Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data
AbstractWe investigate inference in semi-parametric binary regression models, y = 1(xÂ¯ +v+Â² > 0) when Â² is assumed uncorrelated with a set of instruments z, Â² is independentof v conditionally on x and z, and the conditional support of Â² is suÂ¢ciently smallrelative to the support of v. We characterize the set of observationally equivalentparameters Â¯ when interval data only are available on v or when v is discrete. Whenthere exist as many instruments z as variables x, the sets within which lie the scalarcomponents Â¯k of parameter Â¯ can be estimated by simple linear regressions. Also, inthe case of interval data, it is shown that additional information on the distribution ofv within intervals shrinks the identiâ¦cation set. Namely, the closer to uniformity thedistribution of v is, the smaller the identiâ¦cation set is. Point identiâ¦cation is achievedif and only if v is uniform within intervals.
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Bibliographic InfoPaper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 280.
Date of creation: Sep 2004
Date of revision: Jan 2005
Publication status: Published in The Review of Economic Studies, vol.�75, n°3, juillet 2008, p.�835-864.
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Other versions of this item:
- Thierry Magnac & Eric Maurin, 2008. "Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data," Review of Economic Studies, Oxford University Press, vol. 75(3), pages 835-864.
- Thierry Magnac & Eric Maurin, 2004. "Partial Identification in Monotone Binary Models : Discrete Regressors and Interval Data," Working Papers 2004-11, Centre de Recherche en Economie et Statistique.
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