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Zipf's law is one of the most well-known empirical regularities of the city-size distribution and explaining it has long been the Holy Grail of urban economics. There is extensive research on the subject, where each city is treated equally in terms of transactions with other cities. Recent developments in network theory facilitate the examination of asymmetric communication patterns among the cities. Under the scale-free network framework, the chance of observing extremes becomes lower than the Gaussian distribution predicts and therefore it explains the emergence of large clusters. City-size distributions share the same pattern. This paper proposes a way to incorporate network structure into the urban economics with a view to explaining the city-size distribution.
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