Estimating Dynamic Spillover Effects along Multiple Networks in a Linear Panel Model

TL;DR

This paper develops a dynamic linear panel model to estimate and infer the bidirectional spillover effects across multiple networks, demonstrated through an empirical study of bank and sector interactions in Spain.

Contribution

It introduces a novel methodology for simultaneously estimating and testing bidirectional spillovers in a multi-network setting within a dynamic panel framework.

Findings

Positive spillover observed in both directions between banks and sectors

Methodology accommodates multiple networks and bidirectional effects

Empirical evidence supports the presence of spillovers in the studied data

Abstract

Spillover of economic outcomes often arises over multiple networks, and distinguishing their separate roles is important in empirical research. For example, the direction of spillover between two groups (such as banks and industrial sectors linked in a bipartite graph) has important economic implications, and a researcher may want to learn which direction is supported in the data. For this, we need to have an empirical methodology that allows for both directions of spillover simultaneously. In this paper, we develop a dynamic linear panel model and asymptotic inference with large $n$ and small $T$, where both directions of spillover are accommodated through multiple networks. Using the methodology developed here, we perform an empirical study of spillovers between bank weakness and zombie-firm congestion in industrial sectors, using firm-bank matched data from Spain between 2005 and 2012. Overall, we find that there is positive spillover in both directions between banks and sectors.