Data and code for: Local Industrial Policy and Sectoral Hubs
Principal Investigator(s): View help for Principal Investigator(s) Esteban Rossi-Hansberg, Princeton University; Pierre-Daniel Sarte, Federal Reserve Bank of Richmond; Felipe Schwartzman, Federal Reserve Bank of Richmond
Version: View help for Version V1
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application/pdf | 135.9 KB | 02/04/2021 10:03:AM |
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Project Citation:
Rossi-Hansberg, Esteban, Sarte, Pierre-Daniel, and Schwartzman, Felipe. Data and code for: Local Industrial Policy and Sectoral Hubs. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-04-28. https://doi.org/10.3886/E131723V1
Project Description
Summary:
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We study the desirability of industrial policies that generate sectoral hubs using a quantitative spatial model with cognitive non-routine and other occupations. The productivity of each occupation in an industry depends on sector-specific production externalities, which we estimate using a model-implied instrumental variable approach. We find that the optimal policy gives rise to national hubs in coastal cities in tradeable services, like Professional Services, and smaller regional hubs in less tradable services, like Health and Education. The optimal policy prescribes developing Manufacturing in smaller towns. We decompose the implied changes in local costs and the available varieties in each sector.
Scope of Project
Subject Terms:
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Industrial Policy;
Quatitative Spatial Model;
Sectoral Hubs
JEL Classification:
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R12 Size and Spatial Distributions of Regional Economic Activity
R12 Size and Spatial Distributions of Regional Economic Activity
Geographic Coverage:
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United States
Time Period(s):
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2011 – 2015 (stacked ACS data 2011-15)
Universe:
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Industry/City-level data on employment, wages and other auxiliary variables.
Data Type(s):
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administrative records data;
aggregate data;
census/enumeration data;
geographic information system (GIS) data;
survey data
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