Significance of context, metrics and datasets in assessment of multidimensional energy poverty: A case study of Tajikistan

We applied the multidimensional energy poverty index (MEPI) to Tajikistan, using the Demographic and Health Survey (DHS) datasets to assess energy poverty at the national and sub-national levels, along the urban-rural gradient, and over time. The results showed very low energy poverty levels across the board. However, using the Khalon region survey, and applying the original index, we found substantially higher energy poverty levels. Whereas the MEPI results from DHS datasets were 0.15 for 2012 and 0.04 for 2017 for rural areas of Khatlon, the MEPI result from Khatlon dataset was 0.53. This is higher by about 253% against 2012 and a whopping 1225% against 2017 estimates. Modifying the indicators and weights and applying this modified index to the Khatlon dataset showed a higher result (0.54), but still in the moderate energy poverty category. Furthermore, we conducted assessment at the sub-regional level and by access to grid electricity in both the original and modified indices based on the Khatlon dataset, and found differences ranging from 0.47 to 0.80, i.e. moderate to acute energy poverty. Therefore, low results found using the DHS dataset likely underestimate the actual state of energy poverty in Tajikistan, whereas the Khatlon dataset showed substantially higher energy poverty levels that are closer to reality. These results offer valuable insights for policymakers and practitioners to investigate the actual state of energy poverty and explore measures to address this issue. We propose eight recommendations for future research into energy poverty measurement, focusing on study design and choice of indicators.