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Spatio-temporal Analysis of Regional Systems: A Multiregional Spatial Vector Autoregressive Model for Spain

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  • JULIAN RAMAJO
  • MIGUEL A. MARQUEZ
  • GEOFFREY J.D. HEWINGS

Abstract

This paper contributes to the recent literature in spatial econometrics that focuses on space-time data modeling implementing a multi-location time-series statistical framework to analyze a regional system. Therefore, taking as a point of departure the Global Vector Autoregression approach introduced in Pesaran et al. (2004), a multiregional spatial vector autoregressive model (MultiREG-SpVAR) is formulated and then applied to study the spatio-temporal 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 generating' within the Spanish regional system since growth shocks from these regions spill over to a large number of regions of the country, playing a key role in transmitting 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 favor the economic recovery process of the whole Spanish economy.

Suggested Citation

  • Julian Ramajo & Miguel A. Marquez & Geoffrey J.D. Hewings, 2013. "Spatio-temporal Analysis of Regional Systems: A Multiregional Spatial Vector Autoregressive Model for Spain," ERSA conference papers ersa13p159, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa13p159
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    References listed on IDEAS

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    Cited by:

    1. Miguel A. Márquez & Julián Ramajo & Geoffrey JD. Hewings, 2015. "Regional growth and spatial spillovers: Evidence from an SpVAR for the Spanish regions," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 1-18, November.

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