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A nonparametric analysis of the growth process of Indian cities

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  • Luckstead, Jeff
  • Devadoss, Stephen

Abstract

We examine the growth process of the largest cities in India for the post economic reform period 1991–2011 to analyze Gibrat’s and Zipf’s laws by applying nonparametric estimation. The results from stochastic kernel, contour plots, and expected growth rate and variance conditional on city size establish that Gibrat’s law holds for largest cities in India, i.e., city growth is independent of population size, and the local Zipf exponent is around one and stable. Gibrat’s law is also confirmed by the parametric regression of the aggregate relationship of the growth rate on city size.

Suggested Citation

  • Luckstead, Jeff & Devadoss, Stephen, 2014. "A nonparametric analysis of the growth process of Indian cities," Economics Letters, Elsevier, vol. 124(3), pages 516-519.
    • Handle: RePEc:eee:ecolet:v:124:y:2014:i:3:p:516-519
    DOI: 10.1016/j.econlet.2014.07.022
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    References listed on IDEAS

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    Cited by:

    1. Luckstead, Jeff & Devadoss, Stephen, 2014. "Do the world’s largest cities follow Zipf’s and Gibrat’s laws?," Economics Letters, Elsevier, vol. 125(2), pages 182-186.
    2. Devadoss, Stephen & Luckstead, Jeff, 2015. "Growth process of U.S. small cities," Economics Letters, Elsevier, vol. 135(C), pages 12-14.
    3. Devadoss, Stephen & Luckstead, Jeff, 2016. "Size distribution of U.S. lower tail cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 158-162.

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    More about this item

    Keywords

    Gibrat’s law; Growth process; Indian cities; Local Zipf exponent;
    All these keywords.

    JEL classification:

    • D30 - Microeconomics - - Distribution - - - General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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