Increasing linkages among European regions. The role of sectoral composition |
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| Institution: | 1. Universidad de Zaragoza, Spain;2. Banco de España, Spain;1. Department of Economics, Tunghai University, No. 1727, Sec. 4, Xitun Dist., Taiwan Boulevard, Taichung, 40704, Taiwan;2. Department of Accounting, Feng Chia University, Taiwan;1. Department of Business Administration, Pusan National University, Republic of Korea;2. Department of Management and Engineering, Linköping University, Sweden;3. Department of Economics, Pusan National University, Republic of Korea;1. Department of Applied Economics, University of Zaragoza, 4 Gran Vía, Zaragoza 50005, Spain;2. Banco de España, 48 Alcalá, Madrid 28014, Spain;3. CEPR, 33 Great Sutton, London EC1V 0DX, United Kingdom;1. School of Business, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China;2. Department of Finance, East China University of Science and Technology, Shanghai 200237, China;3. Department of Economics, University of Waterloo, 200 University Avenue West, Ontario, N2L 3G1, Canada;1. ESSCA School of Management, France;2. Institut Supérieur de Gestion, 2000, Le Bardo, University of Tunis, Tunisia;3. LAREQUAD FSEG de Tunis, University of Tunis El Manar, Tunisia |
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| Abstract: | This paper analyses changes in economic regional interlinkages in Europe over time and investigates the factors that could explain the dynamics of these changes. Our four main findings are the following: (i) we detect a significant surge in regional synchronisation after the Great Recession; (ii) we identify the regions most interrelated with the rest of Europe, namely, Ile de France, Inner London and Lombardia; (iii) we find that sectoral composition explains regional synchronisation in Europe, mainly after the Great Recession and (iv) we document that sectoral composition has important implications for aggregate economic fluctuations, in particular, that similarities in services-related sectors across regions explain a nonlinear relationship between sectoral composition and regional business cycle synchronisation. We also propose a new method to measure time-varying synchronisation in small samples that combines regime-switching models and dynamic model averaging. |
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| Keywords: | Business cycle Sectoral composition Regime-switching Model averaging C31 C32 E32 R11 |
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