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Multiplicative-error models with sample selection

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  • Koen Jochmans

    (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper presents simple approaches to deal with sample selection in models with multiplicative errors. GMM estimators are constructed for both cross-section data and for panel data. These estimators build only on a specification of the conditional mean of the outcome of interest and are, therefore, semiparametric in nature. In particular, the distribution of unobservables is left unspecified. In the panel-data case, we further allow for group-specific fixed effects whose relation to covariates is left unrestricted. We derive distribution theory for both sampling situations and present Monte Carlo evidence on the finite-sample performance of the approach.

Suggested Citation

  • Koen Jochmans, 2014. "Multiplicative-error models with sample selection," Working Papers hal-00987290, HAL.
  • Handle: RePEc:hal:wpaper:hal-00987290
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-00987290
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    Cited by:

    1. Koen Jochmans & Vincenzo Verardi, 2022. "Instrumental‐variable estimation of exponential‐regression models with two‐way fixed effects with an application to gravity equations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1121-1137, September.
    2. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    3. Chirok Han & Goeun Lee, 2017. "Efficient Estimation of Linear Panel Data Models with Sample Selection and Fixed Effects," Discussion Paper Series 1707, Institute of Economic Research, Korea University.
    4. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2021. "Intercept Estimation in Nonlinear Selection Models," IZA Discussion Papers 14364, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    nonlinear model; sample selection; semiparametric inference; two-stage estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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