29 regressed on different measures of grid‐electricity poverty, the poverty gap at 250 kWh and headcount at 100 kWh, shown in Figure 7, are the two best predictors of access. However, although countries do not overlap, the correlation coefficients are not as high as between access and the economic poverty gap at $3.10 or $1.90. The share of total household expenditures required to consume different amounts of electricity is another predictor of access, but is not as good as the two measures of grid‐electricity poverty.

Figure 7: Comparison of access with grid‐electricity poverty gap and poverty headcount <!-- Start of picture text --> Electricity poverty gap for 250 kWh/month<br>Electricity poverty headcount for 100 kWh/month<br><!-- End of picture text --> <!-- Start of picture text --> Electricity poverty gap for 250 kWh/month<br>Electricity poverty headcount for 100 kWh/month<br><!-- End of picture text --> <!-- Start of picture text --> Electricity poverty gap for 250 kWh/month<br>Electricity poverty headcount for 100 kWh/month<br><!-- End of picture text --> <!-- Start of picture text --> Electricity poverty gap for 250 kWh/month<br>Electricity poverty headcount for 100 kWh/month<br><!-- End of picture text --> <!-- Start of picture text --> Electricity poverty gap for 250 kWh/month<br>Electricity poverty headcount for 100 kWh/month<br><!-- End of picture text --> _Source_ : World Bank staff calculations based on utility information and household survey data.

As mentioned above, because extending grid electricity to rural households is costly and off‐grid electricity will be cheaper for low‐density, low‐consumption areas, and because the grid network is nonexistent in many parts of rural areas, these grid‐electricity poverty statistics are arguably more relevant for urban households. Repeating the above exercise for urban households only delivers similar results, with the urban poverty gap at 250 kWh and urban poverty headcount at 100 kWh having the highest correlation coefficients with urban access rates. The highest correlation coefficients between urban access and the measures of grid‐electricity poverty are obtained when the latter are calculated nationally, and different measures of national grid‐ electricity poverty are better correlated with urban access than with national access. There is no obvious explanation for these results.

The poverty gap and headcount at 30 kWh have the smallest correlation coefficients and have the weakest predictive power for access for both national and urban statistics. This may seem counterintuitive at first glance—should the affordability to the poor not determine the rate of access? Several reasons may be offered for this finding. First, the total household expenditures used include freely acquired food and other items, making cash available much smaller for some households, especially in rural areas. Yet excluding freely acquired goods and services is not necessarily a more compelling approach, because two households with the same cash income but one of which does not have to pay for food are clearly not in the same financial situation. Second, a household that can barely pay for 30 kWh a month of electricity may have other pressing demands on its budget. Third, connection costs are high in many countries (see the next paragraph), and a household that can just afford 30 kWh a month may have no financial resources to pay for the initial connection. Lastly, depending on how many higher‐consumption, better‐off consumers are in the same area, it may not be financially viable for the utility to extend the grid to poor households for whom even 30 kWh a month poses an affordability challenge.