Research Staff

Martin Weidner

Martin joined UCL and the Centre for Microdata Methods and Practice (cemmap) in 2011 after finishing his PhD at the University of Southern California. He is working on theoretical and applied Econometrics, with a special focus on high-dimensional models for the analysis of longitudinal data and social networks.

Selected Publications

Minimizing Sensitivity to Model Misspecification

We propose a framework for estimation and inference when the model may be misspecified. We rely […]

Martin Weidner, Stéphane Bonhomme
9 July 2020 | CWP37/20

Previous version

Minimizing sensitivity to model misspecification
Martin Weidner, Stéphane Bonhomme
9 October 2018 | CWP59/18
Moment Conditions for Dynamic Panel Logit Models with Fixed Effects

This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for […]

Martin Weidner, Bo E. Honoré
9 July 2020 | CWP38/20
Network and Panel Quantile Effects Via Distribution Regression

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

Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
15 June 2020 | CWP27/20

Previous version

Network and panel quantile effects via distribution regression
Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
12 December 2018 | CWP70/18
Bias and Consistency in Three-way Gravity Models

We study the incidental parameter problem in “three-way” Poisson Pseudo-Maximum Likelihood “PPML” gravity models recently recommended […]

Thomas Zylkin, Martin Weidner
7 January 2020 | CWP1/20
Posterior average effects

Economists are often interested in estimating averages with respect to distributions of unobservables. Examples are moments […]

Martin Weidner, Stéphane Bonhomme
13 September 2019 | CWP43/19
Inference on a distribution from noisy draws

We consider a situation where the distribution of a random variable is being estimated by the […]

Martin Weidner, Koen Jochmans
13 September 2019 | CWP44/19

Previous version

Inference on a distribution from noisy draws
Martin Weidner, Koen Jochmans
27 February 2018 | CWP14/18
Nonlinear factor models for network and panel data

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

Martin Weidner, Ivan Fernandez-Val, Mingli Chen
11 April 2019 | CWP18/19

Previous version

Nonlinear factor models for network and panel data
Martin Weidner, Ivan Fernandez-Val, Mingli Chen
3 July 2018 | CWP38/18
Fixed-effect regressions on network data

This paper considers inference on fixed effects in a linear regression model estimated from network data. […]

Martin Weidner, Koen Jochmans
3 April 2019 | CWP16/19

Previous version

Fixed-effect regressions on network data
Martin Weidner, Koen Jochmans
16 July 2018 | CWP44/18
Nuclear norm regularized estimation of panel regression models

In this paper we investigate panel regression models with interactive fixed effects. We propose two new […]

Martin Weidner, Hyungsik Roger Moon
3 April 2019 | CWP14/19
Network and panel quantile effects via distribution regression

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

Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
12 December 2018 | CWP70/18

Latest version

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

Previous version

Network and panel quantile effects via distribution regression
Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
22 March 2018 | CWP21/18