such as furniture, a refrigerator, stove,

television, and things like that. Generally speaking, do you think now is a good or bad time

for people to buy major household items?

Index construction

The ICS is calculated by computing the “relative scores” for each of the five index questions: the

percent giving favourable replies minus the percent giving unfavourable replies, plus 100. Each

relative score is then rounded to the nearest whole number. All five relative scores are then summed

and the sum is divided by 6.7558 (the 1966 base period) and the result is added 2 (a constant to

correct for sample design changes from the 1950s). First Quarter 1966 =100.

VIETNAM

Name of survey

ANZ Roy Morgan Consumer Confidence Survey

Source

ANZ-Roy Morgan

Frequency

Monthly

Scope

A sample of 1,000 individuals

Survey questions

5 questions are asked:

1. Would you say you and your family are better off financially or worse off than you were at

this time last year?

2. This time next year, do you and your family expect to be better off financially or worse off

than you are now?

3. Thinking of economic conditions in Vietnam as a whole, in the next 12 months do you

expect we'll have good times financially, or bad times, or some good and some bad?

4. Looking ahead, what would you say is more likely, than in Vietnam as a whole, we'll have

continuous good times during the next five years or so - or we'll have bad times?

5. Generally, do you think now is a good time - or a bad time - for people to buy major

household items?

Index construction

The overall index is computed as an average of the five questions net balance plus 100.

7. HOUSE PRICE INDICES: METHODOLOGY & SOURCES

ARGENTINA

Name of survey

Indice de Precios Vivienda Usada (Used Housing Price Index)

Source

Cdi Consult

Definition

The index reflects changes in the sales price of used residential dwellings at national level.

Frequency

Monthly

Index scope and construction

Not available

AUSTRALIA

Name of survey

Residential Property Price Index

Source

Australian Bureau of Statistics

Definition

The Residential Property Price Index measures the price change in all residential dwellings within

the eight greater capital city statistical areas over a period of time.

Frequency

Quarterly


The Residential Property Price Index covers the cities of Sydney, Melbourne, Brisbane, Adelaide,

Perth, Hobart, Darwin and Canberra. The index is an aggregation of two indices: the Established

House Price Index (covering all established detached houses on their own block of land) and the

Attached Dwellings Price Index (covering flats, units, apartments, semi-detached, row and terrace

houses). The scope is restricted to those dwellings where the primary purpose is residential (i.e.

excluding commercial properties) regardless of ownership and tenure of the occupants (i.e. including

government owned properties and properties owned by private landlords).

The ABS employs a stratification approach to compile the Residential Property Price Index. The

stratification approach separates the total sample of residential properties into a number of sub-

samples or strata. Dwelling transactions are stratified by dwelling type, long term median price and

Socio-economic Index for Areas score. Each quarter, the strata are re-valued by applying a price

relative (i.e. the current period median price of the stratum compared to the previous period median

price of the same stratum) to the value of the dwelling stock for that stratum to produce a current

period stratum value. The current period values of each stratum are then summed to derive the

current value of the total dwelling stock in the capital city. Index numbers are subsequently derived

from the total values. When the number of price observations available for a stratum is nil or

extremely low in a quarter, a price movement for the stratum is derived using imputation methods

based on price movements of other strata.

AUSTRIA

Name of survey


Source

Österreichische Nationalbank; European Central Bank

Definition

The index reflects the changes in the dwelling prices (new and used condominiums and single-

family homes) in Austria.

Frequency

Quarterly


For the calculation of the real estate price index, the prices of new and used condominiums and

detached homes are used. The data is gathered from Austria Real Estate Exchange (Austria

Immobilienbörse), a platform bringing together 17 real estate agencies. The data pool consists of

more than 27 000 records of transactions and offer prices. The indices for Vienna and Austria

without Vienna are calculated by Österreichische Nationalbank using a hedonic regression model

with a fixed structure over time. Using these two indices, the aggregate index for Austria is

calculated by European Central Bank as a weighted average of mean indices, with the weights

corresponding to the population weights of Vienna and Austria without Vienna.

BELARUS

Name of survey

Minsk Apartment Price Statistics

Source

Realt.by

Definition

The index reflects changes in the average price per square meter of apartments in Minsk.

Frequency

Monthly


The data on apartment prices in Minsk is gathered daily based on the Realt.by database and is

averaged at the end of each week and each month. The data covers 1-room to 4-room apartments

in 9 districts of Minsk. The outliers are eliminated from the data sample.

BELGIUM

Name of survey

Sales price statistics of ordinary residential houses

Source

Statistics Belgium

Definition

The index reflects changes in the average sales price of an ordinary residential house across

Belgium.

Frequency

Quarterly


Sales price statistics are based on all property transactions in which the registration fees have

been paid. Data is collected from Cadastre du SPF Finances.

BRAZIL

Name of survey

Residential Real Estate Collateral Value Index

Source

Banco Central do Brasil

Definition

The Residential Real Estate Collateral Value Index measures the long-run trend in the residential

real estate prices.

Frequency

Monthly


The index is calculated using the values of property tied to mortgages of individuals with

guaranteed residential mortgage on property in the 11 metropolitan areas (Belém, Belo Horizonte,

Brasília, Curitiba, Fortaleza, Goiânia, Porto Alegre, Recife, Rio de Janeiro, Salvador and São

Paulo). Each metropolitan area is subdivided into geographical areas, composed of adjacent

municipalities and that together comprise a minimum monthly amount of grant mortgages. The

median value of property valuation tied to mortgages issued during the past three months in each

geographical area is the representative value of the month for that area. The long-term trend of each

series of monthly medians in each geographical area is obtained by Hodrick-Prescott filter. The

monthly change in the trend of each area is weighted by the number of households obtained from

the IBGE Census 2010 to form the corresponding variation of the metropolitan region. The series of

11 regions are again weighted by the number of households, forming the national index.

BULGARIA

Name of survey

Price Index of Dwellings

Source

National Statistical Institute

Definition

The index is constructed to obtain representative data on average price index of old flats in district

centers and for the total country.

Frequency

Quarterly


The coverage of the survey is defined by two samples:

1. A sample of sold dwellings (flats) built up by standard plans and comparable by predefined

parameters (new flats are excluded from the sample);

2. A sample of real estate agencies with Bulstat registration and main income for the last year

based on the real estate sales.

