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"A Simple Model of City Crowdedness"

Authors: Jordan Rappaport;

"A Simple Model of City Crowdedness"

Abstract

Population density varies widely across U.S. cities. A calibrated general equilibrium model in which productivity and quality-of-life differ across locations can account for such variation. Individuals derive utility from consumption of a traded good, a nontraded good, leisure, and quality-of-life. The traded and nontraded goods are produced by combining mobile labor, mobile capital, and non-mobile land. An eight-fold increase in population density requires an approximate 50 percent productivity differential or an approximate 20 percent compensating differential. A thirty-two-fold increase in population density requires an approximate 95 percent productivity differential or a 33 percent compensating differential. Empirical evidence suggests productivity and quality-of-life differentials of this magnitude are plausible. The model implies that broad-based technological progress can induce substantial migration to localities with high quality-of-life.

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Keywords

Productivity ; Population ; Quality of life ; Cities and towns

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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