Adoption of integrated crop-livestock management practices (ICLMPs) among men and women smallholder farmers in Ghana

References

• Adesina, A. A., & Baidu-Forson, J. (1995). Farmers’ perceptions and adoption of new agricultural technology: evidence from analysis in Burkina Faso and Guinea, West Africa. Agricultural Economics, 13(1): 1–9. https://doi.org/10.1016/0169-5150(95)01142-8
   Web of Science ®Google Scholar
• Ahmed, M. H. (2015). Adoption of multiple agricultural technologies in maize production of the Central Rift valley of Ethiopia. Studies in Agricultural Economics, 117(3), 162–168. https://doi.org/10.7896/j.1521
   Web of Science ®Google Scholar
• Akudugu, M. A., Guo, E., & Dadzie, S. K. (2012). Adoption of modern agricultural production technologies by farm households in Ghana: What factors influence their decisions? Journal of Biology, Agriculture and Healthcare, 2(3), 1–13.
   Google Scholar
• Asante B. O, Villano R. A., & Battese G. E, (2014). The effect of the adoption of yam minisett technology on the technical efficiency of yam farmers in the forest-savanna transition zone of Ghana. African Journal of Agricultural and Resource Economics, 9(2): 75–90.
   Google Scholar
• Asante, B. O., Temoso, O., Addai, K. N., & Villano, R. (2019). Evaluating productivity gaps in maize production across different agroecological zones in Ghana. Agricultural Systems, 176, 102650. https://doi.org/10.1016/j.agsy.2019.102650
   Web of Science ®Google Scholar
• Asante, B. O., Villano, R. A., Patrick, I. W., & Battese, G. E. (2017a). Impacts of exposure and access to seed on the adoption of dual-purpose cowpea and groundnut varieties in Ghana. The Journal of Developing Areas, 51(3), 173–194. https://doi.org/10.1353/jda.2017.0067
   Google Scholar
• Asante, B. O., Villano, R. A., Patrick, I. W., & Battese, G. E. (2017b). Determinants of farm diversification in integrated crop-livestock farming systems in Ghana. Renewable Agriculture and Food Systems, 33(2), 119–131. https://doi.org/10.1017/S1742170516000545
   Web of Science ®Google Scholar
• Asekenye, C., Bravo-Ureta, B. E., Deom, M., Kidula, N., KaluleOkello, D., Okoko, N., & Puppala, N. (2016). Productivity gaps among groundnut farmers in Kenya and Uganda: A stochastic production frontier analysis. African Journal of Agricultural and Resource Economics, 11(2), 85–100.
   Google Scholar
• Aryal, J. P., Farnworth, C. R., Khurana, R., Ray, S., Sapkota, T. B., & Rahut, D. B. (2020). Does women’s participation in agricultural technology adoption decisions affect the adoption of climate‐smart agriculture? Insights from Indo‐Gangetic Plains of India. Review of Development Economics, 24(3): 973–990.
   Web of Science ®Google Scholar
• Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological methods, 8(2), 129, 148. https://doi.org/10.1037/1082-989x.8.2.129
   PubMed Web of Science ®Google Scholar
• Becerril, J., & Abdulai, A. (2010). The impact of improved maize varieties on poverty in Mexico: A propensity score-matching approach. World Development, 38(7), 1024–1035. https://doi.org/10.1016/j.worlddev.2009.11.017
   Web of Science ®Google Scholar
• Belderbos, R., Carree, M., Diederen, B., Lokshin, B., & Veugelers, R. (2004). Heterogeneity in R & D cooperation strategies. International Journal of Industrial Organization, 22(8–9), 1237–1263. https://doi.org/10.1016/j.ijindorg.2004.08.001
   Web of Science ®Google Scholar
• Bortei-Doku, E. (1990). Profile of women in Ghana. Canadian High Commission.
