ICP Prelim Report MainText & App / 0/ 00 : : AMnamely, household final consumption expenditure, actual final consumption of households, government collective final consumption expenditure,

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About the Purchasing Power Parity Preliminary Report

The 2005 round of the International Comparison Program in Asia and the Pacific region (ICP Asia Pacific) has achieved a number of milestones. The simultaneous participation of the People’s Republic of China and India, which together account for 64% of the total real gross domestic product of the 23 participating economies, was a first for the ICP and significantly increased the coverage of the round. In addition, the diversity in the economies in terms of size, geography, and statistical capacities was overcome as the 23 participating economies worked harmoniously to generate price and national accounts data that are broadly comparable. Further, the estimates of purchasing power parities in this round are far more robust than previous rounds because of improvements in methodology, data collection, data review, and data processing. Finally, the ICP Asia Pacific has established the technical know-how and institutional requirements that future ICP rounds could build on.

About the Asian Development Bank

ADB aims to improve the welfare of the people in the Asia and Pacific region, particularly the nearly 1.9 billion who live on less than $2 a day. Despite many success stories, the region remains home to two thirds of the world’s poor. ADB is a multilateral development finance institution owned by 67 members, 48 from the region and 19 from other parts of the globe. ADB’s vision is a region free of poverty. Its mission is to help its developing member countries reduce poverty and improve their quality of life.

ADB’s main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. ADB’s annual lending volume is typically about $6 billion, with technical assistance usually totaling about $180 million a year.

ADB’s headquarters is in Manila. It has 26 offices around the world and more than 2,000 employees from over 50 countries.

Asian Development Bank6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippineswww.adb.org/economicsPublication Stock No. 070907 Printed in the Philippines

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2005 International Comparison Program in Asia and the Pacific

Purchasing Power Parity Preliminary Report

Economics and Research Department

July 2007



Foreword

The 2005 round of the International Comparison Program (ICP) is the largest global statistical undertaking, covering about 140 countries. To run the ICP efficiently, the world was divided into five geographic regions: Africa, Asia and the Pacific, the Commonwealth of Independent States, Latin America and West Asia, plus an additional “region” of countries included in the annual Purchasing Power Parity (PPP) program managed by the Organisation for Economic Co-operation and Development and the Statistical Office of the European Union. A regional organization coordinated the project in each of the five regions, with the Asian Development Bank (ADB) assuming the coordinating agency role for ICP in Asia and the Pacific region (ICP Asia Pacific). The ADB was assisted by the Regional Advisory Board, the highest policy-making body for ICP Asia Pacific, which was responsible for setting regional goals, priorities, and objectives, taking into consideration statistical needs of regional agencies and countries.

The current ICP structure was a result of a comprehensive strategic framework and action plan to address long-standing issues of the program. At its 32nd session in 2001, the UN Statistical Commission requested the World Bank, in collaboration with other agencies and “Friends of the Chair”, to formulate a new ICP framework that was subsequently endorsed during its 33rd session in 2002. The World Bank set up the ICP in 2002 to produce statistically sound comparisons of activity levels and income between countries. The Global Office located at the World Bank provided overall coordination for the project. A high-level ICP Executive Board steered the project to successful completion and delivery of high-quality results.

Initial planning for ICP Asia Pacific was carried out in December 2002 at ADB under the able stewardship of Bishnu Dev Pant, with work on the first stage (developing the product lists) commencing in late March 2003. The 23 economies that participated in the ICP Asia Pacific comparison—inclusive of 21 ADB developing member countries—account for over half of the world population and about a quarter of global gross domestic product. These were Bangladesh; Bhutan; Brunei Darussalam; Cambodia; People’s Republic of China; Fiji Islands; Hong Kong, China; India; Indonesia; Lao People’s Democratic Republic; Malaysia; Maldives; Mongolia; Nepal; Pakistan; Philippines; Singapore; Sri Lanka; Taipei,China; Thailand; and Viet Nam. At their request, the Islamic Republic of Iran and Macao, China also participated.

This publication presents preliminary results on estimates of PPPs of currencies of the participating economies. These include estimates of “real” gross domestic product and its major components, namely, household final consumption expenditure, actual final consumption of households, government collective final consumption expenditure, gross capital formation, and net external trade. The final phase


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of the 2005 global ICP will integrate results from Asia and the Pacific region with results from the other five regions. Final results for Asia and the Pacific region are scheduled for release in late 2007.

ICP Asia Pacific has achieved a number of milestones. The simultaneous participation of the People’s Republic of China and India, which together account for 64 percent of the total real gross domestic product of the 23 participating economies, was a first for the ICP and significantly increased the coverage of the round. In this round, the diversity in the economies in terms of size, geography, and statistical capacities was overcome as the 23 participating economies worked concertedly to generate price and national accounts data that are broadly comparable. Further, the estimates of purchasing power parities in this round are far more robust than previous rounds because of improvements in methodology, data collection, data review, and data processing. Finally, the ICP Asia Pacific has established the technical know-how and institutional requirements that future ICP rounds could build on.

I sincerely thank all those who have contributed to making ICP Asia Pacific a success—the Government of Japan, Department for International Development, Australian Agency for International Development, and World Bank for providing additional funding. The Australian Bureau of Statistics and the ICP Global Office provided technical assistance, and the international and national consultants assisted ADB in many ways. I also wish to thank the dedicated staff of the Economics and Research Department, and most importantly, the national implementing agencies and other government agencies in each of the 23 participating economies for their in-kind and financial contributions, cooperation, and hard work.

Ifzal Ali Chief Economist Asian Development Bank


Acknowledgment

The 2005 International Comparison Program in Asia and the Pacific (ICP Asia Pacific) was carried out by the governments and national statistical offices of 21 developing member countries of the Asian Development Bank (ADB), and the Islamic Republic of Iran and Macao, China. ICP Asia Pacific was financed by ADB through RETA 6088: Strengthening and Collection of Purchasing Power Parity Data in Selected DMCs.

This report, 2005 International Comparison Program in Asia and the Pacific: Purchasing Power Parity Preliminary Report, benefited considerably from partner development institutions that provided in-kind and financial support, including the Australian Agency for International Development and the Australian Bureau of Statistics, particularly Matthew Berger, Keith Blackburn, Mark King, and Timothy Lo who extended valuable technical assistance, and the World Bank.

Computation of purchasing power parity results was made possible through the technical guidance of our international consultants, Sultan Ahmad, Derek Blades, Paul McCarthy, Prasada Rao, Sergey Sergeev, and Kenneth Walsh. The World Bank provided extensive technical advice, particularly Yonas Biru, Stephen Burdette, Cindy Chi, Yuri Dikhanov, Ramgopal Erabelly, Vilas Mandlekar, Vijay Ramachandran, Anil Sawhney, Mahesh Shankaranarayanan, and Frederic Vogel.

Special thanks are due to the ICP National Coordinators and their team members in all participating national statistical offices for their active participation, hard work, and collection of quality price data. The domestic experts from participating economies also deserve appreciation for their committed support; in particular, the following are acknowledged for their participation as members of the Core Group of Experts on Construction: A. Alimaa, Katherine Oi Kwa Leung, Norida binti Shaffii, Nguyen Van Lieu, Vijay Sharma, Ernesto Villanueva, and Mohd Zaid bin Zakaria. A Core Group of Experts for Equipment was also instrumental in data validation—Sher Bahadur Budha, Lay Chhan, Cheng Sea Lai, Tejinder Singh Laschar, Alwin bin Othman, and Chandra Shekhar Roy.

ICP Asia Pacific also acknowledges the technical guidance received from its Regional Advisory Board composed of chair Carmelita Ericta, Administrator of the Philippines’s National Statistics Office; co-chair Ifzal Ali, ADB Chief Economist; Vice Chair from the Statistics Bureau of Japan; Regional Coordinator of ICP Asia Pacific, ADB, as member-secretary; and the following members: Deputy Australian Statistician of the Australian Bureau of Statistics; Commissioner of the National Bureau of Statistics of China; Commissioner of the Census and Statistics Department, Hong Kong, China; Director General of the Central Statistical Organization, India; Director-General of Statistics Indonesia; Director of the Statistics Division, United Nations Economic and Social Commission for Asia and the Pacific; Director of the United Nations Statistical Institute for Asia and the Pacific; and ICP Global Manager of the World Bank as ex-officio member. Valuable inputs from past chairs of the Board are also acknowledged, namely Paul Cheung, former Chief Statistician of the Department of Statistics, Singapore; and Frederick Ho, former Commissioner for Census and Statistics of the Census and Statistics Department, Hong Kong, China.


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This report was prepared by ADB’s Development Indicators and Policy Research Division (ERDI) of the Economics and Research Department, under the overall supervision and guidance of Vaskar Saha, Principal Statistician, with the technical assistance of Lutgarda T. Labios and Eileen P. Capilit. Work on PPP computations was undertaken by the core ERDI team with assistance from domestic consultants Virginia N. Gañac and Gaye A. Parcon. Administrative assistance was provided by Clarita D. Truong and Evelyn E. Andrada. IT assistance was provided by Rhommell S. Rico. Timothy Lo and Ajay Tandon, former ERDI staff, provided technical assistance to the program. Editorial work was performed by Lee Siew Hua and Cherry Lynn T. Zafaralla who also coordinated production with the assistance of Fatima Christine D. Blanco who proofread various versions of the draft. Design and typesetting were performed by Joe Mark Ganaban. This report was published with the support of the ADB Printing Unit under the supervision of Raveendranath Rajan.

Bishnu Dev Pant Assistant Chief Economist Development Indicators and Policy Research Division


contents

Foreword ......................................................................................................................................... iiiAcknowledgment ............................................................................................................................. vAcronyms ......................................................................................................................................... ixBox, Tables, and Figures ................................................................................................................... x

I. Introduction ............................................................................................................................. 1

II. The 2005 International Comparison Program ......................................................................... 3 A. ICP in Asia and the Pacific Region ................................................................................. 3 B. Intercountry Comparisons: Why are Exchange Rates Inappropriate? .............................. 4

III. Purchasing Power Parity Explained ......................................................................................... 6 A. What are PPPs? .............................................................................................................. 6 B. Uses of PPPs ................................................................................................................... 8 C. Caution in the Use of PPPs ............................................................................................ 9

IV. Preliminary Results for Asia and the Pacific Economies .......................................................... 10

V. Product Specification and Price Surveys .................................................................................. 22

VI. National Accounts: Critical for the 2005 ICP ......................................................................... 25

VII. Using PPPs to “Deflate” Basic Heading Expenditures ............................................................. 27

VIII. New Methodologies Introduced in ICP Asia Pacific ................................................................ 28 A. Dwellings ....................................................................................................................... 28 B. Compensation of Employees .......................................................................................... 28 C. Construction .................................................................................................................. 29

IX. Concluding Remarks .............................................................................................................. 30

Appendix A: List of Implementing Agencies in ICP Asia Pacific ....................................................... 32Appendix B: Preliminary PPP Results .............................................................................................. 33Appendix C: Real Expenditure Comparison and Price Level Indices with the Regional Average as Base .................................................................................................... 44Appendix D: Productivity Adjustment for Government Compensation ............................................ 46Appendix E: Glossary of PPP-related Terms ..................................................................................... 49

References ........................................................................................................................................ 52



Acronyms

ADB Asian Development BankAFCH actual final consumption of householdsBOCC basket of construction componentsCPI consumer price indexGDP gross domestic productEKS Elteto-Köves-SzulcHK Hong Kong, ChinaICEH Individual consumption expenditures by householdsICP International Comparison ProgramNPISH nonprofit institutions serving householdsOECD Organisation for Economic Co-operation and DevelopmentPLI price level indexPPP purchasing power parityPRC People’s Republic of ChinaRAB Regional Advisory BoardSNA System of National AccountsSPD structured product descriptionSPM standard-projects-based methodTAG Technical Advisory GroupUN United Nations


Box, tABles, And Figures

Box 1. Special Note ........................................................................................................................ 12

Table 1. Big Mac Index Illustration ................................................................................................ 7Table 2. Summary Table on Gross Domestic Product, 2005 (nominal in Hong Kong dollars) ........ 13Table 3. Summary Table on Gross Domestic Product, 2005 (real in PPP terms, Asia as base) ......... 14Table 4. Summary Table on Actual Final Consumption of Households, 2005 ................................ 15Table 5. Indices of Per Capita Real GDP, 2005 (Asia = 100) .......................................................... 18Table 6. Indices of Per Capita Real GDP, 2005 (Hong Kong, China = 100) ..................................... 18Table 7. GDP Price Level Indices, 2005 (Asia = 100) ........................................................................ 19Table 8. GDP Price Level Indices, 2005 (Hong Kong, China = 100) ................................................ 19Table 9. Gross Domestic Product and Its Structure: Number of Basic Headings and Products, and Average Expenditure Shares, 2005 ........................................................................................... 26

Figure 1. Per Capita Real GDP, 2005 ............................................................................................. 16Figure 2. Per Capita Real Actual Final Consumption of Households, 2005 .................................... 17Figure 3. GDP Price Level Indices, 2005 (Asia = 100) ..................................................................... 20Figure 4. GDP Price Level Indices, 2005 (Hong Kong, China = 100) ............................................. 20

Appendix Table B1. Purchasing Power Parities, 2005 ..................................................................... 34Appendix Table B2. Price Level Indices, 2005 (Hong Kong, China = 100) ..................................... 35Appendix Table B3. Per Capita Real Expenditures, 2005 ............................................................... 36Appendix Table B4. Price Level Indices, 2005 (Asia = 100) ............................................................. 37Appendix Table B5. Real Expenditure, Economy Shares to Asia by Category, 2005 ....................... 38Appendix Table B6. Per Capita Real Expenditure Relatives, 2005 .................................................. 39Appendix Table B7. Nominal Expenditure Shares by Category, 2005 ............................................. 40Appendix Table B8. Per Capita Nominal Expenditures, 2005 ........................................................ 41Appendix Table B9. Nominal Expenditures, Economy Shares to Asia by Category, 2005 ............... 42Appendix Table B10. Per Capita Nominal Expenditure Relatives, 2005 ......................................... 43Appendix Table C. Derivation of Real Expenditures with the Regional Average as Base ................. 45Appendix Table D. Effect of Productivity Adjustment for Selected Economies in ICP Asia Pacific ... 48

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i. introduction

The 2005 International Comparison Program (ICP) is a global statistical project set up upon the recommendation of the United Nations Statistical Commission to enable international comparisons of economic aggregates such as income, price levels, and purchasing power of currencies. The scale of the project—140 participating countries from all the geographic regions of the world—is far greater than all the previous phases of the ICP. The ICP Global Office located in the World Bank is coordinating the overall program, with the assistance of agencies that are managing the regional programs. The Asian Development Bank (ADB) has the lead role as coordinating agency for the ICP in Asia and the Pacific region (ICP Asia Pacific).

The region coordinated by ADB is one of the world’s largest and most diverse regions. The economies in ICP Asia Pacific—including People’s Republic of China (PRC), India, Indonesia, Pakistan, and Bangladesh, which respectively are five of the eight most populous economies in the world—make up more than 50 percent of the world population. In 2005, the ICP Asia Pacific economies contributed over 25 percent of the world’s production, as measured by gross domestic product (GDP) adjusted to a numeraire currency using purchasing power parities (PPPs).

The ADB and various agencies in the 23 participating economies devoted considerable human and financial resources to ICP Asia Pacific. The list of implementing agencies in ICP Asia Pacific is found in Appendix A. The ICP team in ADB worked on the project between 2003 and 2007 with the assistance of a number of international and domestic consultants.

The complex task of conducting a large-scale project like ICP Asia Pacific covering 23 economies is further complicated by the geographical dispersion of the economies, and by the large variations in their size, structure, and standard of living. The huge variety in the types of goods and services produced and consumed in different parts of the region presented ADB with some difficult problems during the process of developing a common list of products to be priced across the region.

Meeting the challenges, ADB undertook the project and released new data that will be available for the analysis of economic and social structures of economies in the region, and for the comparison of significant characteristics such as national production, income, and poverty levels. The major findings of ICP Asia Pacific are presented in this report, namely GDP and its major components for the 23 participating economies, expressed in a numeraire currency, the Hong Kong dollar (HK$), to enable direct comparisons

How Big is ICP Asia Pacific ?

ICP Asia Pacific covers over half of the world’s population that contributes more than a quarter of the world’s

economic output, as measured by gross domestic product.


2005 INTERNATIONAL COMPARISON PROGRAM IN ASIA AND THE PACIFIC

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PURCHASING POWER PARITY PRELIMINARY REPORT

of levels of economic activity, household consumption, and gross fixed capital formation. The results are also expressed in regional average for Asia, to enable comparisons to be made readily between individual economies and the average for Asia and the Pacific region. Comparisons based on individual consumption expenditures by households (ICEH) are also presented. These data will be useful in assessing poverty incidence in the region.

The final stage of the 2005 ICP will be reached when the World Bank releases its report on global comparisons covering about 140 countries around end-2007. The ICP global results will provide comparisons between countries belonging to different regions of the world without affecting the relativities of the countries belonging to the same region. For example, it will be possible to make comparisons between Hong Kong, China in ICP Asia Pacific, with Japan from the Organisation for Economic Co-operation and Development (OECD), or Brazil from Latin America.

The subsequent sections of this preliminary report follow this structure. Section II offers a description of the ICP project globally and in Asia and the Pacific region, and explains why exchange rates are inappropriate for making intercountry comparisons of economic output. Section III discusses the most important concept associated with international comparisons, PPP, using illustrative examples; and also lists the uses and precautions in using PPPs. Section IV sets the context for results for the region. Section V is on product specifications and price surveys, while Section VI discusses the structure and conceptual framework of the System of National Accounts, which supplies all the concepts necessary for international comparisons of major economic aggregates. Section VII describes the technical essentials of using PPPs to “deflate” basic heading expenditures, while Section VIII discusses the new methodologies used in the ICP Asia Pacific such as those for dwellings, compensation, and construction. Section IX concludes. A series of appendices follows, which include the list of implementing agencies in ICP Asia Pacific (Appendix A); a set of 10 tables on GDP and its major aggregates (Appendix B); a note on real expenditure comparison and price level indices with the regional average as base (Appendix C); productivity adjustment for government compensation (Appendix D); a glossary of PPP-related terms (Appendix E); and references.


2005 INTERNATIONAL COMPARISON PROGRAM IN ASIA AND THE PACIFIC PURCHASING POWER PARITY PRELIMINARY REPORT

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ii. the 2005 internAtionAl compArison progrAm

The main objective of the 2005 ICP is to provide measures of real expenditures, derived using PPPs of currencies for a large number of countries, which are computed from price data collected through extensive price surveys.

These statistics have taken on a higher profile in the last few years as the severity of the statistical shortcomings of using exchange rates to make international comparisons has become more widely recognized. As a result, more explicit use is being made of PPP data for global development goal-setting, and for monitoring progress toward achieving the United Nations’s Millennium Development Goals. In addition, the spread of globalization and the worldwide integration of markets and financial institutions have highlighted the importance of reliable and timely measures of internationally comparable macroeconomic aggregates. The current phase of the ICP began with initial planning in 2002 and with 2005 as the benchmark year, hence the title “2005 ICP.” The project will be completed in late 2007 and the ICP-related activities will culminate in the publication of the results for all the regions, including Asia and the Pacific region.

