Estimating Poverty in India without Expenditure Data

A Survey-to-Survey Imputation Approach

Bibliographic Data

ID19916865
AuthorsDavid Newhouse (0000-0003-4051-8130, World Bank Group), Pallavi Vyas (0000-0002-6283-9325, Ahmedabad University)
Year2019
Publication date2019-06-01
Open AccessNo
TypeBOOK
PublisherWorld Bank, Washington, DC (PUBLISHER)
DOI10.1596/1813-9450-8878
OpenAlexW2949080015
LanguageEN
Citations received5
References cited13

This paper applies an innovative method to estimate poverty in India in the absence of recent expenditure data. The method utilizes expenditure data from 2004-05, 2009-10, and 2011-12 to impute household expenditure into a survey of durable goods expenditure conducted in 2014-15. At the $1.90 per day international poverty line, the preferred model predicts a 2014-15 head- count poverty rate of 10 percent in urban areas and 16.4 percent in rural areas, implying a poverty rate of 14.6 percent nationally. The implied poverty elasticity with respect to growth in per capita Gross Domestic Product (GDP) is within the range of past experience, and states with higher gross domestic product growth saw greater predicted poverty reductions. In validation tests, the model's predictions perform comparably to the World Bank's current adjustment method when predicting for 2011-12 but they are far more accurate when predicting for 2004-05. Three alternative specifications give moderately higher estimates of poverty. The results indicate that survey-to-survey imputation, when feasible, is a preferable alternative to the current method used to adjust survey-based poverty estimates to later years

Econometrics · Economic growth · Economics · Environmental health · Geography · Imputation (statistics) · Missing data · Poverty · Statistics · Survey data collection · Survey sampling · Agricultural risk and resilience · Income, Poverty, and Inequality · Mathematics · Medicine · Social and Economic Development in India

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