   Google Scholar
• Byravan, S. 2009. Gender and Innovation in South Asia. RePEc. http://search.proquest.com/docview/1698353421/
   Google Scholar
• Budescu, D. V. (1993). Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychological Bulletin, 114(3), 542–551. https://doi.org/10.1037/0033-2909.114.3.542
   Web of Science ®Google Scholar
• Doss, C. R. 2018. Women and agricultural productivity: Reframing the issues. Development Policy Review, 36(1): 35–50. https://doi.org/10.1111/dpr.12243
   PubMed Web of Science ®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(1), 27–39. Available at: https://doi.org/10.1016/S0169-5150(00)00096-7
   Web of Science ®Google Scholar
• Chavas, J. P., & Di Falco, S. (2012). On the role of risk versus economies of scope in farm diversification with an application to Ethiopian farms. Journal of Agricultural Economics, 63(1), 25–55. https://doi.org/10.1111/j.1477-9552.2011.00319.x
   Web of Science ®Google Scholar
• Chirwa, E. W. (2005) Adoption of fertiliser and hybrid seeds by smallholder maize farmers in Southern Malawi. Development Southern Africa, 22(1), 1–12. https://doi.org/10.1080/03768350500044065
   Google Scholar
• Cameron, A. C., & Trivedi, P. K. (2010). Microeconometrics using stata (5:706). Stata press.
   Google Scholar
• Croppenstedt, A, Goldstein, M., & Rosas, N (2013). Gender and agriculture: Inefficiencies, segregation, and low productivity traps. The World Bank Research Observer, 28(1), 1–31.
   Web of Science ®Google Scholar
• Crost, B., Shankar, B., Bennett, R., & Morse, S. (2007). Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data. Journal of Agricultural Economics, 58(1), 24–36. https://doi.org/10.1111/j.1477-9552.2007.00076.x
   Web of Science ®Google Scholar
• Dennery, P. (1996). Urban food producers’ decision making: A case study of Kibera, city of Nairobi, Kenya. African Urban Quarterly, 11(2–3): 189–200.
   Google Scholar
• Donkoh A. S., & Ayamga M. (2014). Improved rice variety adoption and its effects on farmers’ output in Ghana. Journal of Development and Agricultural Economics, 6(6), 242–248.
   Google Scholar
• Dontsop Nguezet, P. M., Diagne, A., Okoruwa, O. V., Ojehomon, V., & Manyong, V. (2013). Estimating the Actual and Potential Adoption Rates and Determinants of NERICA Rice Varieties in Nigeria. Journal of Crop Improvement, 27(5), 561–585. https://doi.org/10.1080/15427528.2013.811709
   Google Scholar
• Farid K. S., Tanny, N. Z., & Sarma, P. K. (2016). Factors affecting adoption of improved farm practices by the farmers of Northern Bangladesh. Journal of the Bangladesh Agricultural University, 13(2): 291–298. https://doi.org/10.3329/jbau.v13i2.28801
   Google Scholar
• FAO, IFAD, and ILO. 2010. Gender dimensions of agricultural and rural employment: Differentiated pathways out of poverty. Status, trends and gaps. FAO.
   Google Scholar
• Food and Agriculture Organization. 2010. An international consultation on integrated crop-livestock systems for development: The way forward for sustainable production intensification. FAO.
   Google Scholar
• Fisher, M., & V. Kandiwa. 2014. Can agricultural input subsidies reduce the gender gap in modern maize adoption? Evidence from Malawi. Food Policy, 45, 101–111. https://doi.org/10.1016/j.foodpol.2014.01.007
   Web of Science ®Google Scholar
• Gao, L., Zhang, W., Mei, Y., Sam, A. G., Song, Y., & Jin, S. (2018). Do farmers adopt fewer conservation practices on rented land? Evidence from straw retention in China, Land Use Policy, 79, 609–621. https://doi.org/10.1016/j.landusepol.2018.08.026
   Web of Science ®Google Scholar
• Gebre, G. G., Isoda, H., Rahut, D. B., Amekawa, Y., & Nomura, H. (2019). Gender differences in the adoption of agricultural technology: The case of improved maize varieties in southern Ethiopia. Women’s Studies International Forum, 76, 102264. https://doi.org/10.1016/j.wsif.2019.102264
   PubMed Web of Science ®Google Scholar
• Genius, M., Koundouri, M., Nauges, C., & Tzouvelekas, V. (2010). Information transmission in irrigation technology adoption and diffusion: Social learning, extension services and spatial effects. American Journal of Agricultural Economics, 96(1), 328–344.