A. ICP in Asia and the Pacific Region

The ADB is the ICP coordinating agency in Asia and the Pacific region. Twenty-one developing member countries of the ADB joined the ICP program. In addition, the Islamic Republic of Iran and Macao, China are also in the regional comparison. The project has operated with generous funding and support in cash and in kind from the ADB. The project also received both financial and in-kind support from the Australian Agency for International Development, the Australian Bureau of Statistics, the Government of Japan, the Department for International Development, and the World Bank. The project received technical advice and support from the ICP Global Office throughout the tenure of the project. The ICP Global Office also played a major role in conducting activities to link regional results. A project of this magnitude and complexity cannot be managed without the active participation of the national statistical offices of the participating economies, which were responsible for collecting price data and providing the detailed national accounts data.

In ICP Asia Pacific, the Regional Advisory Board (RAB) is the highest policy-making body and is responsible for setting regional goals, priorities, and objectives, taking into consideration statistical needs of regional agencies and economies. The RAB is chaired by the Administrator of the Philippine National Statistics Office and co-chaired by the Chief Economist of ADB. The Vice Chair is the Director General of the Statistical Standards Department, Japan Statistics Bureau. Members are from the following agencies: Australian Bureau of Statistics; National Bureau of Statistics of China; Census and Statistics Department, Hong Kong, China; Ministry of Statistics and Programme Implementation, India; Statistics Indonesia; United Nations Economic and Social Commission for Asia and the Pacific; United Nations Statistical Institute for Asia and the Pacific; and the ICP Global Office as ex-officio member. The ADB, as ICP Asia Pacific Regional Coordinator, sits as member-secretary.



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The diversity in the region is evident when the size of the economies is considered, with the PRC and India, two of the world’s largest economies, participating alongside Hong Kong, China and Singapore, two of the smallest economies in population size but among the richest in income. The participating economies are also at different stages of development: some of the richest and poorest are located in this region, as are some of the fastest-growing economies of the world. ICP Asia Pacific was run successfully by creating a spirit of cooperation amid great diversity, while a series of workshops conducted at various stages was designed to enhance the participation of the economies. This strategy has helped to create a sense of ownership of the project among the participants. The economies are, therefore, the stakeholders of the project.

B. Intercountry Comparisons: Why are Exchange Rates Inappropriate?

Human development has many dimensions—per capita incomes, economic growth, health, education, social progress, globalization, and/or poverty reduction. In each case, it is vital to have internationally comparable, high-quality statistical measures to make reliable intercountry comparisons, monitor progress, and assist in evidence-based decision making.

Comparing economic and social data (such as poverty statistics) is complex because economic aggregates are typically expressed in national currencies. The use of exchange rates is a common method to convert economic data from a national currency to a numeraire currency such as the United States dollar. However, this simplistic approach is not appropriate for comparisons of real income or output and for comparisons of productivity and standards of living.

Using exchange rates to convert aggregates in national currency units can be misleading because exchange rates do not reflect relative domestic price levels and are influenced by extraneous factors such as financial flows. Exchange rates are often subject to large, short-term swings of a speculative nature that can wrongly imply corresponding shifts in relative living standards. In assessing the relative standards of living, it is necessary to compare the volumes of goods and services (value aggregates in real terms or at constant prices) actually available to residents of different countries in their own countries, taking into account the relative price levels of each of the countries.

How does the Japanese Economy Compare with that of the United States?

On an exchange rate basis, Japan’s economy was 60 percent the size of the United States in 1996 but only 38 percent in 2002, which is an economically implausible outcome given their relative rates of economic growth over those 6 years. On the other hand, the comparable estimates on a PPP basis were 39 percent in 1996 and 34 percent in 2002, which aligns fairly well with changes in the relative shares calculated using the average annual rates of economic growth in the United States and Japan of 3.2 and 0.5 percent, respectively, over that period.

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Empirical studies have shown that using exchange rates for international comparisons systematically widens the gap between the outcomes for high-income and low-income countries. Exchange rates are driven by a number of factors, including the prices of traded goods, which are effectively set on world markets. The exchange rates generally overstate the relative price levels of low-income countries and so understate measures such as real GDP per capita. The reason is that the price levels are also low in low-income countries, particularly for services whose prices are largely dependent on labor costs.

In 2001, the United Nations Statistical Commission reaffirmed that the use of exchange rates is inappropriate for most types of international comparisons, which can also lead to quite misleading conclusions. A more appropriate and robust method is to use PPPs of currencies designed to measure differences in the price levels of goods and services in different countries. Differences in levels of economic development measured using exchange rates and PPPs can also be very large.



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iii. purchAsing power pArity explAined

A. What are PPPs?

This section provides some background on PPPs and what they mean. A glossary of PPP-related terms is in Appendix E. A detailed description of the methodology underlying PPPs is set out in the World Bank’s ICP 2003-2006 Handbook (World Bank 2007a).

Purchasing power parity is “…the number of currency units required to purchase an amount of goods and services equivalent to what can be bought with one unit of currency of the base country, for example the United States dollar. PPP conversion rates allow users to compare real economic outputs across countries at a common set of average international prices …” (World Bank 2007a, chapter 1). In practice, any currency can be used as the numeraire currency. In Asia and the Pacific region and in this publication, Hong Kong, China was used as the base economy, which means that results are presented either in terms of values expressed in Hong Kong dollars or as an index with Hong Kong, China = 100. In addition, results are also presented in terms of regional average for Asia 1 to enable comparisons to be made readily between individual economies and the average for all 23 economies. It is important to note that the relative volume and price comparisons across economies remain unchanged when a different currency is used as the numeraire or when the results are expressed in index number form.

The most celebrated example of a PPP is the “Big Mac Index” compiled and regularly published by The Economist magazine. The Big Mac Index is a PPP that is based solely on the price of a Big Mac in various countries, a commodity that is comparable in quality and available in most countries (Table 1).

The Big Mac Index is a simple example of a PPP but is of little use in practice to make international comparisons because it is not representative of all the goods and services included in GDP. It is also not available in all countries. More reliable and true measures of PPPs, such as those compiled as part of the 2005 ICP, are constructed using a large volume of data on prices of a broad range of goods and services that make up GDP. In ICP Asia Pacific, the participating economies priced from a list of around 800 household and nonhousehold products in 2005 and early 2006.

1 Appendix C provides details of how real expenditures with the regional average for Asia as base are computed.

What is a PPP?

A PPP is the number of currency units required to purchase an amount of goods and services equivalent to what can be bought with one unit of currency of a base country.



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To calculate PPPs, it is necessary to identify goods and services of similar quality that are comparable across all the countries involved in the comparison. The selected items should be broadly representative of the goods and services purchased in each country involved (see Section V for more details about what is meant by “comparable and representative products”). It is difficult to identify products that meet these two competing criteria, so compromises have to be made in the process. Once the full range of price data is collected, relative prices of the items are weighted using national accounts data to compute PPPs for different commodity groupings, ranging from detailed component expenditures to broad aggregates such as individual consumption expenditures by households, and to total GDP measured from the expenditure side. PPPs are compiled for different national accounts aggregates, including GDP itself, to convert them to a numeraire currency.

An important use of PPPs is to derive measures of relative price levels between countries by dividing PPPs of each country by the corresponding exchange rate and multiplying them by 100 to present them as an index. In practice, these types of results are presented formally as price level indices (PLI) and can relate to the whole of GDP or to different components of GDP. PLIs are sometimes referred to as “comparative price levels.” PLIs greater than 100 indicate the countries that are relatively more “expensive” than the base or numeraire country (or the regional average, depending on what is chosen as the base, equal to 100). On the other hand, PLIs of less than 100 indicate the “cheaper” countries.

If for example we use the Big Mac Index 2 for Thailand and the United States, the resulting PPP for a Big Mac in Thailand as shown in Table 1, is estimated to be 19.255 (i.e., 62.0/3.22) using the United States as the base (or numeraire) country. The PLI for Thailand, on the other hand, is calculated at 60, i.e., (19.255/31.89)*100, thereby indicating that it is “cheaper” to purchase a Big Mac in Thailand than in the United States.

2 Data were obtained from OANDA (2007).

What is a Price Level Index?

A PLI is the ratio of a PPP to the corresponding exchange rate (times 100). For example, a PLI of 110 indicates that prices in

that country are on average 10 percent higher than the prices in the base country.

Table 1Big Mac Index Illustration

CurrencyPrice (LCU)

as of February 2007

Exchange rate

(to US$)

PPP (US$ numeraire

currency)

PLI (US = 100)

United States US dollar 3.22 1.00 1.00 100

Thailand Thai baht 62.00 31.89 19.255 60

LCU means local currency unit; PLI means price level index; US means United States.



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B. Uses of PPPs

The most common use of PPPs is their application to national accounts data to provide estimates of the levels of GDP, and also GDP per capita that are comparable directly across countries. In other words, PPPs are an intermediate step in determining the levels of outputs expressed in a numeraire currency for all countries included in the comparison. Apart from the obvious use of comparing the levels of GDP and its major components, the main uses of these data are for comparing productivity levels and aggregating real expenditures into regional and subregional totals (e.g., the total GDP in 2005 for Asia and the Pacific region).

The per capita levels of GDP and its various components are useful for many types of analysis. International comparisons now focus more on measures of inequality. This often means that accurate values must be assigned to the poverty income levels between countries, and so robust per capita estimates are important for these calculations. Generally, such analyses focus on actual final consumption of households (AFCH) rather than on GDP to compare living standards across countries or as input into poverty analysis.

As well as being important as an intermediate step in calculating the real (volume) levels for GDP and its major components, PPPs are an essential input in calculating the PLIs that enable the relative price levels in countries to be compared (i.e., determining whether goods and services in a country are relatively expensive or relatively cheap). While the PLI for GDP measures the overall price level in a country, PLIs can also be calculated for main aggregates such as household consumption, capital formation, and government expenditures; and for more detailed levels of expenditures such as food, clothing, transport, construction, etc. Policymakers can use this information to identify goods or services whose price levels are high compared with other countries in the region, and they can determine if these are due to market imperfections that may be remedied by policy measures.

PPPs can also be used to make a wide range of intercountry comparisons relevant for economic and social policy. For example:

Actual final consumption of households, or the sum of individual consumption expenditures by households and individual consumption expenditures by government, both converted by PPPs, are the best available measure of household living standards.

Comparisons of expenditures on gross fixed capital formation show which countries have a strong potential for future economic growth.

Comparisons of total individual and collective consumption expenditures by government show the true size of government in different countries.



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C. Caution in the Use of PPPs

While PPPs are a powerful tool for several kinds of economic analysis, a word of caution is needed. First, PPPs do not tell us what the exchange rate “should be.” When the theory of PPPs was first developed, it was argued that PPPs would be close to “equilibrium exchange rates.” But the PPPs from the 2005 round cover not only tradable products but also nontradables such as construction goods and government services. In any event, exchange rates are determined by the total demand for a particular currency, and financing foreign trade is only one component of this demand. PPPs, therefore, cannot be used to indicate a country’s “correct” exchange rate, which is determined by international currency markets.

Second, PPPs are statistics and so are subject to sampling errors. National accounts statistics that are used as weights in the calculation of PPPs at basic heading level also contain similar errors. When PPPs and national accounts are combined into total or per capita GDP (in PPP terms), they cannot be used to establish strict rankings between countries. Differences between countries of under 5 percent or so are not significant—they are unlikely to represent real differences between them. The reliability of PPPs and volume measures based on them depends on the level of detail. For example, PPPs for “Food and Nonalcoholic Beverages” are quite reliable; PPPs for “Food” are fairly reliable; PPPs for “Bread and Cereals” are likely to be less reliable; and PPPs for “Rice” should be used with caution since small differences between countries are certainly not significant.

Obviously, some components of GDP are more challenging to compare than others. For example, nonmarket services such as the provision of health, education, and other government services remain difficult, despite concerted research efforts that aim to address long-standing problems. Construction projects are another area of weakness in the ICP because of differences in building codes, quality of materials, type and amount of equipment utilized, and labor skills. Striking a delicate balance between comparability and representativity of products and services makes the challenge even more compelling. This is particularly true when countries in the comparison are different in terms of expenditure patterns, as well as in economic and social development. Hence results in difficult-to-compare sectors will have to be approached with greater caution than other GDP components.

Finally, time series of GDP (in PPP terms) are misleading. Real GDP provides a snapshot of the relative real GDP levels among participating countries for a given benchmark year. When benchmark PPP estimates are placed side by side, these snapshots may appear to provide a moving picture of relative real GDP levels over the years, but this apparent time series of real GDP is actually similar to a current price time series showing the combined effect of changes in relative price levels and changes in relative real GDP levels. Within each year, the indices are at a uniform price level, but the uniform price level changes from one reference year to the next. To construct a comparable time series of real GDP for a group of countries, each country’s GDP figures should be converted to a numeraire currency using the PPPs for a selected base year.

PPPs and Poverty Analysis

While the major use of PPPs is to compare economic variables such as GDP, they also have an important use in estimating

incidence of poverty, including the number of poor living under the $1-a-day and $2-a-day international poverty lines.



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iV. preliminAry results For AsiA And the pAciFic economies

The PPP and the real (or volume) measures for different basic headings and national income aggregates are expressed in terms of a “numeraire” currency. In addition, they are presented on the basis of the Asian average, which is useful for analyzing the status of countries compared with the average for Asia and the Pacific region (see Appendix C for details of real expenditure comparison and price level indices with the regional average for Asia as base). The choice of the numeraire currency does not affect the relativities between different countries so the only difference between these two sets of estimates is the base on which they are shown.

The real GDP levels obtained using PPPs indicate the relative size of each economy in Asia and the Pacific region. The results of international comparisons can be presented either in index number form or in terms of values expressed in a “numeraire currency.”

The real measures are also expressed in index form, referred to as expenditure relatives, with the level of an individual country or an average for a group (such as Asia and the Pacific region) set to a value of 100. For example, if per capita GDP in Hong Kong, China is set to an index of 100, then an index of 80 for a country shows that the per capita GDP of the economy is at 80 percent of the level observed for Hong Kong, China. Alternatively, if the Asian regional average is used, the index values show each economy’s position relative to the average for all 23 economies. The relativities between economies are the same whether they are expressed as index numbers or in terms of any one economy’s currency. In this report, the economic aggregates and the per capita levels are presented both in Hong Kong dollars and in regional average for Asia.

The preliminary results cover all the major components of GDP, i.e., individual consumption expenditures by households, actual final consumption of households, collective consumption expenditures by government, gross capital fixed formation, change in inventories and net aquisition of valuables, and balance of exports and imports. PPP-adjusted ICEH and AFCH are two different (but similar) measures of the level of household consumption in each country. According to the Commision of the European Communities et al. (1993) System of National Accounts 1993, ICEH “…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” (Commision of the European

Currency for the Regional Comparison

The currency unit used for Asia and the Pacific region comparisons is the Hong Kong dollar. The relativities between countries are not affected by the currency unit—it is simply a device to provide a meaningful level for the comparisons.



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Real GDP in PPP Terms or “Volume” of GDP

The GDP estimates used in the calculations are “PPP-adjusted”, which means that the GDP for each country,

expressed in its local currency, is divided by the country’s PPP for GDP. The result is referred to as the real GDP (in

PPP terms or “volume of GDP”).

Communities et al. 1993, paragraph 9.4). Paragraphs 9.3 and 9.11 of SNA93 define AFCH as “…the value of the consumption goods and services acquired by households, whether by purchase in general, or by transfer from government units or nonprofit institutions serving households (NPISHs), and used by them for the satisfaction of their needs and wants; it is derived from their ICEH by adding the value of social transfers in kind receivable.” Therefore, AFCH is a broader aggregate than ICEH. The reason for focusing on AFCH rather than ICEH is that the proportion of individual services, such as health and education, produced by government varies significantly from one country to another. AFCH enables comparisons to be made that are not affected by the differing extent to which governments provide such services in different countries.

While it is useful to have a measure of the actual levels of activity for different countries, a more informative measure of the relative living standards of Asia and the Pacific economies is to adjust the measures based on PPPs to take account of the population in each economy; i.e., calculate per capita measures. It is generally acknowledged that GDP per capita is not perfect in a number of ways as a measure of living standards. However, GDP provides the broadest measure of economic activity currently available. There is also a strong correlation between high levels of GDP per capita and high living standards.

All the national income aggregates need to be expressed in per capita terms in order to make comparisons of relative living standards in different countries of the region. The estimates of per capita ICEH and AFCH also provide useful indicators of relative living standards between countries because they reflect the levels of expenditure that residents of a country are able to sustain from their incomes.

It is important to note that PPPs and the national accounts that are used in conjunction with the PPPs are only estimates and as such are subject to statistical errors. Furthermore, the scope or coverage of each country’s national accounts will be reflected in the PPP-based real per capita estimates. As a result, small differences between countries in PPPs and real per capita figures may not be statistically significant.

In interpreting the results, account should be taken of the fact that the shares of consumption and investment in GDP differ from one economy to another throughout the region and so the relativities between economies may be different depending on whether GDP, or investment, or consumption is used as the basis for the comparison. As a result, users need to carefully consider the types of analysis they are undertaking and select the most appropriate indicators for their purposes. Box 1 contains other caveats in viewing and interpreting the results.

Tables 2 and 3 highlight the preliminary results of the ICP, particularly the nominal and real GDP using Hong Kong, China and Asia as base, respectively. Meanwhile, Table 4 provides a summary of the resulting nominal and real AFCH, also with both Hong Kong, China and Asia as base. More detailed information on major aggregates is provided in Appendix Tables B1 to B10 of Appendix B.

ICP Prelim Report MainText & App�� /�0/�00� ��:��:�� AM


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Box 1Special Note

Maldives is participating only in the actual final consumption of households.

The results for the PRC were based on national average prices extrapolated by the World Bank and ADB, using price data for 11 cities submitted by the National Bureau of Statistics of China. The extrapolation methodology was endorsed by an ADB-constituted Expert Group in June 2006 (ADB 2006). In addition, the GDP weights for the PRC at the national level were compiled by a special ADB mission that worked in close collaboration with the National Bureau of Statistics of China in July/August 2006.

In most economies, data for the NPISH are merged with household data because it is difficult to segregate NPISH data. However, for economies that provided data on NPISH, an effort was made to break down their NPISH expenditures into health, education, and other components. The health and education components of NPISH data were merged with the health and education categories of household consumption. Other NPISH expenditures were distributed proportionately among the basic headings for household consumption.

The net expenditures of residents abroad were distributed proportionately among the relevant basic headings under individual consumption expenditures by households.

The prices of fruit and vegetables provided by Taipei,China were high due to unusual climate conditions in 2005. It was, nevertheless, decided to use these exceptional prices because they reflect the actual situation in Taipei,China in the reference year.

For the last several years, Bhutan has been undertaking major construction activities for hydropower projects, roads, bridges, expressways, and housing, resulting in very high expenditure shares for gross fixed capital formation.

