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Estimation of simultaneous-equations models with panel data and censored endogenous variables

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Defense Thèse de doctorat : Univ. Genève, 2013 - SES 797 - 2013/03/22
Abstract In this research we develop an estimation methodology for a system of simultaneous equations where the endogenous variables are subject to censorship and where the data follows a panel structure. The likelihood function of such a model presents several complications, so that traditional optimization procedures cannot be employed. We propose the application of a simulation-based estimator that mimics the Expectation-Maximization (EM) algorithm and also inherits its likelihood-maximizing properties. Simulation exercises for both random-effects and fixed-effect models verify that this estimation methodology performs remarkably well in comparison to traditional methods, without a high cost in terms of loss of efficiency. The same idea is then extended to other types of data limitations and to a dynamic model.
Keywords Simultaneous equations modelsPanel data modelsLimited dependent variable modelSimulation methods
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URN: urn:nbn:ch:unige-283860
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CANTU-BAZALDUA, Fernando. Estimation of simultaneous-equations models with panel data and censored endogenous variables. Université de Genève. Thèse, 2013. https://archive-ouverte.unige.ch/unige:28386

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Deposited on : 2013-06-05

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