   Google Scholar
• Geroski, P. A. (2000). Models of technology diffusion. Research Policy, 29(4–5), 603–625. https://doi.org/10.1016/S0048-7333(99)00092-X
   Web of Science ®Google Scholar
• Ghana Districts Repository. (2018). Districts profiles of Ghana. http://ghanadistricts.com/home/
   Google Scholar
• Ghana Statistical Service. (2014). National accounts statistics. Final 2012 gross domestic product and Revised 2013 gross domestic product. http://www.statsghana.gov.gh/
   Google Scholar
• Gichuki, C. N., & Mulu-Mutuku, M. (2018). Determinants of awareness and adoption of mobile money technologies: Evidence from women micro entrepreneurs in Kenya. Women’s Studies International Forum, 67, 18–22. https://doi.org/10.1016/j.wsif.2017.11.013
   Web of Science ®Google Scholar
• Greene, W. H. (2000). Econometric analysis (4th ed., pp. 201–215). Prentice Hall.
   Google Scholar
• Greene, W. H. (2008). The econometric approach to efficiency analysis. In H. O. Fried, C. A. K. Lovell, & S. S. Schmidt (Eds.), The measurement of productive efficiency and productivity growth. Oxford University Press.
   Google Scholar
• Government of Ghana. (2017). The budget statement and economic policy of the Government of Ghana for the 2017 financial year (1st ed.). Ministry of Finance.
   Google Scholar
• Harrison, M. T., Cullen B. R., & Rawnsley, R. P. (2016). Modelling the sensitivity of agricultural systems to climate change and extreme climatic events, Agricultural Systems, 148, 135–148. https://doi.org/10.1016/j.agsy.2016.07.006
   Web of Science ®Google Scholar
• Heintz, J. 2006. Globalization, economic policy and employment: Poverty and gender implications (Employment Strategy Paper 2006/3). International Labour Organization.
   Google Scholar
• Herrero, M., González-Estrada, E., Thornton, P. K., Quiros, C., Waithaka, M. M., Ruiz, R., & Hoogenboom, G. (2007). IMPACT: Generic household-level databases and diagnostics tools for integrated crop-livestock systems analysis. Agricultural Systems, 92(1–3), 240–265. https://doi.org/10.1016/j.agsy.2006.03.008
   Web of Science ®Google Scholar
• Huyer, S. 2016. Closing the gender gap in agriculture. Gender, Technology and Development, 20(2): 105–116. https://doi.org/10.1177/0971852416643872
   Web of Science ®Google Scholar
• Institute of Statistical, Social and Economic Research. (2016). The state of the Ghanaian economy. Legon, Accra: University of Ghana.
   Google Scholar
• Julien, J., Bravo-Ureta B. E., & Rada, N. (2019). Assessing farm performance by size in Malawi, Tanzania, and Uganda, Food Policy, 84, 153–164. https://doi.org/10.1016/j.foodpol.2018.03.016
   Web of Science ®Google Scholar
• Kabunga, N. S., Dubois, T., & Qaim, M. (2012). Heterogeneous information exposure and technology adoption: The case of tissue culture bananas in Kenya. Agricultural Economics, 43(5), 473–486. https://doi.org/10.1111/j.1574-0862.2012.00597.x
   Web of Science ®Google Scholar
• Kawarazuka, N., Prain, G., Forsythe, L., Mayanja, S., Mudege, N. N., Babini, C., & Polar, V. 2018. Gender in agricultural mechanization: Key guiding questions. International Potato Center.