In the tables, Asia refers only to the 23 economies participating in ICP Asia Pacific.

PPP results were based on data submitted as of 4 July 2007.



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Table 2Summary Table on Gross Domestic Product, 2005

(nominal in Hong Kong dollars; real in PPP terms, Hong Kong, China as base)

Economy CurrencyPurchasing

power parity

Exchange rate

(LCU/HK$)

Price level index

Nominal GDP (millions)

Real GDP (millions)

Population (thousands)

Per capita nominal

GDP

Per capita real GDP

Per capita real

expenditurerelatives

Bangladesh Taka 3.964 8.27 48 475,665 992,554 136,990 3,472 7,245 4

Bhutan Ngultrum 2.781 5.67 49 6,510 13,273 635 10,252 20,903 10

Brunei Darussalam Brunei dollar 0.159 0.21 74 74,129 99,773 370 200,293 269,581 133

Cambodia Riel 224.697 526.21 43 48,826 114,344 13,828 3,531 8,269 4

China, People’s Republic of* Yuan renminbi 0.599 1.05 57 17,451,129 30,710,911 1,303,720 13,386 23,556 12

Fiji Islands Fiji dollar 0.255 0.22 117 23,315 19,869 842 27,674 23,583 12

Hong Kong, China Hong Kong dollar 1.000 1.00 100 1,382,675 1,382,675 6,813 202,941 202,941 100

India Indian rupee 2.583 5.67 46 6,055,915 13,293,351 1,101,318 5,499 12,070 6

Indonesia Rupiah 690.583 1,247.82 55 2,231,853 4,032,766 218,869 10,198 18,427 9

Iran, Islamic Republic of Iranian rial 469.933 1,152.58 41 1,704,656 4,180,903 68,700 24,813 60,857 30

Lao PDR Kip 522.475 1,370.03 38 22,331 58,556 5,651 3,951 10,361 5

Macao, China Pataca 0.923 1.03 90 90,239 100,665 473 190,596 212,617 105

Malaysia Ringgit 0.305 0.49 63 1,066,769 1,701,849 26,128 40,829 65,136 32

Maldives** Rufiyaa 1.65 5,831 294 19,850

Mongolia Tugrik 73.018 154.97 47 18,132 38,482 2,548 7,117 15,104 7

Nepal Nepalese rupee 3.963 9.18 43 67,599 156,533 25,343 2,667 6,177 3

Pakistan Pakistani rupee 3.351 7.65 44 920,875 2,102,724 153,963 5,981 13,658 7

Philippines Philippines peso 3.828 7.08 54 767,759 1,420,689 85,261 9,005 16,663 8

Singapore Singapore dollar 0.189 0.21 88 907,643 1,025,751 4,342 209,123 236,336 116

Sri Lanka Sri Lankan rupee 6.171 12.92 48 186,333 390,191 19,668 9,474 19,839 10

Taipei,China New Taiwan dollar 3.407 4.14 82 2,761,429 3,351,803 22,653 121,908 147,971 73

Thailand Baht 2.800 5.17 54 1,370,535 2,531,331 64,763 21,162 39,086 19

Viet Nam Dông 821.174 2,039.12 40 411,556 1,021,965 83,120 4,951 12,295 6

Asia*** 38,051,705 68,740,957 3,346,291 11,371 20,545

LCU means local currency unit.*Results for the PRC were based on national average prices extrapolated by the World Bank and ADB using price data for 11 cities submitted by the National Bureau of Statistics of China. **Maldives is only participating in the comparison of actual final consumption of households.*** Asia refers only to the 23 participating economies.



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Table 3Summary Table on Gross Domestic Product, 2005

(real in PPP terms, Asia as base)

Economy Price level index Real GDP (millions)

Per capita real GDP

Per capita real expenditure relatives

Bangladesh 87 549,371 4,010 35

Bhutan 89 7,346 11,570 102

Brunei Darussalam 134 55,223 149,211 1,312

Cambodia 77 63,288 4,577 40

China, People’s Republic of* 103 16,998,242 13,038 115

Fiji Islands 212 10,997 13,053 115

Hong Kong, China 181 765,299 112,326 988

India 82 7,357,759 6,681 59

Indonesia 100 2,232,307 10,199 90

Iran, Islamic Republic of 74 2,314,095 33,684 296

Lao PDR 69 32,411 5,735 50

Macao, China 162 55,717 117,682 1,035

Malaysia 113 941,959 36,052 317

Mongolia 85 21,300 8,360 74

Nepal 78 86,640 3,419 30

Pakistan 79 1,163,862 7,559 66

Philippines 98 786,340 9,223 81

Singapore 160 567,950 130,810 1,150

Sri Lanka 86 215,968 10,981 97

Taipei,China 149 1,855,254 81,900 720

Thailand 98 1,401,070 21,634 190

Viet Nam 73 565,649 6,805 60

Asia ** 100 38,048,046 11,371 100

*Results for the PRC were based on national average prices extrapolated by the World Bank and ADB using price data for 11 cities submitted by the National Bureau of Statistics of China.

** Asia refers only to the 23 participating economies.



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Table 4Summary Table on Actual Final Consumption of Households, 2005

(nominal in Hong Kong dollars; real in PPP terms)

Economy

Hong Kong dollar Hong Kong, China as base Asia as baseNominal

AFCH (millions)

Per capita nominal

AFCH (HK$)

Purchasing powerparity

Price level index

Real AFCH (millions)

Per capita

real AFCH

Per capita real

expenditure relatives

Price level index

Real AFCH (millions)

Per capita real

AFCH

Per capita real

expenditure relatives

Bangladesh 369,420 2,697 3.404 41 897,638 6,553 70 87 422,346 3,083 50

Bhutan 3,444 5,424 2.491 44 7,840 12,346 132 93 3,689 5,809 94

Brunei Darussalam 21,210 57,308 0.150 70 30,253 81,744 875 149 14,234 38,461 626

Cambodia 41,985 3,036 205.610 39 107,452 7,771 83 83 50,557 3,656 59

China, People’s Republic of* 7,500,482 5,753 0.527 50 14,996,018 11,502 123 106 7,055,750 5,412 88

Fiji Islands 19,608 23,273 0.201 92 21,260 25,235 270 196 10,003 11,873 193

Hong Kong, China 853,716 125,303 1.000 100 853,716 125,303 1,341 213 401,680 58,956 959

India 3,838,844 3,486 2.115 37 10,292,820 9,346 100 79 4,842,856 4,397 72

Indonesia 1,500,822 6,857 567.056 45 3,302,607 15,089 161 97 1,553,904 7,100 115

Iran, Islamic Republic of 950,422 13,834 371.293 32 2,950,319 42,945 460 68 1,388,149 20,206 329

Lao PDR 14,054 2,487 472.989 35 40,707 7,203 77 73 19,153 3,389 55

Macao, China 27,755 58,623 0.893 87 32,024 67,639 724 184 15,068 31,825 518

Malaysia 546,433 20,914 0.286 59 930,834 35,626 381 125 437,965 16,763 273

Maldives** 3,136 10,677 1.224 74 4,218 14,360 154 158 1,985 6,756 110

Mongolia 11,292 4,432 65.227 42 26,827 10,530 113 89 12,622 4,954 81

Nepal 57,259 2,259 3.513 38 149,577 5,902 63 81 70,377 2,777 45

Pakistan 733,671 4,765 2.756 36 2,036,975 13,230 142 77 958,413 6,225 101

Philippines 558,969 6,556 3.283 46 1,206,002 14,145 151 99 567,434 6,655 108

Singapore 407,987 93,967 0.202 94 432,905 99,706 1,067 200 203,686 46,913 763

Sri Lanka 142,180 7,229 5.299 41 346,735 17,629 189 87 163,142 8,295 135

Taipei,China 1,844,695 81,434 3.087 75 2,471,566 109,108 1,167 159 1,162,892 51,336 835

Thailand 864,994 13,356 2.389 46 1,872,723 28,917 309 98 881,132 13,605 221

Viet Nam 258,671 3,112 743.007 36 709,900 8,541 91 77 334,014 4,018 65

Asia*** 20,571,050 6,147 43,720,915 13,065 100 20,571,050 6,147

AFCH means actual final consumption of households. * Results for the PRC were based on national average prices extrapolated by the World Bank and ADB using price data for 11 cities submitted by the National Bureau of Statistics of China. ** Maldives is only participating in the comparison of AFCH.***Asia refers only to the 23 participating economies.



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In terms of absolute size of their economies, the PRC and India dominate economic activity within the region (refer to Table 2). On a PPP basis, the real GDP of the PRC is HK$30,711 billion while India’s is HK$13,293 billion. Together, they make up 64 percent of the total GDP for Asia and the Pacific,which is pegged at about HK$68,741 billion and dwarfs the rest of the participating economies. It should be noted that the population shares of the PRC and India are 39.0 and 32.9 percent, respectively.

For most purposes, the PPP-based real aggregates are standardized by calculating the real per capita figures. They can relate to GDP itself or to any of the components of GDP depending on the intended use.

Graphical representations, such as those illustrated in Figures 1 and 2, provide another way of presenting PPP results. Both figures manifest the wide disparity across the region in terms of per capita real GDP and AFCH, respectively.

Figure 1Per Capita Real GDP, 2005

(Hong Kong dollars)

BRU - Brunei Darussalam; SIN - Singapore; MAC - Macao, China; HKG - Hong Kong, China; TAP - Taipei,China; MAL - Malaysia; IRN - Islamic Republic of Iran; THA - Thailand; FIJ - Fiji Islands; PRC - People’s Republic of China; BHU - Bhutan; SRI - Sri Lanka; INO - Indonesia; PHI - Philippines; MON - Mongolia;PAK - Pakistan; VIE - Viet Nam; IND - India; LAO - Lao People’s Democratic Republic; CAM - Cambodia; BAN - Bangladesh; and NEP - Nepal.

BRU SIN MAC HKG TAPMAL IRN THA

PRCBHUFIJ SRI INO PHI

MON PAK VIE IND LAOCAM BAN NEP

0

50

100

150

200

250

300Thousands



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Figure 2Per Capita Real Actual Final Consumption of Households, 2005

(Hong Kong dollars)

Comparisons are Independent of the Units Used

Results can be expressed in a numeraire currency or as index numbers but the relativities between countries do not

change when different units are used for the comparison.

Alternative types of presentation can be useful. As an example, rather than showing per capita real GDP in Hong Kong dollars, it is possible to present them as an index. Tables 5 and 6 show the index of the per capita real GDP for each economy in Asia and the Pacific region using Asia = 100 and Hong Kong, China = 100, respectively. The economies are shown in descending order of the indices, but the qualifications contained in Section III about not reading too much into the rank order of economies with very similar index values still apply. Like the data in Hong Kong dollars, the indices are affected by statistical errors associated with the prices and national accounts data sources.

HKG - Hong Kong, China; TAP - Taipei,China; SIN - Singapore; BRU - Brunei Darussalam; MAC - Macao, China; IRN - Islamic Republic of Iran; MAL - Malaysia; THA - Thailand; FIJ - Fiji Islands; SRI - Sri Lanka; INO - Indonesia; MLD - Maldives; PHI - Philippines; PAK - Pakistan; BHU - Bhutan; PRC - People’s Republic of China;MON - Mongolia; IND - India; VIE - Viet Nam; CAM - Cambodia; LAO - Lao People’s Democratic Republic; BAN - Bangladesh; and NEP - Nepal.

BRUSIN MACHKG TAPMALIRN THA

PRCBHUFIJ SRI INO PHI

MONPAK VIEIND LAOCAM BAN NEP

0

20

60

80

100

120

140Thousands

MLD

40



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For example, Table 5 shows the index number of 190 for Thailand, which means that it has a per capita real GDP that is 90 percent higher than the regional average, while the index of 35 for Bangladesh means that its per capita real GDP is 65 percent less than the regional average.

As noted above, the actual relativities between economies will not change whether they are expressed in a numeraire currency or as an index number. In other words, Thailand’s per capita real GDP will be 90 percent above the regional average whether it is expressed as HK$39,086 (compared to a regional average of HK$20,545) or as an index number of 190 (Asian average = 100).

Table 5 Indices of Per Capita Real GDP, 2005

(Asia = 100)*

Economy Index

Brunei Darussalam 1312

Singapore 1150

Macao, China 1035

Hong Kong, China 988

Taipei,China 720

Malaysia 317

Iran, Islamic Republic of 296

Thailand 190

China, People’s Republic of** 115

Bhutan 102

Fiji Islands 115

Sri Lanka 97

Indonesia 90

Philippines 81

Mongolia 74

Pakistan 66

Viet Nam 60

India 59

Lao PDR 50

Cambodia 40

Bangladesh 35

Nepal 30

*The index numbers are shown on a base of 100 rather than the more common 100.0 so that they do not imply false accuracy in the index of real per capita GDP.

**Results for the PRC were based on national average prices extrapolated by the World Bank and ADB using price data for 11 cities submitted by the National Bureau of Statistics of China.

Table 6Indices of Per Capita Real GDP, 2005

(Hong Kong, China = 100)*

Economy Index


Singapore 116

Macao, China 105


Taipei,China 73

Malaysia 32


Thailand 19


Bhutan 10

Fiji Islands 12

Sri Lanka 10

Indonesia 9

Philippines 8

Mongolia 7

Pakistan 7

Viet Nam 6

India 6

Lao PDR 5

Cambodia 4

Bangladesh 4

Nepal 3





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Even though the main use of PPPs is as an intermediate step in deriving per capita real GDP, there is some interest in them in their own right. There is even more interest in examining them in conjunction with exchange rates to determine which are the more or less expensive economies in the region. As has been noted above, the ratio of PPPs to exchange rates (times 100), provides a price level index. An index level greater than 100 shows an economy that is more expensive than the base economy, while an economy with an index value less than 100 is cheaper than the base economy. Table 7 and Figure 3 present the PLIs for GDP (Asia = 100), while Table 8 and Figure 4 show the PLIs for GDP (Hong Kong, China = 100).

Table 7GDP Price Level Indices, 2005

(Asia = 100)*

Economy Index

Fiji Islands 212


Macao, China 162

Singapore 160

Taipei,China 149


Malaysia 113


Indonesia 100

Thailand 98

Philippines 98

Bhutan 89

Sri Lanka 86

Bangladesh 87

Mongolia 85

India 82

Pakistan 79

Nepal 78

Cambodia 77


Viet Nam 73

Lao PDR 69



Table 8GDP Price Level Indices, 2005

(Hong Kong, China = 100)*

Economy Index

Fiji Islands 117


Macao, China 90

Singapore 88

Taipei,China 82


Malaysia 63


Indonesia 55

Thailand 54

Philippines 54

Bhutan 49

Sri Lanka 48

Bangladesh 48

Mongolia 47

India 46

Pakistan 44

Nepal 43

Cambodia 43


Viet Nam 40

Lao PDR 38





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Figure 3GDP Price Level Indices, 2005

(Asia = 100)

Figure 4GDP Price Level Indices, 2005

(Hong Kong, China = 100)

FIJ - Fiji Islands; HKG - Hong Kong, China; MAC - Macao, China; SIN - Singapore; TAP - Taipei,China; BRU - Brunei Darussalam; MAL - Malaysia;PRC - People’s Republic of China; INO - Indonesia; THA - Thailand; PHI - Philippines; BHU - Bhutan; BAN - Bangladesh; SRI - Sri Lanka; MON - Mongolia;IND - India; PAK - Pakistan; NEP - Nepal; CAM - Cambodia; IRN - Islamic Republic of Iran; VIE -Viet Nam; and LAO - Lao People’s Democratic Republic.

BRUSINMACHKG TAPMAL

IRNTHAPRCBHUFIJ SRI

INO PHIMON PAK VIEIND LAO

CAMBAN NEP0

50

150

200

250

100

FIJ - Fiji Islands; HKG - Hong Kong, China; MAC - Macao, China ; SIN - Singapore; TAP -Taipei,China; BRU - Brunei Darussalam; MAL - Malaysia;PRC - People’s Republic of China; INO - Indonesia; THA - Thailand; PHI - Philippines; BHU - Bhutan; BAN - Bangladesh; SRI - Sri Lanka; MON - Mongolia;IND - India; PAK - Pakistan; NEP - Nepal; CAM - Cambodia; IRN - Islamic Republic of Iran; VIE - Viet Nam; and LAO - Lao People’s Democratic Republic.

BRUSINMACHKG TAPMAL

IRNTHAPRCBHUFIJ SRIINO PHI

MON PAK VIEIND LAOCAMBAN NEP

0

50

100

125

150

75

25



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This section has presented the results of the 2005 ICP Asia Pacific. For a clearer understanding of the ICP process, the next sections discuss the requirements for PPP computation, namely product specifications and price surveys (Section V); national accounts (Section VI); how PPPs are used to deflate basic heading expenditures (Section VII); and new methodologies introduced in ICP Asia Pacific (Section VIII).

The most popular example of PPPs is the Big Mac Index, discussed earlier in Table 1. Since this index deals with only one product, it is not useful for international comparisons, which require a fairly comparative and representative set of goods and services, such as those covered in GDP. Thus, ICP Asia Pacific drew up a comprehensive product list for the region that would ensure sufficient product matches (comparability), while at same time also covering products that are consumed in relatively large amounts (representativity). This product list was the basis for price surveys conducted in all the 23 participating economies.

One of the main objectives of the ICP is to compare real GDP expenditure components across all participating economies. GDP estimates covering the full range of economic activities and transactions are essential for making meaningful comparisons. Equally crucial to PPP compilation is the availability of GDP expenditures disaggregated into 155 basic headings, the lowest level of aggregate at which expenditure weights are available. These weights are then used for calculating PPPs for expenditure aggregates above the basic heading level.

Section VIII describes new methodologies adopted in the ICP Asia Pacific that were not included in the ICP Handbook, namely, PPP computations in dwellings and compensation, which had encountered problems in PPP compilation. While the Basket of Construction Components (BOCC) approach for construction PPPs is used by all the ICP regions, this was discussed under this section due to the variation in the derivation of the W2 weights (weights for aggregation of systems) that were used to obtain basic heading PPPs for construction.



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V. product speciFicAtion And price surVeys

Setting up product lists involves balancing the competing demands for the products to be comparable between the countries participating in the region and to be representative of those countries’ expenditures.

The ICP Handbook defines a representative product as “….one that accounts for a significant share of the expenditures within a basic heading in the country in question” (World Bank 2007a, chapter 4). In practice, representative products are likely to feature highly in the goods and services purchased in a country. They are also likely to be widely available in the country. However, a product that is representative of one country’s expenditures will not necessarily be representative of those in another country, even if the two countries have similar types of economies. As a result, trade-offs are required in setting up the lists of products to be priced. Not all products could be priced by each economy in ICP Asia Pacific because some products that were representative in one economy were not representative (or may not even have been available) in other economies in the region. Products that are available but not representative will tend to have a higher price level than representative products. Thus, pricing nonrepresentative products can bias an economy’s price level upward. However, it is necessary for some nonrepresentative products to be priced by economies to enable prices to be matched with those of an economy for which the product is representative. In practice, a balance had to be struck in the pricing process so that each economy had broadly the same proportion of nonrepresentative products entering into the PPP calculations. In this way, the biases involved with pricing nonrepresentative products tended to be offset.

