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Intercept estimation in nonlinear selection models
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Arulampalam, Wiji, Corradi, Valentina and Gutknecht, Daniel (2023) Intercept estimation in nonlinear selection models. Econometric Theory . 1-53 . doi:10.1017/S0266466623000105 ISSN 0266-4666. (In Press)
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Official URL: https://doi.org/10.1017/S0266466623000105
Abstract
We propose various semiparametric estimators for nonlinear selection models, where slope and intercept can be separately identified. When the selection equation satisfies a monotonic index restriction, we suggest a local polynomial estimator, using only observations for which the marginal cumulative distribution function of the instrument index is close to one. Data-driven procedures such as cross-validation may be used to select the bandwidth for this estimator. We then consider the case in which the monotonic index restriction does not hold and/or the set of observations with a propensity score close to one is thin so that convergence occurs at a rate that is arbitrarily close to the cubic rate. We explore the finite sample behavior in a Monte Carlo study and illustrate the use of our estimator using a model for count data with multiplicative unobserved heterogeneity.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | H Social Sciences > HB Economic Theory | ||||||
| Divisions: | Faculty of Social Sciences > Economics | ||||||
| Library of Congress Subject Headings (LCSH): | Parameter estimation, Economics -- Statistical methods, Nonparametric statistics, Regression analysis | ||||||
| Journal or Publication Title: | Econometric Theory | ||||||
| Publisher: | Cambridge University Press | ||||||
| ISSN: | 0266-4666 | ||||||
| Official Date: | 24 April 2023 | ||||||
| Dates: |
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| Page Range: | 1-53 | ||||||
| DOI: | 10.1017/S0266466623000105 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 14 March 2023 | ||||||
| Date of first compliant Open Access: | 14 March 2023 | ||||||
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