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2020-03-12 | Peer Reviewed

Environmental efficiency of small-scale tea processors in Kenya: an inverse data envelopment analysis (DEA) approach

Gatimbu, K. K., Ogada, M. J., & Budambula, N. L. (2019). Environmental efficiency of small-scale tea processors in Kenya: an inverse data envelopment analysis (DEA) approach. Environment, Development and Sustainability, 1-13.
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Vision 2030, Kenya’s development blueprint for the period 2008–2030, envisions transforming the country into middle-income status where citizens enjoy a high quality of life. The blueprint has three pillars: economic, political and social. The thread that binds the three pillars is the natural environment, which supplies both renewable and non-renewable resources. Unfortunately, development in the other sectors may easily compromise the conditions of the natural environment and put the supply of clean water, food and fiber in jeopardy. For example, processing of agricultural products may increase gains from agriculture and lead to rapid expansion of the sector. If this is not carefully done, it may be characterized by wastage of resources, cutting down of forests to provide fuel and more land for cultivation, disposal of raw wastes into water bodies and over-exploitation of the soils. Using the example of small-scale tea processors in the country, this study sought to understand the environmental efficiency of the small-scale agro-processors. Small-scale tea processors were chosen because they have been implementing environmental efficiency-enhancing techniques in their production, yet no study had endeavored to test whether their initiatives were yielding positive results. The study adopted the innovative inverse data envelopment analysis approach on panel data to generate environmental efficiency scores, in the first step. In the second step, it analyzed the predictors of environmental efficiency using Tobit regression. Overall, the results showed that small-scale tea processors in Kenya were still environmentally inefficient, recording a mean efficiency index of only 49%, despite previous initiatives to improve efficiency. Thus, the processors could reduce 51% of the environmentally detrimental inputs without compromising output. Environmental inefficiency could be attributed to pursuit for higher profits and higher cost of investible funds. This shows that investment in environmental conservation is expensive and eats into the profits of the processors. Therefore, the small-scale processors may lack the incentives, in the short term, to invest in environment-friendly technologies. This may be compounded by the high cost of finance to be invested in such initiatives. Policy implication is that government should intervene in terms of tax concessions for firms that invest in environmental conservation, subsidies on technologies that guarantee environmental efficiency and access to cheaper funds for purchase and maintenance of environment-friendly technologies.