It was important to set up the product lists in a way that ensured that the products being priced were comparable between economies. Chapter 4 of the ICP Handbook defines comparability as the situation where two or more products have identical physical and economic characteristics or are sufficiently similar that consumers are indifferent between them.

The first of these points (“their physical and economic characteristics are identical”) was foremost in setting up the product lists because it was impossible to objectively assess consumer indifference to products.

Setting up the product lists was a very lengthy process. It took almost 2 years to complete and involved several meetings between groups of economies to identify representative products, and to specify them in such a way that comparable products would be priced from one economy to another. A key element of the process was to identify the price-determining characteristics of products. The starting point

Representative and Comparable Products

The products priced by countries have to be representative of each country’s expenditures and comparable between different countries.

ICP Prelim Report MainText & App�� /�0/�00� ��:��:�0 AM


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for the process was similar to how statistical offices set out product specifications for the goods and services they include in their consumer price indices (CPIs). However, there was one big difference between the ICP and CPI that had to be taken into account. In enrolling a product in the CPI, a price collector has to identify a product that meets the specifications and then note any other details (such as the model number for a television) that will enable the same product to be priced the next time prices are collected. In ICP Asia Pacific, the product descriptions had to be specified in sufficient detail to enable price collectors in different countries to identify and price the same product.

For this ICP round, a process was developed to set up all the characteristics of a product in a “structured product description” (SPD). Examples of the types of characteristics set out are quantity (e.g., 1 kilogram), type of packaging, brand, type of material, etc. The price-determining characteristics were identified from the full SPDs at meetings of price statisticians from participating economies. Product specifications were then set up based on these characteristics. Trade-offs were involved between (i) tightly specifying products to ensure that the same product was priced in each economy, and (ii) having the products so tightly described that it became impossible to find a product meeting all the criteria. Most food products were very tightly specified, but more flexible specifications had to be used for other items such as electronic products. The clothing specifications had to be made quite loose (basically, generic descriptions) because of the very different types of clothing available in different economies. Consequently, the prices for food turned out to match better between economies than those for clothing, which required a substantial amount of checking, with some prices having to be discarded as a result of economies interpreting the product specifications differently.

In developing the household product specifications, ADB set up a very comprehensive process involving several rounds of meetings to ensure that the final products were as representative and comparable as possible. Groups of about four economies at a time met in Australia in late 2003 to work through the process of developing the SPDs. Workshops were held in Thailand and Malaysia in 2004 for South Asian and Southeast Asian economies, respectively, to identify the products that were most representative of household purchases in those regions. Consultants visited a number of economies to see first-hand the types of products available and to look into their key price-determining characteristics. ADB staff visited many of the participating economies to assist in training staff involved in the ICP work. Much effort also went into making additional clarifications to the product specifications for the health and education lists, as provided by the ICP Global Office, to further ensure comparability of products priced.

To ensure product parity, substantial time and efforts were devoted to improving data quality through a series of regional data review workshops. During these workshops, problems were identified that involved correct product identification and correct entry for the observed quantity. In this regard, ADB prepared and circulated a product catalogue with pictures and detailed product specifications to ensure correct product identification in the economies. A “What to Price” guide was also prepared, which

Setting up Product Lists

The characteristics of products that were commonly available in the region were identified by price statisticians from national statistical offices throughout the region. Product lists for pricing purposes were developed

using the price-determining characteristics of these products.



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specified the units of measurement and quantity ranges that the participating economies should use in price collection; and the values for observed quantity and observed units of measurement that should be entered into ToolPack, the software for processing ICP price surveys. In the course of its data validation exercise, ADB identified some 59 products that were notably problematic in terms of pricing, ToolPack conversion issues, and use of ambiguous units of measurement such as count or service, etc. A “List of Products Needing Special Attention” outlining how these 59 problematic products should be priced and inputted in the ToolPack was also provided. Moreover, household price data benefited significantly from the independent review of international ICP experts.

As most of the national statistical offices do not have the expertise to conduct construction and equipment price surveys, domestic experts were engaged for these sectors. They were then invited to attend workshops where they provided technical inputs in the finalization of the respective product lists, under the technical guidance of international experts. Separate core groups of experts were convened. These experts were selected from participating economies in view of their contribution to the construction and equipment product list finalization workshops, as well as the regional representation in the core group. The core groups met twice between 2003 and 2007 to review price data. Further regional data review workshops with domestic experts were organized under the technical guidance of international experts.

Regional workshops to discuss estimation of GDP expenditure weights for the required 155 basic headings were convened prior to the estimation exercise itself and after the preliminary GDP weights were submitted by the participating economies. Issues and concerns in the estimation procedures were deliberated on in a separate workshop conducted by an international expert on national accounts. GDP expenditure weights also underwent a similar thorough data review and validation as steps were taken to ensure parity through intercountry comparisons, and reconciliation of GDP expenditure aggregates from the economies’ websites, Key Indicators 2007 (ADB 2007), and the United Nations Statistics Division national accounts data. GDP data were also closely reviewed and evaluated by ADB and the international consultant.

For the most part, the ToolPack software was extensively used, particularly in the development of standard survey frames, as well as for data collection, validation, and processing. Seeing its potential and relevance in their price collection activities, a number of economies have expressed interest in adopting the ToolPack for their CPI work as well as for their own intraregional comparison. On the other hand, ADB used the output from ToolPack to validate data for quality and consistency using the Quaranta Tables and Dikhanov (Diagnostic) Tables, and to aggregate PPPs. The system also provided an efficient and standard facility for data transfer back and forth between economies and ADB on one hand, and between ADB and the World Bank on the other. This expedited data validation to ensure quality data were used for PPP computations. It also ensured data integrity as it enabled the economies to record all ICP price survey procedures, and also to edit and analyze the data at many levels including by subregion, data collection center, and outlet. Besides the ToolPack software, the ADB ICP Team also developed automated data validation procedures and data processing that further ensured efficient and timely provision of comments/feedback and exchange of views to and from economies. Likewise, the World Bank provided additional sets of aggregation and report generation tools to make it easier for ADB to analyze, aggregate, and produce standardized tables and reports using the Excel format.



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Vi. nAtionAl Accounts: criticAl For the 2005 icp

The broadest economic data set available in most countries is the national accounts. The framework for compiling and presenting national accounts is set out in detail in the System of National Accounts 1993 (commonly referred to as SNA93). Most countries in the world follow SNA93, although some still use an earlier version released in 1968 even as efforts were exerted to adopt SNA93 recommendations to the extent possible. As a result, national accounts data tend to be comparable between countries in terms of their scope and coverage.

The comparisons of aggregates, which the 2005 ICP is designed to make, are dependent on the consistency of national accounts data among economies. The most comprehensive measure of economic activity is GDP. The 2005 ICP uses GDP at market prices, which is defined by SNA93 as “…the sum of the gross values added of all resident producers at market prices, plus taxes less subsidies on imports.” There are three alternative approaches to measuring GDP, and the 2005 ICP uses the “expenditure approach.” This approach measures GDP as the sum of consumption expenditures by both households and government, investment expenditure (including change in inventories), and exports less imports of goods and services.

The 2005 ICP uses quite detailed distributions of these expenditures in aggregating price data from detailed levels, referred to as “basic headings”, up to the broad consumption and investment aggregates and to GDP itself. According to the ICP Handbook, a basic heading is defined as “… the smallest aggregate for which expenditure data are available.” Expenditures at the basic heading level are used as weights to combine the PPPs that are calculated for each basic heading.

Basic Headings

A basic heading is the lowest level aggregate [national accounts] for

which expenditure data are available.



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The 2005 ICP sets out 155 basic headings. Table 9 presents the numbers of basic headings within each broad expenditure category; and for Asia and the Pacific region, the numbers of products and the share of each category within GDP.

Four of the 23 participating economies (Bangladesh, India, Nepal, and Pakistan) compute their official national accounts data based on their respective fiscal years. For consistency with the other participating economies, their fiscal year estimates were converted to 2005 calendar year levels. The Islamic Republic of Iran’s GDP data was also adjusted to calendar year levels from its estimates based on the Persian calendar.

Table 9Gross Domestic Product and Its Structure: Number of Basic Headings and Products,

and Average Expenditure Shares, 2005

Category Number of basic headings

Number of products

Average share in GDP

GROSS DOMESTIC PRODUCT a+j+k+l+m 155 798 100.00

Actual Final Consumption of Households * a =b+i 132 658 54.06

Individual Consumption Expenditures by Households b = Σ (c to h) 108 656 51.42

Food and Nonalcoholic Beverages c 29 211 14.67

Clothing and Footwear d 5 71 3.01

Housing and Utilities e 7 14 8.08

Health and Education f 8 76 5.34

Transportation and Communication g 16 62 6.12

Other Individual Consumption Items h 43 222 14.20

Individual Consumption Expenditures by Government i 21 ** 2.64

Collective Consumption Expenditures by Government j 5 ** 7.69

Gross Fixed Capital Formation k 12 140 32.01

Changes in Inventories and Net Acquisitions of Valuables l 4 *** 1.98

Balance of Exports and Imports m 2 *** 4.26

*Includes nonprofit institutions serving households and net expenditures of residents abroad.**Government compensation data were used along with reference PPPs for other items. ***Reference PPPs were used.



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Vii. using ppps to “deFlAte” BAsic heAding expenditures

The PPPs in ICP Asia Pacific were calculated at the basic heading level using item-level price data without attaching any weights to different commodities. Generally, the PPP was directly compiled from prices for products that are characteristic of the basic heading. The country-product-dummy method was used to calculate PPPs at the basic heading level. The resulting PPP at the basic heading is used to deflate a basic heading expenditure to obtain a “real” or “volume” expenditure for the basic heading. The country product representativity dummy could also be used to calculate basic heading PPPs. A product is representative if it is consumed in relatively large quantities (see ICP Handbook, World Bank 2007a, chapter 11). However, problems were encountered regarding the implementation of representativity during the price surveys and representativity indicators could not be used.

Within the ICP, PPPs are computed in a hierarchical structure designed for use in the computation of real expenditure at each of the 155 basic headings and for any other prespecified levels of aggregation. Different levels of aggregation are identified through two-digit, three-digit, and four-digit level aggregates defined using the detailed basic headings.

PPPs for individual basic headings are combined to produce PPPs for each desired level of aggregation (e.g., PPP for clothing and footwear, or PPP for machinery and equipment, or for an aggregate like total gross fixed capital formation) up to GDP itself, using the relevant basic heading PPPs and weights for each basic heading from the national accounts. The Elteto-Köves-Szulc (EKS) method described in the ICP Handbook (World Bank 2007a, chapter 11), was used to obtain the broader national accounting aggregates published. The total of PPP-based GDP subaggregates will not sum to the PPP-based total GDP due to the nonadditivity of the EKS results. Details of these methods and the implications of using them are contained in chapters 11 and 12 of the ICP Handbook.

In some cases, it was not possible to obtain the price data required to calculate PPPs at the basic heading level (e.g., for acquisitions of valuables). In such cases, a PPP calculated for another basic heading (or group of basic headings) was used. The term applied to such a PPP is “reference PPP.”



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Viii. new methodologies introduced in icp AsiA pAciFic

Some problems were encountered during the compilation of PPPs for several important basic headings including dwellings, compensation of employees, and construction. The procedures recommended in the ICP Handbook had to be reviewed and suitable new procedures had to be devised in order to obtain meaningful PPPs and volume measures for these basic headings. In this section, some of the modifications introduced are explained in detail.

A. Dwellings

It was originally planned that PPPs for the basic heading of actual and imputed rentals for housing would be estimated using the “quantity approach” as described in chapter 10 of the ICP Handbook. The quantity approach requires economies to provide detailed information on the numbers and characteristics of dwellings. Despite the best efforts of the economies and ADB, it proved impossible to apply the quantity approach because several economies did not have comprehensive and up-to-date information about their housing stock. Therefore, a “reference” method was used, which would usually mean the use of a reference PPP. However, for the dwellings basic heading, a reference volume relative was used. If reference PPPs had been used, the volume relatives, which would have been indirectly obtained by dividing the reference PPPs into the expenditure relatives, would have included the effects of inconsistencies in the economies’ estimates of expenditures on rentals for housing (rents). On the other hand, using the volume relatives for Individual Consumption Expenditures by Households (Excluding Rentals for Housing) as the reference volume relative is a “neutral” approach that does not affect the volume relative for individual consumption expenditures by households. Likewise, it is based on the plausible assumption that the volumes of housing services consumed in each economy rise in line with the volumes of individual final consumption of households.

B. Compensation of Employees

Compensation, as part of government services, was among the most difficult areas of ICP Asia Pacific. Two approaches to compensation measurement are usually used: (i) “an hour is an hour”, which means that productivity is uniform across all countries, and (ii) productivity is adjusted to reflect variations in labor qualifications and capital intensity.

Given that salaries in the participating economies vary by over 100 times (120 times between Lao People’s Democratic Republic and Hong Kong, China in the health sector), it is unrealistic to assume that there would be no differences in productivity between these economies due to different resources being available in the economies. Government workers in high-income economies would certainly be aided by access to modern communications services, high-speed networks, office equipment, etc., compared to workers in low-income economies.



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In ICP Asia Pacific, the existence of productivity differences among government workers was recognized and a simple procedure for adjusting wages for productivity differentials was implemented. Details of the procedure used are explained in Appendix D. The wage level comparisons after making these productivity adjustments are deemed to be satisfactory and have been used to determine PPPs for the compensation aggregate in government consumption.

C. Construction

While the construction sector is described as “comparison resistant”, the ICP requires items included in the construction comparison to be comparable across participating countries, and to be commonly found in the domestic markets of the countries. However, both conditions are often difficult to satisfy for the construction sector. Previous ICP rounds utilized the standard-projects-based method (SPM) using a selected set of standard hypothetical model construction projects. While the prices reflected full market (purchaser) prices that were consistent with prices used in national accounts, and the methodology satisfied comparability, representativity had to be sacrificed. However, the SPM was considered to be expensive and difficult to implement in developing countries due to its detailed and comprehensive data needs, and high survey costs.

Introduced in this ICP round, the BOCC approach divides the three construction basic headings—residential construction, nonresidential construction and civil engineering works—into several systems that are in turn disaggregated into well-defined construction components. It involves pricing identifiable, complete, installed construction components. Examples of components include a reinforced concrete column or painting 100 square meters of a building’s exterior surface. The BOCC requires all countries to price the same construction components, but allows them to vary the mix of inputs in line with building practices and relative input costs in each country. The BOCC strikes a balance between representativity and comparability — it simplifies the technical aspects of the survey procedures and it is less expensive to implement than the SPM method. The new BOCC approach was endorsed by the ICP Technical Advisory Group (TAG). The TAG highlighted the point that the BOCC prices a much smaller list of component activities than the SPM, which prices a complete set of building inputs. In particular the TAG stressed that the BOCC allows components to be set up in such a way that they are more comparable between different economies while still being reasonably representative of actual building projects in those economies. Also, prices can be collected fairly readily in a number of cities/towns throughout the participating economy to obtain better national average prices. The major shortcoming of the approach is that the margins applying to the overall project, particularly profits for the whole project (as distinct from those at the individual component level), are not incorporated in the final quoted price. Such margins can fluctuate significantly, depending on market conditions in the pricing period.

The BOCC approach includes 11 basic inputs and 23 composite components and uses three types of expenditure weights: (i) W1 or weights for aggregation of the three basic headings, residential construction, nonresidential construction, and civil engineering works; (ii) W2 or weights for aggregation of systems; and (iii) W3 or weights at the component level. The W1 weights are the expenditure shares from the national accounts, and the W3 weights were set at unity, meaning that all components within a system were given equal weights. The participating economies were asked to estimate their own W2 weights. However, in view of the difficulties faced by a few economies in providing W2 weights, the geometric means (excluding outliers) of the W2 based on the data submitted by a majority of the economies were used in the ICP Asia Pacific PPP computation.



�0


ix. concluding remArks

The main aim of the 2005 ICP is to provide a reliable set of estimates of the levels of economic activity between countries, expressed in a single (numeraire) currency. A commonly used method of making such comparisons is to adjust values to a numeraire currency using exchange rates. However, this process does not adjust for the differences in price levels between countries. The exchange rate-based estimates (often referred to as “nominal” estimates as distinct from the “real” or “volume” estimates obtained using PPPs) are presented in this report to provide a basis for comparing the outcomes using nominal estimates with the more accurate estimates based on PPPs. PPPs are specifically calculated for each major component of the national accounts, taking account the prices of major products within each expenditure category.

Levels of expenditure, output, and other indicators are useful for many uses, with poverty analysis being of particular interest to the region. It should be remembered that the ranking of economies can change significantly depending on the variable used in the process (e.g., gross domestic product or actual final consumption of households). As a result, anyone using the PPP-based data in this report should carefully consider the type of analysis they are undertaking in selecting the most appropriate data for their purpose.

This report is the culmination of several years of intensive work by the national implementing agencies in each of the 23 participating economies in Asia and the Pacific region and by ADB. ICP Asia Pacific has achieved several important milestones, principally the very interesting results revealed in the tables in this report. For example, based on real GDP, the PRC and India, the two biggest economies in ICP Asia Pacific and which are participating simultaneously for the first time in the ICP, contribute 64 percent of total real GDP of the 23 participating economies.

A quite different picture emerges when the size of the economies is adjusted (or standardized) by taking account of their populations. Rather than dominating the top rankings, the PRC and India dropped to 10th and 18th place, respectively. The per capita real GDP for the PRC was HK$23,556, while that for India was HK$12,070, compared with the regional average of HK$20,545. The five economies that stood out as being significantly richer than the others in Asia and the Pacific region were Brunei Darussalam (HK$269,581); Singapore (HK$236,336); Macao, China (HK$212,617); Hong Kong, China (HK$202,941); and Taipei,China (HK$147,971). No other participating economy had real GDP in excess of HK$100,000. The richest (Brunei Darussalam) had a per capita real GDP more than 13 times the average for developing Asia, and more than 43 times higher than the lowest ranked economy (Nepal, HK$6,177).

While per capita real GDP is the standard statistic used to distinguish between “rich” and “poor” countries, a better measure of the welfare of the population is obtained by comparing household consumption expenditure per capita. The aggregate known as actual final consumption of households is a measure of what households actually consume, comprising both what they purchase directly themselves, plus what they are supplied for individual use by the government (principally education and health). The same group of five economies that were at the top of the list based on per capita real GDP also were the



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top five economies with highest AFCH. However, their order changed when the comparison is based on real AFCH rather than real GDP:

Hong Kong, China moved up from fourth to first place;

Taipei,China also moved up, from fifth to second place; and

Brunei Darussalam dropped from first to fourth.

