Data Envelopment Analysis Approach to Estimating Economic and Scale Efficiency in Processing Cassava into Gari in Ankpa Local Area, Kogi State, Nigeria

Main Article Content

Ezekiel O. Haruna
Elizabeth E. Samuel
Blessing Amechima

Abstract

This study examined the economic and scale efficiency in processing cassava into gari in Ankpa Local Government, Kogi State. Data were collected from 120 cassava processors through a multistage sampling technique in 2019 using questionnaire as the instrument for data collection. Data collected were analyzed through the use of Data Envelopment Analysis (DEA), ordinary Least squares regression analysis and simple descriptive statistics. The result of the study revealed that about 8.33% and 63.33% achieved full technical efficiency (TE = 1) under the CRS and VRS respectively while 12.50% achieved both full allocative and economic efficiency. About 8.33% achieved full scale efficiency. These efficiency scores revealed the presence of considerable level of inefficiency and room for improvement in order to become fully efficient. The returns to scale analysis revealed that majority of cassava processors (about 90%) are operating under increasing returns scale implying that most of the firms in the sample are too small and therefore would benefit from an increase in scale. The OLS result showed that household size, experience and education are the most important and significant factors affecting both technical and economic efficiency of the processors in the study area. We recommend that processors should be encouraged to form and join viable cooperatives where they can access credit, information, training and processing facilities in order to improve their efficiency.

Keywords:
Gari, data envelopment analysis, efficiency, returns to scale.

Article Details

How to Cite
Haruna, E. O., Samuel, E. E., & Amechima, B. (2020). Data Envelopment Analysis Approach to Estimating Economic and Scale Efficiency in Processing Cassava into Gari in Ankpa Local Area, Kogi State, Nigeria. Asian Journal of Agricultural Extension, Economics & Sociology, 38(7), 16-24. https://doi.org/10.9734/ajaees/2020/v38i730371
Section
Original Research Article

References

Adegun IK, Ajimotokan HA, Akinlosoye AA, Babarinde MS. Development of a cassava processing plant for producing improved stone-free Garri. Journal of Agricultural Technology. 2011;7(5):1193-98.

Globaledge; 2018.

Accessed 15 June 2020

Available:https://globaledge.msu.edu/countries/nigeria/economy

Phillips T, Taylor DS, Sanni L, Akoroda M. A Cassava Industrial Revolution in Nigeria. The potential for a new industrial crop. IFAD/FAO, Rome. 2004;43.

Sanni LO, Onadipe OO, Ilona P, Mussagy MD, Abass A, Dixon AGO. Successes and challenges of Cassava enterprise in West Africa: A case study of Nigeria, Benin and Sierra Leone. International Institute of Tropical Agriculture, Ibadan. Nigeria. 2009; 9-11.

IFAD (International Fund for Agricultural Development) and FAO (Food and Agriculture Organization of the United Nations). A review of cassava in Africa with country case studies on Nigeria, Ghana, the United Republic of Tanzania, Uganda and Benin. Proceedings of the Validation Forum on the Global Cassava Development Strategy. 2005;2:66.

Nigeria’s Cassava Industry. Statistical Handbook. International Institute for Tropical Agriculture (IITA); 2004.

Ehinmowo OO, Ojo SO. Analysis of technical efficiency of cassava processing

methods among small scale processors in South – West, Nigeria. American Journal of Rural Development. 2014;2(2):20-23.

Processing of cassava into gari and high quality Cassava flour in West Africa. USAID / CORAF / SONGHAI TRAINING MANUAL (DRAFT); 2010.

Chukwuji CO, Inini OE, Ike PC. Determinants of technical efficiency in gari processing in Delta State Nigeria. Journal of Central European Agriculture. 2007; 8(3):327-36.

Nweke FI. New challenges in Cassava Transformation in Nigeria and Ghana. Paper presented at the Inn WENT, IFPRI, NEPAD and CTA conference on Success in Africa Agriculture. Pretoria; December 1-3; 2003.

NPC (National Population Commission). Population Census of the Federal Republic of Nigeria; Draft Report; 2006.

Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research. 1978;2:429–44.

Bates JM, Baines D, Whynes DK. Measuring the efficiency of prescribing by general analysis. Journal of Operational Research Society. 1996;47(12):1443–51.

Coelli TJ. Recent developments in frontier modelling and efficiency measurement. Australian Journal of Agricultural and Resource Economics. 1995;39(3):219-45.

Banker RD, Charnes A, Cooper WW. Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science. 1984;30: 1078–92.

Farrell MJ. The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General). 1957;120(3): 253-90.

Fletschner DK, Zepeda L. Efficiency of small landholders in Eastern Paraguay. Journal of Agricultural and Resource Economics. 2002;27:554–72.

Wu S, Prato T. Cost efficiency and scope economies of crop and livestock farms in Missouri. Journal of Agricultural and Applied Economics. 2006;38:539–53.

Coelli T, Rahman S, Thirtle C. Technical, allocative, cost and scale efficiencies in Bangladesh rice cultivation: A Non-parametric Approach. Journal of Agricultural Economics. 2002;53(3):607- 26.

Coelli TJ. A Guide to DEAP version 2.1: A Data Envelopment Analysis (computer) Program. Armidale, Australia: Centre for Efficiency and Productivity Analysis, University of New England; 1996.

Liu JS, Lu LY, Lu, WM, Lin BJ. A survey of DEA applications. Omega. 2013;41:893-902.

Banker RD, Natarajan R. Evaluating contextual variables affecting productivity using data envelopment analysis. Operational Resources. 2008;56(1):48-58.

McDonald, J. Using least squares and Tobit in second stage DEA efficiency analyses. European Journal of Operational Resource. 2009;197:792-98.

Johnson AL, Kuosmanen T. One-stage and two-stage DEA estimation of the effects of contextual variables. European Journal of Operational Research. 2012; 220:559-70.

Umar M, Zainalabidin M, Mad NS, Juwaidah S, Abdullahi I. Application of data envelopment analysis for technical efficiency of smallholder pearl millet farmers in Kano State, Nigeria. Bulgarian Journal of Agricultural Science. 2018; 24(2):213–22.

Le TL, Pai PL, Ke CP, Rebecca HC. Technical and cost efficiency estimates of rice production in Vietnam: A two-stage data envelopment analysis. The Journal of Animal and Plant Sciences. 2019;29(1): 299-305.

Ahzar RA. Education and technical efficiency during the Green Revolution in Pakistan. Economic Development and Cultural Change. 1991;39(3):651–65.