Advanced Search
MyIDEAS: Login to save this paper or follow this series

Tobit Model with Covariate Dependent Thresholds

Contents:

Author Info

  • Yasuhiro Omori

    (Faculty of Economics, University of Tokyo)

  • Koji Miyawaki

    (Graduate School of Economics, University of Tokyo)

Abstract

Tobit models are extended to allow threshold values which depend on individuals' characteristics. In such models, the parameters are subject to as many inequality constraints as the number of observations, and the maximum likelihood estimation which requires the numerical maximisation of the likelihood is often difficult to be implemented. Using a Bayesian approach, a Gibbs sampler algorithm is proposed and, further, the convergence to the posterior distribution is accelerated by introducing an additional scale transformation step. The procedure is illustrated using the simulated data, wage data and prime rate changes data.

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.cirje.e.u-tokyo.ac.jp/research/dp/2008/2008cf594.pdf
Download Restriction: no

Bibliographic Info

Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-594.

as in new window
Length: 26pages
Date of creation: Oct 2008
Date of revision:
Handle: RePEc:tky:fseres:2008cf594

Contact details of provider:
Postal: Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033
Phone: +81-3-5841-5644
Fax: +81-3-5841-8294
Email:
Web page: http://www.cirje.e.u-tokyo.ac.jp/index.html
More information through EDIRC

Related research

Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Martijn G. De Jong & Jan-Benedict E. M. Steenkamp & Jean-Paul Fox, 2007. "Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT Model," Journal of Consumer Research, University of Chicago Press, vol. 34(2), pages 260-278, 06.
  2. Melenberg, B. & Van Soest, A., 1991. "Parametric and Semi-parametric Modelling of Vocation Expenditures," Papers 9144, Tilburg - Center for Economic Research.
  3. Wayne S. DeSarbo & Vithala R. Rao & Joel H. Steckel & Jerry Wind & Richard Colombo, 1987. "A Friction Model for Describing and Forecasting Price Changes," Marketing Science, INFORMS, vol. 6(4), pages 299-319.
  4. Mroz, Thomas A, 1987. "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," Econometrica, Econometric Society, vol. 55(4), pages 765-99, July.
  5. Forbes, Shawn M. & Mayne, Lucille S., 1989. "A friction model of the prime," Journal of Banking & Finance, Elsevier, vol. 13(1), pages 127-135, March.
  6. Yasuhiro Omori, 2007. "Efficient Gibbs Sampler for Bayesian Analysis of a Sample Selection Model," CIRJE F-Series CIRJE-F-481, CIRJE, Faculty of Economics, University of Tokyo.
  7. Charemza, Wojciech W. & Majerowska, Ewa, 2000. "Regulation of the Warsaw Stock Exchange: The portfolio allocation problem," Journal of Banking & Finance, Elsevier, vol. 24(4), pages 555-576, April.
  8. Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-44, September.
  9. Christofides, Louis N. & Li, Dingding, 2005. "Nominal and real wage rigidity in a friction model," Economics Letters, Elsevier, vol. 87(2), pages 235-241, May.
  10. Congdon, P., 2005. "Bayesian predictive model comparison via parallel sampling," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 735-753, April.
  11. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649 Elsevier.
  12. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
  13. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
  14. Hill, Daniel H, 1987. "Derived Demand Estimation with Survey Experiments: Commercial Electric Vehicles," The Review of Economics and Statistics, MIT Press, vol. 69(2), pages 277-85, May.
  15. Lin, Tsai-Fen & Schmidt, Peter, 1984. "A Test of the Tobit Specification against an Alternative Suggested by Cragg," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 174-77, February.
  16. Thomas Zuehlke, 2003. "Estimation of a Tobit model with unknown censoring threshold," Applied Economics, Taylor & Francis Journals, vol. 35(10), pages 1163-1169.
  17. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
  18. Timothy Johnson, 2003. "On the use of heterogeneous thresholds ordinal regression models to account for individual differences in response style," Psychometrika, Springer, vol. 68(4), pages 563-583, December.
Full references (including those not matched with items on IDEAS)

Citations

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

Cited by:
  1. Wichitaksorn, Nuttanan & Tsurumi, Hiroki, 2013. "Comparison of MCMC algorithms for the estimation of Tobit model with non-normal error: The case of asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 226-235.

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:tky:fseres:2008cf594. 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: (CIRJE administrative office).

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.