Information on the prices and indices calculations is obtained by the quarterly survey on the

market prices of dwellings. Survey is carried out on an inquiry principle. Registration of prices is

done by qualified personnel (registrars) from RSO who collect information on the real sales of

dwellings (flats) with predefined parameters which characterize the market most precisely.

CANADA

Name of survey

Teranet - National Bank National Composite House Price Index

Source

Teranet; National Bank of Canada

Definition

The index is an independently developed representation of the rate of change of home prices in

eleven metropolitan areas, namely Ottawa-Gatineau, Toronto, Calgary, Vancouver, Montreal,

Halifax, Victoria, Edmonton, Winnipeg, Hamilton and Quebec. The metropolitan areas are combined

to form a composite national index.

Frequency

Monthly


The index is estimated by tracking the sale prices of condominiums, row/town houses and single

family homes within the eleven metropolitan areas. The estimation of the index is based on the

assumption of constant level quality of the single family dwellings and that any price changes are

driven only by market trends. Thus, the indices attempt to reflect market prices by minimizing or

eliminating the influence of any changes in the physical characteristics (e.g., renovations) of the

houses.

The estimation of the indices is based on the “repeat sales methodology”. Properties with at least

two sales are required in the calculations. Such a “sales pair” measures the increase or decrease of

the property value in the period between the sales in a linear fashion. Properties that are affected by

endogenous factors are not considered in the estimation. These factors may include: a) non-arms-

length sale, b) change of type of property, for example after renovations, c) data error, and d) high

turnover frequency (biannual or higher). In the repeat sales methodology, the averaging of price

appreciation from different pairs of sales is done using a complex estimation process in which each

pair is a separate observation.

CHILE

Name of survey


Source

Central bank of Chile

Definition

The index reflects changes in the price of new and second-hand houses and apartments in Chile.

Frequency

Quarterly


The Residential Property Price Index (RPPI) is compiled using unnamed administrative records

collected by the Internal Revenue Service (IRS). These records correspond to effective transactions

of new and second-hand properties covering the entire national territory. The used method is

stratification or also known as mix adjustment method. It responds to the specifics characteristics of

the available information in Chile, and it is in accordance to the best international practices. Fourteen

different groups were established, which are the result of combining seven geographical zones and

two kinds of properties (houses and apartments). The RPPI is a weighted average from the fourteen

groups’ price indicators - indexation unit (Unidad de Fomento) by square meter - which corresponds

to the simple average of the price indicator within each group. The weights are defined as square

meters traded on the previous year.

CHINA

Name of survey

Shanghai Second-hand House Price Index

Source

eHomeday

Definition

The index tracks changes in the second-hand residential house prices in Shanghai.

Frequency

Monthly


Not available

COLOMBIA

Name of survey

Used Housing Price Index (Índice de precios de la vivienda usada)

Source

Banco de la República

Definition

The Used Housing Price Index measures the variation in the prices of used housing. It is based

on the information of mortgage loan assessment provided by selected entities of the financial system

(Davivienda, BBVA, Av. Villas, Bancolombia, Colmena BCSC and Colpatria).

Frequency

Quarterly


The index covers the cities of Bogotá, Medellín, Cali, and municipalities of Soacha in

Cundinamarca, and Bello, Envigado and Itaguí in Antioquia. The index is calculated using an

adaptation of weighted repeat sales methodology proposed by Case and Shiller. The appraisals of

the same housing units in different periods of time are used for the index construction, according to

the information gathered from loan's appraisals reported by the leading mortgage providers in the

country (Davivienda, BBVA, Av. Villas, Bancolombia, Colmena BCSC and Colpatria).

CROATIA

Name of survey

Property Price Index

Source

Centar Nekretnina

Definition

The index is based on the largest monthly sample of current real estate asking prices in Croatia.

The index tracks changes on a monthly basis and provides comprehensive insight into the current

state of the real estate market in Croatia.

Frequency

Monthly


The index is based on real estate asking prices. Centar Nekretnina only takes into consideration

the real estate for which the price was clearly marked in real estate advertisements published on the

CentarNekretnina.net website in the current month.

CZECH REPUBLIC

Name of survey

House Price Index

Source

Czech Statistical Office

Definition

The price index is a synthetic index measuring the development of price levels of residential real

estate in Czech Republic under harmonized EU standards.

Frequency

Quarterly


The index measures price development of both new and second-hand flats and houses including

related land. Only household purchases are considered; other sector purchases are excluded.

DENMARK

Name of survey

Price Index for Sales of Property

Source

Statistics Denmark

Definition

The index shows the developments in the prices of one-family houses in Denmark.

Frequency

Quarterly


The current statistics cover sales in ordinary free trade, intra-family sales and other sales (e.g.

forced sales). The data is collected via registers by the Ministry of Taxation.

All sales, which meet the following conditions are included:

There are no special conditions, i.e. partial property sold, more than one property sold, seller is a

public authority (with the exception of building sites), sales information is missing or price is

exorbitant

The buyer is a private person

Average price per property is calculated as an ordinary average of the sales included in the

number of sales in the price calculation

ESTONIA

Name of survey

Dwelling Price Index

Source

Statistical Office of Estonia

Definition

The index reflects changes in the average price per square meter of new and existing dwellings in

Estonia.

Frequency

Quarterly


For calculations, the geometric mean of the square meter prices of dwellings is used.

The index covers apartments and houses (including detached, semi-detached and

terraced houses). To improve the comparability of data, transactions with apartments

smaller than 18 m2 and bigger than 250 m

2 were left out. To avoid the inclusion of extreme

prices, 2% of transactions with the lowest and the highest square metre prices were cut

off. Transactions with houses and apartments in the Old Town of Tallinn were also

excluded as too exclusive.

FINLAND

Name of survey

Prices of Dwellings Index

Source

Statistics Finland; European Central Bank

Definition

The statistics on the prices of dwellings describe the development in the prices of dwellings in

second-hand blocks of flats and terraced houses.