The largest changes in ranking, however, were by the PRC, which dropped from 10th to 15th; and Bhutan, which dropped from 11th to 14th (excluding Maldives, which was not included in the per capita real GDP comparison). The main reason was that both Bhutan and the PRC had exceptionally high levels of gross fixed capital formation (i.e., investment) during 2005. As a result, the share of AFCH within their GDP was significantly lower than that for other economies in the region. The range of differences in per capita real AFCH between economies is much less than is the case for per capita real GDP. Per capita real AFCH in the top economy (Hong Kong, China) is 20 times greater than that in the lowest economy (Nepal), compared with a factor of 30 times when per capita real GDP is used as the basis for the comparison.

The price level index, which is the ratio of a PPP to the corresponding exchange rate, shows how the price levels of countries compare with each other. When a PLI is presented as an index number on a base of the regional average equalling 100, economies with a PLI greater than 100 had a higher cost of living than the regional average, while those with a PLI less than 100 had relatively lower costs of living. As a general rule, high-income countries will have a relatively high PLI while low-income countries will have a lower than average PLI. The reason is that wages, and therefore the price of services, tend to be low in low-income countries, so PPPs are low compared with exchange rates, which are determined largely by the prices of goods and services traded on the world market. The ICP Asia Pacific results conform with this general rule at the upper and lower end of the income range. The five economies with the highest per capita real GDP all have PLIs at least one-third higher than the regional average, while the eight economies with the lowest PLIs have PLIs 15 percent or more below the regional average. The most notable result is for the Fiji Islands, which has by far the highest PLI (212), due mainly to the fact that a large share of the products consumed in Fiji Islands are imported and therefore, expensive. Several economies are very close to the regional average: PRC (103), Indonesia (100), Philippines (98), and Thailand (98). Lao People’s Democratic Republic (69) and Viet Nam (73) have the lowest PLIs.

The ICP Asia-Pacific has made a number of notable contributions. In a region as diverse as Asia, cross-country comparisons on key development indicators will become much more meaningful with the availability of more robust PPPs at various levels of disaggregation. Most importantly, the poverty PPPs, a central contribution of ICP Asia Pacific, will be pivotal in estimating and monitoring poverty in Asia and the Pacific region. The statistical capacity building that has been an integral component of the 2005 round will contribute to statistical capacity strengthening in both the national accounts and price areas. The dialogue ignited between national statistical offices by the 2005 round will be pivotal as economies catch up with their peers through a process of interaction and collaboration. Together these position the economies in Asia and the Pacific region to be active and successful participants in the next round of the ICP.



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Appendix Alist oF implementing Agencies in icp AsiA pAciFic

The 23 economies that participated in the ICP Asia Pacific comparison—inclusive of 21 ADB developing member countries—account for over half of the global population and about a quarter of the world’s gross domestic product. The following are the ICP Asia Pacific implementing agencies.

Bangladesh – Bangladesh Bureau of StatisticsBhutan – National Statistical BureauBrunei Darussalam – Department of Economic Planning and Development Cambodia – National Institute of StatisticsChina, People’s Republic of – National Bureau of Statistics of ChinaFiji Islands – Fiji Islands Bureau of StatisticsHong Kong, China – Census and Statistics DepartmentIndia – Ministry of Statistics and Programme ImplementationIndonesia – Statistics Indonesia Islamic Republic of Iran – Statistical Centre of IranLao People’s Democratic Republic – National Statistics CentreMacao, China – Statistics and Census ServiceMalaysia – Department of StatisticsMaldives – Ministry of Planning and National DevelopmentMongolia – National Statistical Office of MongoliaNepal – Central Bureau of StatisticsPakistan – Federal Bureau of StatisticsPhilippines – National Statistics OfficeSingapore – Department of StatisticsSri Lanka – Department of Census and StatisticsTaipei,China – Directorate General of Budget, Accounting, and StatisticsThailand – Bureau of Trade and Economic Indices, Ministry of CommerceViet Nam – General Statistics Office of Vietnam



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Appendix BpreliminAry ppp results

This appendix contains 10 tables on gross domestic product and its major aggregates namely, purchasing power parities; price level indices with Hong Kong, China and Asia as bases; per capita real expenditures; real expenditures (economy shares to Asia by category); per capita real expenditure relatives; nominal expenditure shares by category; per capita nominal expenditures; nominal expenditures (economy shares to Asia by category); and per capita nominal expenditures relatives.

Real expenditures are not additive within a participating economy because the Elteto-Köves-Szulc method (as explained in Section VII) of obtaining broader national accounts aggregates is not an additive index.


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Appe

ndix

Tabl

e B1.

Pur

chas

ing

Powe

r Par

ities

, 200

5(H

ong K

ong,

China

as ba

se)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

E

GROS

S DOM

ESTI

C PRO

DUCT

1.00

0.92

0.19

3.41

0.16

3.96

2.78

2.58

469.9

33.9

63.3

56.1

773

.0222

4.70

0.26

690.5

852

2.47

0.31

3.83

0.60

2.80

821.1

7

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

1.00

0.89

0.20

3.09

0.15

3.40

2.49

2.11

371.2

91.2

23.5

12.7

65.3

065

.2320

5.61

0.20

567.0

647

2.99

0.29

3.28

0.53

2.39

743.0

1

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s1.0

00.8

80.2

03.1

20.1

53.4

52.5

42.1

337

1.73

1.28

3.57

2.81

5.47

70.54

219.2

40.2

057

2.46

504.6

80.2

93.3

10.5

52.3

978

9.49

Food

and N

onalc

oholi

c Bev

erag

es1.0

00.9

40.2

03.9

60.1

73.8

92.8

82.4

064

1.81

1.28

3.87

3.79

6.79

79.04

261.3

60.2

065

9.70

680.2

90.3

13.8

10.6

62.8

594

7.48

Brea

d and

Cerea

ls 1.0

00.9

80.1

93.9

70.1

43.8

62.7

82.3

776

8.81

1.12

3.49

3.22

5.75

81.18

199.9

30.1

765

2.24

553.2

60.2

93.2

40.6

32.6

283

5.46

Meat

and F

ish1.0

00.9

60.2

54.0

90.1

94.1

22.7

82.5

478

4.35

1.05

4.09

4.32

7.87

67.53

330.1

50.2

269

6.22

801.4

00.3

13.8

40.6

62.8

812

04.10

Fruits

and V

egeta

bles

1.00

0.91

0.19

4.14

0.20

2.57

2.53

1.84

472.2

31.8

63.1

53.0

86.3

110

8.01

243.6

70.1

948

5.86

577.0

60.3

54.5

40.5

92.7

669

3.24

Othe

r Foo

d1.0

00.8

40.1

73.3

00.1

54.2

32.8

42.5

448

9.93

1.11

4.04

3.97

6.60

84.60

273.8

00.2

070

8.60

758.2

50.2

83.7

70.6

92.8

493

3.46

Cloth

ing an

d Foo

twea

r1.0

01.0

10.2

63.5

20.2

24.9

93.5

82.7

253

8.22

1.51

4.59

3.80

5.77

102.1

230

2.50

0.19

630.9

175

0.45

0.37

4.59

0.89

3.45

1120

.21

Hous

ing an

d Util

ities

1.00

0.73

0.18

2.73

0.13

2.41

1.60

1.41

257.5

92.1

12.6

41.3

32.2

657

.3718

7.42

0.20

454.3

420

6.93

0.27

2.47

0.35

1.23

570.4

3

Healt

h and

Educ

ation

1.00

0.67

0.18

2.01

0.12

1.38

1.23

0.59

206.6

30.3

31.2

71.0

72.4

125

.9468

.810.1

028

1.32

156.6

10.2

11.8

50.2

91.2

823

6.47

Trans

porta

tion a

nd Co

mm

unica

tions

1.00

0.89

0.20

2.84

0.13

5.24

3.44

3.30

206.7

41.2

46.4

93.4

27.1

282

.5127

5.86

0.21

698.7

988

7.09

0.27

4.06

0.56

2.72

1391

.84

Othe

r Ind

ividu

al Co

nsum

ption

Item

s1.0

00.9

80.2

33.2

60.1

74.1

03.1

72.9

750

0.35

1.22

4.68

3.69

7.79

92.30

247.3

50.2

362

7.08

652.4

40.3

43.4

70.6

72.9

996

8.34

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t1.0

00.9

20.1

82.6

20.1

22.7

81.7

01.9

336

9.85

0.69

2.72

2.00

3.11

23.90

70.13

0.17

480.5

717

1.05

0.20

2.89

0.25

2.13

277.0

3

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1.00

1.11

0.17

2.92

0.12

4.09

1.94

2.70

352.3

63.9

12.9

34.2

739

.8199

.220.1

972

7.22

266.8

50.2

23.7

30.4

43.0

848

0.99

Gros

s Fixe

d Cap

ital F

orm

atio

n1.0

01.2

10.1

93.9

30.2

15.0

13.5

73.5

273

6.13

5.00

5.15

8.75

92.10

292.0

60.2

894

5.56

749.0

30.3

34.8

00.7

33.3

510

27.91

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s1.0

01.1

20.2

13.7

00.1

94.6

83.3

53.0

554

6.19

4.72

4.33

7.90

92.12

298.7

80.2

479

9.76

712.1

30.3

34.5

10.7

13.3

110

75.23

Bala

nce o

f Exp

orts

and I

mpo

rts1.0

01.0

30.2

14.1

40.2

18.2

75.6

75.6

711

52.58

9.18

7.65

12.92

154.9

752

6.21

0.22

1247

.8213

70.03

0.49

7.08

1.05

5.17

2039

.12

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina; T

HA - T

haila

nd; a

nd VI

E - Vi

et N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.


��

Appe

ndix

Tabl

e B2.

Pric

e Lev

el In

dice

s, 20

05

(Hon

g Kon

g, Ch

ina =

100)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

E

GROS

S DOM

ESTI

C PRO

DUCT

100

9088

8274

4849

4641

4344

4847

4311

755

3863

5457

5440

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

100

8794

7570

4144

3732

7438

3641

4239

9245

3559

4650

4636

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s10

086

9575

7042

4537

3278

3937

4246

4292

4637

6047

5246

39

Food

and N

onalc

oholi

c Bev

erag

es10

092

9496

7947

5142

5678

4250

5351

5093

5350

6454

6255

46

Brea

d and

Cerea

ls 10

096

9096

6747

4942

6768

3842

4552

3879

5240

6046

6051

41

Meat

and F

ish10

093

115

9988

5049

4568

6445

5661

4463

9956

5863

5463

5659

Fruits

and V

egeta

bles

100

8989

100

9531

4532

4111

334

4049

7046

8839

4272

6456

5334

Othe

r Foo

d10

082

7980

6951

5045

4367

4452

5155

5292

5755

5853

6655

46

Cloth

ing an

d Foo

twea

r10

098

122

8510

260

6348

4792

5050

4566

5789

5155

7565

8567

55

Hous

ing an

d Util

ities

100

7183

6662

2928

2522

128

2917

1737

3693

3615

5535

3324

28

Healt

h and

Educ

ation

100

6585

4957

1722

1018

2014

1419

1713

4623

1144

2627

2512

Trans

porta

tion a

nd Co

mm

unica

tions

100

8791

6961

6361

5818

7571

4555

5352

9856

6555

5754

5368

Othe

r Ind

ividu

al Co

nsum

ption

Item

s10

096

107

7982

5056

5243

7451

4860

6047

105

5048

7049

6458

47

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t10

090

8363

5834

3034

3242

3026

2415

1380

3912

4141

2441

14

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

100

108

7971

5749

3448

3143

3833

2619

8958

1945

5342

6024

Gros

s Fixe

d Cap

ital F

orm

atio

n10

011

788

9597

6163

6264

5567

6859

5612

776

5568

6870

6550

Chan

ge in

Inve

ntor

ies a

nd N

et Ac

quisi

tions

of Va

luab

les

100

108

9889

8857

5954

4751

5761

5957

112

6452

6864

6764

53

Bala

nce o

f Exp

orts

and I

mpo

rts10

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

0

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina; T

HA - T

haila

nd; a

nd VI

E - Vi

et N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.


��

Appe

ndix

Tabl

e B3.

Per C

apita

Rea

l Exp

endi

ture

s, 20

05

(Hon

g Kon

g doll

ars)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

E

GROS

S DOM

ESTI

C PRO

DUCT

2029

4121

2617

2363

3614

7971

2695

8172

4520

903

1207

060

857

6177

1365

819

839

1510

482

6923

583

1842

710

361

6513

616

663

2355

639

086

1229

5

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

1253

0367

639

9970

610

9108

8174

465

5312

346

9346

4294

514

360

5902

1323

017

629

1053

077

7125

235

1508

972

0335

626

1414

511

502

2891

785

41

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s11

9376

6357

494

533

1034

0070

897

6343

1053

088

4540

090

1177

456

3712

850

1626

688

7669

8422

523

1441

664

2531

614

1343

410

502

2611

076

38

Food

and N

onalc

oholi

c Bev

erag

es11

231

9178

8600

1320

013

751

2929

3689

2780

5811

3146

2663

4691

5114

3164

2961

5475

5496

2362

5430

5349

2229

3715

2072

Brea

d and

Cerea

ls 10

6214

6711

7431

1932

7813

0415

7654

098

364

315

5211

5715

7764

512

9585

213

3911

8811

2620

5435

664

378

5

Meat

and F

ish54

8434

4724

2136

3439

7653

039

525

411

8065

623

968

665

915

1365

414

4792

872

516

6618

5278

570

962

2

Fruits

and V

egeta

bles

1296

2273

1439

3167

1864

600

573

1049

1914

609

384

1175

1779

197

434

921

1653

408

1249

627

575

1082

358

Othe

r Foo

d33

8921

7437

6036

1749

6861

812

9711

0223

3513

4666

518

8414

0387

870

623

4018

3917

514

7899

853

913

6533

2

Cloth

ing an

d Foo

twea

r12

445

2953

2791

3587

2322

264

551

378

1847

413

286

719

1490

738

9857

348

980

627

218

428

1359

205

Hous

ing an

d Util

ities

2240

011

615

1612

819

267

1120

515

3531

9217

0215

180

2478

1037

3751

3111

1939

1094

6240

3806

2037

6603

2618

2552

4030

1675

Healt

h and

Educ

ation

1427

375

1512

559

2506

978

6510

8114

8127

4073

5347

9515

8136

9158

217

1522

3430

5915

3111

2822

1020

3523

6540

7533

59

Trans

porta

tion a

nd Co

mm

unica

tions

1169

595

0619

395

1556

819

610

198

206

1008

9020

928

138

758

2220

692

440

2473

1031

423

6750

1083

881

4128

484

Othe

r Ind

ividu

al Co

nsum

ption

Item

s47

332

2284

133

987

3386

415

968

722

2065

1270

5765

1983

614

1105

2748

952

1001

5253

2294

923

9491

2418

2781

8556

1461

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t59

2746

5651

6354

0413

047

149

2357

497

2819

3693

224

167

1426

2540

948

3113

632

961

4861

699

1144

3197

1139

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1060

994

3718

980

1508

050

663

275

3003

801

5162

363

931

1726

1393

707

4216

865

2360

5549

1055

2853

2508

1278

Gros

s Fixe

d Cap

ital F

orm

atio

n42

450

4329

952

609

2623

824

675

1433

8661

2525

8355

961

1679

3321

3599

743

6270

3137

2404

1231

319

1479

8793

5731

94

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s-6

9912

25-6

898

-316

290

4842

758

1834

016

647

378

034

267

4314

1-2

1515

2422

482

525

1

Bala

nce o

f Exp

orts

and I

mpo

rts25

277

6968

860

885

5147

9029

5-2

29-1

684

-166

1307

-445

-365

-862

-276

-71

-759

543

2-3

8391

61-3

7573

3-2

77-2

05

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina; T

HA - T

haila

nd; a

nd VI

E - Vi

et N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.


��

Appe

ndix

Tabl

e B4.

Pric

e Lev

el In

dice

s, 20

05

(Asia

= 10

0)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

E

GROS

S DOM

ESTI

C PRO

DUCT

181

162

160

149

134

8789

8274

7879

8685

7721

210

069

113

9810

398

73

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

213

184

200

159

149

8793

7968

158

8177

8789

8319

697

7312

599

106

9877

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s20

817

819

815

714

687

9378

6716

281

7788

9587

192

9677

125

9710

996

81

Food

and N

onalc

oholi

c Bev

erag

es18

617

017

517

814

787

9478

103

145

7892

9895

9217

298

9211

910

011

610

286

Brea

d and

Cerea

ls 19

718

817

818

913

292

9783

131

134

7583

8810

375

157

103

8011

890

119

100

81

Meat

and F

ish16

415

318

916

314

582

8074

112

105

7393

100

7210

316

492

9610

489

104

9197

Fruits

and V

egeta

bles

228

203

203

229

216

7110

274

9425

878

9211

215

910

620

289

9616

514

712

912

278

Othe

r Foo

d18

615

214

814

912

995

9384

7912

682

9795

102

9717

110

610

310

999

122

102

85

Cloth

ing an

d Foo

twea

r15

014

718

312

715

490

9572

7013

775

7467

9986

134

7682

112

9712

710

082

Hous

ing an

d Util

ities

307

218

254

203

191

9087

7669

393

8853

5411

411

028

711

246

170

107

102

7386

Healt

h and

Educ

ation

456

295

388

221

261

7699

4782

9263

6485

7660

210

103

5220

111

912

411

353

Trans

porta

tion a

nd Co

mm

unica

tions

189

164

173

130

115

120

115

110

3414

213

485

104

101

9918

610

612

310

510

910

110

012

9

Othe

r Ind

ividu

al Co

nsum

ption

Item

s16

115

317

212

713

180

9084

7011

982

7797

9675

169

8176

112

7910

293

76

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t31

428

226

119

918

310

694

107

101

131

9382

7648

4225

112

139

128

128

7612

943

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

220

237

173

155

125

109

7510

567

9484

7356

4119

612

843

9811

692

131

52

Gros

s Fixe

d Cap

ital F

orm

atio

n14

416

912

613

714

087

9189

9279

9797

8680

182

109

7999

9810

093

73

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s18

219

717

916

316

010

310

898

8694

103

111

108

104

204

117

9512

511

612

211

796

Bala

nce o

f Exp

orts

and I

mpo

rts10

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

010

0

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina;

THA -

Thail

and;

and V

IE - V

iet N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.

3. A

sia re

fers o

nly t

o the

23 pa

rticip

ating

econ

omies

.


��

Appe

ndix

Tabl

e B5.

