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A bootstrap test for instrument validity in heterogeneous treatment effect models
Kitagawa, Toru - 2013
This paper develops a specification test for the instrument validity conditions in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. A necessary testable implication for the joint restriction of instrument exogeneity and instrument monotonicity is given...
Persistent link: https://www.econbiz.de/10010190476
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Mostly harmless simulations? : on the internal validity of empirical Monte Carlo studies
Advani, Arun; Kitagawa, Toru; Słoczyński, Tymon - 2018 - This version: September 21, 2018
Currently there is little practical advice on which treatment effect estimator to use when trying to adjust for observable differences. A recent suggestion is to compare the performance of estimators in simulations that somehow mimic the empirical context. Two ways to run such "empirical Monte...
Persistent link: https://www.econbiz.de/10011912535
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Estimation of random coefficients logit demand models with interactive fixed effects
Moon, Hyungsik Roger; Shum, Matthew; Weidner, Martin - 2014 - This draft: April 22, 2014
We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete choice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can...
Persistent link: https://www.econbiz.de/10010345243
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Estimation of random coefficients logit demand models with interactive fixed effects
Moon, Hyungsik Roger; Shum, Matthew; Weidner, Martin - 2012
We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discretechoice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can...
Persistent link: https://www.econbiz.de/10009521645
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Estimation of random coefficients logit demand models with interactive fixed effects
Moon, Hyungsik Roger; Shum, Matthew; Weidner, Martin - 2017 - This version: February 15, 2017
We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coeffcients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can...
Persistent link: https://www.econbiz.de/10011603891
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Model averaging in semiparametric estimation of treatment effects
Kitagawa, Toru; Muris, Chris - 2015
propensity score weighting estimation of the average treatment effects for treated (ATT). The proposed averaging procedures aim …
Persistent link: https://www.econbiz.de/10011309717
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Semiparametrically efficient estimation of the average linear regression function
Graham, Bryan S.; Pinto, Cristine Campos de Xavier - 2018
Let Y be an outcome of interest, X a vector of treatment measures, and W a vector of pre-treatment control variables. Here X may include (combinations of) continuous, discrete, and/or non-mutually exclusive "treatments". Consider the linear regression of Y onto X in a subpopulation homogenous in...
Persistent link: https://www.econbiz.de/10011924562
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Fuzzy differences-in- differences
Chaisemartin, Clément de; D'Haultfœuille, Xavier - 2015
In many applications of the differences-in-differences (DID) method, the treatment increases more in the treatment group, but some units are also treated in the control group. In such fuzzy designs, a popular estimator of treatment effects is the DID of the outcome divided by the DID of the...
Persistent link: https://www.econbiz.de/10011372663
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Quantile regression with panel data
Graham, Bryan S.; Hahn, Jinyong; Poirier, Alexandre; … - 2015
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data …; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the … (NLSY79). Consistent with prior work (e.g., Chamberlain, 1982; Vella and Verbeek, 1998), we find that using panel data to …
Persistent link: https://www.econbiz.de/10010494997
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A quantile correlated random coefficients panel data model
Graham, Bryan S.; Hahn, Jinyong; Poirier, Alexandre; … - 2016
We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data …; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the … (NLSY79). Consistent with prior work (e.g., Chamberlain, 1982; Vella and Verbeek, 1998), we find that using panel data to …
Persistent link: https://www.econbiz.de/10011524832