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Partial independence in nonseparable models
Masten, Matthew A.; Poirier, Alexandre - 2016
We analyze identification 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...
Persistent link: https://www.econbiz.de/10011594336
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Endogenous semiparametric binary choice models with heteroscedasticity
Hoderlein, Stefan - 2009
In this paper we consider endogenous regressors in the binary choice model under a weak median exclusion restriction, but without further specification of the distribution of the unobserved random components. Our reduced form specification with heteroscedastic residuals covers various...
Persistent link: https://www.econbiz.de/10010288422
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Nonparametric identification in nonseparable panel data models with generalized fixed effects
Hoderlein, Stefan; White, Halbert - 2009
well known objects like the slope coefficient in the semiparametric panel data binary choice model with fixed effects. We …
Persistent link: https://www.econbiz.de/10010288425
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Identification in a binary choice panel data model with a predetermined covariate
Bonhomme, Stéphane; Dano, Kevin; Graham, Bryan S. - 2023
We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a …
Persistent link: https://www.econbiz.de/10014480540
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Misclassification and the hidden silent rivalry
Hu, Yingyao; Lin, Zhongjian - 2018
The interaction of economic agents is one of the most important elements in economic analyses. While most empirical studies investigate peer effects on objective final achievements, peer effects on subjective outcomes are inherently difficult to identify and estimate because these variables are...
Persistent link: https://www.econbiz.de/10011941440
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Nonseparable multinomial choice models in cross-section and panel data
Chernozhukov, Victor; Fernández-Val, Iván; Newey, … - 2017
attributes and multidimensional unobserved heterogeneity with cross-section and panel data. We show that derivatives of choice … identification results to models with endogenous heterogeneity using either a control function or panel data. In time stationary … panel models with two periods, we find that differences over time of derivatives of choice probabilities identify utility …
Persistent link: https://www.econbiz.de/10011941481
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Best subset binary prediction
Chen, Le-yu; Lee, Sokbae - 2017
We consider a variable selection problem for the prediction of binary outcomes. We study the best subset selection procedure by which the explanatory variables are chosen by maximizing Manski (1975, 1985)'s maximum score type objective function subject to a constraint on the maximal number of...
Persistent link: https://www.econbiz.de/10011941515
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Identification in dynamic binary choice models
Chamberlain, Gary - 2023
This paper studies identification in a binary choice panel data model with choice probabilities depending on a lagged …
Persistent link: https://www.econbiz.de/10014480457
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Asymptotic properties for a class of partially identified models
Beresteanu, Arie; Molinari, Francesca - 2006
We propose inference procedures for partially identified population features for which the population identification region can be written as a transformation of the Aumann expectation of a properly defined set valued random variable (SVRV). An SVRV is a mapping that associates a set (rather...
Persistent link: https://www.econbiz.de/10010333083
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The identification power of smoothness assumptions in models with counterfactual outcomes
Kim, Wooyoung; Kwon, Koohyun; Kwon, Soonwoo; Lee, Sokbae - 2014
In this paper, we investigate what can be learned about average counterfactual outcomes when it is assumed that treatment response functions are smooth. The smoothness conditions in this paper amount to assuming that the differences in average counterfactual outcomes are bounded under different...
Persistent link: https://www.econbiz.de/10010368182