Finally, the paper demonstrates how a utility can leverage its administrative billing database to recover estimates of household willingness to pay for power and use this information to set fixed prices. Based on the social marginal cost estimate and the historical consumption data from the administrative data set, the paper propose a two-part tariff which allows the utility to fully break-even on its costs. As variable costs are set to the social marginal cost for all households, the recommended tariff does not distort consumption by charging some households more than others, achieving the goal of economic efficiency. The recommended tariff design leads to progressive prices: it generates an average gain of Rs. 4.5 to Rs. 10 for households at the lowest quintile of the income distribution and an average loss of Rs. 20 per month for households in the top quintile.

The proposed schedule aims to stem losses from the residential sector and is likely to benefit both consumers and utilities. Other sources of technical losses, either related to transmission or distribution, are not studied in this paper.

The remainder of the paper proceeds as follows. Section II sets the context by describing the current challenges facing the Indian power sector and summarizes previous topically or methodologically related research. Section III describes the data sets used in our analysis and presents descriptive statistics to provide background for our analysis. Section IV describes the two-step econometric model of energy services demand. Section V describes the estimation procedure and results. Section VI estimates the social marginal cost for electricity in Rajasthan and describes counterfactual tariff experiments using own-price elasticity estimates from the demand model. Section VII concludes the paper.

# **SECTION II:  Residential Electricity Prices and Policies in India and Rajasthan**

Electricity for household consumption accounts for approximately a quarter of all electricity sales in India. As shown in Figure 1, the share of residential end-use of electricity was approximately 27 percent of all sales in 2014-15 and varied between 50 to 17 percent in the larger states. A sizable portion of these sales made by publicly-owned electricity distribution companies (“discoms”), were at prices significantly lower than the average revenue required to recover discoms’ costs. The resulting losses on discoms’ balance sheets, account for 83 to 90 percent of all financial losses in the power sector.<sup>1</sup> In Figure 2, discoms’ losses are decomposed into losses due to collections, distribution and underpricing of electricity. In 2003, the average price charged by discoms was well over the average cost of supply, but by 2011 this trend had reversed: underpricing accounted for 16 percent of the annual losses in the sector. Instead of addressing mispricing directly, discoms have attempted to cover their revenue shortfall by (i) raising external debt to finance operational expenditures (ii) charging a higher price of electricity for industrial and commercial end-uses to cross-subsidize agricultural and domestic consumers as shown in Figure 3<sup>2</sup> (iii) rationing the supply of power to only a few hours of the day to

> 1 Khurana, Mani, and Sudeshna G. Banerjee. 2013. “Beyond Crisis: Financial and Operational Performance of India’s Power Sector.”

> 2 Pargal, Sheoli; Banerjee, Sudeshna Ghosh. 2014. More Power to India: The Challenge of Electricity Distribution. Directions in Development--Energy and Mining. http://openknowledge.worldbank.org/handle/10986/18726

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