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Consumer expenditure distribution in India, 1983–2007: Evidence of a long Pareto tail

Author

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  • Ghosh, Abhik
  • Gangopadhyay, Kausik
  • Basu, B.

Abstract

This work presents a comprehensive study of the evolution of the expenditure distribution in India. The consumption process is theoretically modeled based on certain physical assumptions. The proposed statistical model for the expenditure distribution may follow either a double Pareto distribution or a mixture of log-normal and Pareto distribution. The goodness-of-fit tests with the Indian data, collected from the National Sample Survey Organisation Reports for the years of 1983–2007, validate the proposal of a mixture of log-normal and Pareto distribution. The relative weight of the Pareto tail has a remarkable magnitude of approximately 10%–20% of the population. Moreover, though the Pareto tail is widening over time for the rural sector only, there is no significant change in the overall inequality measurement across the entire period of study.

Suggested Citation

  • Ghosh, Abhik & Gangopadhyay, Kausik & Basu, B., 2011. "Consumer expenditure distribution in India, 1983–2007: Evidence of a long Pareto tail," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 83-97.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:1:p:83-97
    DOI: 10.1016/j.physa.2010.06.018
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    References listed on IDEAS

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    1. Erich Battistin & Richard Blundell & Arthur Lewbel, 2009. "Why Is Consumption More Log Normal than Income? Gibrat's Law Revisited," Journal of Political Economy, University of Chicago Press, vol. 117(6), pages 1140-1154, December.
    2. Xavier Sala-i-Martin, 2006. "The World Distribution of Income: Falling Poverty and … Convergence, Period," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 351-397.
    3. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, September.
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    1. Gao, Li, 2015. "Evolution of consumption distribution and model of wealth distribution in China between 1995 and 2012," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 76-86.
    2. Touzani, Samir & Van Buskirk, Robert, 2016. "Estimating sales and sales market share from sales rank data for consumer appliances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 266-276.
    3. Anand Sahasranaman, 2020. "Long term dynamics of poverty transitions in India," Papers 2010.06954, arXiv.org.
    4. Chatterjee, Arnab & Chakrabarti, Anindya S. & Ghosh, Asim & Chakraborti, Anirban & Nandi, Tushar K., 2016. "Invariant features of spatial inequality in consumption: The case of India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 169-181.
    5. Parikh, Kirit S. & Parikh, Jyoti K., 2016. "Realizing potential savings of energy and emissions from efficient household appliances in India," Energy Policy, Elsevier, vol. 97(C), pages 102-111.
    6. Anand Sahasranaman & Henrik Jeldtoft Jensen, 2021. "Dynamics of reallocation within India’s income distribution," Indian Economic Review, Springer, vol. 56(1), pages 1-23, June.

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