Measuring Income Tax Evasion Using Bank Credit: Evidence from Greece *
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 We document that in semiformal economies, banks lend to tax-evading individuals based on the bank’s assessment of the individual’s true income. This observation leads to a novel approach to estimate tax evasion. We use microdata on household credit from a Greek bank and replicate the bank underwriting model to infer the banks estimate of individuals’ true income. We estimate that 43–45% of self-employed income goes unreported and thus untaxed. For 2009, this implies €28.2 billion of unreported income, implying forgone tax revenues of over €11 billion or 30% of the deficit. Our method innovation allows for estimating the industry distribution of tax evasion in settings where uncovering the incidence of hidden cash transactions is difficult using other methods. Primary tax-evading industries are professional services—medicine, law, engineering, education, and media. We conclude with evidence that contemplates the importance of institutions, paper trail, and political willpower for the persistence of tax evasion.
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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 | 0.001 |
| 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