Accounting for income inequality: empirical evidence from India
Uma Rani (),
Jaya Krishnakumar and
Maurizio Bigotta ()
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Uma Rani: International Labour Office
Jaya Krishnakumar: University of Geneva
Indian Economic Review, 2017, vol. 52, issue 1, 193-229
Abstract This paper decomposes income inequality using the regression-based decomposition technique. The paper analyses the role of education, experience, employment status, industry and their interactions in accounting for differences in income and its inequality in India over the past three decades. The results clearly show that education is the most dominant factor contributing to inequality in both rural and urban areas. Separate inequality decomposition analyses for each employment status group show that although education is the most important factor contributing to inequality for the salaried, and to an extent for the self-employed workers, it is much less important for the casual workers. Other factors such as household size, size of land holdings, and regional variations contribute to increasing inequality among casual and self-employed worker households.
Keywords: Income inequality; Regression-based decompositions; Informal labour; Education; India; J21; J24; C21; D63 (search for similar items in EconPapers)
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