Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257028 
Year of Publication: 
2019
Citation: 
[Journal:] Economies [ISSN:] 2227-7099 [Volume:] 7 [Issue:] 4 [Article No.:] 96 [Publisher:] MDPI [Place:] Basel [Year:] 2019 [Pages:] 1-27
Publisher: 
MDPI, Basel
Abstract: 
This article examines the determinants of household income among urban and rural areas in India and evaluates households' performance with different characteristics in terms of poverty. It uses four rounds of data from the consumer expenditure survey (50th, 1993/1994; 55th, 1999/2000; 61st, 2004/2005; and 66th, 2009/2010) by the National Sample Survey Organization (NSSO) in the empirical section. This study consists of two main parts. In the first, it looks at the impact of the characteristics of the head of the household (age, educational level, marital status, and gender) and household characteristics (main occupational type, household size, and social status) on monthly per capita expenditure through conditional mean least squares (LS) regressions and conditional quantile regressions. Households headed by those who are older, married, belonging to lower castes, and living in less-developed states are more likely to be in poverty. In the second part, the article explores stochastic dominance rankings relative to large classes of welfare functions/preferences between pairwise sub-groups identified by the survey year, gender, social status, and occupational type of the household heads. Our results show that 'inferior groups' such as 'Backward classes', agricultural labor in rural areas, and casual labor in urban areas are vulnerable and may be targeted for poverty alleviation strategies. The first part sheds light on key determinants of household expenditure, while the second provides a picture of poverty outcomes which helps identify potential target groups for poverty-alleviation strategies.
Subjects: 
income determinant
poverty
quantile regression
stochastic dominance
JEL: 
C31
D63
O15
O18
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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