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

Diplôme Thèse Estimation of simultaneous-equations models with panel data and censored endogenous variables eng 2013-03-22 author Cantu-Bazaldua Fernando 560092 director Krishnakumar Jaya 26462 10.13097/archive-ouverte/unige:28386 urn:nbn:ch:unige-283860 SES 797 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. Simultaneous equations models Panel data models Limited dependent variable model Simulation methods Dewey 330 Dewey 330/650 9 Faculté d'économie et de management S false d5969648-d3f4-41b3-87b3-c33f7f0c3003 Thesis Public Cantu.pdf 1185184 application/pdf openAccess Faculté d'économie et de management

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Cantu-Bazaldua, Fernando