Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators

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  • Mikkel Christoffer Barslund
 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
Original languageEnglish
PublisherDepartment of Economics, University of Copenhagen
Number of pages22
Publication statusPublished - 2007

    Research areas

  • Faculty of Social Sciences - censored demand system, Monte Carlo, quasi maximum likelihood, simulated maximum likelihood

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