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  • Generic inference on quantile and quantile effect functions for discrete outcomes 

    Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise; Wüthrich, Kaspar (2016)
    Quantile and quantile effect functions are important tools for descriptive and inferential analysis due to their natural and intuitive interpretation. Existing inference methods for these functions do not apply to discrete ...
  • quantreg. nonpar: An R Package for performing nonparametric series quantile regression 

    Lipsitz, Michael; Belloni, Alexandre; Chernozhukov, Victor; Fernández-Val, Iván (2016)
    The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile ...
  • Counterfactual: an R package for counterfactual analysis 

    Chen, Mingli; Chernozhukov, Victor; Fernández-Val, Iván; Melly, Blaise (The R Foundation for Statistical Computing, 2017)
    The Counterfactual package implements the estimation and inference methods of Cher nozhukov et al. (2013) for counterfactual analysis. The counterfactual distributions considered are the result of changing either the ...
  • Supplement to “program evaluation and causal inference with high-dimensional data" 

    Belloni, Alexandre; Chernozhukov, Victor; Fernandez-Val, Iván; Hansen, Christian (2017)
  • Bias corrections for probit and logit models with two-way fixed effects 

    Cruz-Gonzalez, Mario; Fernández-Val, Iván; Weidner, Mario (StataCorp, 2017)
    We present the Stata commands probitfe and logitfe, which estimate probit and logit panel data models with individual and/or time unobserved effects. Fixed effect panel data methods that estimate the unobserved effects can ...
  • Censored quantile instrumental variable estimation with Stata 

    Chernozhukov, Victor; Fernández‐Val, Iván; Han, Sukjin; Kowalski, Amanda E. (2018-01)
    Many applications involve a censored dependent variable and an endogenous independent variable. Chernozhukov, Fernandez-Val, and Kowalski (2015) introduced a censored quantile instrumental variable estimator (CQIV) for use ...
  • Individual and time effects in nonlinear panel models with large N, T 

    Fernández-Val, Iván; Weidner, Martin (North-Holland, 2016)
    We derive fixed effects estimators of parameters and average partial effects in (possibly dynamic) nonlinear panel data models with individual and time effects. They cover logit, probit, ordered probit, Poisson and Tobit ...
  • Nonseparable sample selection models with censored selection rules: an application to wage decompositions 

    Fernández‐Val, Iván; van Vuuren, Aico; Vella, Francis
    We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects ...
  • Program evaluation and causal inference with high-dimensional data 

    Belloni, Alexandre; Chernozhukov, Victor; Fernández-Val, Iván; Hansen, Christian (Econometric Society, 2017)
    In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data-rich environments. We can ...
  • Disclosure and choice 

    Ben-Porath, Elchanan; Dekel, Eddie; Lipman, Barton L. (Oxford University Press (OUP), 2018-07)
    An agent chooses among projects with random outcomes. His payoff is increasing in the outcome and in an observer's expectation of the outcome. With some probability, the agent can disclose the true outcome to the observer. ...

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