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

Identification & Information in Monotone Binary Models

Contents:

Author Info

  • Thierry Magnac
  • Eric Maurin

    ()

Abstract

Let, y, a binary outcome, v a continuous explanatory variable and x some other explanatory variables. We study inference on the parameter b of the semiparametric binary regression model y=1(xb+v+e>0). We show that the set-up introduced by Lewbel (2000) that is, an uncorrelated-error restriction (E(x'e)=0) combined with a partial-independance assumption (F(e/v,x)=F(e/x)) and a large support assumption (Supp(-xb-e) c Supp(v)) provides exact identification of b and F(e/x). The two restrictions that the population distribution of the random variable w=(y,v,x) should satisfy are Monotone (1) and Large Support (2) conditions: (1) E(y/v,x) is monotone in v and (2) E(y/v,x) varies from 0 to 1 when v varies over its support. Moreover, we show that Lewbel's moment estimator attains the semi-parametric efficiency bound in the set of latent models that he considers. Yet, the uncorrelated-error and partial-independence assumptions are not sufficient to identify b when the support of v is not sufficiently rich. We propose intuitive additional restrictions on the tails of the conditional distribution of e under which b remains exactly identified even when condition(2) is not satisfied. In such a case, Monte-Carlo experiments show that the estimation performs well in moderately small samples. An extension to ordered choice models is provided.

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.inra.fr/Internet/Departements/ESR/UR/lea/documents/wp/wp0309.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Laboratoire d'Economie Appliquee, INRA in its series Research Unit Working Papers with number 0309.

as in new window
Length: 53 pages
Date of creation: Jun 2003
Date of revision:
Handle: RePEc:lea:leawpi:0309

Contact details of provider:
Postal: INRA-LEA, 48, Boulevard Jourdan, 75014 Paris, France
Phone: 331 43136364
Fax: 331 43136362
Web page: http://www.inra.fr/Internet/Departements/ESR/UR/lea/index.html

Related research

Keywords: Binary models; semiparametric methods; efficiency bounds;

Other versions of this item:

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. Lewbel, Arthur, 2007. "Endogenous selection or treatment model estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 777-806, December.
  2. Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
  3. Songnian Chen & Shakeeb Khan & Xun Tang, 2013. "Informational Content of Special Regressors in Heteroskedastic Binary Response Models," PIER Working Paper Archive 13-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  4. Lewbel, Arthur & Schennach, Susanne M., 2007. "A simple ordered data estimator for inverse density weighted expectations," Journal of Econometrics, Elsevier, vol. 136(1), pages 189-211, January.
  5. Stewart, Mark B., 2005. "A comparison of semiparametric estimators for the ordered response model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 555-573, April.

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:lea:leawpi:0309. 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: (Madeleine Roux) The email address of this maintainer does not seem to be valid anymore. Please ask Madeleine Roux to update the entry or send us the correct address.

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.