Binzhi Chen

Binzhi Chen

Senior Research Officer

Institute for Social and Economic Research (ISER), University of Essex

About

I am an econometrician specialising in panel data methods, factor models, and machine learning for causal inference. My current research develops estimators and software tools that uncover latent group structures and interactive fixed effects in large panel datasets.

I am a Senior Research Officer in ISER (Institute for Social and Economic Research) at University of Essex. I completed PhD in Economics at the University of Birmingham (2020–2025), supervised by Marco Barassi and Yiannis Karavias.

Panel data models Grouped fixed effects Interactive fixed effects Double machine learning Factor models Latent group structures Computational econometrics

Research

Job Market Paper

Panel VAR Model With Latent Group Structures

Univariate panel models with interactive fixed effects have been well discussed in previous studies. This paper studies the multivariate panel vector autoregression (PVAR) model with group-based factors. It is flexible: the number of groups, the group membership in each group, and the number of group factors in each equation are not pre-specified, and the model can be extended to group-specific heterogeneous coefficient Panel VAR. Furthermore, it is a parsimonious structural model that is easy to compute. The paper derives the asymptotic distribution and establishes consistency of the estimator for N and T tending to infinity.

Working Papers

  • Double Machine Learning for Static Panel Data Models with Interactive Fixed Effects

    with A. Polselli and P. S. Clarke

  • xtife: Interactive Fixed Effects Estimator for Panel Data in R

    2026

    An R package implementing the interactive fixed effects estimator for panel data.

  • pgfe: Grouped Fixed Effects in Panel Data Models in R

    2026

    An R package implementing the grouped fixed effects (GFE) estimator (Bonhomme & Manresa 2015) for panel data. Available on GitHub.

  • Group Patterns in Income Inequality and Economic Growth

    The relationship between income inequality and economic growth has been debated for a long time. This article uses the grouped fixed effects estimator to examine the growth-inequality nexus across countries. Results indicate a non-linear relationship consistent with the Kuznets curve — inequality has a positive impact on growth at low levels but a negative impact at high levels. The paper also reveals heterogeneity in the response of growth to inequality across groups. Results are robust to two different Gini indexes and different model specifications.

  • Critical Review of Carbon-Emitting Energy as an EKC Regressor: New Evidence from US State-Level Data

    The introduction of total fossil fuel or energy consumption as a regressor variable has become increasingly common in research on the carbon Kuznets curve (EKC). Given the way CO₂ emissions are calculated, this empirical strategy implies a clear endogeneity problem. The paper proposes an alternative model applied to US state-level panel data; empirical results show that bias on the parameters of interest may be important enough to warrant avoiding this common empirical strategy.

CV

View CV (PDF)

Working Experience

Sep 2025 – present
Senior Research Fellow Institute for Social and Economic Research (ISER), University of Essex, Colchester, UK Research Area: Double Debiased Machine Learning & Econometric Theory & Computational Social Science

Education

Sep 2020 – Jan 2025
Ph.D. in Economics University of Birmingham, Birmingham, UK Supervisors: Marco Barassi (University of Birmingham) & Yiannis Karavias (Brunel University London)

References

  • Marco Barassi Associate Professor in Econometrics, University of Birmingham
  • Yiannis Karavias Professor in Finance, Brunel University London