Ivan Fernandez-Val

Selected Publications

Low-rank approximations of nonseparable panel models

We provide estimation methods for panel nonseparable models based on low-rank factor structure approximations. The factor […]

Ivan Fernandez-Val, Hugo Freeman, Martin Weidner
23 October 2020 | CWP52/20
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
15 June 2020 | CWP27/20

Previous version

Network and panel quantile effects via distribution regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
12 December 2018 | CWP70/18
Decomposing Changes in the Distribution of Real Hourly Wages in the U.S.

We analyze the sources of changes in the distribution of hourly wages in the United States […]

Ivan Fernandez-Val, Franco Peracchi, Francis Vella, Aico van Vuuren
18 November 2019 | CWP61/19
Mastering Panel Metrics: Causal Impact of Democracy on Growth

The relationship between democracy and economic growth is of long standing interest. We revisit the panel […]

Shuowen Chen, Victor Chernozhukov, Ivan Fernandez-Val
12 June 2019 | CWP33/19
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
11 April 2019 | CWP18/19

Previous version

Nonlinear factor models for network and panel data
Mingli Chen, Ivan Fernandez-Val, Martin Weidner
3 July 2018 | CWP38/18
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
12 December 2018 | CWP70/18

Latest version

Network and Panel Quantile Effects Via Distribution Regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
15 June 2020 | CWP27/20

Previous version

Network and panel quantile effects via distribution regression
Victor Chernozhukov, Ivan Fernandez-Val, Martin Weidner
22 March 2018 | CWP21/18
Distribution regression with sample selection, with an application to wage decompositions in the UK

We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization […]

Victor Chernozhukov, Ivan Fernandez-Val, Siyi Luo
29 November 2018 | CWP68/18
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