Spatiotemporal Analysis of Regional Systems A Multiregional Spatial Vector Autoregressive Model for Spain

• Published in: International regional science review Vol. 40; no. 1; pp. 75 - 96
• Main Authors: Ramajo, Julián, Márquez, Miguel A., Hewings, Geoffrey J. D.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2017; Sage Publications Ltd
• Subjects: Econometrics; Economic models; Regions; Regression analysis; Spain; vector autoregressions; spillovers; regional growth; spatial econometrics
• ISSN: 0160-0176; 1552-6925
• DOI: 10.1177/0160017615571586

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.