Frequency

Quarterly


Statistics are compiled from the taxation authority’s asset transfer tax statements. The index

calculation combines the classical approach based on classification of data and regression analysis

(so-called hedonic method). Because location, type of building and number of rooms are the most

important price determinants, the composition of sold dwellings is first standardized for these

variables by classification. The largest municipalities are divided into several sub-areas, and the

smallest municipalities where few transactions take place have been combined. Dwellings in blocks

of flats are classified by number of rooms into dwellings with one room, dwellings with two rooms

and dwellings with three or more rooms. The overall index point-number for the whole country is

obtained via aggregated price changes in every index class and price adjustments using a so-called

log-Laspeyres formula. The weights for old dwellings are derived as value-shares of stock of

apartments in 2005.

FRANCE

Name of survey

Second-Hand Dwelling Price Index

Source

Institut national de la statistique et des études économiques

Definition

The index is defined as the ratio of the current value of housing to its reference value in the base

period. It refers only to second-hand houses and apartments, which are more than 5 years old or

which have had a second transfer. In addition, only the following types of property are included:

unoccupied at the time of sale (or occupied by the seller);

with a full ownership acquired in an over-the-counter sale;

residential use properties only.

To avoid non-typical transactions, non-standard goods such as rooms, lofts, workshops or castles

and acquisitions made by real estate professionals are excluded.

Frequency

Quarterly


The index covers flats and houses in central cities as well as in suburban and rural areas across

France (Île-de-France and the province). The index is calculated based on transactions completed

during the quarter. The price used is the net disposal price, excluding transfer duties, legal fees and

agency commissions. The methodology is based on econometric models for each zone, explaining

the price of a house based on its characteristics (neighborhood, time of construction, number of

rooms, average area per unit etc). Using these models, the value of housing stock reference price

for the current period is estimated.

GEORGIA

Name of survey

ISET Policy Institute Real Estate Price Index

Source


Definition

The index reflects the changes in sale prices of residential property in Tbilisi.

Frequency

Monthly


Firstly, the characteristics of a “typical” real estate unit in each month are determined. To

determine a typical flat in any given month the following metrics are calculated: the median of the log

area of the property advertised in that month, mode of renovation type, mode of district, median of

the number of bedrooms, median of the number of bathrooms, and median of the number of

balconies.

Secondly, a linear regression model on the data in each month is constructed using unit price in

log form as a dependent variable and controlling for various characteristics of the real estate unit.

The control for the following measures is implemented: the log area of the property, type of

renovation, district, number of bedrooms, number of bathrooms and number of balconies.

The regression coefficients tell us how different characteristics of the real estate unit (e.g. location,

number of rooms, etc.) affect the price of the property. The coefficient estimates and the

characteristics of a “typical” real estate unit are then combined to calculate the Laspeyres and

Paasche monthly indices. Both measures are then reconciled by calculating a Fisher-type hedonic

imputation index – the geometric average of the Laspeyres and Paasche indices. The Fisher index

is used as the main indicator of real estate price movement.

GERMANY

Name of survey

Hedonic House Price Index

Source

Hypoport AG

Definition

Hedonic House Price Index monitors price changes in residential dwellings across the country.

Frequency

Monthly


The index is based on home-loans transaction data generated on the EUROPACE platform. It is

calculated using a statistical procedure developed in conjunction with Finpolconsult. The hedonic

regression technique is used to ensure a better standardization of the individual characteristics of

real estate. The aim of hedonic regression analysis is to highlight the pure price effect for each

reporting period.

The index includes apartment transactions, newly built and existing homes.

GREECE

Name of survey

Index of Prices of Dwellings

Source

Bank of Greece

Definition

The index reflects the development in residential dwelling prices across Greece, covering Athens

and other urban areas.

Frequency

Quarterly


The Bank of Greece collects data from other banks about the detailed data on the value and

quality characteristics of residential properties underlying loan agreements (based on appraisal

reports by the banks). Before the data is processed to construct the index, a more thorough test of

their plausibility is conducted, using logical and statistical rules. Values outside a plausible range for

each variable are excluded, while values close to the limits are treated as “outliers”; in addition,

values with more than 2.5 standard deviations from the average value of each substrate are also

excluded.

After concretizing individual strata, the first step is to estimate analytical indices for each stratum.

For a group of homogenous properties in each stratum, the price index equals the ratio of average

prices per square meter. The average price per square meter for each property group of the stratum

is calculated using the geometric mean. The real estate price index for quarter t, as against the basis

quarter 0 (if I0,t), is given by the formula:

The weights (wi) used are the ratios of the transaction values of each property group of the

stratum i (i = 1, …, n) to total transactions in the period from the first quarter of 2006 to the third

quarter of 2009. The base year is 2007, as it is thought to represent typical conditions, without

peculiarities that could affect the indices produced.

HONG KONG, CHINA

Name of survey

Private Domestic Property Price Index

Source

The Government of the Hong Kong Special Administrative Region, Rating and Valuation

Department

Definition

The index measures changes in average prices of independent dwellings in Hong Kong.

Frequency

Monthly


Private domestic units are defined as independent dwellings with separate cooking facilities and

bathroom (and/or lavatory). They are sub-divided into 5 classes by reference to floor area. The index

for each class is derived from analysis of all transactions effective in a given period. The composite

index is compiled by calculating a weighted average of the component indices. The weights for

compiling the composite index for each type of domestic premises are based on the number of

transactions effected in the current and previous 11 months.

Average prices are based on an analysis of transactions scrutinised by the Department for stamp

duty purposes. The following types of transactions are excluded: those considered to be

unacceptable for stamp duty purposes, those involving a mix of property types, premises which have

not yet been assessed to rates, domestic premises sold subject to existing tenancies, and primary

sales of domestic premises.

HUNGARY

Name of survey

FHB House Price Index

Source

FHB Mortgage Bank

Definition

The FHB House Price Index measures the run of Hungarian residential real estate prices.

Frequency

Quarterly


For computing the index, the process based on the hedonic method is applied. The hedonic

method is the most widespread statistical way to measure aggregate property price change, and is

based on the theoretical consideration that the value of houses/flats can be divided into the values of

their attributes. The values of FHB House Price Index are computed by making sample parts that

comprise 5 consecutive quarters from the complete database containing 46 quarters. That means

consecutive sample parts overlap for 4 quarters. The hedonic regression is estimated using these

sample parts with 5 quarters, and the value of the index is always calculated based on the

estimation, in the sample of which the given quarter is the last datum. This method ensures that after

one and a half years, we can seal the past, as from now on the new data do not modify the

previously estimated index values any more.

INDIA

Name of survey

NHB Residex

Source

National Housing Bank

Definition

NHB Residex index tracks the movement of prices in the residential housing segment.

