["Journal of Regional Science, EarlyView. ", "\nABSTRACT\nIn 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.\n"]