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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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:
Contact details of provider:
Postal: Øster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark
Phone: (+45) 35 32 30 10
Fax: +45 35 32 30 00
Web page: http://www.econ.ku.dk
More information through EDIRC
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
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Brown, Sarah & Harris, Mark N. & Taylor, Karl, 2012.
"Modelling charitable donations to an unexpected natural disaster: Evidence from the U.S. Panel Study of Income Dynamics,"
Journal of Economic Behavior & Organization,
Elsevier, vol. 84(1), pages 97-110.
- Sarah Brown & Mark N. Harris & Karl Taylor, 2009. "Modelling Charitable Donations to an Unexpected Natural Disaster: Evidence from the U.S. Panel Study of Income Dynamics," Working Papers 2009015, The University of Sheffield, Department of Economics, revised Sep 2009.
- Brown, Sarah & Harris, Mark N. & Taylor, Karl, 2009. "Modelling Charitable Donations to an Unexpected Natural Disaster: Evidence from the U.S. Panel Study of Income Dynamics," IZA Discussion Papers 4424, Institute for the Study of Labor (IZA).
- VERHEYDEN Bertrand & FAYE Ousmane, 2011. "Fertility and Child Occupation: Theory and Evidence from Senegal," CEPS/INSTEAD Working Paper Series 2011-59, CEPS/INSTEAD.
- Kuhlgatz, Christian & Abdulai, Awudu & Barrett, Christopher B., 2009. "Food Aid Allocation Policies: Donor Coordination and Responsiveness to the Needs of Recipient Countries," 2009 Conference, August 16-22, 2009, Beijing, China 51686, International Association of Agricultural Economists.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Hoffmann).
If references are entirely missing, you can add them using this form.