Multiplicative-error models with sample selection
This paper presents a simple approach to deal with sample selection in models with multiplicative errors. Models for non-negative limited dependent variables such as counts fit this framework. The approach builds on a specification of the conditional mean of the outcome only and is, therefore, semip...
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| Veröffentlicht in: | Journal of econometrics 2015-02, Vol.184 (2), p.315-327 |
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| container_title | Journal of econometrics |
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| creator | Jochmans, Koen |
| description | This paper presents a simple approach to deal with sample selection in models with multiplicative errors. Models for non-negative limited dependent variables such as counts fit this framework. The approach builds on a specification of the conditional mean of the outcome only and is, therefore, semiparametric in nature. GMM estimators are constructed for both cross-section data and for panel data. We derive distribution theory and present Monte Carlo evidence on the finite-sample performance of the estimators. |
| doi_str_mv | 10.1016/j.jeconom.2014.09.011 |
| format | Article |
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| ispartof | Journal of econometrics, 2015-02, Vol.184 (2), p.315-327 |
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| language | eng |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Count data Distribution Econometrics Economic models Economic theory Economics and Finance Error Fixed-effect model Generalized method of moments Humanities and Social Sciences Monte Carlo simulation Nonlinear model Panel data Sample selection Semiparametric inference Studies Two-stage estimation |
| title | Multiplicative-error models with sample selection |
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