Consistency and Extrapolation of - Public …pubdocs.worldbank.org/en/331881487259049938/pdf/RCA03...Consistency and Extrapolation of ICP Benchmarks: The Case of Asia Yuri Dikhanov

Consistency and Extrapolation of

ICP Benchmarks: The Case of Asia

Yuri Dikhanov

3rd Regional Coordinating Agencies meeting

October 28-30, 2015

Washington, DC

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Background

• Asian comparisons as a part of the International Comparison

Program (ICP)

• Why extrapolation between benchmark is necessary?

• Inconsistencies between PPPs: ICP benchmarks, national accounts

deflators and CPIs

• Available information for extrapolation and ICP-SNA (CPI)

consistency studies

ICP-CPI inconsistencies

• Biggest difference: PPPs are spatial and CPIs are temporal

indices

• Comparing CPIs to changes in PPPs over time involves many

factors other than price movements.

– CPIs are mostly [but not always] estimated using Laspeyres indices at the

aggregate level, based on different years.

– ICP uses the EKS (Fisher) index.

– Addressing inconsistencies:

• Bridge the two benchmarks (2005 and 2011) using the 12 COICOP category CPI

components

• Predict PPPs by applying CPI components to the corresponding PPP categories

Linking 2005 and 2011 ICP: Asia

• Comparable in terms of:

– Structured product descriptions for individual items of HH

– Set of countries (22 out of 23)

– Sampling framework

– Classification systems used

– Methodology

• Consistent comparison across time and space is

possible

Scope of ICP comparison

• 2011 comparison, 22 countries,

108 basic headings, EKS (Fisher)

aggregation

2005 comparison, 22 countries, 108 basic

headings, EKS (Fisher) aggregation

Joint 2005-2011 comparison

Implicit ICP

inflation

Scope of extrapolation

• 2011 comparison, 8 countries,

• 12 COICOP categories

EKS (Fisher or Tornqvist) aggregation

2005 comparison, 8 countries,

12 COICOP categories

EKS (Fisher or Tornqvist) aggregation

- CPI, 12 COICOP categories

8 countries

- GDP deflators, 12 COICOP

categories

5 countries

Elementary aggregation in ICP

Country-Product Dummy method:

ln cp cp cp cpp y x β ε= = + (1)

where cpp is the price of product p in country c;

jDc and iDp are country and product dummies, respectively;

�p and �c are number of products and countries, respectively;

and 2 1 2

2 1 2

... ...

... ...

cp �c �p

T

�c �p

x Dc Dc DpDp Dp

β α α γ γ γ

=

=

Aggregate index in ICP: EKS (Fisher)

1

1

( )m m

j,l

j,kk,ll

F=EKS F

F=

∏ (2)

where Fj,k - Fisher index for country j and country k

m - number of all countries

Index number problem in extrapolation

• ICP uses multilateral index: EKS (Fisher) and CPD at the

elementary level

• In Asia most CPI uses Laspeyres with varying base years

(aggregate)

– At the elementary level: some uses geometric, harmonic or arithmetic

average

• CPI uses national expenditure weights

• ICP uses national accounts weights (in the context of

international comparison)

Table 1. Consistency of PPPs Estimated at Different Levels of Aggregation

BAN HKG IND MAL PHI SIN SRI THA SD

PPPs: single-year estimation (HKG = 1)

2005

ICP, 22 countries 108 BHs, EKS (Fisher) 3.387 1.000 2.072 0.276 3.277 0.188 5.100 2.404

8 countries, COICOP12, EKS (Törnqvist) 3.481 1.000 2.143 0.278 3.298 0.188 5.236 2.427

COICOP12-8 vs. ICP108-22 (geomean=1) 0.986 1.014 0.980 1.007 1.007 1.014 0.987 1.004 1.25%

8 countries, COICOP12, EKS (Fisher) 3.500 1.000 2.141 0.279 3.312 0.188 5.304 2.439


2011






ICP 2005 and 2011:

