Bibliographic record
Abstract
Currently proposals are actively circulating in China to move to a unified enterprise tax structure with similar tax treatment of state-owned enterprises (SOEs), other private enterprises (OPE) and foreign investment enterprises (FIEs).FIEs presently receive significant tax preferences through a sharply lower tax rate, tax holidays and other provisions.Here we use analytical representations of SOE behavior, which differ from that of the competitive firm, to argue that a unified tax structure may not be a desirable tax change and that typically a higher tax rate on SOEs is called for on efficiency grounds.Using a worker control model with endogenously determined shirking, taxes on SOEs reduce shirking and a reduced SOE tax rate under a unified tax relaxes discipline on SOEs and losses result.Our results indicate a 0.26% of GDP welfare loss using 2004 data from a unified tax, and larger loss relative to an optimal tax scheme.Alternatively, if we use a managerial control model variant, we find a 0.19% welfare loss from a unified tax, and larger losses relative to initial higher SOE tax rates.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".