Spatial Price Differences in China: Estimates and Implications
Bibliographic record
Abstract
Prices differ across space: from province to province, from rural (or urban) areas in one province to rural (or urban) areas in another province, and from rural to urban areas within one province. Systematic differences in prices across a range of goods and services in different localities imply regional differences in the costs of living. If high-income provinces also have high costs of living, and low-income provinces have low costs of living, the use of nominal income measures in explaining such economic outcomes as inequality can lead to misinterpretations. Income should be adjusted for costs of living. We are interested in the sign and magnitude of the adjustments needed, their changes over time, and their impact on economic outcomes in China. In this article, we construct a set of (rural, urban, total) provincial-level spatial price deflators for the years 1984-2002 that can be used to obtain provincial-level income measures adjusted for purchasing power. We provide illustrations of the significant effect of ignoring spatial price differences in the analysis of China’s economy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".