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The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results are...
Persistent link: https://www.econbiz.de/10011295589
We study identification and estimation of the average treatment effect in a correlated random coefficients model that allows for first stage heterogeneity and binary instruments. The model also allows for multiple endogenous variables and interactions between endogenous variables and covariates....
Persistent link: https://www.econbiz.de/10010227690
We study identification and estimation in a binary response model with random coefficients B allowed to be correlated with regressors X. Our objective is to identify the mean of the distribution of B and estimate a trimmed mean of this distribution. Like Imbens and Newey (2009), we use...
Persistent link: https://www.econbiz.de/10009728916
, "Intransitivity in Correlations," related to an under-utilized property from the statistics literature. From this principle, it is …
Persistent link: https://www.econbiz.de/10011631566
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consistent estimates of the joint model: (i) a demand-side instrument, or (ii) a covariance restriction between unobserved demand … and cost shocks. The covariance restriction approach can obtain identification even the absence of instruments. Further …, supply and demand assumptions alone may bound the structural parameters. We develop an estimator for the covariance …
Persistent link: https://www.econbiz.de/10012019872
Persistent link: https://www.econbiz.de/10015333198
squared distance is proposed. The statistic’s asymptotic distribu- tion under the MAR hypothesis is derived. We demonstrate … conditional on covariates X (MCAR(X)). A Monte Carlo study examines finite sample performance of our test statistic. An empirical …
Persistent link: https://www.econbiz.de/10010503886