Adoption of rice cultivation technologies and its effect on technical efficiency in Sagnarigu District of Ghana

References

• Abdallah, A., Ayamga, M., & Donkoh, S. A. (2014). Smallholder adoption of soil and water conservation techniques in Ghana. African Journal of Agricultural Research, 9(5), 539–546. doi:10.5897/AJAR2013.7952
   Google Scholar
• Abdulai, S. (2015). Technical efficiency of maize production in Northern Ghana ( Unpublished master’s thesis). University for Development Studies, Tamale, Ghana.
   Google Scholar
• Abdulai, A., & Huffman, W. (2000). Structural adjustment and economic efficiency of rice farmers in Northern Ghana. Economic Development & Cultural Change, 48, 503–519.
   Web of Science ®Google Scholar
• Aigner, D., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21–37. Retrieved from http://pages.stern.nyu.edu/wgreene/FrontierModeling/Reference-Papers/Aigner-Lovell-Schmidt-JE1977-ALS.pdf10.1016/0304-4076(77)90052-5
   Google Scholar
• Aker, J. C., Block, S., Ramachandran, V., & Timmer, P. C. (2011). West African experience with the world rice crisis, 2007–2008. Working Paper 242. Washington, D.C.: Center for Global Development. Retrieved from http://www.cgdev.org/content/publications/detail/1424823
   Google Scholar
• Akighir, D. T., & Shabu, T. (2011). Efficiency of resource use in rice farming enterprise in Kwande Local Government Area of Benue State, Nigeria. International Journal of Humanities and Social Science, 1(3). Retrieved from http://www.ijhssnet.com/journals/Vol._1_No._3;_March_2011/30.pdf
   Google Scholar
• Alhassan, S. (2008). Technical efficiency of rice farmers in Northern Ghana. African Economic Research Consortium Research Paper, 178. Retrieved from www.aercafrica.org/documents/RP178.pdf
   Google Scholar
• Asante, B. O., Wiredu, A. N., & Martey, E. (2014). NERICA adoption and impact on technical efficiency of rice producing households in Ghana: Implications for research and development. American Journal of Experimental Agriculture, 4, 244–262. doi:10.9734/AJEA/2014/7250
   Google Scholar
• Battese, G. E., & Coelli, T. J. (1995). A stochastic frontier production function incorporating a model of technical inefficiency effects. Working Papers in Econometrics and Applied Statistics. Armidale: University of New England.
   Google Scholar
• Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31–72.
   Web of Science ®Google Scholar
• CARD (Centre for Agricultural and Rural Development). (2013). Overview of progress in the rice sector in sub-Saharan Africa. Paper presented at the 5th CARD General Meeting, February 2–6, 2013.
   Google Scholar
• Diagne, A., & Demont, M. (2007). Taking a new look at empirical models of adoption: Average treatment effect estimation of adoption rate and its determinants. Agricultural Economics, 37, 201–210 http://doi/10.1111/j.1574-0862.2007.00266.x10.1111/j.1574-0862.2007.00266.x
   Web of Science ®Google Scholar
• Donkoh, S. A., & Awuni, J. A. (2011). Adoption of Farm Management Practices in Lowland Rice Production in Northern Ghana. Journal of Agricultural and Biological Science, 2(4), 84–93.
   Google Scholar
• Doss, C. R., & Morris, M. L. (2001). How does gender affect the adoption of agricultural innovations? The case of improved maize technology in Ghana. Agricultural Economics, 25, 27–39. doi:10.1016/S0169-5150(00)00096-7
   Web of Science ®Google Scholar
• Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120(3), 253–281. Retrieved from http://www.jstor.org/stable/234310010.2307/2343100
   Web of Science ®Google Scholar
• Greene, W. H. (2003). Econometric analysis (5th ed.). Upper Saddle River, NJ: Pearson educational Inc.
   Google Scholar
• Greene, W. H. (1997). Econometric Analysis (3rd ed.). Upper Saddle River, NJ: Prentice-Hall Inc.
   Google Scholar
• Heckman, J., Ichimura, H., Smith, J., & Todd, P. (1998). Characterizing selection bias using experimental data. Econometrica, 66(5), 1017–1098.
