Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators
Publikation: Working paper › Forskning
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Estimation of Tobit Type Censored Demand Systems : A Comparison of Estimators. / Barslund, Mikkel Christoffer.
Department of Economics, University of Copenhagen, 2007.Publikation: Working paper › Forskning
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TY - UNPB
T1 - Estimation of Tobit Type Censored Demand Systems
T2 - A Comparison of Estimators
AU - Barslund, Mikkel Christoffer
N1 - JEL Classification: D12, C15, C34
PY - 2007
Y1 - 2007
N2 - Recently a number of authors have suggested to estimate censored demand systems as a system of Tobit multivariate equations employing a Quasi Maximum Likelihood (QML) estimator based on bivariate Tobit models. In this paper I study the efficiency of this QML estimator relative to the asymptotically more efficient Simulated ML (SML) estimator in the context of a censored Almost Ideal demand system. Further, a simpler QML estimator based on the sum of univariate Tobit models is introduced. A Monte Carlo simulation comparing the three estimators is performed on three different sample sizes. The QML estimators perform well in the presence of moderate sized error correlation coefficients often found in empirical studies. With absolute larger correlation coefficients, the SML estimator is found to be superior. The paper lends support to the general use of the QML estimators and points towards the use of simple etimators for more general censored systems of equations
AB - Recently a number of authors have suggested to estimate censored demand systems as a system of Tobit multivariate equations employing a Quasi Maximum Likelihood (QML) estimator based on bivariate Tobit models. In this paper I study the efficiency of this QML estimator relative to the asymptotically more efficient Simulated ML (SML) estimator in the context of a censored Almost Ideal demand system. Further, a simpler QML estimator based on the sum of univariate Tobit models is introduced. A Monte Carlo simulation comparing the three estimators is performed on three different sample sizes. The QML estimators perform well in the presence of moderate sized error correlation coefficients often found in empirical studies. With absolute larger correlation coefficients, the SML estimator is found to be superior. The paper lends support to the general use of the QML estimators and points towards the use of simple etimators for more general censored systems of equations
KW - Faculty of Social Sciences
KW - censored demand system
KW - Monte Carlo
KW - quasi maximum likelihood
KW - simulated maximum likelihood
M3 - Working paper
BT - Estimation of Tobit Type Censored Demand Systems
PB - Department of Economics, University of Copenhagen
ER -
ID: 882575