Spatiotemporal Analysis of Regional Systems: A Multiregional Spatial Vector Autoregressive Model for Spain
International Regional Science Review
Published online on February 20, 2015
Abstract
This article contributes to the recent literature in spatial econometrics that focuses on space–time data modeling implementing a multilocation time-series statistical framework to analyze a regional system. Drawing on the global vector autoregression approach introduced in Pesaran, Schuermann, and Weiner, a multiregional spatial vector autoregressive (MultiREG-SpVAR) model is formulated and then applied to study the spatiotemporal transmission of macroeconomic shocks across the regions in Spain. The empirical application analyzes the extent to which a region’s economic output growth is influenced by the growth of its neighbors (push-in or inward growth effect), and also investigates the relevance of spillovers derived from temporary region specific output growth shocks (push-out or outward growth effect). Our results identify some regions that perform as "growth generators" within the Spanish regional system since growth shocks from these regions spillover to a large number of regions of the country, playing a key role in the transmission of regional business cycles. The policy implications of our results suggest that national and/or regional governments should stimulate economic activity in these leading regions in order to enhance the economic recovery process of the whole Spanish economy.