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Testing for Monocentricity

Authors: Daniel P. McMillen;

Testing for Monocentricity

Abstract

The monocentric city model of Muth (1969) and Mills (1972) is still the dominant model of urban spatial structure. Its central predictions – that population density, land values, and house prices fall with distance from the city center – have been the subject of repeated empirical testing. Indeed, one objective of the model was to explain a set of stylized empirical facts, and extensions of the model were developed in response to empirical testing. This close cooperation between theory and empirical work is one of the hallmarks of the field of urban economics. A consensus appears to have developed that the monocentric city model is no longer an accurate depiction of urban spatial structure. This view is partly due to the unrealistic nature of the model’s assumptions. Clearly not everyone works in the central city, and modern urban areas may be viewed more aptly as polycentric rather than monocentric. The central behavioral assumption of the model, that workers attempt to minimize their commuting cost, is called into question by the literature on “wasteful commuting” (Hamilton 1982). O’Sullivan’s (2002) popular textbook perpetuates the notion that the monocentric city model is designed to explain an old-fashioned city by listing as one of the assumptions “horse-drawn wagons,” implying that the model does not apply to a modern city with cars. In this chapter, I review some of the empirical evidence on the monocentric city model’s predictions. I contend that the demise of the model is exaggerated. The central city still dominates urban spatial patterns, and the basic insights of the model apply to more complex polycentric cities. Much of the apparent decline in the explanatory power of the monocentric city model is actually a misunderstanding of the empirical evidence. And, importantly, many of the ways in which the model now fails are in fact explained by the comparative-statics predictions

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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!
24
Top 10%
Top 10%
Average
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