   Web of Science ®Google Scholar
• Huy, H. T. (2007). Technical efficiency of rice-producing households in the Mekong Delta of Vietnam. Asian Journal of Agriculture and Development, 6(2), 35. Retrieved from http://ageconsearch.umn.edu/bitstream/199075/2/AJAD_2009_6_2_3Huy.pdf
   Google Scholar
• Imbens, G., & Wooldridge, J. M. (2009). Recent developments in the econometrics of program evaluation. Journal of Economic Literature, 47(1), 5–86. doi:10.1257/jel.47.1.5
   Web of Science ®Google Scholar
• Jondrow, J. C., Lovelle, A. K., Materov, V., & Schmidt, P. (1982). On the estimation of technical efficiency in the stochastic frontier production function model. Journal of Econometrics, 19(2–3), 233–238. Retrieved from http://doi=10.1.1.334.1736&rep=rep1&type=pdf10.1016/0304-4076(82)90004-5
   Web of Science ®Google Scholar
• King, G. (1988). Statistical models for political science event counts: Bias in conventional procedures and evidence for the exponential Poisson regression model. American Journal of Political Science, 32, 838–863.
   Web of Science ®Google Scholar
• Kuwornu, J. K. M., Amoah, E., & Seini, W. (2013). Technical efficiency analysis of maize farmers in the Eastern Region of Ghana. Journal of Social and Development Sciences, 4(2), 84–99.
   Google Scholar
• Martey, E., Wiredu, A. N., Asante, B. O., Annin, K., Dogbe, W., Attoh, C., & Alhassan, M. R. (2013). Factors influencing participation in rice development projects: The case of smallholder rice farmers in northern Ghana. International Journal of Development and Economic Sustainability, 1(2), 13–27.
   Google Scholar
• Meeusen, W., & Broeck, V. D. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18(2), 435–444. Retrieved from http://www.jstor.org/stable/252575710.2307/2525757
   Web of Science ®Google Scholar
• MoFA (Ministry of Food and Agriculture). (2011). Facts and figures 2010. Accra: Statistics, Research and Information Directorate.
   Google Scholar
• MoFEP (Ministry of Finance and Economic Planning). (2009). Budget statement and economic policy of the Government of Ghana for the 2010 Fiscal Year. Retrieved from www.mofep.gov.gh/sites/default/files/budget/Budget_2010.pdf
   Google Scholar
• Nutsugah, S. K., Buah, S. S. J., Kanton, R. A. L., Atokple, I. D. K., Dogbe, W., Karikari, A. S., … Ndiaye, K. (2011). Enhancing farmers’ access to technology for increased rice productivity in Ghana. African Journal of Agricultural Research, 6(19), 4455–4466 http://doi:10.5897/AJAR11.1152
   Google Scholar
• Nwanze, K. F., Mohapatra, S., Kormawa, P., Shellemiah, K., & Bruce-Oliver, S. (2006). Rice development in sub-Saharan Africa. Journal of Science of Food and Agriculture, 68, 675–677.10.1002/(ISSN)1097-0010
   Google Scholar
• Olaf, K., & Emmanuel, D. (2009). Global food security response: Ghana rice study. USAID micro-report No. 156. Retrieved from http://pdf.usaid.gov/pdf_docs/pnaea870.pdf
   Google Scholar
• Ragasa, C., Dankyi, A., Acheampong, P., Wiredu, A. N., Chapoto, A., Asamoah, M., & Tripp, R. (2013). Patterns of adoption of improved rice technologies in Ghana. Washington, DC: International Food Policy Research Institute. Retrieved from http://www.ifpri.org/publication/patterns-adoption-improved-rice-technologies-ghana
   Google Scholar
• Ransom, J. K., Paudyal, K., & Adhikari, K. (2003). Adoption of improved maize varieties in the hills of Nepal. Agricultural Economics, 29, 299–305 http://doi:10.1111/j.1574-0862.2003.tb00166.x10.1111/agec.2003.29.issue-3
   Web of Science ®Google Scholar
• Rosenbaum, P., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.
   Web of Science ®Google Scholar
• Smith, J., & Todd, P. (2005). Does matching overcome LaLonde’s critique of non-experimental estimators? Journal of Econometrics, 125(1–2), 305–353.
   Web of Science ®Google Scholar
• Wooldridge, J. M. (2005). Instrumental estimation of the average treatment effect in the correlated random coefficient model. East Lansing, MI: Department of Economics, Michigan State University.
   Google Scholar
• Zhou, Z., Robards, K., Helliwell, S., & Blanchard, C. (2002). Composition and functional properties of rice. International Journal of Food Science & Technology, 37, 849–868 http://doi:10.1046/j.1365-2621.2002.00625.x10.1046/j.1365-2621.2002.00625.x
   Web of Science ®Google Scholar