Economic Efficiency of Cassava Production in Nimba County, Liberia: An Output-Oriented Approach
In Liberia, many of the agricultural households cultivate cassava for either sustenance purposes, or to generate farm income. Many of the concentrated cassava farmers reside in Nimba, a north-eastern County that borders two other economies: the Republics of Cote D’Ivoire and Guinea. With a high demand for cassava output and products in emerging Asian markets coupled with an objective of the Liberia agriculture policies to increase the competitiveness of valued agriculture crops; there is a need to examine the level of resource-use efficiency for many agriculture crops. However, there is a scarcity of information on the efficiency of many agriculture crops, including cassava. Hence the study applying an output-oriented method seeks to assess the economic efficiency of cassava farmers in Nimba County, Liberia. A multi-stage sampling technique was employed to generate a sample for the study. From 216 cassava farmers, data related to on-farm attributes, socio-economic and institutional factors were collected. The stochastic frontier models, using the Translog functional forms, of production and revenue, were used to determine the level of revenue efficiency and its determinants. The result showed that most of the cassava farmers are male (60%). Many of the farmers are either married, engaged or living together with a spouse (83%), with a mean household size of nine persons. Farmland is prevalently obtained by inheritance (95%), average farm size is 1.34 hectares, and most cassava farmers did not access agriculture credits (76%) and extension services (91%). The mean cassava output per hectare is 1,506.02 kg, which estimates average revenue of L$23,551.16 (Liberian dollars). Empirical results showed that the revenue efficiency of cassava farmers varies from 0.1% to 73.5%; with the mean revenue efficiency of 12.9%. This indicates that on average, there is a vast potential of 87.1% to increase the economic efficiency of cassava farmers in Nimba by improving technical and allocative efficiencies. For the significant determinants of revenue efficiency, age and group membership had negative effects on revenue efficiency of cassava production; while farming experience, access to extension, formal education, and average wage rate have positive effects. The study recommends the setting-up and incentivizing of farmer field schools for cassava farmers to primarily share their farming experiences with others and to learn robust cultivation techniques of sustainable agriculture. Also, farm managers and farmers should consider a fix wage rate in labor contracts for all stages of cassava farming.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 226
 Liberia CB of. Central Bank of Liberia Annual Report for 2017. 2017.
 LISGIS-RL. Household Income and Expenditure Survey 2016 Statistical Abstract. Monrovia, Liberia; 2017.
 Ministry of Agriculture, Republic of Liberia. Production estimates of Major Crops and Animals - 2008. Monrovia, Liberia; 2009.
 Coulibaly ON, Abdoulaye T, Arinloye D-DAA, Vodouhe F. Regional Cassava Value Chains Analysis in West Africa: Regional Summary. 2014 (JANUARY):49.
 Liberia CB of. Central Bank of Liberia Annual Report for 2018. 2018.
 Nweke FI, Spencer DSC, Lynam JK. The Cassava Transformation. Africa’s Best Kept Secret. Michigan State University Press, East Lansing, MI. Michigan State University Press • East Lansing; 2002. 293 p.
 Ministry of Commerce and Industry R of L. Liberia: Ministry of Commerce and Industry Transition Report_2017 (Internet). 2017. Available from: http://moci.gov.lr/doc/MoCI.Min.Addy.Transition.Rebranding Commerce.Final_small_1.pdf
 LISGIS. Republic of Liberia 2008 National Population and Housing Census: Final Results. Popul (English Ed. 2009;(May):1–5.
 Government of Liberia (b). Nimba County Development Agenda, Republic of Liberia. 2012.
 Zinnah MM. Liberia Agriculture Transformation Agenda_Six Agro-clusters Identified in Liberia. Monrovia, Liberia: Ministry of Agriculture, Liberia; 2016.
 Kothari CR. Research Methodology: Methods and Techniques (Internet). New Age International Publishers; 2004. 418 p. Available from: http://dspace.utamu.ac.ug:8080/xmlui/bitstream/handle/123456789/181/ Research Methodology - Methods and Techniques 2004.pdf?sequence=1
 Debreu G. The Coefficient of Resource Utilization (Internet). Vol. 19, Source: Econometrica. 1951 (cited 2019 Feb 12). Available from: https://www.jstor.org/stable/pdf/1906814.pdf?refreqid=excelsior%3A3b9856168eaab28ca543b12e39861634
 Koopmans CT. Efficient Allocation of Resources. Econometrica). 1951 (cited 2019 Feb 12). Vol. 19,(No. 4):455–65. Available from: https://about.jstor.org/terms
 Farrell M. The Measurement of Productive Efficiency. R Stat Soc. 1957;120(3):253–90.