Frequency

Quarterly


Index covers residential housing in Delhi. Primary data on housing prices is collected from real

estate agents by commissioning the services of private consultancy/research organizations of

national repute. In addition, data on housing prices is also collected from the housing finance

companies and banks; it is based on housing loans contracted by these institutions. The index is

constructed using the weighted average methodology with the Price Relative Method (modified

Laspeyres approach).

INDONESIA

Name of survey

Residential Property Price Survey

Source

Bank Indonesia

Definition

Residential Property Price Index reflects changes in Indonesian residential property prices as

represented by the development project house sales.

Frequency

Quarterly


Residential Property Price Survey started in 1999 based on development projects from 12 cities,

i.e. Medan Padang, Palembang, Bandar Lampung, Bandung, Semarang, Yogyakarta, Surabaya,

Denpasar, Banjarmasin, Manado, and Makassar. At the first quarter of 2002, coverage expanded to

13 cities including Jabotabek (Jakarta, Bogor, Tangerang, and Bekasi) area. At the first quarter of

2004, coverage became 14 cities

(Pontianak was included). Since 2007 the coverage survey area has been extended including

Banten area (Serang and Cilegon). This survey covers 45 main developers in Jabodebek-Banten,

and about 215 developers in 13 Bank Indonesia Regional Offices. Data collected directly from

developers’ covers price and total sales in the recent quarter and prediction for the next quarter.

Data is processed by type of building, which are small type (≤36 square meters), medium type (>36

and ≤70 square meters), and large type (>70 square meters). Composite Index is developed by

simple average chain index weighted by the city weight resulting from Cost Living Survey of 2007 by

BPS Statistics Indonesia.

IRELAND

Name of survey


Source

Central Statistics Office

Definition

The Residential Property Price Index is designed to measure the change in the average level of

prices paid for residential properties sold in Ireland.

Frequency

Monthly


The Residential Property Price Index is compiled using data on mortgage drawdowns provided on

a monthly basis by 8 of the main Mortgage Lending Institutions under Section 13 of the Housing Act

(2002). This data provides details on the characteristics of properties bought (such as building type

and size) as well as the price paid. It is transactions based; meaning that prices are recorded only

where a sale occurs. Not all residential property transactions are funded by a mortgage (i.e. they are

cash based) and these transactions are excluded from the scope of the index.

The hedonic method is the prevalent statistical process for the measurement of residential price

change. In this method, a number of characteristics which influence prices are analysed so that we

can estimate and exclude the part of the price change that can be attributed to them. These

characteristics are: location, building type, floor area, number of bedrooms, new or old and first time

buyer or not. By excluding the price change determined by these characteristics we are left with an

index of pure price change for a consistent set of characteristics. This index uses the rolling year

hedonic regression model.

Weights are calculated at the beginning of each year based on the value of transactions during

the previous year as given by the mortgage drawdown data. The index is an annual chain-linked

Laspeyres-type index. It is calculated by updating the previous month’s weights by the estimated

monthly changes in their average prices.

ISRAEL

Name of survey

Prices of Dwellings Index

Source

Central Bureau of Statistics

Definition

The Prices of Dwellings Index measures changes in the owner-occupied apartment prices in

Israel.

Frequency

Monthly


Information on purchasing of owner-occupied dwellings is regularly collected by tax offices across

the country. The sample covers 40 localities in 9 geographical areas: Jerusalem, Tel Aviv, Haifa,

Gush Dan, Center, South, Sharon, North and its suburbs. The information includes purchases of

new apartments and acquisitions of second-hand apartments that have changed ownership. The

sample does not include homes that have been self-constructed, homes purchased by purchasing

groups and public companies, and apartments with no market value. The price index is calculated

based on the methodology that takes into account various housing properties (location, number of

rooms, age, area of the dwelling etc.)

ITALY

Name of survey

House price Index

Source

Banca D’Italia; Tecnoborsa; Agenzia del Territorio

Definition

The index reflects changes in house prices according to a survey of real estate agents in Italy.

Frequency

Quarterly


Not available

JAPAN

Name of survey

Monthly Data of Real Estate Economy

Source

The Land Institute of Japan

Definition

The index reflects changes in the average cost per square meter of sold new condominiums in

Tokyo metropolitan area.

Frequency

Monthly


Not available

KAZAKHSTAN

Name of survey

Developed housing resale prices

Source

The Agency of Statistics of the Republic of Kazakhstan

Definition

Developed housing resale price index measures the inflation or deflation of the price of resold

second-hand flats over a period of time.

Frequency

Monthly


The index covers 18 cities: Astana, Almaty, Aktau, Aktobe, Atyrau, Jezkazgan, Kokshetau,

Karagandy, Kostanay, Kyzylorda, Oral, Oskemen, Pavlodar, Petropavl, Semey, Taldykorgan, Taraz,

and Shymkent.

The housing categories included in the survey are one-flat houses (separate houses that have

their own roof and a separate entrance, including cottage houses), and houses with two or more

flats (dwellings in blocks of flats). The data is collected for three types of flats: standard, high-quality

and elite. The information is gathered from the authorities responsible for registering real estate

sales. The data is collected if the characteristics of the flats have not changed during the observed

period. The dwelling characteristics are:

- Flat condition

- Number of rooms

- Construction materials

- Date of construction

- Urban area where the flat is located

The average price of a square meter of dwelling for each city is calculated as a weighted average

based on the data on actual transaction prices; the weights are derived from the total amount of

square meters of sold flats. The average price across the country is calculated as a weighted

average of all cities, with the weights based on the share of the total amount of flats entering the

market in each region (shares are differentiated by construction materials, flat sizes).

LATVIA

Name of survey

Average price of standard-type apartments

Source

Arco Real Estate

Definition

The index reflects changes in the average price of standard-type apartments (1 to 4 rooms) in

Riga.

Frequency

Monthly


The information sources for the analysis are the SIA “Arco Real Estate” real estate transactions

database, the analysis of the clients’ demand and supply, information provided by the partners of

“Arco Real Estate” and publicly available information sources.

LITHUANIA

Name of survey

Ober-Haus Lithuanian Apartment Price Index

Source

Ober-Haus Real Estate Advisors

Definition

Ober-Haus Real Estate Lithuanian apartment price index shows a summary of apartment price

changes in the five largest Lithuanian cities (Vilnius, Kaunas, Klaipėda, Šiauliai, and Panevėžys).