Consistency of Joint vs. Single-year aggregation


ICP2005, EKS, 108 BH 3.387 1.000 2.072 0.276 3.277 0.188 5.100 2.404

ICP2005, EKS, 108 BH Joint 3.287 1.000 2.025 0.273 3.201 0.187 5.019 2.387

ICP2011, EKS, 108 BH 4.281 1.000 2.586 0.270 3.188 0.191 7.099 2.181

ICP2011, EKS, 108 BH Joint 4.405 1.000 2.637 0.273 3.255 0.192 7.217 2.207

2005, Joint vs. Individual 0.985 1.015 0.992 1.003 0.991 1.009 0.999 1.007 0.96%

2011, Joint vs. Individual 1.015 0.986 1.006 0.997 1.007 0.990 1.002 0.998 0.87%

CPI vs. Implicit ICP Deflators (Joint)


CPI, official 1.678 1.176 1.655 1.177 1.329 1.197 1.774 1.199

22 countries 108 BHs, EKS (Fisher) 1.681 1.255 1.634 1.253 1.276 1.288 1.804 1.160



difference from official CPI

22 countries 108 BHs, EKS (Fisher) 1.002 1.067 0.987 1.065 0.960 1.076 1.017 0.968 4.33%

8 countries, COICOP12, EKS (Törnqvist) 0.988 1.065 0.979 1.068 0.960 1.076 1.023 0.968 4.52%

8 countries, COICOP12, EKS (Fisher) 0.982 1.065 0.983 1.065 0.957 1.067 1.019 0.966 4.40%

0.900

0.950

1.000

1.050

1.100

BAN HKG IND MAL PHI SIN SRI THA

IMPLICIT ICP DEFLATORS VS. CPI

22 countries 108 BHs, EKS (Fisher) 8 countries, COICOP12, EKS (Törnqvist)

8 countries, COICOP12, EKS (Fisher)

CPI vs. Implicit ICP Deflators

Detailed CPI

extrapolation: Eliminate

both differences in index

numbers between ICP and

CPIs and index number

differences among CPIs.

> Apply detailed CPI by 12

COICOP categories to both

benchmarks

> Compare the results to

the actual benchmarks

Table 4. ICP-CPI CONSISTENCY: EXTRAPOLATION VS. ACTUAL

BENCHMARK

extrapolation, 2011 to 2005, with CPI

components BAN HKG IND MAL PHI SIN SRI THA SD






extrapolation, 2005 to 2011, with CPI

components






Table 4. ICP-CPI Consistency: Extrapolation vs. Actual Benchmark

Precision: CPI vs. GDP (HHCE) Deflator Components

0.85

0.90

0.95

1.00

1.05

1.10

BAN HKG IND MAL PHI SIN SRI THA

Precision of Extrapolation with CPI Components

extrapolation, 2011 to 2005, with CPI components


0.9

0.95

1

1.05

1.1

1.15

HKG MAL PHI SIN THA

Precision of Extrapolation with GDP deflators


extrapolation, 2011 to 2005, with SNA components

1.1

1.15

1.2

1.25

1.3

1.35

HKG MAL PHI SIN THA

Various Measures of Inflation

international inflation (from joint 2005-2011 comparison) official CPI

CPI est. (Tornqvist) official GDP deflator

GDP deflator est. (Tornqvist)

Comparative Measures of Inflation:

CPI, GDP (HHCE) deflators, ICP implicit inflation

Summary

• The current study shows that in extrapolating ICP benchmarks

with CPIs and GDP deflators, we observe in Asia:

– Accuracy of extrapolation

• 3.4 to 4.1% (CPI components)

• 5.1% to 5.9% (with GDP (HHCE) component deflators)

– These discrepancies are irreducible further

• Two distinct clusters observed:

– Higher income showing price levels higher than predicted with the CPI;

– Lower income having price levels close to or lower than their predicted

values.

