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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/10011665568

Nonseparable multinomial choice models in cross-section and panel data

Chernozhukov, Victor; Fernández-Val, Iván; Newey, … - In: Journal of econometrics 211 (2019) 1, pp. 104-116

Persistent link: https://www.econbiz.de/10012303601

Generic inference on quantile and quantile effect functions for discrete outcomes

Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise - 2016

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for possibly discrete or mixed discrete-continuous random variables. The construction is generic and does not depend on the nature of the underlying problem. It works in conjunction...

Persistent link: https://www.econbiz.de/10011538584

Generic inference on quantile and quantile effect functions for discrete outcomes

Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise - 2016

Persistent link: https://www.econbiz.de/10011524697

Generic inference on quantile and quantile effect functions for discrete outcomes

Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise - 2017

Persistent link: https://www.econbiz.de/10011647471

Generic machine learning inference on heterogenous treatment effects in randomized experiments

Chernozhukov, Victor; Demirer, Mert; Duflo, Esther; … - 2017

We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments. These key features include best linear predictors of the effects using machine learning proxies, average effects sorted by impact groups, and average characteristics of most...

Persistent link: https://www.econbiz.de/10011775335

Inference for extremal conditional quantile models, with an application to market and birthweight risks

Chernozhukov, Victor; Fernández-Val, Iván - 2009 - This version: December 26, 2009

Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...

Persistent link: https://www.econbiz.de/10009419329

Inference for extremal conditional quantile models, with an application to market and birthweight risks

Chernozhukov, Victor; Fernández-Val, Iván - 2011

Persistent link: https://www.econbiz.de/10009271130

Inference for extremal conditional quantile models : with an application to market and birthweight risks

Chernozhukov, Victor; Fernández-Val, Iván - In: The review of economic studies 78 (2011) 2, pp. 559-589

Persistent link: https://www.econbiz.de/10009238868

Fast algorithms for the quantile regression process

Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise - In: Empirical economics : a quarterly journal of the … 62 (2022) 1, pp. 7-33

Persistent link: https://www.econbiz.de/10012819429