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

Publikation: Working paperForskning

Standard

Estimation of Tobit Type Censored Demand Systems : A Comparison of Estimators. / Barslund, Mikkel Christoffer.

Department of Economics, University of Copenhagen, 2007.

Publikation: Working paperForskning

Harvard

Barslund, MC 2007 'Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators' Department of Economics, University of Copenhagen.

APA

Barslund, M. C. (2007). Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators. Department of Economics, University of Copenhagen.

Vancouver

Barslund MC. Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators. Department of Economics, University of Copenhagen. 2007.

Author

Barslund, Mikkel Christoffer. / Estimation of Tobit Type Censored Demand Systems : A Comparison of Estimators. Department of Economics, University of Copenhagen, 2007.

Bibtex

@techreport{0e20f6c04cc211dcbee902004c4f4f50,
title = "Estimation of Tobit Type Censored Demand Systems: A Comparison of Estimators",
abstract = " 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",
keywords = "Faculty of Social Sciences, censored demand system, Monte Carlo, quasi maximum likelihood, simulated maximum likelihood",
author = "Barslund, {Mikkel Christoffer}",
note = "JEL Classification: D12, C15, C34",
year = "2007",
language = "English",
publisher = "Department of Economics, University of Copenhagen",
address = "Denmark",
type = "WorkingPaper",
institution = "Department of Economics, University of Copenhagen",

}

RIS

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