Do Political Connections Weaken Tax Enforcement Effectiveness?
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 This paper examines whether ties to politicians by corporate boards of directors weaken the effectiveness of tax authorities in constraining tax avoidance in China. We use a unique data set to measure geographic time‐variant tax enforcement, including the probability of income tax audit, the expertise of tax officers, and the consequences of underreporting tax liabilities. Based on a sample of 11,121 firm‐years from 2003 to 2013, we find that the deterrent effect of the probability that a firm's taxable income understatement will be detected and lead to heavy penalties is significantly undermined if the board is politically connected. To enhance our analysis, we use opportunities for income shifting, the most likely mechanism through which Chinese firms avoid taxes on an ongoing basis, to illustrate how connected boards exert power to unwind the constraining effect of tax enforcement. Overall, our results suggest that a board's ties to politicians can be a significant challenge to the effective enforcement of tax compliance in a politically controlled economy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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