 Schmidt P, Lovell CAK. Estimating Technical and Allocative Inefficiency relative to Stochastic Production & Cost Frontiers. J Econom. 1979;9:343–66.
 Aigner DJ and, Chu SF. On Estimating the Industry Production Function. Am Econ Rev. 1968;58(3):531–7.
 Meeusen W, Van Den Broeck J. Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. Int Econ Rev (Philadelphia). 1977;18(2):435–44.
 Aigner D, Lovell CAK, Schmidt P. Formulation and Estimation of Stochastic Frontier Production Models. J Econom. 1977;6:21–37.
 Afriat S n. Efficiency Estimation of Production Functions. Int Econ Rev (Philadelphia). 1972;13(3):568–98.
 Fare R, Knox Lovell CA. Measuring the technical efficiency of production. J Econ Theory. 1978;19(1):150–62.
 Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision-making units. Eur J Oper Res. 1978;2(6):429–44.
 Coelli TJ, Rao DSP, O’Donnell CJ, Battese GE. An Introduction to Efficiency and Productivity Analysis. 2nd Editio. Springer Science + Business Media, Inc; 233 Spring Street, New York; 2005. 331 p.
 Kumbhakar SC, Lovell C a. K. Stochastic frontier analysis. Stoch Front Anal (Internet). 2000;69:680. Available from: http://books.google.com/books?hl=en&lr=&id=wrKDztxLWZ8C&oi=fnd&pg=PR9&dq=Stochastic+frontier+analysis&ots=L1Ptx0MJ21&sig=k1yR968QVtd1YCORupspxcLgtDs
 Cooper WW, Seiford LM, Tone K. Data Envelopment Analysis: A comprehensive text with Models, Applications, References and DEA-Solver Software. Second Edi. Springer Science + Business Media, LLC. 2007. 512 p.
 Mukherjee C, White H, Wuyts M. Econometrics and data analysis for developing countries. Paul Mosle. London & New York: Routledge, London & New York; 1998. 515 p.
 Fuss M, McFadden DL. Production Economics: A Dual Approach to Theory and Applications, M. Fuss and D. McFadden, 1978, North-Holland (Internet). North-Holland; 1978 (cited 2020 Feb 18). Available from: https://eml.berkeley.edu/~mcfadden/prodecon1.html
 Rapsomanikis G. The economic lives of smallholder farmers An analysis based on household data from nine countries. 2015;52(1):114–7. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0080210716307531
 Khan H, Saeed I. Measurement of Technical , Allocative and Economic Efficiency of Tomato Farms in Northern Pakistan. International Conference on Management, Economics and Social Sciences. 2011.
 Maina FW. Assessing the Economic Efficiency of Milk Production Among Small-scale Dairy Farmers in Mukurweini Sub-county, Nyeri County, Kenya. University of Nairobi; 2018.
 Nginyangi JM. Economic Efficiency of Smallholder Coffee Production in Mathira District, Kenya. University of Nairobi; 2011.
 Tauer LW. Age and Farm Productivity. 1995;17(1):63–9.
 Lema HT. Comparison of economic efficiency of organic and conventional coffee farming systems in Moshi rural district - Tanzania. University of Nairobi; 2013.
 Mutoko M c., Ritho CN, Benhim J. Technical and allocative efficiency gains from integrated soil fertility management in the maize farming system of Kenya. J Dev Agric Econ (Internet). 2015;7(4):143–52. Available from: http://academicjournals.org/journal/JDAE/article-abstract/6EE942E51490
 Abdul-kareem MM, Sahinli M. Demographic and socio-economic characteristics of cassava farmers influencing output levels in the Savannah Zone of Northern Ghana. African J Agric Res. 2018;13(4):189–95.
 Adeyemo R, Oke JTO, Akinola AA. Economic Efficiency of Small Scale Farmers in Ogun State , Nigeria. Tropicultura. 2010;28(2):84–8.
 Ogunleye AS, Adeyemo R, Binuiomote. ASBSO. Cassava production and technical efficiency in ayedaade local government area of Osun State, Nigeria. Elixir Agric. 2014;71:24465–8.
 Muzungu PG. Technical Efficiency of Smallholder Irish Potato Production in Nyabihu District, Rwanda (Master Thesis, University of Nairobi) (Internet). 2011 (cited 2019 Feb 23). Available from: https://ageconsearch.umn.edu/record/243460/