Estimating Dynamic Binary Panel Data Model with Random Effects: A Computational Note

Gang Yu (), Wei Gao, Weiguo Wang and Shaoping Wang
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Gang Yu: Dongbei University of Finance and Economics
Weiguo Wang: Dongbei University of Finance and Economics
Shaoping Wang: Huazhong University of Science and Technology

Computational Economics, 2018, vol. 51, issue 3, No 8, 535-539

Abstract: Abstract Recently, Gao et al. (J Time Ser Anal, 2016 doi: 10.1111/jtsa.12178 ) propose a new estimation method for dynamic panel probit model with random effects, where the theoretical properties of estimator are derived. In this paper, we extend their estimation method to the $$T\ge 3$$ T ≥ 3 case, and some Monte Carlo simulations are presented to illustrate the extended estimator.

Keywords: Binary panel data; Random effects; Probit model; Maximum likelihood estimator (MLE) (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10614-016-9620-1

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