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Macroeconomic Implications of Agglomeration

Author

Listed:
  • Toni M. Whited

    (University of Rochester)

  • Jonas D.M. Fisher

    (Chicago Fed)

  • Morris A. Davis

    (University of Wisconsin)

Abstract

We construct a dynamic general equilibrium model of cities and use it to estimate the effect of local agglomeration on per capita consumption growth. Agglomeration affects growth through the density of economic activity: higher production per unit of land raises local productivity. Firms take productivity as given; produce using a technology that has constant returns in developed land, capital, and labor; and accumulate land and capital. If land prices are rising, as they are empirically, firms economize on land. This behavior increases density and contributes to growth. We use a panel of U.S. cities and our model's predicted relationship among wages, output prices, housing rents, and labor quality to estimate the net e®ect of agglomeration on local wages. The impact of agglomeration on the level of wages is estimated to be 2 percent. Combined with our model and observed increases in land prices, this estimate implies that agglomeration raises per capita consumption growth by 10 percent.

Suggested Citation

  • Toni M. Whited & Jonas D.M. Fisher & Morris A. Davis, 2010. "Macroeconomic Implications of Agglomeration," 2010 Meeting Papers 1330, Society for Economic Dynamics.
  • Handle: RePEc:red:sed010:1330
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Gerald A. Carlino, 2011. "Three keys to the city: resources, agglomeration economies, and sorting," Business Review, Federal Reserve Bank of Philadelphia, issue Q3, pages 1-13.
    2. Pierre-Philippe Combes & Gilles Duranton & Laurent Gobillon, 2016. "The Production Function for Housing: Evidence from France," PSE Working Papers halshs-01400852, HAL.
    3. Davis, Morris A. & Fisher, Jonas D. M. & Veracierto, Marcelo, 2013. "Gross Migration, Housing and Urban Population Dynamics," Working Paper Series WP-2013-19, Federal Reserve Bank of Chicago.
    4. Jeffrey Lin, 2011. "Urban productivity advantages from job search and matching," Business Review, Federal Reserve Bank of Philadelphia, issue Q1, pages 9-16.
    5. Wukuang Cun & M. Hashem Pesaran, 2018. "Land Use Regulations, Migration and Rising House Price Dispersion in the U.S," CESifo Working Paper Series 7007, CESifo Group Munich.
    6. repec:eee:moneco:v:93:y:2018:i:c:p:89-109 is not listed on IDEAS
    7. Huang, Daisy J. & Leung, Charles K. & Qu, Baozhi, 2015. "Do bank loans and local amenities explain Chinese urban house prices?," China Economic Review, Elsevier, vol. 34(C), pages 19-38.
    8. Jeffrey Brinkman & Daniele Coen-Pirani & Holger Sieg, 2012. "Estimating a dynamic equilibrium model of firm location choices in an urban economy," Working Papers 12-26, Federal Reserve Bank of Philadelphia.
    9. Jan Eeckhout & Roberto Pinheiro & Kurt Schmidheiny, 2010. "Spatial Sorting: Why New York, Los Angeles and Detroit Attract the Greatest Minds as well as the Unskilled," CESifo Working Paper Series 3274, CESifo Group Munich.
    10. repec:bla:etrans:v:25:y:2017:i:3:p:439-469 is not listed on IDEAS
    11. Brinkman, Jeffrey C., 2016. "Congestion, agglomeration, and the structure of cities," Journal of Urban Economics, Elsevier, vol. 94(C), pages 13-31.
    12. Herkenhoff, Kyle F. & Ohanian, Lee E. & Prescott, Edward C., 2018. "Tarnishing the golden and empire states: Land-use restrictions and the U.S. economic slowdown," Journal of Monetary Economics, Elsevier, vol. 93(C), pages 89-109.
    13. Davis, Morris A. & Van Nieuwerburgh, Stijn, 2015. "Housing, Finance, and the Macroeconomy," Handbook of Regional and Urban Economics, Elsevier.

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