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Investigating space-time patterns of regional industrial resilience through a micro-level approach
- Source :
- Journal of Regional Science, 60(4), 653-676. Wiley
- Publication Year :
- 2020
-
Abstract
- This paper introduces a new methodology to identify space-time patterns of regional resilience using a micro-level approach. The novel empirical tool combines geographically weighted regression with panel stochastic frontier analysis with endogenous covariates. The analysis is implemented on a panel of farm holdings operating in the Italian wine industry, focusing on the impact of a major institutional change. The results show the effectiveness of the new procedure in identifying geographical clusters of wine producers who reacted to the shock in similar ways. The responses are found to be homogeneous within specific territories and heterogeneous between regions.
- Subjects :
- STOCHASTIC FRONTIER MODEL
geographically weighted regression
TECHNICAL EFFICIENCY
0211 other engineering and technologies
02 engineering and technology
endogeneity
Environmental Science (miscellaneous)
Development
spatial nonstationarity
SHOCKS
Stochastic frontier analysis
0502 economics and business
Regional science
EMPLOYMENT
ECONOMIC RESILIENCE
Endogeneity
050207 economics
Resilience (network)
resilience
Wine
PRODUCTIVITY
endogeneity, geographically weighted regression, resilience, spatial nonstationarity, stochastic frontier
Space time
05 social sciences
021107 urban & regional planning
Shock (economics)
stochastic frontier
Geographical cluster
GROWTH
Business
LEVEL EVIDENCE
Wine industry
PANEL-DATA
Subjects
Details
- Language :
- English
- ISSN :
- 00224146
- Volume :
- 60
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Journal of Regional Science
- Accession number :
- edsair.doi.dedup.....213a1116de4fb397e87946eaf34b1fb7
- Full Text :
- https://doi.org/10.1111/jors.12480