Frequency

Monthly


The index covers five cities: Vilnius, Kaunas, Klaipėda, Šiauliai, and Panevėžys. In order to

ensure the accuracy and efficiency of results, the index is calculated using a large variety of

information and data sources: Ober-Haus Real Estate gained information and databases, the data

from public and private institutions, and other information and data sources that may influence the

final outcome.

To construct the index, a certain weighting system is used. For each property group (apartments

in different cities), appropriate weights are assigned, which determine the generalized prices. The

construction of the weighting system is based on the following parameters: the amount of

apartments and the number of transactions in different geographical segments (different urban areas

and district groups) and qualitative housing characteristics (area, age, completeness). In the event of

significant changes in the real estate market or housing characteristics, the weighting system can be

adjusted according to the significance of these changes.

MACEDONIA

Name of survey

Index of Housing Prices

Source

National Bank of the Republic of Macedonia

Definition

The index reflects changes in the apartment prices in the territory of Skopje.

Frequency

Quarterly


The index is developed on the basis of data relating to notices of sale published by real estate

agencies. The calculation of the index is made by using the hedonic method. Hedonic price

indices are based on hedonic pricing models, whereby the price of a product is a function

arising from its features. The price of the apartment is a function arising from the size of

the apartment, the neighbourhood in which it is located, the floor, whether the apartment

has central heating and whether the apartment is new.

MALAYSIA

Name of survey

Malaysian House Price Index

Source

Ministry of Finance, Valuation and Property Services Department

Definition

The Malaysian House Price Index is a transaction-based house price index which captures the

change in prices paid for an “average” house.

Frequency

Quarterly


The index covers terraced, high-rise, detached and semi-detached housing units. The price

change is estimated by pricing a basket of house characteristics of the “average” house transacted

in the current period and comparing this price with the price of the same basket of house

characteristics in the base year (2010). Fundamentally, it is a ratio that shows how much the cost of

housing has changed between two periods (the base and the current periods) if the house buyers

maintain the standard of living in the latter period.

The hedonic methodology is used as the basic approach to price measurement of an “average”

house whereby houses are not priced for themselves as such but for the set of fixed characteristics

which are embodied in the assets. The fixed set of house characteristics is mainly comprised from

location, physical and legal characteristics. The “average” house is constructed by a statistical

method based on house transactions selected according to the sampling frame that was estimated

from the population of housing transactions in the base year (2010).

The Valuation Information System (VIS) of the Valuation and Property Services Department and

the Memorandum of Transfers of Land and Survey Department, Sarawak are the main sources of

data for the index computation. They provide sales data of housing properties that people buy and

sell in the 14 states and Federal Territories throughout the country every day. On average, the size

of data is about 20,000 observations per quarter. They contain information on the location, physical

and legal characteristics of various types of houses sold.

MEXICO

Name of survey

Index of Housing Prices

Source

Sociedad Hipotecaria Federal

Definition

The index reflects changes in the housing prices in the metropolitan areas of Mexico City,

Guadalajara, Monterrey, Puebla-Tlaxcala and Toluca.

Frequency

Quarterly


Not available

NETHERLANDS

Name of survey

House Price Index

Source

Statistics Netherlands

Definition

The House Price Index aims to evaluate price changes of existing residential dwellings situated on

Dutch territory sold to private buyers.

Frequency

Monthly


For the calculation of the index, selling prices as registered by Dutch Land Registry Office are

used, and for the appraisals the Property Assessment Act values from the most recent period are

used. The index is calculated on the basis of the so-called Sale Price Appraisal Ratio (SPAR)

method. The method uses matched pairs, i.e. it combines (officially) estimated selling prices with

actual prices. The following formula reflects the SPAR method:

Where It is the price index over the period t, Sj,t the selling price of dwelling j in period t, Aj,0 is the

appraised selling prices (appraisal) of dwelling j on reference moment 0 and n is the number of

transactions. Due to the fact that the selling prices of most dwellings sold in a particular period are

unknown in the base period, selling prices are estimated by using appraisal data. The numerator

reflects the price developments of dwellings sold in a particular month relative to the appraisals from

base period of these dwellings. The denominator corrects for under- and overestimation of the

appraisal relative to the actual selling price in the reference period.

NEW ZEALAND

Name of survey

House Price Index

Source

Reserve Bank of New Zealand

Definition

The HPI measures the movement in house prices for local council areas throughout New Zealand,

providing an indicator of capital growth and how prices are trending in an area. House prices are

sourced from PropertyIQ.

Frequency

Quarterly


Not available

NORWAY

Name of survey

House Price Index

Source

Statistics Norway

Definition

The house price index measures the development of the value of the total housing stock in

Norway, based on price information from dwellings sold on the free market.

Frequency

Quarterly


The index covers three types of housing: detached houses, row houses and multi-dwelling.

Dwellings with particularly small or large useful floor spaces or very high or low square meter prices

are not included in the calculation of index. Sub-indices for three housing classes and eleven

geographical regions are calculated by using the hedonic method. These 33 sub-indices are

weighted into total indices for each region and for the country as a whole. The weights are the

estimated total value of housing stock of each housing class and within each region.

Statistics Norway receives the house price data from FINN.no AS through cooperation with the

Norwegian Association of Real Estate Agents (NEF) and the Association of Real Estate

Undertakings (EFF). FINN.no cooperates with the most important real estate agencies in Norway.

PERU

Name of survey

Apartment Price Index

Source

Banco Central de Reserva del Perú

Definition

The index measures the development of the price of apartments per square meter in the main

districts of Lima (La Molina, Miraflores, San Borja, San Isidro and Surco).

Frequency

Quarterly


Not available

PHILIPPINES

Name of survey

Manila residential condominium price statistics

Source

Colliers International

Definition

The index reflects changes in the average price per square meter of condominiums in Manila.

Frequency

Quarterly


The index covers comparative values of luxury 3-bedroom condominiums in Manila central

business district.

POLAND

Name of survey

Home price index

Source

Narodowy Bank Polski

Definition

The index reflects changes in the housing price in 7 largest cities in Poland.

Frequency

Quarterly


The index covers average transaction price per square meter of housing in 7 major cities

(Gdańsk, Gdynia, Łódź, Kraków, Poznań, Warszawa and Wrocław).

