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Income convergence in India: a nonparametric approach

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  • Arfat Ahmad Sofi

    () (Pondicherry University)

  • S. Raja Sethu Durai

    (Pondicherry University)

Abstract

Abstract This study tests the convergence hypothesis across 22 Indian states for the time period from 1980–1981 to 2010–2011. Using second order Gaussian Kernel density function, results reveal a multi-modal behavior of income distribution with significant signs of club formation across different income strata over the transitional process. The results from quantile estimation shows that Indian states are diverging in absolute sense however converging on conditional basis. Moving from lower to higher quantile the strength of absolute divergence weakens whereas the conditional convergence is getting stronger.

Suggested Citation

  • Arfat Ahmad Sofi & S. Raja Sethu Durai, 2016. "Income convergence in India: a nonparametric approach," Economic Change and Restructuring, Springer, vol. 49(1), pages 23-40, February.
  • Handle: RePEc:kap:ecopln:v:49:y:2016:i:1:d:10.1007_s10644-015-9169-3
    DOI: 10.1007/s10644-015-9169-3
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    Keywords

    Growth; Convergence; Kernel density; Quintile regression; Panel data; India;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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