Ivan Fernandez-Val

Selected Publications

Nonlinear factor models for network and panel data

Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. […]

Mingli Chen, Ivan Fernandez-Val, Martin Weidner
3 July 2018 | CWP38/18

Latest version

Nonlinear factor models for network and panel data
Mingli Chen, Ivan Fernandez-Val, Martin Weidner
11 April 2019 | CWP18/19
Fixed effect estimation of large T panel data models

This article reviews recent advances in fixed effect estimation of panel data models for long panels, […]

Ivan Fernandez-Val, Martin Weidner
28 March 2018 | CWP22/18

Previous version

Fixed effect estimation of large T panel data models
Ivan Fernandez-Val, Martin Weidner
3 October 2017 | CWP42/17
Network and panel quantile effects via distribution regression

This paper provides a method to construct simultaneous confidence bands for quantile functions and quantile effects […]

Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
22 March 2018 | CWP21/18

Latest version

Network and panel quantile effects via distribution regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
12 December 2018 | CWP70/18
Nonseparable sample selection models with censored selection rules

We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ […]

Ivan Fernandez-Val, Aico van Vuuren, Francis Vella
2 February 2018 | CWP10/18
Extremal quantile regression: an overview

Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with […]

Victor Chernozhukov, Ivan Fernandez-Val, Tetsuya Kaji
30 December 2017 | CWP65/17
Counterfactual analysis in R: a vignette

The R package Counterfactual implements the estimation and inference methods of Chernozhukov et al. (2013) for […]

Mingli Chen, Victor Chernozhukov, Ivan Fernandez-Val, Blaise Melly
30 December 2017 | CWP64/17
Generic machine learning inference on heterogenous treatment effects in randomized experiments

We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized […]

Victor Chernozhukov, Mert Demirer, Esther Duflo, Ivan Fernandez-Val
30 December 2017 | CWP61/17
Semiparametric estimation of structural functions in nonseparable triangular models

This paper introduces two classes of semiparametric triangular systems with nonadditively separable unobserved heterogeneity. They are […]

Victor Chernozhukov, Ivan Fernandez-Val, Whitney K. Newey, Sami Stouli, Francis Vella
8 November 2017 | CWP48/17
Fixed effect estimation of large T panel data models

This article reviews recent advances in fixed effect estimation of panel data models for long panels, […]

Ivan Fernandez-Val, Martin Weidner
3 October 2017 | CWP42/17

Latest version

Fixed effect estimation of large T panel data models
Ivan Fernandez-Val, Martin Weidner
28 March 2018 | CWP22/18
Nonseparable multinomial choice models in cross-section and panel data

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze […]

Victor Chernozhukov, Ivan Fernandez-Val, Whitney K. Newey
27 June 2017 | CWP33/17