PORTUGAL

Name of survey

Average Value of Bank Evaluation on Housing

Source

Statistics Portugal

Definition

The index tracks the developments in the residential market in Portugal. The index is based on

the evaluation of houses and apartments reflecting both the qualitative characteristics of dwellings

and the effect of inflation.

Frequency

Monthly


The information for constructing the index is provided by a set of credit institutions operating in

Portugal. The received data is used to calculate the indicators of average value of dwellings for each

property type, period (t) and territorial unit (i) using the formula:

where

Ytij – value of the assessment of a certain type property j, in period t, in the territorial unit i;

Atij – corresponding floor area of a certain type property j, in period t, in the territorial unit i;

n – number of assessments of certain type properties in period t, in the territorial unit i.

QATAR

Name of survey

Real Estate Price Index

Source

Qatar Central Bank

Definition

The Real Estate Price Index measures percentage changes in transacted property prices

(including land, villa and residential sales).

Frequency

Monthly


Qatar Central Bank gathers information on sale transactions of real estate property from the

Ministry of Justice. The gathered data cover the municipalities of Doha Al Rayyan, Umm Salal, Al

Wakrah, Al Khor, Al A Dayeen, and Al Shamal. Based on this data (i.e. suburb-level real estate

transactions data) a monthly series of Real Estate Index (REI) is developed. Given the inherent

limitations of the data (e.g., lack of information on the location and age of building, number of rooms,

available amenities such as furnished or unfurnished), the information is first adjusted for outliers

and heterogeneity. Subsequently, a mix-adjusted real estate measure is developed, after seasonally

decomposing the data to isolate the effects of seasonal trends. Percentage changes of the Real

Estate Price Index show changes relative to the base period (year 2009-2010 (April-March) was

chosen as base year).

ROMANIA

Name of survey


Source

National Institute of Statistics

Definition

The index reflects changes in the average residential property price across Romania.

Frequency

Quarterly


The Residential Property Price Index is a Laspeyres-type index which involves measuring the

evolution of prices in the current period as against a base period (2009) for residential properties.

Given the existing limitations for real estate sales, the qualitative changes that occur over time, the

method used to estimate the indices is the “hedonic” method. The hedonic method takes into

account the fact that the heterogeneous goods can be described by a set of characteristics or

attributes. In the case of dwellings, this set may include both characteristics related to the structure

of the dwelling and characteristics relating to the location of the property.

RUSSIA

Name of survey

Housing Price Index

Source


Definition

The index reflects changes in the average price of different types of used apartments across

Russia.

Frequency

Quarterly


The primary data is gathered from real estate agencies across Russia. The data covers

transactions of low-quality, standard, high-quality and elite apartments with different number of

rooms in various types of houses. Only urban housing is included in the data.

For calculating the average price per square meter of sold apartments for each city, a fixed

weighting system is used, where the weights are annual shares of sold apartments by type relative

to the total sales volume in the previous year for each city. For the total index calculation, the

weights are based on the information of the urban population in the covered cities at the beginning

of the year.

SERBIA

Name of survey

Price statistics of dwellings in new construction

Source

Statistical Office of the Republic of Serbia

Definition

The index reflects changes in the average price per square meter of dwellings in new construction

in Serbia.

Frequency

Quarterly


The index is calculated based on the average price per square meter of dwellings in new

construction. The data refer to prices of newly built dwellings that were sold by legal and physical

persons in the reference period. It covers all newly built dwellings in urban settlements for which sale

contracts were signed between the customer and seller. The total price of a dwelling covers

construction price, land price and other costs.

SINGAPORE

Name of survey


Source

Urban Redevelopment Authority

Definition

Residential Property Price Index is used to monitor movements of residential property in

Singapore and is defined as a ratio of the current price per square meter compared to the price in

the reference period.

Frequency

Quarterly


The information used to compute the property price index is obtained from caveats lodged with

the Singapore Land Registry. A caveat is usually lodged by the purchaser to protect his/her interest

soon after an option to purchase a property is exercised or a sale and purchase agreement is

signed. The price of the property is the agreed purchase price of the property between the purchaser

and the vendor as entered in the caveat form.

To compute the price index, transactions are first grouped by property type and locality. The

grouping is selected on the basis of frequent transactions and similar prices ($ per sq m). The

median price in each group is used to compute a sub-index. The price index of a particular property

type is the weighted average of all the sub-indices of that property type in the various planning

areas.

From the 4th quarter of 1998, the price indices are computed based on the Moving Average

method. This means the weights are computed based on the moving average of the value of

transactions over the last 12 quarters, instead of being based on the value of transactions in a

particular year. The weights in the price indices are therefore updated quarterly so that they are as

current as possible.

SLOVAKIA

Name of survey

Index of Residential Property Prices

Source

National Bank of Slovakia

Definition

The Index of Residential Property Prices reflects movements in prices per square meter of flats

and houses in Slovak Republic.

Frequency

Quarterly


The National Bank of Slovakia has signed an agreement with the National Association of Real

Estate Offices of Slovakia (NARKS) on ensuring the processing of data on real estate prices. The

output compilations of prices for existing apartments and houses are made on the basis of classified

advertisement records. A weighted arithmetic average is used to calculate the average prices per

square meter for particular types of apartments and houses in individual regions. The weights are

the total number of transactions involving the particular types of apartments and houses in districts

of the respective region. Then an average offer price per square meter for particular types of

apartments and houses in Slovakia is calculated. Using a weighted arithmetic average, this value is

calculated by taking the sum of the multiples of the prices per square meter for particular apartment

and house types in individual regions and the selected weight coefficients (in %) for the individual

regions, and dividing this figure by 100 (the individual regions as the sum of their relative shares in

the assumed real transactions in apartments for the whole of Slovakia, in %). Using the stated

weighting, the average price per square meter of the respective residential property is calculated for

the whole of Slovakia.

SLOVENIA

Name of survey

Residential Housing Price Index

Source

Statistical Office of the Republic of Slovenia

Definition

The index measures changes in new and second-hand flat and family house prices in Slovenia.

Frequency

Quarterly


For calculating the price index, only transactions of the following flats are used:

flats that are larger than 17 m2 but smaller than 250 m

2;

flats that were constructed less than 250 years ago but more than three years ago;

flats whose average price per square meter of usable floor area is not lower than EUR 300 but not

higher than EUR 6 000.

