Households’ energy preference and consumption intensity in Kenya

Abstract

Background: There have been notable joint efforts from the private and public sectors in promoting households’ access to clean and efficient energy sources. Despite the noteworthy progress realized over the years, the consumption and reliance on clean energy sources are reportedly low. This scenario is evident among households practicing multiple energy use, whereby energy proportions consumed from the clean energy sources are much lower compared to non clean energy sources. As such, reliance on non-clean energy has greatly hindered the projected welfare and productive gains that comes along with access to clean energy sources. To understand households’ energy consumption behavior, this study takes into consideration that energy preference (choice) and intensity (proportions consumed) are two independent decisions. Therefore, a succinct understanding of the factors affecting these decisions acts as a basis for an optimal transition to clean energy sources. Methods: The study utilized a nationally representative cross-sectional household dataset (3663 households) across Kenya. A series of diagnostic and specification tests were carried out so as to identify the most suitable estimation technique in achieving the underlying objectives of the study. The preference for Cragg’s double-hurdle model was premised on the fact that the model postulates that households must pass two separate hurdles before a positive level of consuption is observed. Maximum likelihood estimations were derived, followed by the marginal effects for the probability of participation and consumption intensity (conditional and unconditional) to unveil the effects of explanatory variables on the dependent variable. Results: Results show the diversity in magnitude and direction of how various factors affect the preference and consumption intensity among households. For instance, households’ energy preference and consumption intensity are predominantly affected by location (rural or urban), household’s decision maker on energy use, education level, age of the household head, and the average monthly income. Conclusion: In this regard, the promotion of clean energy use should target households in rural areas and households with lower level of education and lower income brackets. Uptake of clean energy sources such as liquefied petroleum gas should be encouraged among rural and urban poor households through reducing the upfront cost of acquiring cylinders and the refilling costs.