ANNEX: Case of Africa

• Time period: 2005-11

• 18 countries

• COICOP 12 (most countries)

• No joint comparison (so no direct estimate of ICP inflation)

• No GDP details (HHCE) available

0.500

1.000

2.000

4.000

ben bfa civ cmr dji gab gnb gui/gin mdg mli mrt mwi ner sen tgo tza uga zaf

Inconsistencies between CPI and PPP movements (versus geomean)

Total Household/Individual Consumption by household Food and Non-alcoholic Beverages

Alcoholic Beverages, Tobacco and Narcotics Clothing and Footwear

Housing, water, electricity, gas and other fuels Furnishings, household equipment and routine household maintenance

Health Transport

Communication Recreation and Culture

Education Restaurants and hotels

Miscellaneous Goods and Services

CPI-ICP inconsistencies, by component

CPI/ICP INCONSISTENCIES ben bfa civ cmr dji gab gnb gui/gin mdg mli mrt mwi ner sen tgo tza uga zaf max/min mean CV

Total Household/Individual Consumption by household0.967 0.875 1.100 1.029 1.063 0.966 0.991 1.122 1.273 1.062 1.105 0.844 0.940 0.975 0.963 0.961 0.951 0.901 1.5095 1.0000 10.0%

Food and Non-alcoholic Beverages 1.019 0.859 1.182 1.059 1.180 0.865 1.001 1.183 1.194 1.127 1.157 0.702 0.934 1.021 0.907 0.909 0.997 0.883 1.7015 1.0000 13.8%

Alcoholic Beverages, Tobacco and Narcotics 1.088 0.985 1.064 1.093 1.288 0.774 1.032 0.968 0.941 0.840 0.959 1.183 1.6634 1.0089 13.3%

Clothing and Footwear 0.988 0.762 0.866 0.910 0.965 1.041 1.208 1.007 1.714 0.989 1.277 0.871 1.008 0.968 1.191 0.980 1.007 0.639 2.6834 1.0000 22.3%

Housing, water, electricity, gas and other fuels 0.733 0.886 1.059 1.041 1.222 1.912 1.399 0.919 0.755 1.121 0.758 1.007 0.673 0.974 1.198 2.8389 1.0058 30.2%

Furnishings, household equipment and routine household maintenance0.866 0.937 1.120 0.893 1.102 1.134 0.855 0.797 1.514 0.956 0.922 1.006 1.126 1.007 1.055 0.974 1.184 0.780 1.9396 1.0000 16.8%

Health 0.657 0.721 1.513 0.690 1.050 0.896 0.984 1.407 2.127 1.191 0.829 0.850 1.051 1.245 0.880 0.903 3.2377 1.0111 36.0%

Transport 1.255 1.181 1.231 0.958 1.022 1.216 0.951 1.023 1.122 0.918 0.988 0.984 1.064 0.964 0.964 0.722 0.680 1.8466 1.0016 15.5%

Communication 3.498 0.799 0.909 0.513 2.270 0.850 0.578 1.063 1.720 0.629 6.8192 1.0529 86.0%

Recreation and Culture 1.015 0.880 1.190 1.186 0.799 1.264 0.810 0.699 1.621 1.187 1.011 1.092 0.945 0.877 1.106 0.938 2.3173 1.0173 21.4%

Education 0.601 1.743 1.029 0.628 0.887 0.885 0.958 0.712 1.649 0.584 2.878 1.674 0.756 0.582 1.113 1.532 4.9461 1.0147 59.1%

Restaurants and hotels 0.992 1.165 1.259 1.045 1.045 0.774 2.338 0.798 1.001 0.978 1.183 0.844 0.749 3.1226 1.0406 37.7%

Miscellaneous Goods and Services 1.185 0.807 1.286 0.756 0.809 0.647 1.599 1.176 1.378 1.098 0.814 0.918 1.079 0.819 1.023 2.4701 0.9955 25.8%

Conclusions

• The largest inconsistencies observed are for

Education (CV – 59.1%), Communication – 86%;

• Predicted vs. Benchmark ratio for Household

Consumption ranged from 84.4% to 127.3%;

• No distinct pattern or clustering observed

Documents

Consistency and Extrapolation of - Public …pubdocs.worldbank.org/en/331881487259049938/pdf/RCA03...Consistency and Extrapolation of ICP Benchmarks: The Case of Asia Yuri Dikhanov