Rea

l Exp

endi

ture

, Eco

nom

y Sha

res t

o Asia

by C

ateg

ory,

2005

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAS

IA

GROS

S DOM

ESTI

C PRO

DUCT

2.01

0.15

1.49

4.88

0.15

1.44

0.02

19.34

6.08

0.23

3.06

0.57

0.06

0.17

0.03

5.87

0.09

2.48

2.07

44.67

3.68

1.49

100.0

0

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

1.95

0.07

0.99

5.65

0.07

2.05

0.02

23.54

6.75

0.01

0.34

4.66

0.79

0.06

0.25

0.05

7.55

0.09

2.13

2.76

34.30

4.28

1.62

100.0

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s2.0

00.0

71.0

15.7

50.0

62.1

30.0

223

.906.7

60.0

10.3

54.8

50.7

80.0

60.2

40.0

57.7

40.0

92.0

32.8

133

.594.1

51.5

610

0.00

Food

and N

onalc

oholi

c Bev

erag

es0.7

40.0

40.3

62.8

90.0

53.8

70.0

229

.543.8

50.0

10.6

56.9

70.9

70.0

80.4

00.0

411

.610.1

31.3

74.4

028

.032.3

21.6

610

0.00

Brea

d and

Cerea

ls 0.3

20.0

30.2

23.1

10.0

57.8

60.0

426

.192.9

70.0

11.7

37.8

41.3

70.0

70.7

90.0

312

.900.3

01.3

07.7

120

.451.8

32.8

710

0.00

Meat

and F

ish1.6

70.0

70.4

73.6

80.0

73.2

50.0

112

.493.6

30.0

10.2

74.7

20.5

80.1

70.4

00.0

59.0

90.1

81.9

57.0

745

.782.0

52.3

110

0.00

Fruits

and V

egeta

bles

0.30

0.04

0.21

2.40

0.02

2.75

0.01

38.62

4.40

0.01

0.33

6.05

1.17

0.02

0.20

0.03

12.10

0.08

1.09

1.79

25.08

2.34

1.00

100.0

0

Othe

r Foo

d0.7

00.0

30.5

02.5

00.0

62.5

80.0

337

.014.8

90.0

10.5

18.8

50.8

40.0

70.3

00.0

612

.280.0

31.1

82.6

021

.442.7

00.8

410

0.00

Cloth

ing an

d Foo

twea

r4.9

40.0

80.7

14.7

30.0

52.1

10.0

224

.247.3

90.0

10.4

26.4

51.7

10.1

10.0

80.0

36.2

40.0

30.9

51.0

832

.525.1

20.9

910

0.00

Hous

ing an

d Util

ities

1.61

0.06

0.74

4.61

0.04

2.22

0.02

19.82

11.03

0.01

0.28

6.11

0.65

0.05

0.16

0.06

8.81

0.12

1.82

2.36

35.18

2.76

1.47

100.0

0

Healt

h and

Educ

ation

1.05

0.04

0.59

6.14

0.03

1.60

0.01

32.60

5.46

0.02

0.43

6.14

0.12

0.05

0.33

0.03

3.62

0.07

0.62

1.88

33.31

2.85

3.02

100.0

0

Trans

porta

tion a

nd Co

mm

unica

tions

1.81

0.10

1.91

7.99

0.16

0.61

0.00

25.16

14.04

0.01

0.08

2.64

0.99

0.04

0.14

0.05

5.11

0.05

4.00

2.09

26.04

6.06

0.91

100.0

0

Othe

r Ind

ividu

al Co

nsum

ption

Item

s3.7

20.1

21.7

08.8

50.0

71.1

40.0

216

.124.5

70.0

10.1

81.9

60.6

20.0

30.1

60.0

55.7

90.0

62.8

62.3

841

.816.3

91.4

010

0.00

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t1.2

80.0

70.7

13.8

70.1

50.6

50.0

517

.316.1

30.0

30.1

80.8

10.8

90.2

00.4

10.0

84.3

80.1

74.0

21.8

847

.186.5

53.0

010

0.00

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1.12

0.07

1.28

5.31

0.29

0.59

0.03

13.73

5.52

0.14

2.23

0.53

0.06

0.15

0.06

2.95

0.21

2.26

1.40

57.87

2.53

1.65

100.0

0

Gros

s Fixe

d Cap

ital F

orm

atio

n1.6

50.1

21.3

03.3

90.0

51.1

20.0

315

.853.2

70.1

41.4

70.3

70.0

50.0

60.0

33.9

10.0

81.8

30.9

359

.353.4

51.5

110

0.00

Chan

ge in

Inve

ntor

ies a

nd N

et Ac

quisi

tions

of Va

luab

les

-0.35

0.04

-2.18

-0.52

0.00

0.00

0.00

34.17

29.05

0.63

1.86

0.68

0.14

0.03

0.02

0.69

0.06

-0.41

9.44

21.25

3.88

1.52

100.0

0

Bala

nce o

f Exp

orts

and I

mpo

rts10

.622.0

416

.307.1

92.0

6-1

.93-0

.07-1

1.24

5.54

-0.70

-3.47

-1.05

-0.04

-0.06

-0.39

5.83

-0.13

14.76

-1.97

58.94

-1.10

-1.05

100.0

0

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina;

THA -

Thail

and;

and V

IE - V

iet N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.

3. A

sia re

fers o

nly t

o the

23 pa

rticip

ating

econ

omies

.


��

Appe

ndix

Tabl

e B5.

Rea

l Exp

endi

ture

, Eco

nom

y Sha

res t

o Asia

by C

ateg

ory,

2005

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAS

IA

GROS

S DOM

ESTI

C PRO

DUCT

2.01

0.15

1.49

4.88

0.15

1.44

0.02

19.34

6.08

0.23

3.06

0.57

0.06

0.17

0.03

5.87

0.09

2.48

2.07

44.67

3.68

1.49

100.0

0

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

1.95

0.07

0.99

5.65

0.07

2.05

0.02

23.54

6.75

0.01

0.34

4.66

0.79

0.06

0.25

0.05

7.55

0.09

2.13

2.76

34.30

4.28

1.62

100.0

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s2.0

00.0

71.0

15.7

50.0

62.1

30.0

223

.906.7

60.0

10.3

54.8

50.7

80.0

60.2

40.0

57.7

40.0

92.0

32.8

133

.594.1

51.5

610

0.00

Food

and N

onalc

oholi

c Bev

erag

es0.7

40.0

40.3

62.8

90.0

53.8

70.0

229

.543.8

50.0

10.6

56.9

70.9

70.0

80.4

00.0

411

.610.1

31.3

74.4

028

.032.3

21.6

610

0.00

Brea

d and

Cerea

ls 0.3

20.0

30.2

23.1

10.0

57.8

60.0

426

.192.9

70.0

11.7

37.8

41.3

70.0

70.7

90.0

312

.900.3

01.3

07.7

120

.451.8

32.8

710

0.00

Meat

and F

ish1.6

70.0

70.4

73.6

80.0

73.2

50.0

112

.493.6

30.0

10.2

74.7

20.5

80.1

70.4

00.0

59.0

90.1

81.9

57.0

745

.782.0

52.3

110

0.00

Fruits

and V

egeta

bles

0.30

0.04

0.21

2.40

0.02

2.75

0.01

38.62

4.40

0.01

0.33

6.05

1.17

0.02

0.20

0.03

12.10

0.08

1.09

1.79

25.08

2.34

1.00

100.0

0

Othe

r Foo

d0.7

00.0

30.5

02.5

00.0

62.5

80.0

337

.014.8

90.0

10.5

18.8

50.8

40.0

70.3

00.0

612

.280.0

31.1

82.6

021

.442.7

00.8

410

0.00

Cloth

ing an

d Foo

twea

r4.9

40.0

80.7

14.7

30.0

52.1

10.0

224

.247.3

90.0

10.4

26.4

51.7

10.1

10.0

80.0

36.2

40.0

30.9

51.0

832

.525.1

20.9

910

0.00

Hous

ing an

d Util

ities

1.61

0.06

0.74

4.61

0.04

2.22

0.02

19.82

11.03

0.01

0.28

6.11

0.65

0.05

0.16

0.06

8.81

0.12

1.82

2.36

35.18

2.76

1.47

100.0

0

Healt

h and

Educ

ation

1.05

0.04

0.59

6.14

0.03

1.60

0.01

32.60

5.46

0.02

0.43

6.14

0.12

0.05

0.33

0.03

3.62

0.07

0.62

1.88

33.31

2.85

3.02

100.0

0

Trans

porta

tion a

nd Co

mm

unica

tions

1.81

0.10

1.91

7.99

0.16

0.61

0.00

25.16

14.04

0.01

0.08

2.64

0.99

0.04

0.14

0.05

5.11

0.05

4.00

2.09

26.04

6.06

0.91

100.0

0

Othe

r Ind

ividu

al Co

nsum

ption

Item

s3.7

20.1

21.7

08.8

50.0

71.1

40.0

216

.124.5

70.0

10.1

81.9

60.6

20.0

30.1

60.0

55.7

90.0

62.8

62.3

841

.816.3

91.4

010

0.00

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t1.2

80.0

70.7

13.8

70.1

50.6

50.0

517

.316.1

30.0

30.1

80.8

10.8

90.2

00.4

10.0

84.3

80.1

74.0

21.8

847

.186.5

53.0

010

0.00

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1.12

0.07

1.28

5.31

0.29

0.59

0.03

13.73

5.52

0.14

2.23

0.53

0.06

0.15

0.06

2.95

0.21

2.26

1.40

57.87

2.53

1.65

100.0

0

Gros

s Fixe

d Cap

ital F

orm

atio

n1.6

50.1

21.3

03.3

90.0

51.1

20.0

315

.853.2

70.1

41.4

70.3

70.0

50.0

60.0

33.9

10.0

81.8

30.9

359

.353.4

51.5

110

0.00

Chan

ge in

Inve

ntor

ies a

nd N

et Ac

quisi

tions

of Va

luab

les

-0.35

0.04

-2.18

-0.52

0.00

0.00

0.00

34.17

29.05

0.63

1.86

0.68

0.14

0.03

0.02

0.69

0.06

-0.41

9.44

21.25

3.88

1.52

100.0

0

Bala

nce o

f Exp

orts

and I

mpo

rts10

.622.0

416

.307.1

92.0

6-1

.93-0

.07-1

1.24

5.54

-0.70

-3.47

-1.05

-0.04

-0.06

-0.39

5.83

-0.13

14.76

-1.97

58.94

-1.10

-1.05

100.0

0

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Peo

ple’s R

epub

lic of

China

; TH

A - Th

ailan

d; an

d VIE

- Viet

Nam

.No

te:

1. Re

sults

for t

he PR

C wer

e bas

ed on

natio

nal a

vera

ge pr

ices e

xtra

polat

ed by

the W

orld

Bank

and A

DB us

ing pr

ice da

ta fo

r 11 c

ities

subm

itted

by th

e Nat

ional

Bure

au of

Stat

istics

of Ch

ina.

2. M

aldive

s is o

nly p

artic

ipatin

g in t

he co

mpa

rison

of ac

tual

final

cons

umpt

ion of

hous

ehold

s.3.

Asia

refer

s onl

y to t

he 23

parti

cipat

ing ec

onom

ies.

Appe

ndix

Tabl

e B6.

Per C

apita

Rea

l Exp

endi

ture

Rel

ativ

es, 2

005

(Asia

=10

0)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAS

IA

GROS

S DOM

ESTI

C PRO

DUCT

988

1035

1150

720

1312

3510

259

296

3066

9774

4011

590

5031

781

115

190

6010

0

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

959

518

763

835

626

5094

7232

911

045

101

135

8159

193

115

5527

310

888

221

6510

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s98

052

277

684

958

252

8673

329

9746

106

134

7357

185

118

5326

011

086

214

6310

0

Food

and N

onalc

oholi

c Bev

erag

es36

329

627

842

644

495

119

9018

810

286

151

165

102

9617

717

776

175

173

7212

067

100

Brea

d and

Cerea

ls 15

621

617

345

948

319

223

280

145

9522

917

023

295

191

125

197

175

166

303

5295

116

100

Meat

and F

ish82

151

636

354

459

579

5938

177

9836

103

9922

798

217

139

109

250

277

118

106

9310

0

Fruits

and V

egeta

bles

145

254

161

354

208

6764

117

214

6843

131

199

2249

103

185

4614

070

6412

140

100

Othe

r Foo

d34

622

238

436

950

763

132

112

238

137

6819

214

390

7223

918

818

151

102

5513

934

100

Cloth

ing an

d Foo

twea

r24

2557

654

469

945

351

107

7436

080

5614

029

014

419

112

9516

122

4283

265

4010

0

Hous

ing an

d Util

ities

793

411

571

682

396

5411

360

537

8837

133

110

6939

221

135

7223

493

9014

359

100

Healt

h and

Educ

ation

516

272

454

906

284

3954

9926

617

357

133

2162

8111

155

4180

7485

147

121

100

Trans

porta

tion a

nd Co

mm

unica

tions

887

721

1471

1181

1487

1516

7668

470

1057

168

5233

188

7832

512

8267

313

3710

0

Othe

r Ind

ividu

al Co

nsum

ption

Item

s18

2788

113

1213

0761

628

8049

222

7724

4310

637

3920

389

3636

693

107

330

5610

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t62

749

354

757

213

8116

250

5329

839

124

1815

126

910

033

067

102

515

7412

133

812

110

0

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

552

491

988

785

2638

1415

642

269

1948

9073

3721

945

123

289

5514

913

167

100

Gros

s Fixe

d Cap

ital F

orm

atio

n81

082

610

0350

047

127

165

4815

918

3263

6914

120

6046

235

3715

217

861

100

Chan

ge in

Inve

ntor

ies a

nd N

et Ac

quisi

tions

of Va

luab

les

-170

298

-167

7-7

77

012

104

1415

8340

115

190

865

1134

-52

371

5520

161

100

Bala

nce o

f Exp

orts

and I

mpo

rts52

1714

383

1256

610

6218

636

-47

-348

-34

270

-92

-75

-178

-57

-15

-156

889

-79

1891

-77

151

-57

-42

100

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina;

THA -

Thail

and;

and V

IE - V

iet N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.

3. A

sia re

fers o

nly t

o the

23 pa

rticip

ating

econ

omies

.


�0

Appe

ndix

Tabl

e B7.

Nom

inal

Expe

nditu

re Sh

ares

by Ca

tego

ry, 2

005

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAV

G

GROS

S DOM

ESTI

C PRO

DUCT

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

61.7

30.8

45.0

66.8

28.6

77.7

52.9

63.4

55.8

53.8

84.7

79.7

76.3

62.3

86.0

84.1

67.2

62.9

51.2

72.8

43.0

63.1

62.9

54.1

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s58

.828

.642

.964

.024

.876

.246

.060

.352

.146

.082

.278

.972

.756

.882

.475

.164

.959

.946

.469

.640

.956

.959

.751

.4

Food

and N

onalc

oholi

c Bev

erag

es5.5

4.43.9

10.4

5.439

.618

.321

.413

.012

.342

.138

.928

.422

.741

.718

.328

.529

.78.6

32.0

10.4

9.719

.414

.7

Brea

d and

Cerea

ls 0.5

0.70.5

2.51.1

17.5

7.54.1

2.62.2

22.2

8.17.4

4.713

.92.4

6.912

.11.7

10.4

1.61.5

6.53.0

Meat

and F

ish2.7

1.71.3

3.01.8

7.61.9

2.13.2

2.14.0

6.54.2

9.311

.65.2

5.110

.72.6

11.2

3.71.9

7.43.6

Fruits

and V

egeta

bles

0.61.1

0.62.6

0.95.4

2.56.2

3.23.5

4.97.9

9.21.9

5.72.9

6.34.4

2.24.5

2.42.7

2.53.4

Othe

r Foo

d1.7

0.91.4

2.41.7

9.16.3

9.04.0

4.611

.016

.37.6

6.710

.47.8

10.2

2.52.1

5.92.6

3.53.1

4.6

Cloth

ing an

d Foo

twea

r6.1

1.51.6

2.51.2

4.63.4

3.33.5

1.95.4

6.07.0

6.81.6

1.82.4

1.11.2

1.62.7

4.32.3

3.0

Hous

ing an

d Util

ities

11.0

4.36.4

10.4

3.512

.98.8

7.713

.716

.011

.210

.95.7

10.1

11.0

21.1

13.6

7.88.9

10.2

6.34.5

9.58.1

Healt

h and

Educ

ation

7.02.6

5.110

.02.3

5.23.1

5.25.3

4.98.2

8.61.1

4.08.3

5.13.4

3.32.4

5.94.8

4.87.9

5.3

Trans

porta

tion a

nd Co

mm

unica

tions

5.84.3

8.58.8

5.93.6

1.210

.76.5

3.53.7

5.712

.95.2

6.58.8

5.76.9

9.26.9

3.510

.36.7

6.1

Othe

r Ind

ividu

al Co

nsum

ption

Item

s23

.311

.417

.421

.96.5

10.3

11.2

12.1

10.1

7.411

.88.9

17.5

8.013

.320

.011

.311

.116

.213

.213

.223

.414

.014

.2

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t2.9

2.22.0

2.83.8

1.46.9

3.13.6

7.82.5

0.73.6

5.53.6

9.02.4

3.04.8

3.22.1

6.23.1

2.6

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

5.25.3

7.28.7

14.4

3.910

.07.0

6.413

.35.8

6.06.0

5.03.8

13.6

4.911

.66.1

6.28.9

7.16.1

7.7

Gros

s Fixe

d Cap

ital F

orm

atio

n20

.926

.622

.020

.511

.925

.053

.228

.521

.553

.519

.618

.923

.730

.111

.728

.723

.333

.320

.614

.441

.528

.632

.532

.0

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s-0

.30.7

-3.2

-0.2

0.00.0

0.34.2

11.1

0.06.6

1.63.1

6.50.5

1.10.3

1.9-0

.410

.81.1

2.52.7

2.0

Bala

nce o

f Exp

orts

and I

mpo

rts12

.536

.629

.14.2

45.1

-6.6

-16.4

-3.0

5.3-2

0.6-1

6.7-6

.1-9

.1-3

.9-2

.0-2

7.44.2

-9.7

22.4

-4.2

5.5-1

.3-4

.14.3

AVG

mea

ns av

erag

e.HK

G - H

ong K

ong,

China

; MAC

- M

acao

, Chin

a; SIN

- Sin

gapo

re; T

AP - T

aipei,

China

; BRU

- Br

unei

Daru

ssalam

; BAN

- Ba

nglad

esh;

BHU

- Bhu

tan;

IND

- Ind

ia; IR

N - I

slam

ic Re

publi

c of Ir

an; M

LD -

Mald

ives;

NEP -

Nep

al; PA

K - Pa

kista

n;SR

I - Sr

i Lan

ka; M

ON -

Mon

golia

; CAM

- Ca

mbo

dia; F

IJ - F

iji Isl

ands

; INO

- Ind

ones

ia; LA

O - L

ao Pe

ople’

s Dem

ocra

tic Re

publi

c; MA

L - M

alays

ia; PH

I - Ph

ilippin

es; P

RC -

Peop

le’s R

epub

lic of

China

; THA

- Tha

iland

; and

VIE -

Viet

Nam

. No

te:

1. Re

sults

for t

he PR

C wer

e bas

ed on

natio

nal a

vera

ge pr

ices e

xtra

polat

ed by

the W

orld

Bank

and A

DB us

ing pr

ice da

ta fo

r 11 c

ities

subm

itted

by th

e Nat

ional

Bure

au of

Stat

istics

of Ch

ina.

2. M

aldive

s is o

nly p

artic

ipatin

g in t

he co

mpa

rison

of ac

tual

final

cons

umpt

ion of

hous

ehold

s.


��

Appe

ndix

Tabl

e B8.

