Volatility and Regional Growth in Europe: Does Space Matter?

Abstract

This paper examines the relationship between output volatility and regional growth in Europe. To that end, we present a spatially augmented stochastic growth model with technological interdependence among economies. Spatial externalities are used to model technological interdependence, which ultimately implies that the economic growth rate of a particular region is affected not only by its own degree of volatility but also by the output fluctuations experienced by the remaining regions. In order to investigate the empirical validity of this result, we examine the link between volatility and economic growth in a sample of 272 European regions over the period 1991–2011 using spatial econometric techniques. Our estimates show the existence of a negative and statistically significant relationship between volatility and economic performance in the European regions. This is partly due to the role played by spatial spillovers induced by volatility in neighbouring regions. The observed relationship is robust to the inclusion in the analysis of different explanatory variables that may affect both regional growth and business cycle fluctuations. We also check that our results do not depend on the measure or volatility used in the analysis or the econometric specification employed to capture the nature of spatial spillovers.

Volatilité et expansion régionale en Europe: l’espace est-il important?

Résuméla présente communication se penche sur les rapports entre la volatilité de la production et l’expansion régionale en Europe. À cette fin, nous présentons un modèle d’expansion stochastique accrue sur le plan spatial, présentant une interdépendance technologique entre les économies. On fait usage d’externalités spatiales pour modéliser l’interdépendance technologique, ce qui implique au bout du compte que le taux d’expansion économique d’une région est affecté non seulement par son propre degré de volatilité, mais aussi par les fluctuations de production relevée dans les autres régions. Afin d’examiner la validité empirique de ce résultat, nous examinons le lien entre la volatilité et l’expansion économique dans un échantillon de 272 régions d’Europe au cours de la période 1991–2011.

Volatilidad en el crecimiento regional en Europa: ¿El espacios importante?

Resumeneste estudio analiza la relación entre la volatilidad de la producción y el crecimiento regional en Europa. Con este propósito, presentamos un modelo de crecimiento estocástico ampliado de manera espacial con la interdependencia tecnológica entre las economías. Las externalidades espaciales se usan para modelar la interdependencia tecnológica, lo que en última instancia implica que la tasa de crecimiento de una región particular se ve afectada no solamente por su propio grado de volatilidad, sino también por las fluctuaciones de la producción que experimentan las regiones vecinas. Con el fin de investigar la validez empírica de este resultado, examinamos la relación entre la volatilidad y el crecimiento económico en una muestra de 272 regiones europeas durante el periodo comprendido entre 1991 y 2011.

欧洲波动与区域增长: 空间是否重要?

摘要: 本文探讨欧洲产出波动与区域增长之间的关系。为此,我们提出包含经济体技术相互依赖性的空间增强随机增长模型。我们采用空间外部性建立技术相互依赖性模型, 该模型最终显示, 特定区域的经济增长率不仅受其自身的波动程度影响, 也受其余地区的产出波动影响。为调查该结果的实证效度, 我们对 1991 至 2011 年期间 272 个欧洲地区取样, 分析波动和经济增长之间的联系。

Keywords:

• Volatility
• growth
• spatial effects
• regions
• Europe

JEL Classification:

• R11
• E32

Notes

1. This list of factors is not exhaustive. For further information, see the recent papers by Crespo Cuaresma & Feldkircher (2013) and Crespo Cuaresma et al. (2014), who consider other potential determinants of regional growth in Europe.

2. NUTS is the French acronym for ‘Nomenclature of Territorial Units for Statistics’, a hierarchical classification of subnational spatial units established by Eurostat according to administrative criteria. In this classification, NUTS-0 corresponds to the country level, while increasing numbers indicate increasing levels of territorial disaggregation.

3. In addition to these contributions based on aggregate data, Ezcurra (2010) employs sectorally disaggregated data for six manufacturing activities to investigate the relationship between the fluctuations of the business cycle and output growth in the European regions between 1980 and 2006. Furthermore, Chandra (2003) tests the predictions of the portfolio model of the economy with European regional data. Using different frontier estimation methods, this author provides evidence of the existence of a convex growth-instability frontier for the more aggregated regions of Europe.

4. The lack of data has obliged us to exclude from the study the French overseas departments and territories, and the Portuguese islands in the Atlantic.

5. This specific measure was selected due to the lack of data for other alternative indicators. Nevertheless, it is worth noting that the nature of this variable implies that its use as a human capital control may be questionable, which should be taken into account when interpreting our findings.

6. In order to investigate whether the observed relationship between volatility and economic growth is stable over time, we repeat the estimation of Equation (19) for the periods 1991–2006 and 1996–2011, using three subperiods of five years in each case. The results are very similar to those described in the text. In fact, the only noticeable difference has to do with the direct effect of volatility on economic growth for the period 1996–2011, which is negative but not statistically significant at conventional levels.

7. As an alternative, one may to consider the possibility of estimating Equation (19) separately for two groups of regions defined according to the level of development at the beginning of the study period. However, this would imply to use different spatial weights matrices in the two groups, thus ignoring the spatial interdependences between them.

8. We would like to thank an anonymous referee for attracting our attention on this issue.