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The economic performance of cities: a Markov-switching approach

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

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.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2006-056.

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Date of creation: 2007
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Publication status: Published in Journal of Urban Economics, November 2008, 64(3), pp. 538-50
Handle: RePEc:fip:fedlwp:2006-056
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  2. Glaeser, E.L. & Scheinkman, J.A., 1993. "Economic Growth in a Cross-Section of Cities," Harvard Institute of Economic Research Working Papers 1645, Harvard - Institute of Economic Research.
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  21. Engelhardt, Gary V., 2003. "Nominal loss aversion, housing equity constraints, and household mobility: evidence from the United States," Journal of Urban Economics, Elsevier, vol. 53(1), pages 171-195, January.
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  25. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
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