Per C

apita

Nom

inal

Expe

nditu

res,

2005

(H

ong K

ong d

ollar

s)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAV

G

GROS

S DOM

ESTI

C PRO

DUCT

2029

4119

0596

2091

2312

1908

2002

9334

7210

252

5499

2481

319

850

2667

5981

9474

7117

3531

2767

410

198

3951

4082

990

0513

386

2116

249

5111

372

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

1253

0358

623

9396

781

434

5730

826

9754

2434

8613

834

1067

722

5947

6572

2944

3230

3623

273

6857

2487

2091

465

5657

5313

356

3112

6147

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s11

9376

5444

889

688

7800

949

697

2647

4718

3317

1293

091

3621

9347

2268

8640

4029

1020

788

6614

2367

1893

862

7154

7612

042

2957

5847

Food

and N

onalc

oholi

c Bev

erag

es11

231

8410

8104

1265

010

911

1376

1873

1174

3236

2450

1122

2324

2689

1614

1471

5078

2905

1173

3493

2878

1388

2048

963

1668

Brea

d and

Cerea

ls 10

6214

0310

6229

9622

0360

977

422

665

643

859

148

770

233

849

267

770

048

067

694

121

432

632

234

4

Meat

and F

ish54

8432

1427

8435

9635

1326

419

311

380

341

810

638

740

165

941

014

4051

842

410

5010

0449

539

436

740

6

Fruits

and V

egeta

bles

1296

2015

1276

3169

1765

186

255

341

784

687

132

473

869

137

201

814

644

172

904

402

324

578

122

391

Othe

r Foo

d33

8917

7829

8128

8934

2931

765

149

499

390

829

397

671

747

936

821

4610

4497

863

531

354

749

152

526

Cloth

ing an

d Foo

twea

r12

445

2895

3413

3050

2380

159

347

182

863

378

143

357

665

486

5651

024

744

470

141

362

906

112

342

Hous

ing an

d Util

ities

2240

082

2013

310

1271

969

5344

890

042

333

9331

7129

865

254

471

839

058

3113

8630

836

4891

484

395

746

991

9

Healt

h and

Educ

ation

1427

348

6410

683

1217

445

0918

032

028

513

1896

621

951

710

928

729

214

1134

512

997

553

264

410

1239

060

7

Trans

porta

tion a

nd Co

mm

unica

tions

1169

582

3717

702

1069

911

911

125

125

587

1618

697

9833

912

2336

923

024

3057

727

437

4262

147

221

7433

069

6

Othe

r Ind

ividu

al Co

nsum

ption

Item

s47

332

2182

236

476

2671

613

033

358

1153

666

2503

1474

313

533

1657

567

471

5529

1153

439

6610

1185

1767

4945

694

1615

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t59

2741

7542

8034

2576

1150

706

169

905

1541

6644

343

392

126

2485

244

120

1976

285

277

1314

155

301

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1060

910

172

1495

210

648

2875

513

610

2538

215

7826

3615

535

657

035

813

337

6550

446

024

7655

611

9514

9430

287

4

Gros

s Fixe

d Cap

ital F

orm

atio

n42

450

5078

746

086

2496

123

910

869

5459

1567

5336

1061

952

411

3122

4821

3941

379

3223

7713

1484

2512

9755

5460

6116

1036

40

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s-6

9913

27-6

767

-283

250

2922

927

570

175

9428

946

419

298

2873

-147

971

150

527

133

226

Bala

nce o

f Exp

orts

and I

mpo

rts25

277

6968

860

885

5147

9029

5-2

29-1

684

-166

1307

-408

2-4

45-3

65-8

62-2

76-7

1-7

595

432

-383

9161

-375

733

-277

-205

485

AVG

mea

ns av

erag

e.HK

G - H

ong K

ong,

China

; MAC

- M

acao

, Chin

a; SIN

- Sin

gapo

re; T

AP - T

aipei,

China

; BRU

- Br

unei

Daru

ssalam

; BAN

- Ba

nglad

esh;

BHU

- Bhu

tan;

IND

- Ind

ia; IR

N - I

slam

ic Re

publi

c of Ir

an; M

LD -

Mald

ives;

NEP -

Nep

al; PA

K - Pa

kista

n;SR

I - Sr

i Lan

ka; M

ON -

Mon

golia

; CAM

- Ca

mbo

dia; F

IJ - F

iji Isl

ands

; INO

- Ind

ones

ia; LA

O - L

ao Pe

ople’

s Dem

ocra

tic Re

publi

c; MA

L - M

alays

ia; PH

I - Ph

ilippin

es; P

RC -

Peop

le’s R

epub

lic of

China

; THA

- Tha

iland

; and

VIE -

Viet

Nam

. No

te:

1. Re

sults

for t

he PR

C wer

e bas

ed on

natio

nal a

vera

ge pr

ices e

xtra

polat

ed by

the W

orld

Bank

and A

DB us

ing pr

ice da

ta fo

r 11 c

ities

subm

itted

by th

e Nat

ional

Bure

au of

Stat

istics

of Ch

ina.

2. M

aldive

s is o

nly p

artic

ipatin

g in t

he co

mpa

rison

of ac

tual

final

cons

umpt

ion of

hous

ehold

s.


��

Appe

ndix

Tabl

e B9.

Nom

inal

Expe

nditu

res,

Econ

omy S

hare

s to A

sia by

Cate

gory

, 200

5

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAS

IA

GROS

S DOM

ESTI

C PRO

DUCT

3.63

0.24

2.39

7.26

0.19

1.25

0.02

15.91

4.48

0.02

0.18

2.42

0.49

0.05

0.13

0.06

5.87

0.06

2.80

2.02

45.86

3.60

1.08

100.0

0

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

4.15

0.13

1.98

8.97

0.10

1.80

0.02

18.66

4.62

0.02

0.28

3.57

0.69

0.05

0.20

0.10

7.30

0.07

2.66

2.72

36.46

4.20

1.26

100.0

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s4.1

60.1

31.9

99.0

30.0

91.8

50.0

218

.674.5

40.0

10.2

83.7

20.6

90.0

50.2

10.0

97.4

00.0

72.5

32.7

336

.493.9

91.2

610

0.00

Food

and N

onalc

oholi

c Bev

erag

es1.3

70.0

70.6

35.1

30.0

73.3

80.0

223

.173.9

80.0

10.5

16.4

10.9

50.0

70.3

60.0

811

.390.1

21.6

44.4

032

.422.3

81.4

310

0.00

Brea

d and

Cerea

ls 0.6

30.0

60.4

05.8

90.0

77.2

40.0

421

.613.9

10.0

11.3

06.5

01.2

00.0

70.5

90.0

513

.290.2

41.5

36.9

624

.261.8

32.3

210

0.00

Meat

and F

ish2.7

50.1

10.8

95.9

90.1

02.6

60.0

19.1

84.0

60.0

10.2

04.3

90.5

80.1

20.4

20.0

98.3

30.1

82.0

26.3

047

.491.8

82.2

510

0.00

Fruits

and V

egeta

bles

0.67

0.07

0.42

5.48

0.05

1.95

0.01

28.65

4.11

0.02

0.26

5.57

1.31

0.03

0.21

0.05

10.76

0.07

1.80

2.62

32.24

2.86

0.77

100.0

0

Othe

r Foo

d1.3

10.0

50.7

43.7

20.0

72.4

60.0

230

.923.8

70.0

20.4

28.5

40.8

00.0

70.2

90.1

012

.980.0

31.2

82.5

726

.252.7

60.7

210

0.00

Cloth

ing an

d Foo

twea

r7.4

00.1

21.2

96.0

30.0

81.9

10.0

217

.455.1

70.0

10.3

24.8

01.1

40.1

10.0

70.0

44.7

30.0

21.0

71.0

541

.245.1

20.8

210

0.00

Hous

ing an

d Util

ities

4.96

0.13

1.88

9.37

0.08

2.00

0.02

15.14

7.58

0.03

0.25

3.26

0.35

0.06

0.18

0.16

9.86

0.06

3.10

2.53

35.74

2.02

1.27

100.0

0

Healt

h and

Educ

ation

4.79

0.11

2.28

13.58

0.08

1.22

0.01

15.47

4.46

0.01

0.27

3.92

0.11

0.04

0.20

0.06

3.72

0.04

1.25

2.23

41.33

3.23

1.59

100.0

0

Trans

porta

tion a

nd Co

mm

unica

tions

3.42

0.17

3.30

10.41

0.19

0.74

0.00

27.75

4.77

0.01

0.11

2.24

1.03

0.04

0.14

0.09

5.43

0.07

4.20

2.27

26.41

6.04

1.18

100.0

0

Othe

r Ind

ividu

al Co

nsum

ption

Item

s5.9

70.1

92.9

311

.200.0

90.9

10.0

113

.583.1

80.0

10.1

51.5

20.6

00.0

30.1

20.0

94.6

70.0

53.2

01.8

742

.655.9

31.0

710

0.00

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t4.0

10.2

01.8

57.7

10.2

80.6

80.0

418

.486.1

80.0

50.1

70.6

70.6

70.1

00.1

70.2

15.3

00.0

75.1

32.4

235

.878.4

61.2

810

0.00

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

2.47

0.16

2.22

8.25

0.36

0.64

0.02

14.39

3.71

0.03

0.13

1.88

0.38

0.03

0.06

0.11

3.77

0.09

2.21

1.62

53.29

3.31

0.86

100.0

0

Gros

s Fixe

d Cap

ital F

orm

atio

n2.3

70.2

01.6

44.6

40.0

70.9

80.0

314

.173.0

10.0

30.1

11.4

30.3

60.0

40.0

50.0

54.2

70.0

61.8

10.9

159

.443.2

21.1

010

0.00

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s-0

.630.0

8-3

.89-0

.850.0

00.0

00.0

033

.4625

.090.0

00.5

91.9

20.7

50.1

60.0

40.0

30.8

10.0

5-0

.5110

.9725

.954.5

21.4

610

0.00

Bala

nce o

f Exp

orts

and I

mpo

rts10

.622.0

416

.307.1

92.0

6-1

.93-0

.07-1

1.24

5.54

-0.07

-0.70

-3.47

-1.05

-0.04

-0.06

-0.39

5.83

-0.13

14.76

-1.97

58.94

-1.10

-1.05

100.0

0

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina; T

HA - T

haila

nd; a

nd VI

E - Vi

et N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.

3. A

sia re

fers o

nly t

o the

23 pa

rticip

ating

econ

omies

.


��

Appe

ndix

Tabl

e B10

. Per

Capi

ta N

omin

al Ex

pend

iture

Rel

ativ

es, 2

005

(Asia

=10

0)

Expe

nditu

re Ca

tego

ry/E

cono

my

HKG

MAC

SIN

TAP

BRU

BAN

BHU

IND

IRN

MLD

NEP

PAK

SRI

MON

CAM

FIJIN

OLA

OM

ALPH

IPR

CTH

AVI

EAS

IA

GROS

S DOM

ESTI

C PRO

DUCT

1785

1676

1839

1072

1761

3190

4821

823

5383

6331

243

9035

359

7911

818

644

100

Actu

al Fi

nal C

onsu

mpt

ion o

f Hou

seho

lds

2038

954

1529

1325

932

4488

5722

517

437

7811

872

4937

911

240

340

107

9421

751

100

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by H

ouse

hold

s20

4293

115

3413

3485

045

8157

221

156

3881

118

6950

356

113

4032

410

794

206

5110

0

Food

and N

onalc

oholi

c Bev

erag

es67

350

448

675

865

482

112

7019

414

767

139

161

9788

304

174

7020

917

383

123

5810

0

Brea

d and

Cerea

ls 30

840

730

887

064

017

722

566

190

127

172

141

204

9814

319

720

313

919

627

362

9593

100

Meat

and F

ish13

5079

168

588

586

565

4828

198

103

2695

9916

210

135

412

710

425

824

712

297

9010

0

Fruits

and V

egeta

bles

331

515

326

810

451

4865

8720

017

634

121

222

3551

208

165

4423

110

383

148

3110

0

Othe

r Foo

d64

433

856

754

965

260

124

9418

917

356

186

136

9170

408

199

1816

410

167

142

2910

0

Cloth

ing an

d Foo

twea

r36

3584

699

789

169

547

101

5325

211

142

104

194

142

1614

972

1313

741

106

265

3310

0

Hous

ing an

d Util

ities

2437

894

1448

1384

756

4998

4636

934

532

7159

7842

634

151

3339

799

9210

451

100

Healt

h and

Educ

ation

2351

801

1760

2006

743

3053

4721

715

936

8518

4748

232

5721

161

8810

616

764

100

Trans

porta

tion a

nd Co

mm

unica

tions

1680

1184

2544

1537

1712

1818

8423

210

014

4917

653

3334

983

3953

889

6831

247

100

Othe

r Ind

ividu

al Co

nsum

ption

Item

s29

3213

5222

5916

5580

722

7141

155

9119

3310

335

2934

271

2740

973

109

306

4310

0

Indi

vidua

l Con

sum

ptio

n Exp

endi

ture

s by G

over

nmen

t19

7213

8914

2411

4025

3217

235

5630

151

322

1411

413

042

827

8140

657

9592

437

5110

0

Colle

ctive

Cons

umpt

ion E

xpen

ditu

res b

y Gov

ernm

ent

1214

1164

1711

1218

3290

1611

744

181

1841

6541

1543

158

5328

364

137

171

3410

0

Gros

s Fixe

d Cap

ital F

orm

atio

n11

6613

9512

6668

665

724

150

4314

714

3162

5911

218

6536

231

3615

316

744

100

Chan

ge in

Inve

ntor

ies an

d Net

Acqu

isitio

ns of

Valu

able

s-3

1058

8-3

000

-125

110

1310

212

2278

4212

820

69

132

1233

-65

430

6723

459

100

Bala

nce o

f Exp

orts

and I

mpo

rts52

1714

383

1256

610

6218

636

-47

-348

-34

270

-92

-75

-178

-57

-15

-156

889

-79

1891

-77

151

-57

-42

100

HKG

- Hon

g Kon

g, Ch

ina; M

AC -

Mac

ao, C

hina;

SIN -

Singa

pore

; TAP

- Taip

ei,Ch

ina; B

RU -

Brun

ei Da

russa

lam; B

AN -

Bang

lades

h; BH

U - B

huta

n; IN

D - I

ndia;

IRN

- Isla

mic

Repu

blic o

f Iran

; MLD

- M

aldive

s; NE

P - N

epal;

PAK -

Pakis

tan;

SRI -

Sri L

anka

; MON

- M

ongo

lia; C

AM -

Cam

bodia

; FIJ

- Fiji

Islan

ds; IN

O - I

ndon

esia;

LAO

- Lao

Peop

le’s D

emoc

ratic

Repu

blic;

MAL -

Mala

ysia;

PHI -

Philip

pines

; PRC

- Pe

ople’

s Rep

ublic

of Ch

ina; T

HA - T

haila

nd; a

nd VI

E - Vi

et N

am.

Note

:1.

Resu

lts fo

r the

PRC w

ere b

ased

on na

tiona

l ave

rage

price

s ext

rapo

lated

by th

e Wor

ld Ba

nk an

d ADB

using

price

data

for 1

1 citi

es su

bmitt

ed by

the N

ation

al Bu

reau

of St

atist

ics of

China

. 2.

Mald

ives i

s onl

y par

ticipa

ting i

n the

com

paris

on of

actu

al fin

al co

nsum

ption

of ho

useh

olds.

3. A

sia re

fers o

nly t

o the

23 pa

rticip

ating

econ

omies

.



��


Appendix creAl expenditure compArison And price leVel indices

with the regionAl AVerAge As BAse

In the main body of this preliminary report, several tables report results relative to the regional average as the base. In particular, per capita real GDP and expenditures as well as price level indices (PLI) are presented with Asian average equal to 1 (or 100). This Appendix seeks to explain the basic methodology used in measuring regional averages.

The gross domestic product (GDP) of each country is expressed in that country’s national currency, referred to here as local currency units (LCU). To make valid comparisons among various countries, these GDP figures must first be converted to a numeraire currency, in this case the Hong Kong dollar. These conversions may be accomplished using official exchange rates. GDPs converted to the Hong Kong dollar using official exchange rates are expressed in nominal terms because they will incorporate differences in price levels among countries. On the other hand, when GDPs are converted to a numeraire currency using purchasing power parities (PPP), they are expressed in real terms. They become comparable from one country to another, because the purchasing power of each local currency has been taken into account. Being comparable, these GDP figures can be summed directly to calculate a regional GDP. Note that it does not matter what currency is used as the “numeraire” currency. It can be Hong Kong dollars, Indian rupees, or any other currency, including one from outside the region, such as United States dollars. The shares of each country’s GDP within the regional GDP will not change nor will the position of each country compared with other countries in the region.

As practiced in other regions, the results are presented in a currency of one country “regionalized” to represent the whole region. 1 The advantage of this is that, when a regional average currency is used, each participating economy is being compared to the average for the region as a whole. The changing of the base from the Hong Kong dollar to the regional average was constructed in such a way that the resulting sum of the real GDPs is the same as the sum of the nominal GDPs in Hong Kong dollars.

The calculation is explained in Appendix Table C. The table shows national GDPs in local currency (column 1), PPPs with Hong Kong, China equal to one (column 2), and official exchange rates with Hong Kong dollar (column 4). GDPs in local currencies are converted to Hong Kong dollar in real terms using the PPPs (column 1 / column 2 = column 3). These are summed to obtain the regional GDP in Hong Kong dollars in real terms (3a). Meanwhile, the GDPs in local currencies are converted to Hong Kong dollars using the exchange rate (column 1 / column 4 = column 5). These GDPs are summed to obtain a total regional GDP in Hong Kong dollars in nominal terms (5a).

To calculate the conversion factor between the regional average for Asia and the actual Hong Kong dollar, we divide the nominal regional total in Hong Kong dollars by the real regional total in Hong Kong dollars: (5a) / (3a) = (6). Real GDPs expressed in Hong Kong dollars are converted to real GDP with Asia as base by multiplying by the factor calculated above (column 3 * (6) = column 7). In the context of the average for Asia, the PLI is the ratio between the nominal GDP in Hong Kong dollars and real GDP based on the Asian average (column 5 / column 7 = column 8). The PLI indicates the price level within a country relative to the region as a whole. When the index is greater than one, it means that prices are higher in that country than the regional average. Note that the relativities of countries based on the PLI would be exactly the same if we had used any other regionalized currency.

Note also that the purchasing power of one Hong Kong dollar is not the same as the purchasing power of one unit based on the regional average. It is actually equal to 0.55; see item (6) in Appendix Table C.

This methodology is applied at each level of analysis. Thus, the conversion factor differs from one expenditure category to another.

1 A similar practice is used in OECD/Eurostat/Commonwealth of Independent States, African, West Asian, and Latin American comparisons. In those regions, the regional currencies are calibrated to the United States dollar.



