Abstract
This paper introduces a spatial panel data model describing local agents’ intertemporal decision-making with their network interactions and network evolution. Our model’s purpose is to give a tool to analyze local governments’ behaviors when there exist network interactions among them with endogenously changing networks. To provide a theoretical foundation of our model, we establish a network interaction model for forward-looking agents. An agent’s current action can affect his future network links via time-varying economic indicators. To estimate the model’s parameters, we consider a GMM estimation method based on first-order conditions of agents’ approximated lifetime problems. Asymptotic properties of the GMM estimator are studied for statistical inferences. Using our model, we find evidence of positive spillovers among U.S. states’ public welfare expenditures with coevolution between them and spatial-economic networks.
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