International Comparison Program

1. International Comparison Program International Comparison Program - 2005 Round FV comments to ITAG—Feb 2009

2. Overview • Summary of methodology used in ICP 2005 • Reflections • Regions • National vs Urban/Rural • Ring

3. Scope and Coverage of Data Collection - Asia W. Asia Africa Latin CIS America Eurostat Ring Category OECD Food and non - alcoholic beverages 356 223 198 422 147 353 281 Alcoholic beverages and tobacco 41 19 20 72 8 21 30 Clothing and footwear 128 78 104 319 136 162 132 Housing and utilities 21 17 22 64 18 12 35 Furnishing and household equipment 95 85 91 460 77 83 124 Health 144 112 75 244 51 69 162 Transportation 55 65 47 365 33 29 96 Communication 19 19 16 81 8 12 28 Recreation and Culture 49 70 79 336 54 59 96 7 Education 7 7 7 5 10 11 60 Restaurants* 51 25 45 117 14 20 Misc. goods and services . 34 56 36 136 22 31 44 Total consumption 1000 776 740 2621 578 862 1095 General Government 50 50 50 50 50 Construction 34 34 34 34 34 Equipment 108 108 108 108 108

4. Diversity of regions required different methods • Five regions • (plus Eurostat-OECD) • Have different: • Economies (size, structure) • Statistical capacity • Methodologies Africa Asia CIS South America Western Asia Eurostat-OECD

5. Comparison of Methodology

6. Reflections--Workload • There is a limit to what countries can do at one time • Shop items in 2005—2-4 collections • Construction, equipment, gov’t and ring in 2006 • Can # of products be reduced? • Can scope of coverage be reduced? • Assess quality trade off from number of collections vs. number of products?

7. Reflections--Representativity • Representative product is representative of all products in the BH and has a representative price???? Was not understood • Instead, can more flexibility be added to price collection for coding? • Price determining characteristics • Outlet type • Outlet location • Loosen specs—add coding characteristics?

8. Reflections—Aggregation to BH • CPD vs EKS? • CPD more robust • CPD provided Dikhanov tables showing structure of variability

9. Back Data Validation - Prices From Dikhanov Tables 2 3 4 5 6 7 8 9 1 2 3 4 5 6 7 8 9 1

10. Reflections--Housing • Learn from how regions were linked—CPD with quantity and quality indicators for 106 countries • Start process much earlier with review of national accounts • Eurostat-OECD and CIS provide same quantity/quality data for all countries? • Two stage estimation—Quantity for all—rents where available?

11. Reflections--Compensation • Global specs developed—Eurostat/OECD use? CIS use? • Data quality—multiple data collections? • Productivity—evaluate for all regions--review alternatives • Subregions of like countries within regions • Create subregions of like countries across regions

12. Reflections--Equipment • Equipment—was everything priced sold? • Number of items? • Specifications reflect developing country purchases? • Harmonize with Eurostat-OECD-CIS? • Give modified X-rates another consideration

13. Reflections—Basket of construction components

14. Reflections-Construction • Basket of Construction Components • Composite vs basic inputs—data quality • Weights needed—should more than one set of weights be provided; for example, for more than one kind of residentual building? • Can more use be made of basic components? • Harmonize with CIS/BOQ?

15. Reflections—Urban vs Rural • What is rural? • Share of rural population in France • 27 % using French definition • 30% using Spanish definition • 51 % using Italian definition • Only 18% of Dutch population live in urban areas • What is urban/rural boundary? • Some rural in commuting range of large urban area

16. Reflections—urban vs rural • Definitions vary significantly • Price variability depends on geographic dispersion rather than urban/rural • Issue should be whether need a national price or capital or primary city prices • ICP designed to provide PPPs to compare the GDP. • Need separate survey measuring what the poor purchase?

17. Reflections--Expenditures • Start tomorrow to review national accounts • !55 Basic headings needed? • What about NPISH—own consumption?

18. Reflections--Ring • Can a core ring list be subset of regional lists? • Can more price determining characteristics be obtained during data collection of regional data? • Can these be used to identify core products to become the ring list? • Can/should the Eurostat-OECD also use the SPD/PS? • What is the optimum number of ring countries?

19. Reflections—regional and linking • Should countries be grouped by economic similarities vs geographic location for global volumes? • Should be global volumes be first estimated, then distributed to geographic regions and/or economic regions?

20. Linking Factors – Numerical Example 1. 4. 5. 6. 2. 3. Base Country for Region I For the ICP: US Base Region For the ICP: OECD

21. Regional Price Level Indices and linking Regional Price Level Indices (US = 100) for each level of aggregation

22. Conclusions • Most intensive effort ever to measure PPPs across countries: • New methodology; • Improved data collection and processing; • Intensive data validation; • Inclusion of China and India plus better coverage of Africa has given widest coverage ever. • However, more to improve • Need to include more countries

23. Success from Partnerships Thanks to the Technical Advisory Group and looking forward to future efforts