Energy Efficiency and Substitution Possibilities in Kenya’s Manufacturing Sector

Abstract

Energy holds a pivotal role in an economy’s social and economic transformation and it is a key ingredient driving the production of nearly entire goods and services. Consequently, energy demand has been increasing over years globally and locally owing to expanded population and economic activity. The manufacturing sector, a key engine of growth, is one of the largest energy end-user. While energy is a key input in the manufacturing processes, there is unease over its effects on the environmental quality, human health, and competitiveness of firms. This thesis sought to analyze energy efficiency, productivity, and energy and non-energy input substitution possibilities in Kenya’s manufacturing sector. It was structured into three essays. The first essay analyzed sub-sector energy efficiency differences, energy efficiency change as well as energy efficiency drivers in Kenya’s manufacturing sector. Sub-sectors of concern were: chemicals, pharmaceuticals and plastics, food, textiles and garments, and paper and other manufacturing. Analysis was also conducted at the sectoral level for robustness check. The stochastic frontier analysis and more specifically translog input distance functions were estimated by adopting a pooled regression model covering the period 2007, 2013, and 2018 in the assessment of electricity efficiency and 2007 and 2013 in the assessment of fuel efficiency. The Malmquist index was applied to analyze energy efficiency change over the period under review. The World Bank Enterprise Surveys provided data used in this analysis. Study findings show considerable space to cut electricity and fuel wastage across the four sub-sectors and the overall sector. The Malmquist index showed an improvement in electricity efficiency in the chemicals, pharmaceuticals and plastics and textiles and garments sub-sectors. A decline in electricity efficiency was observed in the food and paper and other manufacturing sub-sectors and overall sector. Fuel efficiency improved in food and paper and other manufacturing sub-sectors and overall sector but declined in chemicals, pharmaceuticals and plastics and textiles and garments sub-sectors. Findings show that electricity and fuel efficiency could be enhanced by investing in research and development, exporting activities, female firm ownership, and highly experienced top management. The influence of these variables varied between the two energy forms and across sub-sectors. Firm age and size had no clear effect on electricity and fuel efficiency while labour productivity had a negative effect. These findings reveal the need to design policies that enhance technological innovations, uptake of new technologies, exporting and female firm ownership.

The second essay sought to explore the energy efficiency and productivity relation in the Kenyan manufacturing sector. Energy intensity was applied to indicate energy efficiency. Total factor productivity was analyzed using the Levinsohn-Petrin algorithm. A dynamic panel data model was employed to establish the energy efficiency and total factor productivity relation. An unbalanced panel data for the years 2007, 2013, and 2018 drawn from World Bank Enterprise Survey was also adopted in this essay. Study findings showed heterogeneity in energy intensity across sub-sectors. Heterogeneity in total factor productivity was also observed across sub-sectors, firm sizes, and firm age. Energy efficiency was found to positively influence total factor productivity. Study findings also showed that capital intensity, age and size of the firm, top manager’s experience, foreign ownership, and exporting status positively influenced total factor productivity. The effect of these variables was found to be heterogeneous across sub-sectors and firm sizes. Study findings suggest that policies to improve energy efficiency should be matched with policies to enhance total factor productivity. The third essay sought to assess energy and non-energy input substitution possibilities besides establishing whether these substitution possibilities varied with firm size in the Kenyan manufacturing sector. Iterated seemingly unrelated regression was applied on a pooled model and an unbalanced panel dataset for the years 2007, 2013, and 2018 drawn from World Bank Enterprise Survey and Energy and Petroleum Regulatory Authority. Analysis was performed in two steps. In the first step, there was a joint estimation of a translog cost function with cost-share equations. Elasticities were then worked out from parameter estimates of the translog cost function and cost shares in the second step. The Cross-price elasticities indicated that capital and labour were substitutes for energy across all sub-sectors and overall sector but capital was a weak substitute for energy in the chemicals, pharmaceuticals and plastics sub-sector. The Morishima elasticities affirmed that capital and labour were substitutes for energy across all sub-sectors and the overall sector. The cross-price elasticities at firm size level analysis showed that capital and labour were substitutes for energy across all firm sizes but capital was at best a weak substitute for energy in small firms. The Morishima elasticities further affirmed that capital and labour were substitutes for energy across firm sizes. Substitution of capital for energy was found to increase with firm size but no consistent pattern was observed in the substitution of labour for energy. Study findings suggest that energy price policies could reduce energy consumption and potentially boost capital intensiveness, employment, and environmental quality.