Abstract
We investigate into the rank-size distributions of urban agglomerations for India between 1981 to 2011. The incidence of a power law tail is prominent. A relevant question persists regarding the evolution of the power tail coefficient. We have developed a methodology to meaningfully track the power law coefficient over time, when a country experience population growth. A relevant dynamic law, Gibrat’s law, is empirically tested in this connection. We argue that these empirical findings for India are in contrast with the findings in case of China, another country with population growth but monolithic political system.
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Gangopadhyay, K., Basu, B. (2013). Evolution of Zipf’s Law for Indian Urban Agglomerations Vis-à-Vis Chinese Urban Agglomerations. In: Abergel, F., Chakrabarti, B., Chakraborti, A., Ghosh, A. (eds) Econophysics of Systemic Risk and Network Dynamics. New Economic Windows. Springer, Milano. https://doi.org/10.1007/978-88-470-2553-0_8
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DOI: https://doi.org/10.1007/978-88-470-2553-0_8
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