Gibrat's Law for (All) Cities: A Rejoinder
Yannis Ioannides () and
Spyros Skouras ()
No 740, Discussion Papers Series, Department of Economics, Tufts University from Department of Economics, Tufts University
We establish that the debate between Eeckhout (2004; 2009) and Levy (2009) has still not resolved the key issue of whether the distribution of large US urban places in 2000 is consistent with a lognormal for the intire size range. We resolve this by introducing a new distribution function which switches between a lognormal and a power distribution and estimating it with the data used by Eeckhout and Levy (2009). We find that there is a sudden transition from lognormality to power behavior as city populations icrease above sudden transition from lognormality to power behavior as city populations increase above 100,000. Gibrat's law holds for most cities but a power law holds for most of the population.
Keywords: Gibrat's Law; Zipf's law; upper tail; mixture of distributions; switching regressions; urban evolution; urban heirarchy (search for similar items in EconPapers)
JEL-codes: D30 D51 J61 R12 C24 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-geo and nep-ure
References: Add references at CitEc
Citations: View citations in EconPapers (14) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:tuf:tuftec:0740
Access Statistics for this paper
More papers in Discussion Papers Series, Department of Economics, Tufts University from Department of Economics, Tufts University Medford, MA 02155, USA.
Bibliographic data for series maintained by Marcus Weir ().