   Google Scholar
• Karbo, N., & Agyare, W. (2002). Crop livestock systems in Northern Ghana [Paper presentation]. Workshop on Crop-Livestock Systems in Dry Savannas of West and Central Africa, Ibadan, Nigeria.
   Google Scholar
• Kariyasa, K., & Dewi, A. (2011). Analysis of factors affecting adoption of Integrated Crop Management Farmer Field School (Icm-Ffs) in swampy areas. International Journal of Food and Agricultural Economics, 1(2), 29–38.
   Google Scholar
• Karshenas, M., & Stoneman, P. (1995). Technological diffusion. In Handbook of the economics of innovation and technological change. Blackwell Publisher.
   Google Scholar
• Kassie, M., Jaleta, M., Shiferaw, B., Mmbando, F., & Mekuria, M. (2013). Adoption of interrelated sustainable agricultural practices in smallholder systems: Evidence from rural Tanzania. Technological Forecasting and Social Change, 80(3), 525–540. https://doi.org/10.1016/j.techfore.2012.08.007
   Web of Science ®Google Scholar
• Kassie, M., Teklewold, H., Jaleta, M., Marenya, P., & Erenstein, O. (2015). Understanding the adoption of a portfolio of sustainable intensification practices in Eastern and Southern Africa. Land Use Policy, 42(1), 400–411. https://doi.org/10.1016/j.landusepol.2014.08.016
   Google Scholar
• Kassie, M., Zikhali, P., Manjur, K., & Edwards, S. (2009). Adoption of organic farming technologies: Evidence from semi-arid regions of Ethiopia. Natural Resources Forum, 33(3), 189–198. https://doi.org/10.1111/j.1477-8947.2009.01224.x
   Web of Science ®Google Scholar
• Khonje, M., Manda, J., Alene, A. D., & Kassie, M. (2015). Analysis of adoption and impacts of improved maize varieties in eastern Zambia. World Development, 66, 695–706. https://doi.org/10.1016/j.worlddev.2014.09.008
   Web of Science ®Google Scholar
• Koomson, I., Annim, S. K., & Peprah, J. A. (2016). Loan refusal, household income and savings in Ghana: A dominance analysis approach. African Journal of Economic and Sustainable Development, 5(2), 172–191. https://doi.org/10.1504/AJESD.2016.076095
   Google Scholar
• Kristjanson, P., Bryan, E., Bernier, Q., Twyman, J., Meinzen-Dick, R., Kieran, C., Ringler, C., Jost, C., & Doss, C. 2017. Addressing gender in agricultural research for development in the face of a changing climate: Where are we and where should we be going? International Journal of Agricultural Sustainability, 15(5): 482–500. https://doi.org/10.1080/14735903.2017.1336411
   Web of Science ®Google Scholar
• Mariano, M. J., Villano, R., & Fleming, E. (2012). Factors influencing farmer’s adoption of modern rice technologies and good management practices in the Philippines. Agricultural systems, 110(2012) 41–53. https://doi.org/10.1016/j.agsy.2012.03.010
   Google Scholar
• Mignouna, B., Manyong, M., Rusike, J., Mutabazi, S., & Senkondo, M. (2011). Determinants of adopting Imazapyr-resistant maize technology and its impact on household income in Western Kenya. AgBioforum, 14(3), 158–163.
   Google Scholar
• Ministry of Food and Agriculture. (2010). Medium term agriculture sector investment plan (METASIP). Statistics, Research and Information Directorate (SRID). https://agricinghana.files.wordpress.com/2013/02/medium-term-agriculture-sector-investment-plan-ghana.pdf
   Google Scholar
• Ministry of Food and Agriculture. (2016). Agriculture facts and figures. Statistics, Research and Information Directorate (SRID).
