Abstract

Introduction: Nepal has an agriculture-based economy. According to 2021 Census, 51% of the households here use wood/fire wood for cooking. Biogas is used for cooking in 1.2% of the households. The use of grid electricity for lighting purposes is in 92.1% of the total households. Hydropower projects are the major sources of grid electricity in Nepal. In such agriculture-based economy, cattle are also kept for their draft power and milk. Biogas generates energy from the dung produced by farm animals and also from agricultural wastes. Thus, Biogas as an alternative energy source is very suitable for Nepal.
Methodology: This study is based on data collected from two sample surveys. They are namely survey of 300 households of national grid energy users and 400 households of Biogas users. It was conducted in three different rural settings of Nepal. The responses to questions were classified into multiple choice options. This generated categorical data and reduced ambiguity and confusion between interviewer and interviewee. Such data were classified into ordinal scale and modeled. As the dependent variable had more than two categories, polytomous and not dichotomous models were developed and fitted. In this way, qualitative socioeconomic variables were quantified. The results thus obtained were objective and indisputable.
Results: Interrelationships between the variables is explained using polytomous models. Ten different hypotheses assessing and measuring the energy consumption dynamics were tested. Values of parameters of these model and odds ratio were used in quantifying the impact of change with respect to energy consumption. The variables considered were namely time spent in the collection of firewood, type of house, amount of firewood saved, time saved, employer and school located within 15 min distance.
Conclusion: Benefits of use of energy are not only direct but permeate in an intangible manner to several sectors. Ten different hypotheses related to energy consumption pattern of normal users and Biogas users are tested with the help of this data. In eight of these ten hypotheses the null hypothesis of no dependence is rejected. It is found that location of school, location of employer and socioeconomic status plays a critical role in the energy consumption dynamics for both types of users. Energy poverty is assessed with the help of socioeconomic poverty in these hypotheses. The use of odds ratio has been used in quantifying the impact. Such data-based studies are very crucial for country like Nepal which lacks a strong backbone of accurate and regularly updated official records. They can be generalized to other counties of Asia and Africa. Such results provide guidelines to policy makers and planners regarding formulation of realistic energy policies for such countries.