Abstract
Combining evolutionary economic geography and the recombinant knowledge approach, we test whether the level of entropy in available capabilities affects the level of a region’s economic complexity. Merging different data sources on 103 Italian NUTS-3 regions and 9 years (between 2008 and 2016), our panel regressions show that a higher level of economic complexity in a region is explained by a higher average level of entropy in the region’s capabilities. We also find this effect stronger in the northern and central regions of Italy, and it is due only to entropy in the available technologies, not in capital or skills. Using structural equation models, we show that variety of skills and relative capital endowment are indirectly linked to the level of economic complexity in Italian regions, since they first stimulate a greater technological diversification.
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Notes
While the ECI captures a region’s economic structure by combining the diversity of its export basket with the ubiquity of its industries, and linking them through a series of linear iterative equations, the Fitness Index uses a series of non-linear iterations to combine the number of industries in a region, weighted by their level of complexity, and the level of complexity of each industry, which is inversely proportional to the number of regions with complex industries.
We have only excluded cultivated assets since the primary sector is not considered when computing the ECI.
The eight job titles are: 1 – legislators, senior officials, and managers; 2 – professionals; 3 – technicians and associate professionals; 4 – clerks; 5 – service workers, shop, and market sales workers; 6 – craft and related trades workers; 7 – plant and machine operators, and assemblers; 8 – elementary occupations. We have excluded agriculture and fishery workers, and other (not specified) occupations.
We have used the new release available at: https://sites.google.com/site/institutionalqualityindex/dataset. For all methodological details, see: https://drive.google.com/file/d/1cLiQ9pqJmpLc77PNEZTIpXu9rJh-VAxr/view.
These results are confirmed even when we split the sample in two, separating the period 2008–2012 (during which unemployment roughly doubled in Italy from 6.7 to 12.5%) from the years 2013–2016, characterized by a higher economic stability. The results are provided in the Appendix, Tables A3 and A4.
The results do not change if we replace SKILL-Entropy with TASK-Entropy, as shown in the Appendix, Table A5.
Table A6 in the Appendix shows the results of the 2SLS regression analysis when we replace SKILL-Entropy with TASK-Entropy.
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Antonietti, R., Burlina, C. Exploring the entropy-complexity nexus. Evidence from Italy. Econ Polit 40, 257–283 (2023). https://doi.org/10.1007/s40888-022-00265-9
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DOI: https://doi.org/10.1007/s40888-022-00265-9