Estimating Poverty in India Without Expenditure Data: A Survey-to-Survey Imputation Approach

David Newhouse, Pallavi Vyas
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引用次数: 6

Abstract

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.
在没有支出数据的情况下估计印度的贫困:一种调查对调查的归因方法
本文采用了一种创新的方法,在缺乏最近支出数据的情况下估计印度的贫困状况。该方法利用2004-05年、2009-10年和2011-12年的支出数据,将家庭支出纳入2014-15年的耐用品支出调查。按照每天1.90美元的国际贫困线,首选模型预测2014-15年城市地区的人口贫困率为10%,农村地区为16.4%,这意味着全国贫困率为14.6%。相对于人均国内生产总值(GDP)增长的隐含贫困弹性在过去经验的范围内,国内生产总值增长较高的州预测贫困减少程度更高。在验证测试中,该模型的预测在预测2011-12年时的表现与世界银行目前的调整方法相当,但在预测2004-05年时要准确得多。三种可供选择的标准给出了相对较高的贫困估计值。结果表明,在可行的情况下,调查与调查之间的归算是一种较好的替代办法,而不是将基于调查的贫穷估计数调整到以后的年份。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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