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Simulated multivariate random-effects probit models for unbalanced panels

Author

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  • Alexander Plum

    (Otto von Guericke University Magdeburg)

Abstract

This article develops a method for implementing a simulated multivariate random-effects probit model for unbalanced panels (with gaps) and illustrates the model by using artificial data. Halton draws generated by mdraws are used to simulate multivariate normal probabilities with the mvnp() egen function. The estimator can be easily adjusted, for example, to allow for autocorrelated errors. The advantages of this simulated estimation, when compared with existing commands such as redpace, are high accuracy and improved stability. Copyright 2014 by StataCorp LP.

Suggested Citation

  • Alexander Plum, 2014. "Simulated multivariate random-effects probit models for unbalanced panels," Stata Journal, StataCorp LLC, vol. 14(2), pages 259-279, June.
    • Handle: RePEc:tsj:stataj:v:14:y:2014:i:2:p:259-279
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    Cited by:

    1. Ricardo Goncalves & Peter J. Simmons & Yuanyuan Xie, 2017. "Rebel with(out) a cause? Inter-generational smoking dependence in Chinese households," Discussion Papers 17/20, Department of Economics, University of York.
    2. Alexander Plum, 2019. "The British low-wage sector and the employment prospects of the unemployed," Applied Economics, Taylor & Francis Journals, vol. 51(13), pages 1411-1432, March.
    3. Federico Antonioli & Simone Severini & Mauro Vigani, 2023. "Visa for competitiveness: foreign workforce and Italian dairy farms’ performance," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(1), pages 115-150.

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