Efficient estimation of probit models with correlated errors

Maximum Likelihood (ML) estimation of probit models with correlated errors typically requires high-dimensional truncated integration. Prominent examples of such models are multinomial probit models and binomial panel probit models with serially correlated errors. In this paper we propose to use a ge...

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Veröffentlicht in:	Econometrics 2010-06, Vol.156 (2), p.367-376
Hauptverfasser:	Liesenfeld, Roman, Richard, Jean-François
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applications Correlation Correlation analysis Discrete choice Discrete choice Importance sampling Monte Carlo integration Panel data Simulated maximum likelihood Distribution theory Econometrics Estimating techniques Estimation Exact sciences and technology Importance sampling Insurance, economics, finance Mathematical analysis Mathematics Maximum likelihood method Measure and integration Model testing Monte Carlo integration Monte Carlo simulation Numerical analysis Numerical analysis. Scientific computation Numerical methods in probability and statistics Panel data Probability and statistics Sciences and techniques of general use Simulated maximum likelihood Statistics Studies
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