Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/124287
Title: 

An Alternative Interpretation of Regional Resilience: Evidence from Italy

Authors: 
Modica, Marco
Reggiani, Aura
Year of Publication: 
2014
Series/Report no.: 
54th Congress of the European Regional Science Association: "Regional development & globalisation: Best practices", 26-29 August 2014, St. Petersburg, Russia
Abstract: 
This paper provides a different interpretation of resilience on the light of a very well known empirical regularities that is Gibrat's Law. Gibrat's Law is a rule stating that the growth of a given entity (city, firm, income and so on) is independent on its size. Resilience, instead, is a concept firstly adopted in ecology and subsequently 'exported' in different research fields. It refers to the capacity of a given system to respond to shocks by recovering to a state similar to the initial one. Although, at the first glance, the two concepts look quite different, Gibrat's Law can be interpreted in economic terms, as the reproposal, after a certain (long) time, of the deterministic pattern generated by some structural fundamental variables. Indeed Gibrat's Law arises as the steady state equilibria of stochastic processes that describe the underlying economic or demographic forces and characteristically, the steady state is independent of initial conditions. Then, this paper aims at reassessing the idea of resilience in the light of Gibrat's Law. In more detail, we provide a comparison with a previous research on resilience that shows a high degree of homogeneity of the resilience across Italian regions in the period 1890-2009 using data on real per capita income. In particular we adopt different methodologies commonly used in evaluating Gibrat's Law over the same dataset used in the previous research. We first check for departures from the Gibrat Law, using a linear test, that means testing the deviations of logarithms of capita income levels from their means. Secondly, we use a unit root test approach to check whether the data show mean reversion in the stochastic growth process. Finally we compare our results with those of the previous research. Our results show that, although not perfectly, we can define a relationship between Gibrat's law and resilience.
Subjects: 
Population growth
Economic resilience
Shock impact
Recovery
JEL: 
O40
R11
Document Type: 
Conference Paper

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