Assessing the Impact of Tax and Transfer Policies on Labour Supply: A Survey
Bibliographic record
Abstract
Changes in parameters of tax and transfer programs can induce individuals to alter their behaviour in a wide variety of ways, including changes in labour supply, in the nature of employee compensation, in the choice of working in the underground economy, in savings decisions, in human capital investments and in fertility decisions. The magnitude of these responses is of critical importance in the formulation of adequate tax and transfer policies. Thus the behavioural effects of income taxes and those implicit in means-tested transfer programs may strongly influence the impact of these policies on income, tax receipts, budgetary costs and welfare. In this paper, we abide with the tradition of evaluating the impact of tax and transfer programs on labour supply at both the extensive (the decision to work or not) and the intensive margins (the number of hours worked). We provide both a theoretical and empirical survey of the labour supply impact of tax and transfer programs. An important part of the empirical results discussed in this paper focuses on the labour supply impact of tax and transfer reforms that occurred in the US, in the UK and in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".