The Evolution of Income Inequality in Rural China
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Bibliographic record
Abstract
with an emphasis on investigating increases in inequality associated with transition and economic development. With a backdrop of perceived improvements in average living standards, we ask whether increases of inequality may have offset, or even threaten welfare gains associated with economic reforms. The centerpiece of the paper is an empirical analysis based on a set of household surveys conducted by the China’s Research Center for Rural Economy (RCRE) in Beijing. These surveys permit us to construct a set of comparable estimates of household income and consumption from a panel of over 100 villages from nine Chinese provinces. We provide a variety of summary statistics, including Gini coefficients, as well as more nonparametric summaries of the income distribution (i.e., Lorenz curves). In addition, we decompose the sources of inequality, exploring the contributions of spatial inequality to overall inequality, and the role of non-agricultural incomes in explaining rising dispersion of incomes. We find that the distribution of income improved by most measures during the early part of the period, as average incomes rose substantially with only a modest increase in inequality. However, the distribution has worsened significantly since 1995, with rising inequality, and falling absolute incomes, especially at the bottom end of the income distribution. We attribute most of the recent decline in welfare to collapsing agricultural incomes, probably brought about by lower farm prices. At the same time,
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it