Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators
AbstractRecently 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.
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Bibliographic InfoPaper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 07-16.
Length: 14 pages
Date of creation: Aug 2007
Date of revision:
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censored demand system; Monte Carlo; quasi maximum likelihood; simulated maximum likelihood;
Find related papers by JEL classification:
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
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