Reducing out-of-pocket expenditures to reduce poverty: a disaggregated analysis at rural-urban and state level in India

Abstract

Out-of-pocket (OOP) expenditure on health care has significant implications for poverty in many developing countries. This paper aims to assess the differential impact of OOP expenditure and its components, such as expenditure on inpatient care, outpatient care and on drugs, across different income quintiles, between developed and less developed regions in India. It also attempts to measure poverty at disaggregated rural-urban and state levels. Based on Consumer Expenditure Survey (CES) data from the National Sample Survey (NSS), conducted in 1999-2000, the share of households' expenditure on health services and drugs was calculated. The number of individuals below the state-specific rural and urban poverty line in 17 major states, with and without netting out OOP expenditure, was determined. This also enabled the calculation of the poverty gap or poverty deepening in each region. Estimates show that OOP expenditure is about 5% of total household expenditure (ranging from about 2% in Assam to almost 7% in Kerala) with a higher proportion being recorded in rural areas and affluent states. Purchase of drugs constitutes 70% of the total OOP expenditure. Approximately 32.5 million persons fell below the poverty line in 1999-2000 through OOP payments, implying that the overall poverty increase after accounting for OOP expenditure is 3.2% (as against a rise of 2.2% shown in earlier literature). Also, the poverty headcount increase and poverty deepening is much higher in poorer states and rural areas compared with affluent states and urban areas, except in the case of Maharashtra. High OOP payment share in total health expenditures did not always imply a high poverty headcount; state-specific economic and social factors played a role. The paper argues for better methods of capturing drugs expenditure in household surveys and recommends that special attention be paid to expenditures on drugs, in particular for the poor. Targeted policies in just five poor states to reduce OOP expenditure could help to prevent almost 60% of the poverty headcount increase through OOP payments.