A MEASURE FOR REGIONAL RESILIENCE TO ECONOMIC CRISIS

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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

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VOLUME 16 , ISSUE 2 (June 2015) > List of articles

A MEASURE FOR REGIONAL RESILIENCE TO ECONOMIC CRISIS

Małgorzata Markowska

Keywords : economic crisis, aggregate measure, NUTS 2.

Citation Information : Statistics in Transition New Series. Volume 16, Issue 2, Pages 293-308, DOI: https://doi.org/10.21307/stattrans-2015-016

License : (CC BY 4.0)

Published Online: 31-October-2017

ARTICLE

ABSTRACT

The purpose of the study (presented in this article) was to develop a measure of resilience to crisis, one that may be applied to regional data. In principle, such measure can take either positive or negative values. A positive value confirms resilience to crisis, whereas a negative one confirms the absence of resilience (sensitivity/vulnerability). The measure uses growth rates referred to the previous year under the assumption that crisis results in a slowdown in growth, or even in a decline in values of important economic indicators. Growth rates are standardized by dividing values of original change rates by medians specified based on spatio- temporal data modules. Such division results in each characteristic being brought to equal validity. Simultaneously, the original character is maintained and variables are not “flattened” by the outliers. Changing destimulants into stimulants occurs during growth rates calculation. The measure of resilience to crisis is calculated as an arithmetic mean of the values of characteristics brought to comparability. The measure of resilience can be converted into the measure of sensitivity by multiplying it by (-1). The application of the proposed measure to assessing the resilience to crisis in the period 2006-2011 is presented for regions meant as the European Union NUTS2 units. The measure is based on comparable data, which allowed for using only six variables measuring changes in GDP, salaries, investments, household income, employment and unemployment.

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