in the billing data and comparing it to the IBT structure publicly issued by the utility. Appendix 2 contains an example of how this exercise is carried out.

In general, JVVNL generates a new bill once every two months. In some cases, however, bills are delivered before or after the two-month interval based on the route taken by the utility’s roving meter readers to visit respective households. Observations for which the billing interval is more than 180 days are excluded from the analysis. If the meter reader is unable to establish contact with the household or if the meter appears to be malfunctioning at the time of reading, the consumption figures for the household are not captured in the billing data set. In such cases, JVVNL makes an imputation based on the average consumption of the household over the past six months. Such observations are dropped from the sample resulting in exclusion of an additional 1,250 observations (13% of the data).

To provide an overview of prices and consumption variables in the data set, Table 1 shows the summary statistics for all households over 2014-2017 period. The average monthly per capita consumption of electricity in the sample is 39.7 kWhs – more than double the per capita residential usage of 15 kWh in Rajasthan in 2012.<sup>11</sup> The increase in the per capita electricity consumption reflects robust economic growth and rapid rates of electrification in the region.

Policy induced changes in prices are key to recovering model estimates. Marginal prices on the increasing block tariff for residential consumption were revised twice within the sample period. Figure 6 shows the distribution of average daily household consumption by the month of bill issuances,<sup>12</sup> with red labels in the horizontal axis indicating the periods in which these price changes occurred. There is considerable heterogeneity in consumption across households within a month which provides the household-level variation required to estimate the parameters of the model. Expectedly, there is seasonality in the consumption levels – with peak and lows during the summer and winter months respectively. Appendix 2 contains additional validation checks.

# 2.2 _Household characteristics_

Household characteristics were collected through a survey carried out in two districts of Rajasthan. The survey, conducted as part of World Bank electricity lending program in the state, was administered by a local team of fieldworkers with extensive experience working and residing in these areas. The goal of the survey was to collect household demographics, socio-economic data, appliance ownership and use, and unique household level billing codes to match survey data to the billing database. The survey enumerated approximately 2,000 households.<sup>13</sup>

> 11 Prayas (Energy Group), Residential Electricity Consumption in India: What do we know? December 2016. <u>http://www.prayaspune.org/peg/publications/item/download/709_95c95aa4a9ad64d4f944fc8dcd78000c.html</u> _12_ T T n n <u>o</u> Average daily household consumption by month of issuance = T T n n

> 13 The sampling for the survey was done in two stages. The first stage picked a representative population of villages for rural areas, and TT n TT o n uuTTuu ccTTnnuun nncc uunn TThnn nnuuT TT n TToo ccTTdduu ccTTccn nncc uunn TThnn nnuuT ppn uuTTcc enumeration blocks (EBs) for urban areas, stratified by district. In the second stage, all structures within a village or EB were enumerated, and then a representative sample was drawn from this listing. In rural areas, a single household was randomly drawn from each structure, stratifying on three strata: (i) Households with no electricity bills, (ii) Households receiving electricity bills and below the poverty line, (iii) Households receiving electricity bills and above the poverty line. In urban areas, households were sampled randomly without stratification. In all 67 enumeration blocks and 60 villages were listed and 4,755 structures were selected for sampling of households at the second stage. The total population in our sample was approximately 11% more than the total census-2011 population. The population growth reflects an annualized growth rate of 1.8% in this region.

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