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A spatial analysis of employment multipliers in the US

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Abstract

The actual effectiveness of employment promotion policies depends on the ability of the intervention at creating new jobs in the targeted sector, but also, to a large extent, on the impact they have on other parts of the local economy. Estimating the latter effect is therefore quite important for regional economic development policies. Along the lines of Moretti (Am Econ Rev Pap Proc 100:373–377, 2010), we present an empirical analysis of local employment multipliers using data on 123 US Metropolitan Statistical Areas over the period 1980–2010. From the methodological point of view, in this work not only endogeneity (via instrumental variables estimates), but also spatial spillovers are taken into account. According to the results, the magnitude of the multiplier could be rather limited. On the other hand, there is clear indication that the impact of these interventions is not fully contained within the local economy and they have a positive effect on closely surrounding ones.

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Notes

  1. The elasticity of housing supply depends on geography and land use regulations. The elasticity of local labor depends on the residents’ tastes for leisure, the local pool of unemployment and the degree of labor mobility across cities.

  2. Details on this technique can be found in Vega and Elhorst (2015). We thank the authors for providing the MATLAB routine.

  3. Since data in the Integrated Public Use Microdata Series are originally classified according to the 1990 Census Bureau industrial classification scheme, we mapped them into the two-digit NAICS code classification using industry code crosswalks provided by the US Census Bureau. As in Moretti (2010) we exclude agriculture, mining, government and the military.

  4. The MAUP relates to the fact that imposing artificial boundaries on a continuous geographical phenomenon generates artificial spatial patterns and the spatial patterns generated at different spatial scales or with different aggregation criteria differ from each other.

  5. We have also estimated the same model using a W matrix with no threshold. Results are analogous but the spillover effect becomes slightly weaker (0.0930 with a p-level of 0.069).

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Acknowledgments

We gratefully acknowledge two anonymous referees for their insightful comments and constructive suggestions that have helped to significantly improve this work. Needless to say, all errors and remaining infelicities of style are our own responsibility.

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Correspondence to Stefano Magrini.

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Gerolimetto, M., Magrini, S. A spatial analysis of employment multipliers in the US. Lett Spat Resour Sci 9, 277–285 (2016). https://doi.org/10.1007/s12076-015-0157-z

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