China's Prosperous Middle Class and Consumption-led Economic Growth: Lessons from Household Survey Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Can the expansion of a prosperous middle class help China to rebalance to consumption-led growth? We address this question through analysis of macro- and micro-level data. Using macro statistics, we examine trends in national aggregate consumption and GDP growth from 2000 through 2019. We observe growth in aggregate consumption but do not find convincing evidence of consumption-led growth. Using micro-level household survey data from 2002, 2007, 2013 and 2018, we estimate the size of China's prosperous middle class and its contribution to aggregate consumption growth. We find that the prosperous middle class expanded rapidly but contributed less to aggregate consumption growth than expected. We discuss features of this class that diminished its contribution to consumption-led growth, including its low propensity to consume out of income and its limited expansion beyond urban subgroups. We conclude that the expansion of the prosperous middle class is necessary but not sufficient to bring about rebalancing.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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