Ivan Fernandez-Val

Selected Publications

Arellano-bond lasso estimator for dynamic linear panel models

The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. […]

Victor Chernozhukov, Ivan Fernandez-Val, Chen Huang, Weining Wang

26 April 2024 | CWP09/24

Distribution regression with sample selection and UK wage decomposition

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

Victor Chernozhukov, Ivan Fernandez-Val, Siyi Luo

26 April 2023 | CWP09/23

Previous version

Distribution regression with sample selection, with an application to wage decompositions in the UK

Victor Chernozhukov, Ivan Fernandez-Val, Siyi Luo

29 November 2018 | CWP68/18

Dynamic heterogeneous distribution regression panel models, with an application to labor income processes

We consider estimation of a dynamic distribution regression panel data model with heterogeneous coefficients across units. […]

Ivan Fernandez-Val, Wayne Yuan Gao, Yuan Liao, Francis Vella

8 April 2022 | CWP10/22

Low-rank approximations of nonseparable panel models

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

Ivan Fernandez-Val, Hugo Freeman, Martin Weidner

4 March 2021 | CWP10/21

Previous version

Low-rank approximations of nonseparable panel models

Ivan Fernandez-Val, Hugo Freeman, Martin Weidner

23 October 2020 | CWP52/20

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