arXiv 29 Aug 2025 · Econometrics
arXiv:2508.21583 · PDF · DOI · OpenAlex · Extracted main text
This paper develops a framework for identifying treatment effects when a policy simultaneously alters both the incentive to participate and the outcome of interest -- such as hiring decisions and wages in response to employment subsidies; or working decisions and wages in response to job trainings. This framework was inspired by my PhD project on a Belgian reform that subsidised first-time hiring, inducing entry by marginal firms yet meanwhile changing the wages they pay. Standard methods addressing selection-into-treatment concepts (like Heckman selection equations and local average treatment effects), or before-after comparisons (including simple DiD or RDD), cannot isolate effects at this shifting margin where treatment defines who is observed. I introduce marginality-weighted estimands that recover causal effects among policy-induced entrants, offering a policy-relevant alternative in settings with endogenous selection. This method can thus be applied widely to understanding the economic impacts of public programmes, especially in fields largely relying on reduced-form causal inference estimation (e.g. labour economics, development economics, health economics).
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Rosenbaum, P. R. and D. B. Rubin (1983) The central role of the propensity score in observational studies for causal effects | 0.644 | 2 | 2 | 100% |
| 2 | Heckman, J. J. and E. J. Vytlacil (2005) Structural equations, treatment effects, and econometric policy evaluation | 0.511 | 2 | 2 | 50% |
| 3 | Abadie, A. and G. W. Imbens (2006) Large sample properties of matching estimators for average treatment effects | 0.405 | 1 | 1 | 100% |
| 4 | Branstetter, L., F. Lima, L. J. Taylor, and A. Venâncio (2014) Do entry regulations deter entrepreneurship and job creation? Evidence from recent reforms in Portugal | 0.405 | 1 | 1 | 100% |
| 5 | Deng, H. and G. Bijnens (2025) A theory of new employer entry: Entrepreneurial decision under uncertainty self | 0.405 | 1 | 1 | 100% |
| 6 | Heckman, J. J., H. Ichimura, and P. E. Todd (1997, 10) (1997) Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme | 0.405 | 1 | 1 | 100% |
| 7 | Hirano, K., G. W. Imbens, and G. Ridder (2003) Efficient estimation of average treatment effects using the estimated propensity score | 0.405 | 1 | 1 | 100% |
| 8 | Hombert, J., A. Schoar, D. Sraer, and D. Thesmar (2020) Can unemployment insurance spur entrepreneurial activity? Evidence from France | 0.405 | 1 | 1 | 100% |
| 9 | Imbens, G. W. and J. D. Angrist (1994) Identification and estimation of local average treatment effects | 0.405 | 1 | 1 | 100% |
| 10 | Imbens, G. W (2004) Nonparametric estimation of average treatment effects under exogeneity: A review | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 13 scored citations.