Stochastic meta-frontier function analysis of the regional efficiency and technology gap ratios (TGRs) of small-scale cassava producers in Liberia

References

  • Abdul-kareem MM & Sahinli M, 2018. Demographic and socio-economic characteristics of cassava farmers influencing output levels in the Savannah Zone of Northern Ghana. African Journal of Agricultural Research 13(4): 189–95. https://doi.org/10.5897/AJAR2017.12268
  • Adeyemo R, Oke JTO & Akinola AA, 2010. Economic efficiency of small scale farmers in Ogun State, Nigeria. Tropicultura 28(2): 84–8.
  • Alem H, Lien G, Hardaker JB & Guttormsen A, 2017. Regional differences in technical efficiency and technological gap of Norwegian dairy farms: A stochastic meta-frontier model. Applied Economics 51(4), 409–21. https://doi.org/10.1080/00036846.2018.1502867
  • Alidou GM & Niehof A, 2013. Gender roles in cotton production and management of related organizations in Benin. Gender, Technology and Development 17(3): 313–35. https://doi.org/10.1177/0971852413498739
  • Battese GE & Coelli TJ, 1992. Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis 3: 153–69. https://doi.org/10.1007/BF00158774
  • Battese GE & Rao DSP, 2002. Technology gap, efficiency, and a stochastic metafrontier function. International Journal of Business and Economics 1(2): 87–93.
  • Battese GE, Rao DSP & O'Donnell CJ, 2004. A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis 21: 91–103.
  • Carroll RJ, Ruppert D & Welsh AH, 1998. Local estimating equations. Journal of the American Statistician Association 93(441): 214–27.
  • Coelli TJ, Rao DSP, O’Donnell CJ & Battese GE, 2005. An introduction to efficiency and productivity analysis. Second edition. New York: Springer Science + Business Media.
  • Coulibaly ON, Arinloye D-DAA, Faye M, Abdoulaye T, Vodouhe F, Adjovi GM, Kakpo A & Bankole VNFH, 2014. Regional cassava value chains analysis in West Africa: Regional summary. Technical Report. https://doi.org/10.13140/2.1.2510.2403
  • Debertin DL, 2012. Agricultural production economics. Second edition. Lexington KY: Author.
  • Gbigbi MT, 2011. Economic efficiency of smallholder sweet potato producers in Delta State, Nigeria: A case study of Ughelli South Local Government Area. Research Journal of Agriculture and Biological Sciences 7(2): 163–8.
  • Handwerker WP, 1981. Productivity, marketing efficiency, and price-support programs: Alternative paths to rural development in Liberia. Human Organization 40(1): 27–39.
  • Hayami Y & Ruttan VW, 1971. Induced innovation in agricultural development. Discussion Paper No. 3, Center for Economics Research, Department of Economics, University of Minnesota, Minneapolis.
  • Huang CJ, Huang T & Liu N, 2014. A new approach to estimating the metafrontier production function based on a stochastic frontier framework. Journal of Productivity Analysis 42(3): 241–54.
  • Jondrow J, Knox Lovell CA, Materov IS & Schmidt P, 1982. On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics 19(2–3): 233–8. https://doi.org/10.1016/0304-4076(82)90004-5
  • Khan H & Saeed I, 2011. Measurement of technical, allocative and economic efficiency of tomato farms in northern Pakistan. Proceedings of the International Conference on Management, Economics and Social Sciences (ICMESS 2011), 23–24 December, Bangkok, Thailand.
  • Kinkingninhoun-Mêgagbé FM, Diagne A, Simtowe F, Agboh-Noameshine AR & Adégbola PY, 2010. Gender discrimination and its impact on income, productivity, and technical efficiency: Evidence from Benin. Agriculture and Human Values 27: 57–69. https://doi.org/10.1007/s10460-008-9170-9
  • Kumbhakar SC & Lovell CAK, 2000. Stochastic frontier analysis. Cambridge: Cambridge University Press.
  • Lah MK, Akaba S, Bosompem M & Ntifo-Siaw E, 2018. Public and private extension services delivery to cassava farmers in Sanniquellie and Saclepea Mah Districts in Nimba County, Liberia. Journal of Sustainable Development in Africa 20(1): 64–86.
  • Lebot V, 2009. Tropical root and tuber crops: Cassava, sweet potato, yams and aroids. Crop production science in horticulture Series 17. Wallingford, Oxfordshire: CAB International.
  • LISGIS-RL, 2017. Household income and expenditure survey 2016: Statistical abstract. Monrovia, Liberia: Liberia Institute of Statistics & Geo-Information Services.
  • Maina FW, 2018. Assessing the economic efficiency of milk production among small-scale dairy farmers in Mukurweini sub-county, Nyeri County, Kenya. Master's thesis, University of Nairobi, Kenya.
  • Ministry of Agriculture, 2008. Food and agriculture policy and strategy: “From subsistence to sufficiency”. Monrovia, Liberia: Ministry of Agriculture, Republic of Liberia. Available at https://www.gafspfund.org/sites/default/files/inline-files/Liberia_5_of_7_FAPS_Food_Agriculture_Strategy_0.pdf
  • Nginyangi JM, 2011. Economic efficiency of smallholder coffee production in Mathira District, Kenya. Master's thesis, University of Nairobi, Kenya.
  • Nweke FI, Spencer DSC & Lynam JK, 2002. The cassava transformation. Africa’s best kept secret. East Lansing MI: Michigan State University Press.
  • O’Donnell CJ, Rao DSP & Battese GE, 2008. Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics 34: 231–55. https://doi.org/10.1007/s00181-007-0119-4
  • Ogunleye AS, Adeyemo R, Bamireand AS & Binuiomote SO, 2014. Cassava production and technical efficiency in Ayedaade local government area of Osun State, Nigeria. Elixir Agriculture 71: 24465–8.
  • Rapsomanikis G, 2015. The economic lives of smallholder farmers An analysis based on household data from nine countries. Rome: FAO.
  • Tauer L, 1995. Age and farmer productivity. Review of Agricultural Economics 17(1): 63–9. Available at https://www.jstor.org/stable/1349655
  • Twyman J, Muriel J & García MA, 2015. Identifying women farmers: Informal gender norms as institutional barriers to recognizing women’s contributions to agriculture. Journal of Gender, Agriculture and Food Security 1(2): 1–17.
  • Udry C, Hoddinott J, Alderman H & Haddad L, 1995. Gender differentials in farm productivity: Implications for household efficiency and agricultural policy. Food Policy 20(5): 407–23.
  • Ville S, Po A, Tsun JY, Sen A, Bui A & Melgar-Quiñonez H, 2019. Food security and the Food Insecurity Experience Scale (FIES): Ensuring progress by 2030. Food Security 11(3): 483–91. https://doi.org/10.1007/s12571-019-00936-9
  • White H, 1982. Maximum likelihood estimation of misspecified models. Econometrica 50(1): 1–25. https://doi.org/10.2307/1912526
  • Zinnah MM, 2016. Liberia agriculture transformation agenda: Six agro-clusters identified in Liberia. Monrovia, Liberia: Ministry of Agriculture.