Analysis of Price and Production Efficiency of Sesame: Dual Cost, Stochastic Frontier and Tobit Model Approach

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Published on International Journal of Agriculture & Agribusiness
ISSN: 2391-3991, Volume 2, Issue 1, page 70 – 90
Publication Date: 11 February 2019

Hika Wana
Department of Agricultural Economics, Wollega University
Shambu, Wollega Zone, Oromia Region, Ethiopia

Journal Full Text PDF: Analysis of Price and Production Efficiency of Sesame: Dual Cost, Stochastic Frontier and Tobit Model Approach (Study Sesame Sesamum Indicum L Production in Babogambel District of Ethiopia).

Abstract
The aim of the study was to measure the levels of price and production efficiencies of sesame producers and identify factors affecting them in Babogambel district of Oromia Region, Ethiopia. The study was based on cross-sectional data collected in 2016 production season from 124 randomly selected farm households. Stochastic production frontier model by dual cost method was used to estimate price and production efficiency levels, whereas Tobit model was used to identify factors affecting efficiency levels. Accordingly, the mean price and production efficiencies of sample households were 72.95% and 53.95%, respectively. The results indicated that there was substantial amount of inefficiency in sesame production in the study area. Land, labor and oxen were the variables that positively affected the production of sesame. Results of the Tobit model revealed that experience in sesame production, family size and extension contact affected price efficiency negatively and significantly but soil fertility and education level affected price efficiency positively and significantly. Education level, experience in sesame production and soil fertility affected production efficiency positively and significantly, However, extension contact affected production efficiency negatively and significantly. Results indicate that there is a room to increase the efficiency in sesame production of the study area. Therefore, government authorities and other concerned bodies should take into consideration the above mentioned socio economic and institutional factors to improve the productivity, cost effectiveness and production of sesame in the study area.

Keywords: Babogambel, price efficiency, production efficiency, stochastic, tobit.

1. Introduction
Sesame is produced in around 75 countries of the world. The production of sesame seeds in the world is dominated by a few countries that lie in the African and Asian continents. The top five sesame producing countries are China, India, Myanmar, Sudan, and Tanzania. Ethiopia is the second top exporter of sesame seed next to India (IEA, 2016). Ethiopia is one of the centers of biodiversity for several oilseeds which can be considered as specialty high value seeds on the international markets. The major sesame seed producing areas in the country are Tigray region, Western and North Western zones, (especially Humera, Tsegede and Welkaite districts); Amhara region, North Gondar zone (specifically Metema, Kuara, West Armachiho, Tach Armachiho and Tegede districts); Oromiya region: Western Wollega (Oda, SirbaAbay, Jarso, Babo-gembel, Gimbi and Manasibu and the surroundings), Eastern Wollega (Gidayana, Diga and Gutin), Horo-guduru (Abedongoro), Keluem Wollega, Jima as well as Illubabor zones; and Benshangul Gumuz region (Assossa, Sherkole, Homsha, Mengie, Kumruk, Kamashi, Aqelo Meti, Yaso, and surroundings) (ECX, 2015). Despite the high oil seed crop productivity variations across the region, the growth rate of productivity is significantly increased within each region except sesame during the same period.
The annual average oil seed crop productivity growth rate was: Neug 11.12%, 8.61% & 4.81% Linseed 12%, -8.45% & 9.36% and Sesame 0.01%, 5.62% & -1.04% in Tigray, Amhara and Oromia regions respectively, Sesame crop productivity shows the list productivity growth among the other oil seed crops in the last ten years in all three major oilseed growing regions of Ethiopia (CSA, 2015). According to CSA (2015), in 2013/14 production year, sesame covered 299,724 ha of land at national level. The total production of sesame in the same year at national level was 2.2 million qt. In the same year, the total productivity of the crop at national level was 7.35qt per ha. From 2013/14 to 2014/15 production season, production of sesame has increased by 27.27% but productivity has decreased by 6.53% at national level.
The same source indicated that in Oromia region, the total area covered by sesame in the production year of 2013/14 was 48,182ha and 379,240qt of sesame have been produced with the productivity of 7.87qt per ha. From 2013/14 to 2014/15, production of sesame has increased by 41.3% but productivity has decreased by 6.6% in Oromia region. Even though there is an effort by some research centers in Ethiopia in variety development and agronomic practices, surprisingly from 1995/96 (1988 E.C) to 2014/15 (2007 E.C) sesame productivity was drastically reduced from 9.8qt per ha to 6.87qt per ha. This implies the research attention that has been given to improve this crop is not comparable with the contribution of this crop in Ethiopian economy for long period of time. Therefore, possible ways should be sought to improve the efficiency of the farmers in Ethiopia.
Babogambel district, which is one of the districts of West Wollega Zone, is known by oilseed production specially sesame and Niger. Out of the total 86400 hectares of land in the district, land used for cultivation occupies 41 percent of it. As sesame is concerned for this study, it occupies 12.1 percent of the total cultivable land of the district. In 2014/15 production year, the total production and productivity of sesame in the district was 27,860.95qt and 7.15qt/ ha respectively (BDARDO, 2015). Among the oil crops of Ethiopia, sesame seed commands a leading position because it is highly adapted to arid and semiarid low land environment and yields well …….

2. Literature Review
Analytical Framework
Models of efficiency measurement provides analytical framework for analysis of frontier in the economic literature. There has always been a close link between the measurement of efficiency and the use of frontier functions. Different techniques have been utilized to either calculate or estimate these frontier functions. The production frontier, or the maximum potential output of a completely efficient DMU, cannot be observed directly and a wide range of techniques has been developed to overcome this problem, the foremost techniques being non parametric (DEA) and parametric (DFA and SFA). The selection of specific frontier model depends upon many considerations such as the type of data, cross-sectional or panel data, the underlying behavioral assumptions of firms, the relevance to consider and extent of noise in the data and the objective of the study. The following reviews focus mainly on these two broad categories of frontier models.

Non-parametric frontier models
The mathematical programming approach to the construction of frontiers and the measurement of efficiency relative to the constructed frontiers goes by the descriptive title of data envelopment analysis. It truly does envelop a data set; it makes no accommodation for noise, and so does not “nearly” envelop a data set the way the deterministic kernel of a stochastic frontier does. Moreover, subject to certain assumptions about the structure of production technology …….