characteristics, the urban and rural shares of consumption can be used as weights to proportionately allocate fixed costs across households.

More specifically, 27.8% and 72.2% of the utility’s total annual fixed cost requirements (after adjusting for lump-sum transfer of subsidies) are divided equally across all rural and urban households respectively. Figure 20 shows the results of this exercise. In contrast to Figure 19, the consumer welfare goes up in all quartiles but change in surplus relative to the current schedule persists to be negative.

To further improve the targeting of fixed costs, and especially to defray the fixed costs borne by households in the lowest quintile, the next counterfactual explores the use of historical householdlevel consumption data as a proxy for household’s willingness to pay for electricity. Historical consumption data is indicative of the level of investment made by households in buying electrical appliances. Households with greater ownership of these appliances (and therefore greater consumption in the past periods) will have a higher demand for energy and may potentially be willing to pay more for electricity. Following this rationale, fixed costs across households are allocated using the following formula: 2 2⁄ ) + 1 nn2⁄ ii � ~~�~~ ii − (∑QQ NN FFCC = (FFCC−1) ∗�1 +<sup>QQii</sup> where, denotes the fixed cost allocated to household �∑QQnn for each day in the billing cycle, ii NN is the per household per day fixed cost requirement of the utility,<sup>29</sup> 2 is the square of historical consumption ii FFCC uu FFCC across all billing cycles in a year and is the total number of residential consumers served by the utility. ii 2 QQ The term ⁄ is the mean of the square of annualized consumption across all residential NN consumers. The deviation of household’s annual consumption from the mean is used as a weighting nn ii factor to allocate fixed costs. Households with low levels of yearly consumption have a larger negative ∑QQ NN deviation from the mean and therefore pay a smaller share of the total fixed cost requirement. In contrast, large consumers pay a larger share due to a larger positive deviation from the mean. The square of consumption term allocates larger weights on observations that further from the mean – implying lower fixed cost charges for households with historically low levels of consumption and viceversa. Finally, the constant 1 is included in the equation to ensure that irrespective of the weighting factor, all households pay at least 1 rupee per day as their contribution to fixed cost requirements.

Figure 21 shows that median households in the first to the third income quintile are expected to achieve positive gains in consumer surplus under this scenario. The welfare loss for the median household in the fourth and fifth quintile is approximately Rs. 9 and Rs. 21 per month respectively.<sup>30</sup> Welfare gains in the first three quintile are achieved by transferring a greater share of fixed cost requirements to historically high consuming households in the richest quintiles. To illustrate the fixed cost burden on households implicit under this scenario, Figure 22 compares the allocation of fixed costs under JVVNL’s current tariff schedule to the counterfactual scenario. The figure shows that the

> 29 <u>( )</u> , where A is the annual revenue requirement in rupees per unit , is the social marginal cost in rupees AAR −SSMMSS∗QQ per unit , is the cotemporaneous total residential energy demand in kWh across all households under a given marginal price and is the total number of residential consumers.  FFCC= (365∗NN) AA SSMMCC 30 Based on footnote 28, if we included the domestic SCC into SMC, the energy cost of power would rise to Rs. 6.13/kWh. The QQ NN welfare gains for each quintile using this methodology and updated SMC would be Rs. –4.2, Rs.7, Rs. –9.3, Rs. –30 and Rs. –44 per month, at an elasticity of -0.3 (negative sign indicates welfare losses).

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