Global Purchasing Power Parities and Real Expenditures : 2005 International Comparison Program
Bibliographic record
Abstract
The International Comparison Program (ICP) is a worldwide statistical initiative to collect comparative price data and estimate purchasing power parities (PPPs) of the world's economies. Using PPPs instead of market exchange rates to convert currencies makes it possible to compare the output of economies and the welfare of their inhabitants in real terms (that is, controlling for differences in price levels). This report brings together the results of two separate PPP programs. The first is the global ICP program conducted by the ICP global office within the World Bank, which provided overall coordination for the collection of data and calculation of PPPs in more than 100 (mostly developing) economies. The program was organized into five geographic areas: Africa, Asia-Pacific, Commonwealth of Independent States, South America, and Western Asia. Regional agencies took the lead in coordinating the work in the five regions. In parallel, the Statistical Office of the European Communities (Eurostat) and the Organization for Economic Co-operation and Development (OECD) conducted their 2005 PPP program, which comprised 46 economies. Eurostat covered 37 economies: the 25 European Union (EU) member states; the European Free Trade Association (EFTA) economies (Iceland, Norway, and Switzerland); and Albania, Bosnia-Herzegovina, Bulgaria, Croatia, Macedonia, Montenegro, Romania, Serbia, and Turkey. The OECD part of the program included 9 other economies: Australia, Canada, Israel, Japan, the Republic of Korea, Mexico, New Zealand, the Russian Federation, and the United States. The main reasons for conducting the ICP on a regional basis are that the products to be priced are more homogeneous within regions, the expenditure patterns are likely to be more similar, and language differences are reduced. Moreover, dividing the ICP organization among a number of regional offices in relatively close proximity to the economies they are coordinating provides operational benefits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.030 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".