Figure 4 replicates the results of the PSLM data analysis presented in Figure 2. There are some key differences in the results. Most notably, household electricity use is considerably lower according to the billing data. Around 30 percent of the poorest two deciles consumed less than 50 kWh/month (the lifeline slab) according to the billing data, compared to less than 10 percent in the PSLM data. Again, this may be due to reporting of other electricity expenses (such as batteries) in the household survey measure. Despite the generally lower consumption levels, however, the pattern across the welfare distribution is similar: electricity consumption rises gradually with welfare, but almost all households still consume less than 300 kWh/month and therefore benefit from subsidies. This graph also implies that the subsidy cuts in 2013 likely had a direct impact on only a small proportion of households, since the tariff increases were restricted to slabs above 200 kWh/month.

Figure 5 shows that the distribution of subsidies is disproportionately in favor of the richest households, with the top 20 percent of households receiving about 24 percent of the total subsidy. It can also be seen that the 50‐100 and 100‐200 kWh/month slabs account for the majority of subsidies: any substantial cuts to subsidies will need to be focused on these slabs, and this would adversely impact the majority of lower and middle‐income households.

The current subsidy system does not take into account natural intra‐year variation in electricity consumption. Given Pakistan’s warm summer climate and cool winters, electricity expenditures vary widely by season (Figure 6). Even poor households that qualify for the lifeline in the winter (Q3) move into higher slabs during the summer (Q1 & Q4). In the winter, around 13 percent of rich households qualify for the lifeline subsidy. These findings indicate that a static subsidy scheme throughout the year is failing to protect the poor, and provides an unnecessary benefit to the richest households in the winter months, when electricity affordability is less of a concern.

# **Robustness Checks**

# **_Low match rate_**

Our analysis is predicated on the assumption that the PMT scores matched to the billing data tell us about the patterns of electricity consumption and welfare at the national level. However, only 45 percent of DISCO records could be matched with the PMT score through the NSER.<sup>10</sup> A relatively small share of records could not be matched due to errors in the CNICs records in the DISCO database. The majority of the unmatched households could not be found in the NSER survey data, however, likely because those families did not have a CNIC at the time of the survey in 2010. The survey is currently in the process of being updated, however, meaning that in future the match rate is likely to be significantly higher.

> 10 The unmatched 55% will have similar socioeconomic breakdown or might be skewed towards the better off households as records of the initial NSER survey shows that most refusals came from better off households. The K‐density plot shows the variance in PMT across the matched sample (see Appendix, part E).

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