   Google Scholar
• Mponela, P., Tamene, L., Ndengu, G., Magreta, R., Kihara, J., & Mango, N. (2016). Determinants of integrated soil fertility management technologies adoption by smallholder farmers in the Chinyanja Triangle of Southern Africa, Land Use Policy, 59, 38–48. https://doi.org/10.1016/j.landusepol.2016.08.029
   Web of Science ®Google Scholar
• Mulwa, C., Marenya, P., Rahut, D. B., & Kassie, M. (2017). Response to climate risks among smallholder farmers in Malawi: A multivariate probit assessment of the role of information, household demographics, and farm characteristics. Climate Risk Management, 16(1), 208–221. https://doi.org/10.1016/j.crm.2017.01.002
   Google Scholar
• Muzari, W., Gatsi, W., & Muvhunzi, S. (2012). The impacts of technology adoption on smallholder agricultural productivity in Sub-Saharan Africa: A review. Journal of Sustainable Development, 5(8), 69–77. https://doi.org/10.5539/jsd.v5n8p69
   Google Scholar
• Mwangi, M., & Kariuki, S. (2015). Factors determining adoption of new agricultural technology by smallholder farmers in developing countries. Journal of Economics and Sustainable Development, 6(5), 208–216.
   Google Scholar
• Nathans, L. L., Oswald, F. L., & Nimon, K. (2012). Interpreting multiple linear regression: A guidebook of variable importance. Practical Assessment, Research and Evaluation, 17(9), 2.
   Google Scholar
• Ndiritu, S. W., Kassie, M., & Shiferaw, B. (2014). Are there systematic gender differences in the adoption of sustainable agricultural intensification practices? Evidence from Kenya. Food Policy, 49, 117–127. https://doi.org/10.1016/j.foodpol.2014.06.010
   Web of Science ®Google Scholar
• Ngome, I., & Foeken, D. (2012). “My garden is a great help”: gender and urban gardening in Buea, Cameroon. Geo Journal, 77(1), 103–118. https://doi.org/10.1007/s10708-010-9389-z
   Google Scholar
• Ogada, M. J., Mwabu, G., & Muchai, D. (2014). Farm technology adoption in Kenya: a simultaneous estimation of inorganic fertilizer and improved maize variety adoption decisions. Agricultural and Food Economics, 2(1), 1–18. https://doi.org/10.1186/s40100-014-0012-3
   Google Scholar
• Peterman, A., Julia B., & Agnes Q. (2010). A review of empirical evidence on gender differences in non-land agricultural inputs, technology, and services in developing countries. International Food Policy Research Institute (IFPRI).
   Google Scholar
• Ragasa, C. (2012, August 18–24). Gender and institutional dimensions of agricultural technology adoption: A review of literature and synthesis of 35 case studies [Poster presentation]. International Association of Agricultural Economists (IAAE) Triennial Conference, Foz do Iguaçu, Brazil
   Google Scholar
• Satyavathi, C. T., Bharadwaj, C., & Brahmanand, P. S. (2010). Role of farm women in agriculture. Gender, Technology and Development, 14(3), 441–449. https://doi.org/10.1177/097185241001400308
   Google Scholar
• Santillán-Fernández, A., Santoyo-Cortés, V. H., García-Chávez, L. R., Covarrubias-Gutiérrez, I., & Merino, A. (2016). Influence of drought and irrigation on sugarcane yields in different agroecoregions in Mexico. Agricultural Systems, 143, 126–135. https://doi.org/10.1016/j.agsy.2015.12.013
   Web of Science ®Google Scholar
• Sulo, T., Koech, P., Chumo, C., & Chepng’eno, W. (2012). Socioeconomic factors affecting the adoption of improved agricultural technologies among women in Marakwet county Kenya, Journal of Emerging Trends in Economics and Management Sciences (JETEMS), 3(4), 312–317.
