Dynamic Probit Models With Network Interdependence and Unobserved Heterogeneity With an Application to Multinational‐Firm Participation in China

ABSTRACT In many areas of regional/spatial economics, we are faced with analyzing discrete dynamic choice problems of economic agents interacting with some network structure through general equilibrium, input‐output links, or strategic interaction. Stochastic estimating equations for such problems can be difficult for many practitioners to estimate. This paper proposes MCMC estimation approaches based on control functions for estimating dynamic panel probit models where a large number of cross‐sectional units is observed over a short period of time, and cross‐sectional units feature network interdependencies. The proposed approaches enable accounting for dynamic adjustment and different types of cross‐sectional dependence. These features should make the approaches interesting for applications in many empirical contexts. The paper outlines the estimation approaches, illustrates their suitability by simulation examples, and provides an application to study dynamic multinational‐firm participation among regionally connected Chinese firms.

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Publication Details

Journal
Journal of Regional Science
Published
2026-06-09
DOI
https://doi.org/10.1111/jors.70072
Primary Topic
Regional Economics and Spatial Analysis
Type
article
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article

Dynamic Probit Models With Network Interdependence and Unobserved Heterogeneity With an Application to Multinational‐Firm Participation in China

Michaela Kesina, Peter H. Egger
Journal of Regional Science
Regional Economics and Spatial Analysis
article

Dynamic Probit Models With Network Interdependence and Unobserved Heterogeneity With an Application to Multinational‐Firm Participation in China

Michaela Kesina, Peter H. Egger
article en

Abstract

ABSTRACT In many areas of regional/spatial economics, we are faced with analyzing discrete dynamic choice problems of economic agents interacting with some network structure through general equilibrium, input‐output links, or strategic interaction. Stochastic estimating equations for such problems can be difficult for many practitioners to estimate. This paper proposes MCMC estimation approaches based on control functions for estimating dynamic panel probit models where a large number of cross‐sectional units is observed over a short period of time, and cross‐sectional units feature network interdependencies. The proposed approaches enable accounting for dynamic adjustment and different types of cross‐sectional dependence. These features should make the approaches interesting for applications in many empirical contexts. The paper outlines the estimation approaches, illustrates their suitability by simulation examples, and provides an application to study dynamic multinational‐firm participation among regionally connected Chinese firms.

Journal of Regional Science
Austrian Institute of Economic Research (AT), Ifo Institute for Economic Research (DE), ETH Zurich (CH), Centre Pour La Recherche Economique et ses Applications (FR), RWTH Aachen University (DE)
Openalex Percentile: Top 3%
Regional Economics and Spatial Analysis
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Dynamic Probit Models With Network Interdependence and Unobserved Heterogeneity With an Application to Multinational‐Firm Participation in China — Michaela Kesina, Peter H. Egger · Journal of Regional Science (2026) | TGRS Research Map | TGRS