Advanced Search
MyIDEAS: Login

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

Contents:

Author Info

  • Mikkel Barslund

    (Department of Economics, University of Copenhagen)

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.

Download Info

If 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.
File URL: http://www.econ.ku.dk/english/research/publications/wp/2007/0716.pdf/
Download Restriction: no

Bibliographic Info

Paper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 07-16.

as in new window
Length: 14 pages
Date of creation: Aug 2007
Date of revision:
Handle: RePEc:kud:kuiedp:0716

Contact details of provider:
Postal: Ă˜ster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark
Phone: (+45) 35 32 30 10
Fax: +45 35 32 30 00
Email:
Web page: http://www.econ.ku.dk
More information through EDIRC

Related research

Keywords: censored demand system; Monte Carlo; quasi maximum likelihood; simulated maximum likelihood;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. 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.
  2. VERHEYDEN Bertrand & FAYE Ousmane, 2011. "Fertility and Child Occupation: Theory and Evidence from Senegal," CEPS/INSTEAD Working Paper Series 2011-59, CEPS/INSTEAD.
  3. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:kud:kuiedp:0716. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Hoffmann).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.