For calculating the price index, only transactions of the following family houses are used:

houses that are larger than 40 m2 but smaller than 300 m

2;

houses that were constructed less than 250 years ago but more than three years ago (new houses

are excluded);

houses whose average price per square metre of usable floor area is not lower than EUR 300 but

not higher than EUR 5 000;

houses whose associated building plot is not larger than 5 000 m2.

The data is processed according to the so-called hedonic principle. The core of this approach is

multiple regression analysis of real estate characteristics influencing price formation. Regression

coefficients of individual real estate characteristics indicate the impact of individual characteristics on

the formation of the total real estate price. The next step is the final calculation of the price index

according to the selected method, i.e. characteristics price index, which is based on the use of

calculated regression coefficients in the formula for the Laspeyres index. The basis for weighting in

the formula is average values of real estate characteristics in the fourth quarter of the previous year.

For calculation of pooled price index of several types of residential real estate the value of

transactions is used for weighting.

SOUTH AFRICA

Name of survey

ABSA House Price Index

Source

ABSA

Definition

The ABSA House Price Index is based on the total purchase price of residential houses in the

medium-size category, in respect of which mortgage loan applications were approved by ABSA.

Data is seasonally adjusted.

Frequency

Monthly


Not available

SOUTH KOREA

Name of survey

Housing Purchase Price Index

Source

Kookmin Bank; The Bank of Korea

Definition

The index reflects changes in the purchase price of various types of dwellings across Korea.

Frequency

Monthly


The index includes single houses, row houses and apartments.

SPAIN

Name of survey

House Price Index (Índice de Precios de la Vivienda)

Source

Banco de España, Instituto Nacional de Estadística

Definition

The House Price Index (HPI) is intended to measure the evolution of the transaction prices of

free-sector housing, both new and second-hand, over time.

Frequency

Quarterly


The HPI reference population or stratum includes the entire population (individuals), resident both

inside and outside Spain, who have acquired a dwelling during the reference period. Merchantings

carried out by legal entities or financial institutions do not form part of the HPI population scope.

The information used for calculating the HPI is taken from the General Council of Notaries, with

whom the INE has signed a partnership agreement aimed at enabling the use of data from notaries

for statistical purposes. Pursuant to this, the General Council of Notaries, via the Notarial

Certification Agency (ANCERT), provides the data making up the main source of information for this

indicator.

The HPI calculation system is based on the combining of two basic elements reflecting the

features of the property market: housing prices, which represent the convergence of market supply

and demand, and weightings, or relative importance of each type of housing, by expenditure by

households when buying a dwelling. The combining of these two elements in order to obtain the HPI

is carried out by means of the chain-linked Laspeyres index formula. The period used for linking is

the fourth quarter of each year.

SWEDEN

Name of survey

Real Estate Price Index

Source

Statistics Sweden

Definition

The index reflects price changes of one- and two-dwelling buildings for permanent living in

Sweden.

Frequency

Quarterly


One-or two-dwelling buildings for permanent living include detached one-or two-dwelling

buildings, terraced houses and linked buildings. Real estate with site leasehold rights is included.

Price changes are estimated using the purchase price coefficient (K/T). K/T is the ratio between the

price and the assessed value for a certain time and is counted as an unweighted mean value.

SWITZERLAND

Name of survey

Asking Price Index of Rented Apartments

Source

Swiss National Bank; Wüest & Partner

Definition

Asking Price Index of Rented Apartments is a nationwide index of asking prices for rented

apartments, measuring price changes over time.

Frequency

Quarterly


To construct the index, real estate deals for eight geographic regions are gathered. For most of

the deals, additional information is also collected (e.g. size (number of rooms), macro situation

(community) and state (new or old)). The price index is calculated as a weighted average.

Specifically, the dwellings are divided into homogenous groups using the available information. In

each group, an average price is determined. This information is then combined to form a so-called

Lowe index, which uses an average weight (as opposed to a past or a present weighting).

TAIWAN

Name of survey

Lutheran House Price Index

Source

Sinyi Realty Estate

Definition

Lutheran House Price Index provides a measure of price trends of residential dwellings in Taiwan.

Frequency

Quarterly


The sample covers Taipei City, Taipei County, Taichung, Kaohsiung and several other Taiwan

regions.

THAILAND

Name of survey

Housing Price Index

Source

Government Housing Bank

Definition

Housing price index captures the change in prices of condominiums in Thailand.

Frequency

Monthly


The index covers condominiums in Bangkok and its vicinity (Bangkok, Nonthaburi and

Pathumthani). The data from assessment of collateral by Government Housing Bank is used for

index construction; the method implemented is the hedonic approach. The data mostly covers

medium- to low-end of the housing market and is concentrated mostly on the periphery of the central

BKK and vicinity.

TURKEY

Name of survey

TCMB House Price Index

Source

Central Bank of the Republic of Turkey

Definition

The HPI, which covers the whole country, is constructed for the purpose of monitoring price

movements in the Turkish housing market.

Frequency

Monthly


Price data related to all houses subject to sale, regardless of the construction year are used to

develop the HPI. The HPI, which is constructed on a countrywide basis, covers data pertaining to all

appraised houses in 75 cities.

The “Stratified Median Price Method” has been implemented in constructing the HPI to develop a

measure for price movements in the heterogeneous housing market. In the scope of the current HPI

implementation, in which the geographical stratification approach is applied, houses with different

characteristics are grouped together to form homogenous strata and the median unit price for each

stratum is weighted by the number of houses sold to reach the overall price index.

HPI (2010=100), which measures changes in the house prices compared with the base year, is

calculated using the Chain Laspeyres Index method. The reason for implementing the chain index

method is that the weights are updated each year.

UKRAINE

Name of survey

Kiev Apartment Price Statistics

Source

Blagovest

Definition

The index reflects changes in the average price per square meter of apartments in Kiev.

Frequency

Monthly


The index covers the apartments of 1 to 3 rooms in Kiev. The data is gathered at the end of each

month from the information in the database of Blagovest. In order to get more reliable results, the

data do not include apartments located in the same district and having the same number of rooms, if

their amount in the database is less than six.


Name of survey

Dubai House Price Index

Source

Colliers International

Definition

The index reflects changes in the prices of residential property in Dubai.

