Econometric modelling of the regional knowledge production function in Europe

Charlot, Sylvie, Crescenzi, Riccardo ORCID: 0000-0003-0465-9796 and Musolesi, Antonio (2015) Econometric modelling of the regional knowledge production function in Europe. Journal of Economic Geography, 15 (6). pp. 1227-1259. ISSN 1468-2702

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Abstract

By adopting a semiparametric approach, the ‘traditional’ regional knowledge production function is developed in three complementary directions. First, the model is augmented with region-specific time trends to account for endogeneity due to selection on unobservables. Second, the nonparametric part of the model relaxes the standard assumptions of linearity and additivity regarding the effect of R&D and human capital. Finally, the assumption of homogeneity in the effects of R&D and human capital is also relaxed by explicitly accounting for the differences between developed and lagging regions. The analysis of the genesis of innovation in the regions of the European Union unveils nonlinearities, threshold effects, complex interactions and shadow

Item Type:	Article
Official URL:	http://joeg.oxfordjournals.org/
Additional Information:	© 2014 The Authors
Divisions:	Geography & Environment Spatial Economics Research Centre
Subjects:	H Social Sciences > HC Economic History and Conditions
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C23 - Models with Panel Data O - Economic Development, Technological Change, and Growth > O3 - Technological Change; Research and Development > O32 - Management of Technological Innovation and R&D R - Urban, Rural, and Regional Economics > R1 - General Regional Economics > R11 - Regional Economic Activity: Growth, Development, and Changes
Date Deposited:	06 Nov 2014 13:34
Last Modified:	12 Dec 2024 00:49
Funders:	ESPON 2013 –KIT, LSE-SERC, INRA CESAER, INRA SAE2
URI:	http://eprints.lse.ac.uk/id/eprint/60088

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