Market Structure, Imperfect Tariff Pass-Through, and Household Welfare in Urban China
Bibliographic record
Abstract
This paper investigates the tariff pass-through mechanism and the distributional effects of trade liberalization in urban China. We study how market structure, specifically the size of the private sector, affects tariff pass-through, and how this mechanism influenced the extent to which households benefited from the trade liberalization. Our results suggest that a higher share of private sector in Chinese cities is associated with higher levels of tariff pass-through rates. This effect works both through the distribution sector, and through the production of final goods. By incorporating the changes in consumer prices of tradable and non-tradable goods, we next investigate the impact of WTO accession on household welfare through changes in the cost of consumption. The results show that WTO accession of China was associated with welfare gains to almost every household across the per capita expenditure spectrum, and that the distributional effect is strongly pro-poor. The average welfare gain of WTO accession on Chinese households is estimated to be 7.3%. The distributional effect through higher levels of privatization was also pro-poor, indicating that privatization enhanced the pro-poor impact of trade liberalization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".