Frequency

Quarterly


The index covers prices of apartments, villas and townhouses in Dubai.

UNITED KINGDOM

Name of survey

House Price Index

Source

Nationwide

Definition

The House Price Index is a measure for tracking a representative house price over time.

Frequency

Monthly


Nationwide house price series utilize only owner-occupied property information. In addition,

properties that are not typical and may distort the series are also removed from the data set.

Therefore, the following criteria are used to select which properties to include:

House purchases - remortgages and further advances are excluded

Owner occupied properties – buy to let properties are excluded

Properties sold at true market prices - right to buy sales at discounted price are excluded

Floor size has to be within specified limits for a give type of property

The number of cases that are used to calculate the average price for a given month will depend

on the volume of monthly mortgage activity and out of these the cases that meet the criteria in the

cleaning process. The monthly sample size varies from month to month.

All house price information is derived using Nationwide mortgage data. This data is extracted

monthly for mortgages that are at the approvals stage and after the corresponding valuation report

has been completed. Approvals data is used as opposed to mortgage completions since it should

give an earlier indication of current trends in prices in the housing market.

The price of a property depends on the characteristics of the property. Using mortgage data, the

Nationwide house price system relates all the observed combinations of these characteristics and

relates them to the price of which the house was sold for. From this, the model can estimate how

much on average a house would cost given a set value for these characteristics, in particular a set of

characteristics that describes the ‘typical’ house. This typical house does not physically exist; it is an

‘average’ house across all the characteristics that the model uses. This method is repeated on data

sets at different points in time and changes in the price of this typical house reflect only the price

changes over the same time periods, and not the mixture of properties sold in the current or

previous periods.

USA

Name of survey

Purchase-Only House Price Index

Source

Federal Housing Finance Agency

Definition

The House Price Index is a measure designed to capture changes in the value of single-family

houses in the U.S.

Frequency

Monthly


The House Price Index (HPI) covers all nine Census Divisions, the 50 states and the District of

Columbia, and every Metropolitan Statistical Area (MSA) in the U.S., excluding Puerto Rico. The HPI

is based on transactions involving conforming, conventional mortgages purchased or securitized by

Fannie Mae or Freddie Mac. Only mortgage transactions on single-family properties are included.

Each month, Fannie Mae and Freddie Mac provide Federal Housing Finance Agency with

information on their most recent mortgage transactions. These data is combined with the data from

previous periods to establish price differentials on properties where more than one mortgage

transaction has occurred. The data is merged, creating an updated historical database that is then

used to estimate the HPI.

The national index is constructed using quarterly growth rates for the Census Divisions. After

setting the base quarter, the national index for the following quarter is increased (or decreased) by

the weighted average quarterly price change for the nine Census Divisions. Then, in each

subsequent quarter, the national index grows by a rate equal to the average quarterly growth rate for

relevant quarter.

The weights used in constructing the weighted average quarterly growth rates reflect an estimate

of the Census Division’s contemporary share of one-unit detached properties in the U.S. For years in

which a Census was taken, the share from the relevant Census is used. For intervening years, a

Census Division’s share is the weighted average of the relevant shares in the prior and subsequent

Censuses, where the weights are changed by ten percentage points each year. Until the 2010

Census data become available, for years between 2001 and 2009, Census Division weights will be

set to the relevant shares in the 2000 Census.

The monthly indexes are calculated in the same way as the quarterly indexes are constructed,

except transactions from the same quarter are no longer aggregated. To construct the quarterly

index, all transactions from the same quarter are aggregated and index values are estimated using

the assigned quarters. In the monthly indexing model, all transactions for the same month are

aggregated and separate index values are estimated for each month.

8. STOCK MARKET INDICES

Country Index Name

Algeria Algiers Stock Exchange Index

Argentina MERVAL Index

Australia S&P/ASX 200 Index

Austria Vienna Stock Exchange Austrian Traded Index

Belgium BEL 20 Index

Bosnia-Herzegovina SASX10 Index

Brazil Bovespa Index

Bulgaria SOFIX Index

Canada S&P/TSX Composite Index

Chile IGPA Index

China Shanghai Stock Exchange Composite Index

Colombia COLCAP Index

Costa Rica IBNV Index

Croatia CROBEX Index

Czech Republic Prague Stock Exchange Index

Denmark OMX Copenhagen 20 CAP Index

Ecuador ECU Index

Egypt EGX30 Index

Estonia OMX Tallinn Index

Finland OMX Helsinki Index

France CAC40 Index

Georgia GSX Index

Germany DAX Index

Greece Athex Composite Share Price Index

Hong Kong, China Hong Kong Hang Seng Index

Hungary BUX Index

India NSE Nifty 50 Index

Indonesia JSX Composite Index

Iran TEDPIX Index

Ireland ISEQ Overall Index

Israel TA-100 Index

Italy FTSE MIB Index

Japan Nikkei 225 Index

Jordan ASE General Index

Kazakhstan KASE Index

Kenya NSE20 Index

Kuwait Kuwait Stock Exchange Index

Latvia OMX Riga Index

Lithuania OMX Vilnius Index

Macedonia MBI10 Index

Malaysia KLCI Index

Mexico IPC Index

Netherlands AEX Index

New Zealand S&P/NZX All Index

Nigeria NSE All-Share Index

Norway OSEBX Index

Pakistan KSE100 Index

Peru S&P/BVL Peru General Index

Philippines PSEi Index

Poland WIG20 Index

Portugal PSI All-Share Index

Qatar Qatar Exchange Index

Romania BET Index

Russia MICEX Index

Saudi Arabia Tadawul All Share Index

Serbia BELEXline Index

Singapore Straits Times Index

Slovakia SAX Index

Slovenia Slovene Blue-Chip Index

South Africa FTSE/JSE All Share Index

South Korea KOSPI 200 Index

Spain IBEX 35 Index

Sweden OMXS30 Index

Switzerland SMI Index

Taiwan Taiwan Stock Exchange Weighted Index

Thailand SET Index

Tunisia Tunisia Stock Market Index

Turkey BIST-100 Index

Ukraine PFTS Index

United Arab Emirates Abu Dhabi Securities Market General Index

United Kingdom FTSE All-Shares Index

Uruguay BVMBG Index

USA S&P 500 Index

Venezuela IBC Index

Vietnam VN Index

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