TY  - UNPB
M1  - master
N2  - This thesis has sought to find out what factors are most important regarding (un)employment recovery after the Great Recession from an evolutionary and structural economic viewpoint by exploiting an Ordinary Least Squares regression method and calculating two indices for both industry concentration and (un)related variety. The main results tell that industry concentration and ?related variety? are closely related and individually positively contribute to growth. Furthermore, when these variables are statistically combined, there is an interesting trade-off visible that demonstrates how related variety in conjunction with industry concentration (also interpreted as specialization) impacts regional resilience. Essentially, there is an intersection at 65% related variety and 35% unrelated variety where industry concentration as being either low or high is more or less beneficial to (un)employment recovery. Below the intersection, high concentration is more beneficial, and after that low to no concentration is. Interpretation arrives at the notion of negative regional ?lock-in? and the stages of economic development the regions (371 Local Authority Districts) find themselves in. Concluding, there have been produced spatial results with use of GIS that show that the regions with generally high related variety and low concentration perform best. NUTS-1 region London is the most pronounced example of this, and Scotland most negatively affects resilience.
ID  - theses_frw3817
Y1  - 2022///
UR  - https://frw.studenttheses.ub.rug.nl/3817/
A1  - Rooij, Robin van
EP  - 91
TI  - The two-way significance of relatedness: An analysis of the regional determinants of resilience in Great Britain?s financial services sector during recovery of the 2008-2014 Great Recession
AV  - public
ER  -