��

Appendix Table C. Derivation of Real Expenditures with the Regional Average as Base

Economy GDP(LCU)

PPP(LCU/HK$)

Real GDP(HK$)

Exchange rate(LCU/HK$)

Nominal GDP(HK$)

Real GDP(Asian average

as base)

PLI(Asia=100)

(1) (2) (3) = (1) / (2) (4) (5) = (1) / (4) (7) = (3) * (6) (8) = (5) / (7)HKG 1,382.68 1.000 1382.68 1.00 1,382.68 765.27 181

MAC 92.95 0.923 100.66 1.03 90.24 55.71 162

SIN 194.24 0.189 1025.75 0.21 907.64 567.72 160

TAP 11,421.26 3.407 3351.80 4.14 2,761.43 1,855.11 149

BRU 15.86 0.159 99.77 0.21 74.13 55.22 134

BAN 3,934.30 3.964 992.55 8.27 475.67 549.35 87

BHU 36.91 2.781 13.27 5.67 6.51 7.35 89

IND 34,339.01 2.583 13293.35 5.67 6,055.91 7,357.43 82

IRN 1,964,745.00 469.933 4180.90 1,152.58 1,704.66 2,313.99 74

MLD* 9.60 1.65

NEP 620.31 3.963 156.53 9.18 67.60 86.64 78

PAK 7,046.82 3.351 2102.72 7.65 920.88 1,163.79 79

SRI 2,407.78 6.171 390.19 12.92 186.33 215.96 86

MON 2,809.90 73.018 38.48 154.97 18.13 21.30 85

CAM 25,692.64 224.697 114.34 526.21 48.83 63.29 77

FIJ 5.07 0.255 19.87 0.22 23.31 11.00 212

INO 2,784,960.40 690.583 4032.77 1,247.82 2,231.85 2,232.00 100

LAO 30,594.09 522.475 58.56 1,370.03 22.33 32.41 69

MAL 519.45 0.305 1701.85 0.49 1,066.77 941.92 113

PHI 5,437.91 3.828 1420.69 7.08 767.76 786.31 98

PRC** 18,386.79 0.599 30710.91 1.05 17,451.13 16,997.48 103

THA 7,087.66 2.800 2531.33 5.17 1,370.54 1,401.01 98

VIE 839,211.00 821.174 1021.96 2,039.12 411.56 565.62 73

(3a) (5a) (7a)

Asia*** 68,741 38,046 38,046 100

Conversion Factor (6) = (5a) / (3a)

Asian Average / HK$ 0.55

LCU means local currency unit; PLI mean price level index.HKG - Hong Kong, China; MAC - Macao, China; SIN - Singapore; TAP - Taipei,China; BRU - Brunei Darussalam; BAN - Bangladesh; BHU - Bhutan; IND - India;IRN - Islamic Republic of Iran; MLD - Maldives; NEP - Nepal; PAK - Pakistan; SRI - Sri Lanka; MON - Mongolia; CAM - Cambodia; FIJ - Fiji Islands; INO - Indonesia;LAO - Lao People’s Democratic Republic; MAL - Malaysia; PHI - Philippines; PRC - People’s Republic of China; THA - Thailand; and VIE - Viet Nam.*Maldives is only participating in the comparison of actual final consumption of households.**Results for the PRC were based on national average prices extrapolated by the World Bank and ADB using price data for 11 cities submitted by the National Bureau of Statistics of China. ***Asia refers only to the 23 participating economies.



��


Appendix dproductiVity Adjustment For goVernment compensAtion

The 23 participating economies span the whole range of development levels: from some of the highest in the world to some of the lowest. Hong Kong, China is ranked in PPP terms as No. 9 and Nepal as No. 179, respectively, in the World Development Indicators 2007 (World Bank 2007b). In this respect, the Asian comparison faces unique challenges compared to other regional comparisons. For example, the difference between the highest and the lowest GDP per capita in PPP terms among South American countries is only 3 to 1, whereas in Asia the difference between Singapore and Nepal reaches 40 times in real and 83 times in nominal terms.

Services in general, and the compensation part of government services in particular, are among the most difficult areas of the ICP Asia Pacific. There are two approaches to compensation measurement. Approach 1 is “an hour is an hour”, which means that productivity is uniform across all countries. In Approach 2, productivity is adjusted to reflect differences in capital intensity. (We confine the adjustment to differences in capital inputs and assume constant quality of labor.)

Given that salaries across the region vary by over 100 times (120 times between Lao People’s Democratic Republic and Hong Kong, China in the health sector), it is unrealistic to expect that there would be no differences in productivity between those nations, especially given the fact that large differences in productivity can be observed in the rest of the GDP. Government workers in high-income countries would certainly be aided by access to modern communications services, high-speed networks, office equipment, science laboratories in schools and universities, and modern medical equipment in hospitals, compared to workers in low-income countries.

In describing the two approaches, we employ the Cobb-Douglas functional form. In its typical homothetic (linear homogenous) specification, output (Y) is a function of labor (L) and capital (K), with labor and capital coefficients being α and (1-α), respectively, or Y = CLa K 1-a. We denote the government part with subscript G; the symbols referring to the whole economy are without a subscript. Thus LG becomes the labor input in government sectors whereas L refers to the economywide labor input. L in our case is employment (estimated as the 15–64 age group) adjusted for labor quality (in the government case, employment is estimated as total compensation divided by average annual wages 1). The government production function is expressed as:

αα −= 1GGG KcLY (1)

Under Approach 1 (without productivity adjustment), formula (1) becomes

GG LcY 1= (2)Productivity is expressed as

α−

=

1

G

G

G

G

LKc

LY

(3)

and, in the case with no adjustment,

1cLY

G

G =

(4)

1 It is important to note that the Cobb-Douglas production function would refer to increases in both quality and quantity of labor and capital. Whereas we can assume that quality of capital is reflected in its price and thus is included in our value estimates, quality of labor should reflect cross-country differences in professional composition, education, skills, etc. For our purposes we assume that for the government sector, we collect salaries for equivalent qualifications and thus LG refers to standard quality of labor employed in the government sector across countries. So while for the whole economy L = LQuality LQuality , for the government sector LG = LG

QualityLGQuality = LG

Quality.

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As we cannot assess the government-specific capital–labor ratio directly, we have to make the assumption that capital intensity in government in different countries is proportional across sectors: i.e., if in one economy K/L in government is lower than the finance sector but higher than agriculture, the same proportions among those sectors would be found in other countries as well. Thus, one needs to estimate K/L only for the whole economy.

The capital-to-output ratio was estimated based on the perpetual inventory method with geometric decline as

∑=

−+=

2005

198120052005 )05.01(t

ttIK

(5)

where It is total investments in year t and 0.05 is the depreciation rate.K/Y ratio has been found to vary from 2.5 to 3.5, with the high-income countries having higher values. It is

important to note that even though this perpetual inventory method calculation omits investments prior to 1981, it nevertheless estimates the capital consistently across different countries.

With this in mind, equation (3) can be rewritten as follows: 2

α−

∗=

1

YK

LYc

LY

G

G

(6)

One problem with such a presentation is that we need to know productivity before we can compute productivity adjustment, as Y (real GDP) can be estimated only after the productivity adjustment has been made and incorporated into the computation of Y for the whole economy, thus necessitating iterations. This would make computation somewhat cumbersome, necessitating six or seven iterations. Another solution would be using Y/L ratio only for the components of GDP other than government. In that case iterations are not needed: one would compute Y/L ratio for the GDP without government and then proceed with formula (6). Practically, the second approach may turn out to be difficult in many countries as it is difficult to collect relevant data.

Next, one needs to determine the labor coefficient. Usually in the Cobb-Douglas specification this is determined by the wage share in GDP. Labor coefficient is usually higher in more developed economies and lower in less developed ones. In this exercise, we assumed that the low-income countries had a labor coefficient of 50 percent and high-income countries, 70 percent. Hence, (1-α) in equation (6) is set at 0.5 and 0.3 for low-income and high-income countries, respectively.

An obvious improvement in estimating productivity adjustment could come from measuring service-specific capital–output ratios. However, this would be even more difficult practically and would lie even further away in the future.

2 It is important to note that the Cobb-Douglas production function for the whole economy would refer to increases in both quality and quantity of labor and capital. While we can assume that quality of capital is reflected in its price and thus is included in our value estimates, quality of labor differences are harder to measure because they should reflect cross-country differences in professional composition, education, skills etc. For our purposes, we assume that for the government sector, we collect salaries for equivalent qualifications and thus LG refers to standard quality of labor employed in the government sector across countries.

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Effects of productivity adjustment for Asian economies are shown in Appendix Table D below. Prior to the adjustment, Lao People’s Democratic Republic had government services without intermediate consumption (i.e., the part as described in equations (1) and (2)) 3 at a much higher level than Hong Kong, China or Taipei,China; Viet Nam was higher than Thailand and so forth. That contributed to total government services (which include components other than compensation) in Lao People’s Democratic Republic being almost as high as in Thailand (56.1 versus 60.5 of Hong Kong, China, respectively); and more than half of Hong Kong, China’s level. The picture significantly changes after the adjustment. Appendix Table D below shows total government services before and after adjustment; the compensation part, with labor input unadjusted and adjusted for capital intensity; and the adjustment itself. The adjustment for Lao People’s Democratic Republic, for example, is 0.19, which means that the compensation component in Lao People’s Democratic Republic gets adjusted by a factor of 0.19 when compared to Hong Kong, China.

3 Government services consist mostly of two major categories—compensation and intermediate consumption. Only the compensation part is adjusted according to formula (6). The intermediate consumption and others are estimated using reference PPPs.

Appendix Table D. Effect of Productivity Adjustment for Selected Economies in ICP Asia Pacific (per capita real expenditures, regional average as base)

HKG TAP BHU IND MON LAO MAL PRC THA VIEWith Adjustment

Government Services 876 1,064 348 69 188 178 537 212 282 124

of which:

Compensation (labor input) 548 527 208 40 142 163 281 113 159 96

Economy’s GS Share to Hong Kong, China (%) 100.0 121.4 39.7 7.9 21.4 20.3 61.4 24.2 32.2 14.2

Without Adjustment

Government Services 402 565 352 82 206 226 376 221 244 154

of which:

Compensation (labor input) 152 164 208 50 166 243 142 120 118 138

Economy’s GS Share to Hong Kong, China (%) 100.0 140.4 87.4 20.4 51.3 56.1 93.4 54.9 60.5 38.3

Reference

Productivity Adjustment 1.00 0.89 0.28 0.22 0.24 0.19 0.55 0.26 0.37 0.19

Individual Consumption 7,389 6,227 606 550 550 399 1,809 649 1,622 478

GS means government services. HKG - Hong Kong, China; TAP - Taipei,China; BHU - Bhutan; IND - India; MON - Mongolia; LAO - Lao Democratic People’s Republic; MAL - Malaysia;PRC - People’s Republic of China; THA - Thailand; and VIE - Viet Nam.

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Appendix eglossAry oF ppp-relAted terms

The definitions in this glossary are based on definitions from the following references: Commission of the European Communities et al. (1993), Kravis et al. (1982), OECD (2000), and World Bank (2007a).

Term Definition

Actual final consumption of households

AFCH is the value of the consumption goods and services acquired by households, whether by purchase in general, or by transfer from government units or nonprofit institutions serving households, used for the satisfaction of needs and wants. It is derived from household final consumption expenditure by adding the value of social transfers in kind receivable.

Basic heading In principle, a group of similar well-defined goods or services for which a sample of products can be selected that are both representative of their type and of the purchases made in participating countries. In practice, a basic heading is defined as the smallest aggregate for which expenditure data are available.

Collective consumption service A service provided by local governments simultaneously to all members of the community (e.g., defense or fire protection services) or to all members of a particular section of the community, such as all households living in a particular region.

Comparability A requirement for participating countries to uniformly price products that are identical or, if not identical, equivalent. Pricing comparable products ensures that differences in prices between countries for a product reflect actual price differences and are not influenced by differences in quality. Two or more products are said to be comparable: if their physical and economic characteristics are identical, or if they are sufficiently similar that consumers are indifferent between them.

Comparative price levels See “price level index.”

Consumer durables Durable goods acquired by households for final consumption (i.e., those that are not used by households as stores of value or by unincorporated enterprises owned by households for purposes of production); may be used for purposes of consumption repeatedly or continuously over a period of one year or more.

Country product dummy method

The CPD method is a generalized multilateral method that uses regression techniques to obtain transitive PPPs for each basic heading. The data for a given category consist of all the prices available for the various specifications for the entire collection of countries in the region. The traditional country product dummy model assumes that the ratio of prices for each product within a basic heading is the same in every country.

Country-product-representativity-dummy method

The CPRD method is an extension of the CPD method. Unlike the CPD method, which assumes that all the products priced are equally representative in each country, the CPRD method explicitly takes into account whether each product is representative or nonrepresentative in each country in which it is priced.



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Term Definition

Elteto-Köves-Szulc method A procedure that enables binary PPPs, which are nontransitive when more than two countries are involved in the comparison, to be transformed into transitive PPPs, so that comparisons made between any pair of countries are mutually consistent. The EKS method produces transitive PPPs that are as close as possible to the nontransitive PPPs originally calculated in the binary comparisons. In practice, the EKS method is relevant only to the second part of this process (i.e., making the PPPs transitive). Volumes of final expenditures calculated using EKS-based PPPs are not additive.

Expenditure relatives Real measures expressed in index form with the level of an individual country or an average for a group (such as Asia and the Pacific region) set to a value of 100.

Final consumption Goods and services used up by individual households or the community to satisfy their individual or collective needs or wants.

Final expenditure Final consumption expenditure and gross fixed capital formation.

Government final consumption expenditure

Government expenditure, including imputed expenditure, incurred by national governments on both individual consumption goods and services and collective consumption services.

Gross domestic product – expenditure-based

Total final expenditures at purchasers’ prices (including free-on-board value of exports of goods and services), less the free-on-board value of imports of goods and services.

Gross fixed capital formation Measures the total value of a producer’s acquisitions, less disposals, of fixed assets during the accounting period. This includes certain additions to the value of nonproduced assets (such as subsoil assets or major improvements in the quantity, quality, or productivity of land), as realized by the productive activity of institutional units.

Household 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.

Numeraire currency Currency unit selected as the common currency in which PPPs and final expenditures on GDP (nominal and volumes) are expressed. The numeraire is usually an actual currency (such as the United States dollar) but it can be an artificial currency unit developed for the purposes of PPP comparisons. The Hong Kong dollar is the numeraire currency for the ICP Asia Pacific regional comparisons.

Per capita real expenditure (or volume)

Standardized measures of real expenditure (or volume). They indicate the relative levels of the product groups or aggregates being compared after adjusting for differences in the size of populations between countries. At the level of GDP, they are often used to compare the economic well-being of populations. They may be presented either in terms of a particular currency or as an index number.

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Term Definition

Price level index The PLI for a basic heading (or broader aggregate) in the ratio of the relevant PPP to the exchange rate. It is expressed as an index with a base of 100. A PLI greater than 100 means that when the national average prices are converted at exchange rates, the resulting prices within the basic heading tend to be higher, on average, than prices in the base country (or countries) of the region (and vice versa). At the level of GDP, PLIs provide a measure of the differences in the general price levels of countries. PLIs are also referred to as “comparative price levels.”

Purchaser’s price The amount paid by a purchaser, excluding any deductible value-added tax or similar deductible tax, in order to claim a unit of a good or service at the time and place required by the purchaser; the purchaser’s price of a good includes any transport charges paid separately by the purchaser to enable delivery at the required time and place.

Real expenditure Measures obtained by using PPPs to convert final expenditures on product groups, major aggregates, and GDP of different countries into a common currency, by valuing them at a uniform price level. They are the spatial equivalent of a time series of GDP for a single country expressed at constant prices. They provide a measure of the relative magnitudes of the product groups or aggregates being compared. At the level of GDP, they are used to compare the economic size of countries. They may be presented either in terms of a particular currency or as an index number.

Purchasing power parity PPP is a price relative that measures the number of units of country B’s currency that are needed in country B to purchase the same quantity of an individual good or service, which one unit of country A’s currency can purchase in country A.

Reference PPPs Used for basic headings for which no prices are collected. They are based on prices collected for other basic headings.

Representative product An item that accounts for a significant share of the expenditures within a basic heading in the country in question.

Transitivity The property whereby the direct PPP between any two countries (or regions) yields the same result as an indirect comparison via a third country (or region). It is sometimes referred to as “circularity.”

Volume See “ Real expenditure.”



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reFerencesADB. 2006. “Highlights of the Expert Group Meeting on Extrapolation Methodology.” Minutes of the meeting. 19–20 June,

Asian Development Bank, Manila.

———. 2007. Key Indicators. Asian Development Bank, Manila.

Commission of the European Communities (Eurostat), International Monetary Fund, Organisation for Economic Co-operation and Development, United Nations, and World Bank. 1993. System of National Accounts 1993. Brussels/Luxembourg, New York, Paris, Washington, DC.

Kravis, Irving B., A. Heston, and R. Summers. 1982. World Product and Income: International Comparisons of Real Gross Product. Baltimore and London: The Johns Hopkins University Press.

OANDA Corporation. 2007. “The Hamburger Standard.” Available: http://www.oanda.com/products/bigmac/bigmac.shtml.

Organisation for Economic Co-operation and Development. 2000. System of National Accounts, 1993—Glossary. Paris.

World Bank. 2007a. ICP 2003–2006 Handbook. Available: http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS/ICPEXT/

0,,contentMDK:20962711~menuPK:2666036~pagePK:60002244~piPK:62002388~theSitePK:270065,00.html.

———. 2007b. World Development Indicators 2007. Washington, DC.


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About the Purchasing Power Parity Preliminary Report

The 2005 round of the International Comparison Program in Asia and the Pacific region (ICP Asia Pacific) has achieved a number of milestones. The simultaneous participation of the People’s Republic of China and India, which together account for 64% of the total real gross domestic product of the 23 participating economies, was a first for the ICP and significantly increased the coverage of the round. In addition, the diversity in the economies in terms of size, geography, and statistical capacities was overcome as the 23 participating economies worked harmoniously to generate price and national accounts data that are broadly comparable. Further, the estimates of purchasing power parities in this round are far more robust than previous rounds because of improvements in methodology, data collection, data review, and data processing. Finally, the ICP Asia Pacific has established the technical know-how and institutional requirements that future ICP rounds could build on.

About the Asian Development Bank

ADB aims to improve the welfare of the people in the Asia and Pacific region, particularly the nearly 1.9 billion who live on less than $2 a day. Despite many success stories, the region remains home to two thirds of the world’s poor. ADB is a multilateral development finance institution owned by 67 members, 48 from the region and 19 from other parts of the globe. ADB’s vision is a region free of poverty. Its mission is to help its developing member countries reduce poverty and improve their quality of life.

ADB’s main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. ADB’s annual lending volume is typically about $6 billion, with technical assistance usually totaling about $180 million a year.

ADB’s headquarters is in Manila. It has 26 offices around the world and more than 2,000 employees from over 50 countries.

Asian Development Bank6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippineswww.adb.org/economicsPublication Stock No. 070907 Printed in the Philippines

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ICP Prelim Report MainText & App / 0/ 00 : : AMnamely, household final consumption expenditure, actual final consumption of households, government collective final consumption expenditure,