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OLS estimator in a rank-rank regression. We show that the probability limits of these estimators may be too large or too …
Persistent link: https://www.econbiz.de/10014416045
Persistent link: https://www.econbiz.de/10003385784
The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in …
Persistent link: https://www.econbiz.de/10011295589
The understanding of co-movements, dependence, and influence between variables of interest is key in many applications. Broadly speaking such understanding can lead to better predictions and decision making in many settings. We propose Quantile Graphical Models (QGMs) to characterize prediction...
Persistent link: https://www.econbiz.de/10011775380
theory for the OLS estimator in a general rank-rank regression specification without making assumptions about the continuity …
Persistent link: https://www.econbiz.de/10014536213
This paper introduces Stata commands [R] npivreg and [R] npivregcv, which implement nonparametric instrumental variable (NPIV) estimation methods without and with a cross-validated choice of tuning parameters, respectively. Both commands are able to impose monotonicity of the estimated function....
Persistent link: https://www.econbiz.de/10011758353
The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baselinepretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing...
Persistent link: https://www.econbiz.de/10003989944
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
Persistent link: https://www.econbiz.de/10003161224