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The economic performance of cities: a Markov-switching approach

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  • Michael T. Owyang
  • Jeremy M. Piger
  • Howard J. Wall
  • Christopher H. Wheeler

Abstract

This paper examines the determinants of employment growth in metro areas. To obtain growth rates, we use a Markov-switching model that separates a city?s growth path into two distinct phases (high and low), each with its own growth rate. The simple average growth rate over some period is, therefore, the weighted average of the high-phase and low-phase growth rates, with the weight being the frequency of the two phases. We estimate the effects of a variety of factors separately for the high-phase and low-phase growth rates, along with the frequency of the low phase. We find that growth in the high phase is related to human capital, industry mix, and average firm size. In contrast, we find that growth in the low phase is mostly related to industry mix, specifically, the relative importance of manufacturing. Finally, the frequency of the low phase appears to be related to the level of non-education human capital, but to none of the other variables. Overall, our results strongly reject the notion that city-level characteristics influence employment growth equally across the phases of the business cycle.

Suggested Citation

  • Michael T. Owyang & Jeremy M. Piger & Howard J. Wall & Christopher H. Wheeler, 2007. "The economic performance of cities: a Markov-switching approach," Working Papers 2006-056, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2006-056
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    Cited by:

    1. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    2. Paolo Di Caro, 2015. "Recessions, recoveries and regional resilience: evidence on Italy," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 8(2), pages 273-291.
    3. Camacho, Maximo & Leiva-Leon, Danilo, 2019. "The Propagation Of Industrial Business Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 23(1), pages 144-177, January.
    4. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2013. "Discordant city employment cycles," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 367-384.
    5. Ana Gómez-Loscos & M. Dolores Gadea & Eduardo Bandres, 2020. "Business cycle patterns in European regions," Empirical Economics, Springer, vol. 59(6), pages 2639-2661, December.
    6. Ioannides, Yannis M., 2018. "A DMP model of intercity trade," Labour Economics, Elsevier, vol. 50(C), pages 97-111.
    7. Ghent, Andra C. & Owyang, Michael T., 2010. "Is housing the business cycle? Evidence from US cities," Journal of Urban Economics, Elsevier, vol. 67(3), pages 336-351, May.
    8. Francis Neville & Owyang Michael T. & Sekhposyan Tatevik, 2012. "The Local Effects of Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(2), pages 1-38, March.
    9. Hernández-Murillo, Rubén & Owyang, Michael T. & Rubio, Margarita, 2017. "Clustered housing cycles," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 185-197.
    10. Sungyup Chung, 2016. "Assessing the regional business cycle asymmetry in a multi-level structure framework: a study of the top 20 US MSAs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 229-252, January.
    11. Kristie M. Engemann & Ruben Hernandez-Murillo & Michael T. Owyang, 2011. "Regional aggregation in forecasting: an application to the Federal Reserve’s Eighth District," Review, Federal Reserve Bank of St. Louis, vol. 93(May), pages 207-222.
    12. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
    13. Maximo Camacho & Matias Pacce & Camilo Ulloa, 2017. "Business cycle phases in Spain," Working Papers 17/20, BBVA Bank, Economic Research Department.
    14. Amy Y. Guisinger & Michael T. Owyang & Daniel Soques, 2020. "Industrial Connectedness and Business Cycle Comovements," Working Papers 2020-052, Federal Reserve Bank of St. Louis, revised 04 Aug 2021.
    15. Wall, Howard J., 2013. "The employment cycles of neighboring cities," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 177-185.
    16. Sungyup Chung, 2016. "Assessing the regional business cycle asymmetry in a multi-level structure framework: a study of the top 20 US MSAs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 229-252, January.
    17. Sergei S. Shibaev, 2016. "Recession Propagation In Small Regional Economies: Spatial Spillovers And Endogenous Clustering," Working Paper 1369, Economics Department, Queen's University.
    18. Camacho, Máximo & Pacce, Matias & Ulloa, Camilo, 2018. "Regional Business Cycle Phases in Spain/Ciclos económicos regionales en España," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 857-896, Septiembr.
    19. Rachidi Kotchoni & Dalibor Stevanovic & Stéphane Surprenant, 2019. "Identification des points de retournement du cycle économique au Canada," CIRANO Project Reports 2019rp-05, CIRANO.
    20. Leora Friedberg & Michael Owyang & Anthony Webb, 2008. "Identifying Local Differences in Retirement Patterns," Working Papers, Center for Retirement Research at Boston College wp2008-18, Center for Retirement Research, revised Dec 2008.

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    Business cycles; Cities and towns;

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