Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data
We investigate inference in semi-parametric binary regression models, y = 1(x¯ +v+² > 0) when ² is assumed uncorrelated with a set of instruments z, ² is independentof v conditionally on x and z, and the conditional support of ² is su¢ciently smallrelative to the support of v. We characterize the set of observationally equivalentparameters ¯ 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 ¯k of parameter ¯ 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 identi…cation set. Namely, the closer to uniformity thedistribution of v is, the smaller the identi…cation set is. Point identi…cation is achievedif and only if v is uniform within intervals.
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|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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