Debasree Bose & Arijita Dutta
UNU-MERIT working papers #2017-023
Introduction: India bears a disproportionate burden of open defecation in spite of investing more and more funds and ushering in several institutional efforts including Swachh Bharat Mission in the recent past. A large share of rural households still lack basic sanitation facilities in India and members practice open defecation.
Objective: The study endeavours to examine the existing anomaly between meagre sanitation productivity and enhanced resource allocation in rural sanitation in India. The study attempts to develop an instrument to monitor the differential regional performances across India.
Methodology: The paper applied data exploration to identify spatial inequality and economic inequity across the nation. The extent of inequality and inequity are measured through appropriate measure statistical indices. To quantify the level of efficiency of the districts in translating social spending in to sanitation coverage and usage, non-parametric data envelopment technique (DEA) has been applied to identify best-in-class performers. Finally, a regional sanitation performance index that premises on three dimensions of performance: efficiency, equity and equality is introduced.
Findings: Efficiency analysis reveals huge potential of India to attain a far higher sanitation access and usage with the given flow of social spending. The study unfolds that India is suffering from dual burden of spatial inequality and economic inequity. While the regional divergence in sanitation access escalates, households from lower income group increasingly construct toilets in comparison to their higher income counterpart even within the same region, originating a paradox in sanitation in India.
Conclusion: The performance index has the potential to be served as an instrument to monitor and evaluate regional performances on sanitation and to inform investment decisions for targeted improvement. This index is expected to serve as a useful tool for policy watch as it clearly identifies the best and the worst performers by allowing fair comparison among them.