Partial independence in nonseparable models

Matthew Masten and Alexandre Poirier

No CWP26/16, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: We analyze identi cation of nonseparable models under three kinds of exogeneity assumptions weaker than full statistical independence. The first is based on quantile independence. Selection on unobservables drives deviations from full independence. We show that such deviations based on quantile independence require non-monotonic and oscillatory propensity scores. Our second and third approaches are based on a distance-from-independence metric, using either a conditional cdf or a propensity score. Under all three approaches we obtain simple analytical characterizations of identi ed sets for various parameters of interest. We do this in three models: the exogenous regressor model of Matzkin (2003), the instrumental variable model of Chernozhukov and Hansen (2005), and the binary choice model with nonparametric latent utility of Matzkin (1992).

Keywords: Nonparametric Identi cation; Partial Identi cation; Sensitivity Analysis; Nonseparable Models; Selection on Unobservables; Instrumental Variables; Binary Choice (search for similar items in EconPapers)
JEL-codes: C14 C21 C25 C26 C51 (search for similar items in EconPapers)
Date: 2016-06-21
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-ger
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Citations: View citations in EconPapers (9)

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Working Paper: Partial independence in nonseparable models (2016)
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