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Cesar A. Hidalgo @cesifoti
, 13 tweets, 5 min read Read on Twitter
What knowledge do firms need to survive? In this paper we use data on the work history of all formal workers in Brazil to measure the industry-specific, occupation-specific, & location-specific knowledge that workers bring into new firms:… (thread 1/)
We measure these three knowledge channels by looking at workers that switched jobs, focusing on changes among related and unrelated industries, occupations, and locations. 2/
For instance, a worker moving between related industries (banking & insurance) should carry more industry-specific knowledge than a worker moving between two unrelated industries (e.g. banking and soybean farming) 3/
We then look at the effect of these three knowledge flow networks in the probability that new firms survive or grow. We used a variety of statistical models: a fixed-effect panel regression, a cox-proportional hazards model, and a new type of Bartik instrument in a 2SLS. 4/
We also separated among pioneer firms (firms operating in an industry that was not present in a location) & non-pioneer firms (firms operating in an industry that was present in a location). 5/
For pioneers, we found that survival increases when they hire workers with industry & location specific knowledge, but not with occupation-specific knowledge. This is after controlling for schooling, firm size, wages, & industry, location, & time fixed-effects 6/
This finding is confirmed by a cox proportional hazards model, and by a Bartik 2SLS, which uses national level fluctuations in an industry as an exogenous shock in the local labor supply of related industries. 7/
We also compared the survival rates of pioneers & non-pioneers (in the Appendix), finding that the effects of industry-specific knowledge are more pronounced for pioneers. Occupation-specific knowledge appears to play a minor role for non-pioneers 8/…
These results are interesting for a few reasons. First, they are helping us understand the role of relatedness in diversification at a more micro-level. 9/
The fact that regions are more likely to enter related economic activities is well known, but here, we can see exactly who entered, who was hired, & the experience each worker had. By splitting experience into 3 channels we can finally see inside relatedness' "black-box."10/
The results also suggest that industry-specific knowledge may be less transferable, more valuable (it enhances firm survival), and maybe more tacit than occupation-specific knowledge. 11/
More importantly (to me), is the fact that this paper represents the debut of @Cristian_jf as first author in a high impact factor journal. Cristian Jara is a fantastic scholar who deserves all the credit & will soon complete his PhD in my group. Keep him on your radar! 12/
The paper was also a collaboration between three members of @CollectiveMIT (Cristian Jara, Bogang Ju, and I) & @HarvardEcon (Ed Glaeser). It shows that by collaborating across disciplines, we can create work combining the best of different academic worlds. /End_Thread
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