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Deviations from Zipf’s Law for American cities: an empirical examination

  • Rafael, González-Val

This work presents a simple method for calculating deviations regarding city size and the size which would correspond to it with a Pareto exponent equal to one unit (Zipf’s Law). Recent works show that when considering the entire sample without size restrictions, the estimated Pareto exponent tends to be much lower than one. Our aim is to analyse the distribution element by element, taking data from all American cities in 2000, and explain the deviation of the size predicted by Zipf’s Law and the real size of each city, using variables for each city of per capita income, distribution of employment among sectors, individuals by level of education, etc.; explicative variables which attempt to capture the influence of local externalities. To do this a Multinomial Logit Model is used.

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File URL: https://mpra.ub.uni-muenchen.de/11504/1/MPRA_paper_11504.pdf
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File URL: https://mpra.ub.uni-muenchen.de/20224/1/MPRA_paper_20224.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 11504.

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Date of creation: 10 Nov 2008
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Handle: RePEc:pra:mprapa:11504
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  1. Rosen, Kenneth T. & Resnick, Mitchel, 1980. "The size distribution of cities: An examination of the Pareto law and primacy," Journal of Urban Economics, Elsevier, vol. 8(2), pages 165-186, September.
  2. Kwok Tong Soo, 2004. "Zipf's law for cities: a cross country investigation," LSE Research Online Documents on Economics 19947, London School of Economics and Political Science, LSE Library.
  3. Edward L. Glaeser & Matthew E. Kahn, 2001. "Decentralized Employment and the Transformation of the American City," Harvard Institute of Economic Research Working Papers 1912, Harvard - Institute of Economic Research.
  4. Duncan Black & Vernon Henderson, 2003. "Urban evolution in the USA," Journal of Economic Geography, Oxford University Press, vol. 3(4), pages 343-372, October.
  5. Small, Kenneth A & Hsiao, Cheng, 1985. "Multinomial Logit Specification Tests," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(3), pages 619-27, October.
  6. Esteban Rossi-Hansberg & Mark L. J. Wright, 2006. "Urban structure and growth," Staff Report 381, Federal Reserve Bank of Minneapolis.
  7. Edward L. Glaeser & Joseph Gyourko & Raven E. Saks, 2006. "Urban growth and housing supply," Journal of Economic Geography, Oxford University Press, vol. 6(1), pages 71-89, January.
  8. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-99, June.
  9. Xavier Gabaix, 1999. "Zipf's Law for Cities: An Explanation," The Quarterly Journal of Economics, Oxford University Press, vol. 114(3), pages 739-767.
  10. Jan Eeckhout, 2004. "Gibrat's Law for (All) Cities," American Economic Review, American Economic Association, vol. 94(5), pages 1429-1451, December.
  11. J. Scott Long & Jeremy Freese, 2006. "Regression Models for Categorical Dependent Variables using Stata, 2nd Edition," Stata Press books, StataCorp LP, edition 2, number long2, September.
  12. Y Ioannides & Henry Overman, 2000. "Zipfs Law for Cities: An Empirical Examination," CEP Discussion Papers dp0484, Centre for Economic Performance, LSE.
  13. Gilles Duranton, 2007. "Urban Evolutions: The Fast, the Slow, and the Still," American Economic Review, American Economic Association, vol. 97(1), pages 197-221, March.
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