After more than 3 years of research and hard work, at last I am able to compute the Energy Poverty Index or EPI. The EPI measures the degree of energy poverty in percentages, where negative sign indicates energy poverty and positive sign indicates energy prosperity.

Camel loaded with firewood - Muzaffargarh, Pakistan

Why we need to compute a separate index for energy poverty?

Despite the fact that energy is the major obstacle for socio-economic development in rural communities of developing countries, the literature in energy and development and policy analysis  lacked concrete measure for representing this wide spread problem in rural communities of developing countries.

Dimensions of EPI

Firstly, the EPI takes into account several sub factors relevant to energy source used by a rural household, to determine the energy inconveniences. Based on these factors, we computed the energy inconvenience index (EII) and subsequently based on EIE, the depth of energy inconveniences by setting a cutt-off point 30% above the sample EIE. The result is expressed as EIE % – energy inconvenience excess, where positive values represent energy conveniences in percentages and negative values represent energy inconveniences in percentages. Note that the energy inconveniences are weighted based on the kilowatt hours share of each energy sources in total household energy.

Secondly, we took into account another aspect of energy poverty, i.e., actual energy consumption  (AEC – in kilowatt hours) for each household. The threshold value for energy consumption of also known as total energy requirements (TER) is equal to 0.7  TOE per annum per capita which based on 1 TOE (required to maintain 0.8 HDI value). This values is further readjusted for rural communities(for details, plz check the working paper). To know the depth of energy shortfall, we took the difference of AEC and TER and then divide it by TER. As in EIE, these values are also represented by percentages with positive and negative signs (+ve = excess of energy [or no shortfall]; -ve = shortfall of energy)

And finally, for computing the EPI, we took the unweighted average of the EIE and ES. This is done due to the fact, that rural households exert efforts and inconveniences based on the degree of their energy shortfall. If households have relatively higher energy shortfalls, they exert more efforts and this results in higher score on energy inconveniences excess (EIE) so that they can lower their energy shortfalls.

Results

The paper also present results from 27 rural communities of Punjab which shows that 23.1% of
rural households in our sample experience high degrees of energy inconveniences, spending ample amount of their time and effort in collecting or buying different energy sources. Furthermore, 96.6% rural households experience severe energy shortfalls due to lack of modern, sustainable and continuous energy supple. And lastly, EPI reveals that 91.7% of all rural households are in the state of severe energy poverty.

Another important aspect of results is the comparison of different income groups in our sample. Based on Headcount ratio (HCR), we found that 34.1% people in lowest income group, 32.8% in lower income group, 24.1% in middle income group, 13.6% in upper middle income group and 11.0% in upper income groups are in the state of sever energy energy inconveniences.

Furthermore, the average depth of energy poverty, expressed by the EPI is equal to -23.5%, including -29.6% in lowest income group, -31.2% in lower income group, -26.5% in middle income group, -19.6% in upper middle income group and -16.7% in upper income group.

Full working paper is available online (for limited time) at following link:

Towards a new measurement of energy poverty: A cross-community analysis of rural Pakistan, by Bilal Mirza and Adam Szirmai

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