B0279
Title: Recovering latent linkage structures and spillover effects with structural breaks in panel data models
Authors: Wendun Wang - Erasmus University Rotterdam (Netherlands) [presenting]
Abstract: The aim is to capture time-varying spillover effects in a panel data setting. We consider panel models where the outcome of a unit depends not only on its own characteristics but also on the characteristics of other units (spillover effects). The effect of own characteristics can be unit-specific or homogeneous (common effects). We allow the linkage structure, i.e., which units interact with which, to be latent. Moreover, the structure and the spillover effects may both change at an unknown break point. To estimate the breakpoint, linkage structure, and spillover and common effects, we solve a penalized least squares optimization and employ double machine learning procedures to improve the convergence and inference. We establish the super consistency of the breakpoint estimator, which allows us to make inferences on other parameters as if the breakpoint was known. We illustrate the theory via simulated data.
