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abstract
How do regions diversify over time? Inspired by recent studies, we argue that regions diversify into industries that make use of capabilities in which regions are specialized. Since the spread of capabilities occurs through mechanisms that have a strong regional bias, we expect that capabilities that are available at the regional level play a larger role than do capabilities that are available at the country level for the development of new industries. To test this hypothesis, we analyze the emergence of new industries in 50 S panish regions at the NUTS 3 level in the period 1988–2008. We calculate the capability-distance between new export products and existing export products in S panish regions and provide econometric evidence that regions tend to diversify into new industries that use similar capabilities as existing industries in these regions. We show that proximity to the regional industrial structure plays a much larger role in the emergence of new industries in regions than does proximity to the national industrial structure. This finding suggests that capabilities at the regional level enable the development of new industries.
Acknowledgments
Asier Minondo acknowledges financial support from the Spanish Ministry of Science and Innovation (ECO2010-21643/ECON and ECO2011-27619/ECON).
Notes
Notes
To calculate proximity indexes, we used a sample of countries that provided data in all the years that are included in the analysis. We excluded countries with a population of less than 3 million. To avoid endogeneity problems, we excluded Spain from the sample.
These data are in the Combined Nomenclature eight-digit classification. They needed to be transformed to SITC Rev 2. four-digits, to match the classification used to calculate the proximity indexes.
Since the NBER database ends in 2000, we used proximity indexes for 2000 to calculate densities in 2003.
The unconditional probability of developing a comparative advantage in a new product is 2.7 percent. The unconditional probability of keeping a comparative advantage in a product is 69.1 percent.
To draw the figures, we used the epanechnikov kernel estimator in STATA, calculated on n = 50 points, and allowing the estimator to calculate the optimal bandwidth.
Both in and in , the t test for the equality of the average density between products that remained without a comparative advantage and products that developed a comparative advantage was strongly rejected.
To avoid the influence of outliers, we removed from the sample observations below the 1st percentile and above the 99th percentile in both density calculated at the province level and density calculated at the country level. To control for possible errors in the recording of export data, we also excluded those observations in which the province p exports of eight-digit product i were zero in year t, but the comparative advantage for the same product and province was 1 or above 1 in year t + 5.
To avoid the influence of outliers, we removed those observations with a revealed comparative advantage index above the 99th percentile.