Measuring and explaining household access to electrical energy services: Evidence from rural northern India
Electrification policy must look beyond connections to supply availability, measured in hours per day
Read the published paper ↗doi.org/10.1016/j.enpol.2020.111782
What a connection does not tell you
Connection rates are the statistic through which India reports progress on rural electrification. A connection is a precondition for using electricity, not a description of what a household can do with it.
Two households recorded identically as 'connected' may receive very different supply. The multi-tier framework (MTF) scores each supply dimension on tiers from 0 (lowest) to 5 (highest). Availability is measured in hours per day and reliability in outages per month. In its aggregate form, the MTF lets the lowest-performing dimension define a household's overall tier. This assumes all dimensions are equally important, which had not been tested empirically. We ask how disaggregate supply dimensions relate to household use of distinct electrical energy services and to satisfaction with supply. If the dimensions differ in the marginal utility they deliver, a single aggregate tier discards information a planner needs.
Eight energy services against disaggregate supply dimensions
We use the two-wave ACCESS panel survey, representative of rural areas in six contiguous states of northern India. It covers 8,563 households in 714 villages in 2014–15 and 9,072 households in 756 villages in 2018. We map appliances owned to eight electrical energy services: lighting, information and communication technologies (ICTs), entertainment, space cooling, refrigeration, thermal loads, mechanical loads and cooking. The primary outcome is the count of distinct services a household utilises.
Supply enters both as continuous measures (daily supply hours, monthly outage days) and in tier form, so we can compare the two directly. We also propose a supply–access index: mean daily supply hours among electrified households, multiplied by the share of households with access, divided by 24. We estimate survey-design weighted linear regressions of total services utilised, with state, district, village or household fixed effects in parallel specifications. Weighted logistic regressions model supply satisfaction and the use of each service, reported as average marginal effects. Robust standard errors are clustered at village level.
Availability relates to service use while reliability does not
We find that one additional hour of daily supply relates to a 0.022 [95% CI: 0.014 to 0.03] increase in the number of distinct services utilised. Over twelve hours (two standard deviations), that is approximately 0.26 more services, against a mean of 3.2 services in 2018. Twelve additional hours also correspond to 38%-points higher satisfaction with supply. Supply reliability showed no statistically significant association with either outcome. Following electrification, households were highly likely to use lighting and ICTs regardless of availability. A twelve-hour improvement was associated with higher likelihoods of space cooling (12.3%-points [10.7 to 13.9]) and entertainment (13.4%-points [11.2 to 15.6]).
The supply–access index separates states that connection rates render identical. In 2018, Jharkhand and Odisha both reported an access rate of 86%. Yet the index was 35% in Jharkhand against 64% in Odisha, reflecting poorer supply availability in Jharkhand. Energy-intensive services (thermal and mechanical loads, refrigeration, electric cooking) remain out of reach for most rural households, due largely to low incomes rather than supply availability.
Aggregate tiers hide what helps households
Using the lowest-performing dimension to define an aggregate MTF tier from survey recall data will not accurately reflect the utility of supply. Improvements to each dimension do not provide households the same marginal utility, so an extra hour of daily supply and one outage day fewer are not interchangeable.
We argue that policy makers in India should look at disaggregate supply dimensions when developing household electrification policy, paying special attention to availability in hours per day. More broadly, a disaggregate understanding of supply, energy needs and socio-economic constraints across the population can support a shift towards electrification policy that unlocks desired capabilities, using all available technologies.
@article{pelz_measuring_2020,
title = {Measuring and explaining household access to electrical energy services: {Evidence} from rural northern {India}},
volume = {145},
copyright = {All rights reserved},
issn = {03014215},
shorttitle = {Measuring and explaining household access to electrical energy services},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0301421520305036},
doi = {10.1016/j.enpol.2020.111782},
abstract = {Household electrification aims to provide populations with access to a wide range of energy services for social and economic development, ranging from lighting to electric cooking. Electrification policy has historically focused on grid connections, however, rather than household capabilities to satisfy energy service needs. We explore a representative panel dataset of households from rural areas of six states across northern India in order to link distinct dimensions of electricity supply with electrical energy service utilisation. Using a regression framework, we show that household electrification policy in India must look beyond connections and consider disaggregate dimensions of supply, paying special attention to supply availability measured in hours per day. Following electrification, households surveyed were highly likely to utilise lighting and ICTs regardless of availability, while an improvement of 12 h was associated with higher likelihoods of space cooling (12.3\%points [CI: 10.7 to 13.9]) and entertainment (13.4\%-points [11.2 to 15.6]) services utilisation. In contrast, mechanical loads, thermal loads, refrigeration and electric cooking remain constrained by household wealth and other factors. Disaggregate supply analysis supports the shift towards electrification policy that unlocks desired capabilities while using all available technologies, both grid and off-grid, to achieve more just outcomes for all.},
language = {en},
urldate = {2023-01-28},
journal = {Energy Policy},
author = {Pelz, Setu and Urpelainen, Johannes},
month = oct,
year = {2020},
pages = {111782},
}