The main purpose of this study is to construct a women’s empowerment index for handloom weavers by adopting the tools developed by the Oxford Poverty & Human Development Initiative (OPHI). Within Assam, India, 1000 sample respondents were selected for the study from five leading handloom production districts. For the study, individual-level data were collected by interviewing handloom weavers comprising seven domains and 25 indicators. A regression analysis was used in the study, and the results revealed that out of the five districts in Assam, the empowerment index of handloom weavers is highest for Kamrup (rural) (0.72), followed by Barpeta (0.64), Kokrajhar (0.61), Nagaon (0.58), and Chirang district (0.44). Overall, the women’s empowerment index for handloom weavers is less than the global standard empowerment weighted average of 0.80. It was also found that empowerment is linked to wages, education, availability of electricity, media exposure, and other household characteristics. Therefore, policies should set out a minimum wage structure for weavers that is fixed by the government and implemented properly as well as initiatives regarding other factors that encourage empowerment.

This paper analyses the determinants of household electricity consumption with the focus to find the impact of government subsidies and surcharges on the demand for electricity services in the rural areas. Using surveyed household data of 332 samples, quantile regression has been employed for checking heterogeneity in electricity demand across different quantile of households. We find government subsidy has enhanced the household demand for electricity consumption with the elasticity ranging from 45 to 65%. Skeptically, electricity consumers of higher quantile tend to consume more even in the presence of outstanding bill while it is the opposite for low quantile group. Surprisingly, income and other socioeconomics variables don't necessarily affect the households demand for electricity. This implies demand for electricity is inelastic to income and selected socioeconomic variables in rural regions. However, electricity demand decreases for households with dwelling characteristics categorized as poorer quantile. Based on our empirical findings implications are drawn for policy makers.

Electricity is the basic need for individuals, households and industries. It is used for everyday life activities by the households, agricultural activities, commercial buildings and industries. The per capita electricity consumption is a proxy indicator growth and development status of a region. All the north eastern states consume per-capita electricity lesser than the national average except Sikkim. The per capita consumption of electricity by Nagaland, Assam and Manipur is nearly just one-third of the national average. Notably, these three north eastern states consume just 40 percent of per capita electricity compared to the highest consumer state Meghalaya. The present study is an evaluation of the per-capita electricity consumption trend and inequality amongst the north-eastern states of India using Gini coefficient and Lorenz curve for two different time periods i.e. 2007 and 2017. We find that Tripura’s annual linear growth rate of per-capita electricity consumption is the highest (3 percent) while that of Meghalaya is the least (1 percent) and the other five states are growing equally at the rate of 2 percent. The Gini coefficient is found to be decreasing from 0.137 in 2007 to 0.122 in 2017. We conclude that the level of inequality is reducing among north eastern states of India though the per-capita consumption of electricity is less than the national average.

In this paper we have analysed the electricity consumption inefficiency of households in rural area by using stochastic frontier analysis (SFA) applying single stage one-sided approach on the primary data collected using stratified random sampling. We find the mean efficiency of the households is 77.25 percent where the stochastic demand frontier reveals government subsidy and minimum watt have a significant positive impact on household electricity consumption. Surprisingly, numbers of living room does not increase electricity consumption demand in rural areas.We found the inefficiency factors; a reduction in cut in minutes and cut frequency can reduce the inefficiency of electricity consumption by the households in rural areas. Intuitively, a reduction in cut time duration and number of times electricity is cut in a day on an average can reduce inefficiency of the households by 15 percent and 39 percent respectively. Additionally, households living in pukka floors and having inverter as secondary source of lighting could reduce their inefficiency by 11 and 7 percent respectively. Overall, we found inefficiency in electricity consumption in the rural areas lie more on the supply side constraints compared to the demand side.