Technical Efficiency and Technology Gap Ratio in Cocoa Production in Nigeria: A Stochastic Metafrontier-Tobit (Sm-Tobit) Approach

The study analysed the technical efficiency and technology gap ratio in cocoa production in Nigeria. A multistage sampling technique was used to select 390 cocoa farmers from three zones where cocoa is commercially grown in Nigeria. Separate stochastic frontier models were estimated for farmers in Kwara, Edo and Ondo States, along with a metafrontier model to obtain alternative estimates for the technical efficiencies of farmers in the different states. Subsequently, a Tobit model was used to access the factors influencing cocoa production in the study area. Results revealed that, the average technical efficiency level was 0.685 for the pooled sample, 0.506, 0.837 and 0.713 for Kwara, Edo and Ondo States respectively, suggesting that there is substantial scope to improve cocoa production in Nigeria. The mean MTR values of 0.506, 0.837 and 0.712 for Kwara, Edo and Ondo States respectively, implied that Edo State was more technically efficient than other states in the study area. The mean technology gap ratio (TGR) value of 84.3% indicated that, on the average, the cocoa farmers in the study areas would have to close a gap of about 15.7% in order for them to be technically efficient. The study recommended that cocoa farmers in Edo and Ondo States could improve their technical efficiency through a better management using the available technologies and resources while intervention to raise technology that will help close the gap between the regional frontier curve and the global frontier curve through raising and distributing disease resistant and high yielding cocoa seedlings to the farmers should be adopted in Kwara State.

ENERGY EFFICIENCY OF INDONESIA’S SUGAR INDUSTRY BASED ON ECONOMIC FRAMEWORK: STOCHASTIC METAFRONTIER ANALYSIS

This study investigates the efficiency of energy use and technology gap in the Indonesian sugar industry and the factors influencing energy efficiency. Using the firm-level data of sugar mills in 42 regencies in Indonesia from 2010 to 2014, this study applies the meta stochastic frontier based on the input distance function. The metafrontier analysis is applied in sugar mills in the East Java province and other provinces in Indonesia. All the data used in this study are the secondary data taken from the Indonesian Central Board of Statistics. The results reveal that there is a large room to save energy consumption in this industry. The mills in East Java provinces have higher energy efficiency, technology gap ratio, and metafrontier energy efficiency compared to the mills in other provinces. According to the metafrontier energy efficiency, energy inefficiencies in both groups come from operational inefficiency and technology gap. The size of the mills and age of the mills have a positive relationship with the energy efficiency of sugar mills and the size of the mills is positively related to the technology gap ratio. Meanwhile, the productivity of labor and the types of ownership do not affect the energy efficiency and technology gap.

Technical efficiency of the small-scale tea processors in Kenya: a stochastic metafrontier approach

PurposeImportance of small-scale tea producers in Kenya is not in doubt. They account for 60% of all tea produced in the country, serve about 560,000 tea farmers and employ about 10,000 people directly. However, the subsector faces a myriad of challenges ranging from declining yields and rising costs of production to fluctuating world prices. Thus, it is imperative that the producers entrench efficiency as a critical success factor. This makes it important for the producers to understand their relative performances to inform decisions on improving input use. Congruent with this motivation, this study sought to analyze the technical efficiency (TE) of the country's small-scale tea processors within and across the regions under the management of Kenya Tea Development Authority.Design/methodology/approachTo allow comparison across regions, this study adopted a stochastic metafrontier approach and to be able to decompose inefficiency into persistent and time-varying components, the study adopted regression analysis.FindingsResults showed that the small-scale tea processors operated at a mean TE level of 76% with a technology gap ratio (TGR) of 97%. This implies that the prevailing level of output could be maintained even if inputs were reduced by 24%. Persistent inefficiency could be reduced possibly through rationalization of structural and managerial components of the firms.Research limitations/implicationsWhile it is important to adopt yield-enhancing technologies and innovation, small-scale tea processors have the latitude to improve their earnings through enhanced TE. They can save up to 24% of their input and be able to pay farmers better even with the fluctuating global tea prices. Enhancing TE should be given priority because it is within the control of the individual firms.Originality/valueThis is a pioneering study in panel data analysis of TE of small-scale tea processors within and across regions in Kenya.

A Comparative Study of Different Energy Efficiency of OECD and Non-OECD Countries

Greater and greater attention is being paid to air pollution problems, because of their negative impact on the environment and human health. This article measures energy efficiency, carbon dioxide emissions efficiency, and particulate matter (PM2.5) concentration efficiency to compare the energy efficiency differences between Organisation for Economic Co-operation and Development (OECD) member countries and non-OECD member countries from 2010 to 2014 using a metafrontier dynamic Data Envelopment Analysis model. We calculate technology gap ratio and input and output efficiency values to measure the energy efficiencies of each economy, finding that (a) OECD countries have a technology gap ratio of 1 or very close to 1; and except for the United Arab Emirates and Singapore, both of which exhibit annual improvements, the non-OECD countries have a significant need for efficiency improvements; (b) the average technology gap ratio of OECD is higher than that of non-OECD countries; that is, while OECD countries’ technology gap ratio (TGR) changes are relatively stable, non-OECD countries’ TGRs are gradually increasing; (c) non-OECD countries have large PM2.5 concentration efficiency gaps, with the annual efficiencies in China, India, and Nepal being less than 0.2; (d) Switzerland, Denmark, France, the United Kingdom, Iceland, Luxembourg, Norway, the United States, and the United Arab Emirates all have new and traditional energy efficiency values of 1; and (e) Botswana, Algeria, and Cambodia have poor traditional energy efficiencies, but better new energy efficiencies, whereas Hungary, South Korea, Slovakia, and Slovenia have poor new energy efficiencies and better traditional energy efficiencies.