arXiv 4 Oct 2017 · Econometrics · 2 citations (OpenAlex)
arXiv:1710.01423 · PDF · DOI · OpenAlex · Extracted main text
This paper presents a new estimator of the intercept of a linear regression model in cases where the outcome varaible is observed subject to a selection rule. The intercept is often in this context of inherent interest; for example, in a program evaluation context, the difference between the intercepts in outcome equations for participants and non-participants can be interpreted as the difference in average outcomes of participants and their counterfactual average outcomes if they had chosen not to participate. The new estimator can under mild conditions exhibit a rate of convergence in probability equal to $n^{-p/(2p+1)}$, where $p\ge 2$ is an integer that indexes the strength of certain smoothness assumptions. This rate of convergence is shown in this context to be the optimal rate of convergence for estimation of the intercept parameter in terms of a minimax criterion. The new estimator, unlike other proposals in the literature, is under mild conditions consistent and asymptotically normal with a rate of convergence that is the same regardless of the degree to which selection depends on unobservables in the outcome equation. Simulation evidence and an empirical example are included.
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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 | Heckman (1990) `Varieties of selection bias.' American Economic Review 80, 313–318 | 1.000 | 15 | 4 | 100% |
| 2 | Andrews and Schafgans (1998) `Semiparametric estimation of the intercept of a sample selection model.' Review of Economic Studies 65, 497–517 | 0.977 | 15 | 5 | 93% |
| 3 | Lewbel (2007) `Endogenous selection or treatment model estimation.' Journal of Econometrics 141, 777–806 | 0.941 | 6 | 3 | 83% |
| 4 | Khan and Tamer (2010) `Irregular identification, support conditions, and inverse weight estimation.' Econometrica 78, 2021–2042 | 0.874 | 5 | 2 | 100% |
| 5 | Schafgans (2000) `Gender wage differences in Malaysia: Parametric and semiparametric estimation.' Journal of Development Economics 63, 351–378 | 0.693 | 7 | 1 | 100% |
| 6 | Heckman (1976) `The common structure of statistical models of truncation, sample selection and limited dependent variables, and a simple estima… | 0.644 | 2 | 2 | 100% |
| 7 | Heckman (1979) `Sample selection bias as a specification error.' Econometrica 47, 153–161 | 0.644 | 2 | 2 | 100% |
| 8 | Khan and Nekipelov (2013) `On uniform inference in nonlinear models with endogeneity.' Unpublished paper | 0.644 | 2 | 2 | 100% |
| 9 | Klein and Spady (1993) `An efficient semiparametric estimator for binary response models.' Econometrica 61, 387–421 | 0.644 | 2 | 2 | 100% |
| 10 | Oaxaca (1973) `Male-female wage differentials in urban labor markets.' International Economic Review 14, 693–709 | 0.644 | 2 | 2 | 100% |
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