   Google Scholar
• Tanellari, E., Kostandini, G., Bonabana-Wabbi, J., & Murray, A. (2014). Gender impacts on adoption of new technologies: the case of improved groundnut varieties in Uganda, African Journal of Agricultural and Resource Economics, 9(4), 300–308.
   Google Scholar
• Temoso, O., Villano, A., & Hadley, D. (2016). Evaluating productivity gaps between commercial and traditional beef production systems in Botswana. Agricultural Systems, 149, 30–39. https://doi.org/10.1016/j.agsy.2016.07.014
   Web of Science ®Google Scholar
• Teklewold, H., Kassie, M., & Shiferaw, B. (2013). Adoption of multiple sustainable agricultural practices in Rural Ethiopia, Journal of Agricultural Economics, 64(3), 597–623. https://doi.org/10.1111/1477-9552.12011
   Web of Science ®Google Scholar
• Thornton, P. K., van de Steeg, J., Notenbaert, A., & Herrero, M. (2009). The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agricultural Systems, 101(3), 113–127. https://doi.org/10.1016/j.agsy.2009.05.002
   Web of Science ®Google Scholar
• Tinsley, C. H., & Ely, R. J. (2018, May–June). What most people get wrong about men and women: Research shows the sexes are not so different. Harvard Business Review. https://hbr.org/2018/05/what-most-people-get-wrong-about-men-and-women
   Google Scholar
• Tsige, M., Synnevåg, G., & Aune, J. B. (2020). Gendered constraints for adopting climate-smart agriculture amongst smallholder Ethiopian women farmers. Scientific African, 7, e00250. https://doi.org/10.1016/j.sciaf.2019.e00250
   Google Scholar
• Uaiene, R., Arndt, C., & Masters, W. (2009) Determinants of agricultural technology adoption in Mozambique. Discussion papers No. 67E. Ministry of Planning and Development, Republic of Mozambique, Tete.
   Google Scholar
• Uduji, J. I., & Okolo-Obasi, E. N. (2018). Adoption of improved crop varieties by involving farmers in the e-wallet program in Nigeria. Journal of Crop Improvement, 32(5), 717–737. https://doi.org/10.1080/15427528.2018.1496216
   Web of Science ®Google Scholar
• Villano, R., Asante, B. O., & Bravo-Ureta, B. (2019). Farming systems and productivity gaps: Opportunities for improving smallholder performance in the Forest-Savannah transition zone of Ghana. Land Use Policy, 82, 220–227. https://doi.org/10.1016/j.landusepol.2018.12.010
   Web of Science ®Google Scholar
• Whitfield, S., Dixon, J. L., Mulenga, B. P., & Ngoma, H. (2015). Conceptualising farming systems for agricultural development research: Cases from Eastern and Southern Africa. Agricultural Systems, 133, 54–62. https://doi.org/10.1016/j.agsy.2014.09.005
   Web of Science ®Google Scholar
• Wiredu, A. N., Gyasi, K. O., Saaka, S. S. J., Asante, B. O., & Mensah-Bonsu, A. (2012). Factors affecting proportions of land allocated to the mini-sett technology by yam producers in Northern Ghana. African Journal of Agricultural Research, 7(29), 4158–4166.
   Google Scholar
• Wooldridge, J. M., 2002. Econometric analysis of cross section and panel data (3rd ed.). MIT Press.
   Google Scholar
• World Bank, FAO, and IFAD. 2009. Gender in agriculture sourcebook. The World Bank, Food and Agriculture Organization, and International Fund for Agricultural Development.
   Google Scholar
• World Bank. (2007). Ghana: Meeting the challenge of accelerated and shared growth. In Z. Bogetic (Ed.), Country economic memorandum (pp. 1–80). World Bank.
   Google Scholar
• Wu, J. J., & Babcock, B. A. (1998). The choice of tillage, rotation, and soil testing practices: Economic and environmental implications. American Journal of Agricultural Economics, 80(3), 494–511. https://doi.org/10.2307/1244552
   Web of Science ®Google Scholar