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On the effects of skill upgrading in the presence of spatial labor market frictions: an agent-based analysis of spatial policy design

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  • Dawid, Herbert
  • Gemkow, Simon
  • Harting, Philipp
  • Neugart, Michael

Abstract

We report results of economic policy experiments carried out in the framework of the EURACE agent-based macroeconomic model featuring a distinct geographical dimension and heterogeneous workers with respect to skill types. Using a calibrated model able to replicate a range of stylized facts of goods and labor markets, it is examined in how far e ffects di ffer if policy measures aiming at an improvement of general skills are uniformly spread over all regions in the economy or focused in one particular region. We find that it depends on the level of spatial frictions on the labor market how the spatial distribution of policy measures aff ects the e ffects of the policy. Furthermore, we show that a reduction in spatial frictions does not necessarily improve the growth of output and household income.
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  • Dawid, Herbert & Gemkow, Simon & Harting, Philipp & Neugart, Michael, 2009. "On the effects of skill upgrading in the presence of spatial labor market frictions: an agent-based analysis of spatial policy design," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56074, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:56074
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/56074/
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    Cited by:

    1. Michael Neugart & Matteo G. Richiardi, 2012. "Agent-based models of the labor market," LABORatorio R. Revelli Working Papers Series 125, LABORatorio R. Revelli, Centre for Employment Studies.
    2. Herbert Dawid & Philipp Harting & Sander Hoog & Michael Neugart, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 467-538, March.
    3. Chen, Siyan & Desiderio, Saul, 2018. "What moves the Beveridge curve and the Phillips curve: An agent-based analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-30.
    4. Wei Zhao & Yi Lu & Genfu Feng, 2019. "How Many Agents are Rational in China’s Economy? Evidence from a Heterogeneous Agent-Based New Keynesian Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 575-611, August.
    5. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    6. Marcel Ausloos & Herbert Dawid & Ugo Merlone, 2015. "Spatial Interactions in Agent-Based Modeling," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 353-377, Springer.
    7. Herbert Dawid & Simon Gemkow & Philipp Harting & Michael Neugart, 2013. "Labor Market Integration Policies and The Convergence of Regions: The Role of Skills and Technology Diffusion," Economic Complexity and Evolution, in: Guido Buenstorf & Uwe Cantner & Horst Hanusch & Michael Hutter & Hans-Walter Lorenz & Fritz Rahmeyer (ed.), The Two Sides of Innovation, edition 127, pages 167-186, Springer.
    8. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. "Debt, deleveraging and business cycles: An agent-based perspective," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-49.
    9. Cardullo, Gabriele & Guerci, Eric, 2019. "Interpreting the Beveridge curve. An agent-based approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 84-100.
    10. Gross, Marco, 2022. "Beautiful cycles: A theory and a model implying a curious role for interest," Economic Modelling, Elsevier, vol. 106(C).
    11. Jung-Seung Yang, 2022. "Dynamics of Firm’s Investment in Education and Training: An Agent-based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1317-1351, December.
    12. Özge Dilaver & Robert Calvert Jump & Paul Levine, 2018. "Agent‐Based Macroeconomics And Dynamic Stochastic General Equilibrium Models: Where Do We Go From Here?," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1134-1159, September.
    13. Patrick Mellacher & Timon Scheuer, 2021. "Wage Inequality, Labor Market Polarization and Skill-Biased Technological Change: An Evolutionary (Agent-Based) Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 233-278, August.
    14. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.

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