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Does the Adoption of Climate-Smart Agricultural Practices Impact Farmers’ Income? Evidence from Ghana

Author

Listed:
  • Wonder Agbenyo

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

  • Yuansheng Jiang

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

  • Xinxin Jia

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

  • Jingyi Wang

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

  • Gideon Ntim-Amo

    (College of Management, Sichuan Agricultural University, Chengdu 610000, China)

  • Rahman Dunya

    (College of Management, Sichuan Agricultural University, Chengdu 610000, China)

  • Anthony Siaw

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

  • Isaac Asare

    (College of Management, Sichuan Agricultural University, Chengdu 610000, China)

  • Martinson Ankrah Twumasi

    (College of Economics, Sichuan Agricultural University, Chengdu 610000, China)

Abstract

People’s lives, particularly farmers’, have been affected by extreme weather conditions that have reduced the yield of numerous crops due to climate change. Climate-smart agriculture practices can reduce or eliminate greenhouse gas emissions and have the propensity to increase farm income and productivity. Therefore, the purpose of this study is to ascertain whether CSA practices impact farmers’ income. This study includes all cocoa farmers in the selected districts in the Ashanti Region. The population includes those who live in the six cocoa production villages. The multistage sampling procedure was considered based on the dominants of literature. The study used an endogenous switching regression framework to examine the effects of the adoption of climate-smart agricultural practices (CSAPs) on farmers’ income. While estimating treatment effects, telasso uses lasso techniques to select the appropriate variable sets. The results revealed that gender, farm experience, age, household size, and farm size do not significantly influence the adoption of irrigation and crop insurance. The study revealed a significant positive impact of access to credit on adopting irrigation and crop insurance. The adoption of climate-smart practices has a positive coefficient. This indicates that if all respondents in each region adopts these practices, their income would increase significantly. This study shows that adopting irrigation practices leads to an increase in household income of 8.6% and 11.1%, respectively, for cocoa farmers. Crop insurance has a positive coefficient and is statistically significant on household income, on-farm, and off-farm. This paper shows that climate-smart practices such as crop insurance can positively influence farmers’ income in Ghana. We also conjecture that crop insurance is the most effective and efficient climate-smart practice among the various agricultural practices. The study suggests that access to credit and mass awareness should be compulsory modules coupled with the consistent training of farmers on new technologies for effective policy implementation. Expanding access to extension officers could enhance farmers’ adaptive capacity and warrant the efficiency of implemented practices.

Suggested Citation

  • Wonder Agbenyo & Yuansheng Jiang & Xinxin Jia & Jingyi Wang & Gideon Ntim-Amo & Rahman Dunya & Anthony Siaw & Isaac Asare & Martinson Ankrah Twumasi, 2022. "Does the Adoption of Climate-Smart Agricultural Practices Impact Farmers’ Income? Evidence from Ghana," IJERPH, MDPI, vol. 19(7), pages 1-25, March.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:7:p:3804-:d:777644
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    References listed on IDEAS

    as
    1. Malikov, Emir & Sun, Kai & Kumbhakar, Subal C., 2018. "Nonparametric estimates of the clean and dirty energy substitutability," Economics Letters, Elsevier, vol. 168(C), pages 118-122.
    2. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    3. World Bank, 2013. "The World Bank Annual Report 2013," World Bank Publications - Books, The World Bank Group, number 16091, December.
    4. Hou, J. & Huo, X., 2018. "Does Computer Usage Change Farmers Production and Consumption? Evidence from China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276943, International Association of Agricultural Economists.
    5. Sébastien Foudi & Katrin Erdlenbruch, 2012. "The role of irrigation in farmers’ risk management strategies in France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(3), pages 439-457, July.
    6. Ochieng, Justus & Kirimi, Lilian & Mathenge, Mary, 2016. "Effects of Climate Variability and Change on Agricultural Production: The Case of Small-Scale Farmers in Kenya," Working Papers 229711, Egerton University, Tegemeo Institute of Agricultural Policy and Development.
    7. Dillon, Andrew, 2011. "The Effect of Irrigation on Poverty Reduction, Asset Accumulation, and Informal Insurance: Evidence from Northern Mali," World Development, Elsevier, vol. 39(12), pages 2165-2175.
    8. Robert Aidoo & James Osei Mensah & Prosper Wie & Dadson Awunyo-vitor, 2014. "Prospects of Crop Insurance as a Risk Management Tool among Arable Crop Farmers in Ghana," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(3), pages 341-354, March.
    9. Kaczan, David & Arslan, Aslihan & Lipper, Leslie, 2013. "Climate-Smart Agriculture? A review of current practice of agroforestry and conservation agriculture in Malawi and Zambia," ESA Working Papers 288985, Food and Agriculture Organization of the United Nations, Agricultural Development Economics Division (ESA).
    10. Robert Aidoo & James Osei Mensah & Prosper Wie & Dadson Awunyo-Vitor, 2014. "Prospects of Crop Insurance as a Risk Management Tool among Arable Crop Farmers in Ghana," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(3), pages 341-354.
    11. Burney, Jennifer A. & Naylor, Rosamond L., 2012. "Smallholder Irrigation as a Poverty Alleviation Tool in Sub-Saharan Africa," World Development, Elsevier, vol. 40(1), pages 110-123.
    12. Daadi, Bunbom Edward & Latacz-Lohmann, Uwe, 2021. "Organic Fertilizer Adoption, Household Food Access, and Gender-Based Farm Labor Use: Empirical Insights from Northern Ghana," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 53(3), pages 435-458, August.
    13. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    14. Muhammad Khalid Anser & Tayyaba Hina & Shahzad Hameed & Muhammad Hamid Nasir & Ishfaq Ahmad & Muhammad Asad ur Rehman Naseer, 2020. "Modeling Adaptation Strategies against Climate Change Impacts in Integrated Rice-Wheat Agricultural Production System of Pakistan," IJERPH, MDPI, vol. 17(7), pages 1-18, April.
    15. Awudu Abdulai & Wallace Huffman, 2014. "The Adoption and Impact of Soil and Water Conservation Technology: An Endogenous Switching Regression Application," Land Economics, University of Wisconsin Press, vol. 90(1), pages 26-43.
    16. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    17. Wanglin Ma & Xiaobing Wang, 2020. "Internet Use, Sustainable Agricultural Practices and Rural Incomes: Evidence from China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1087-1112, October.
    18. Edmond Totin & Alcade C. Segnon & Marc Schut & Hippolyte Affognon & Robert B. Zougmoré & Todd Rosenstock & Philip K. Thornton, 2018. "Institutional Perspectives of Climate-Smart Agriculture: A Systematic Literature Review," Sustainability, MDPI, vol. 10(6), pages 1-20, June.
    19. Imran, Muhammad Ali & Ali, Asghar & Ashfaq, Muhammad & Hassan, Sarfraz & Culas, Richard & Ma, Chunbo, 2019. "Impact of climate smart agriculture (CSA) through sustainable irrigation management on Resource use efficiency: A sustainable production alternative for cotton," Land Use Policy, Elsevier, vol. 88(C).
    20. Nelson, Gerald C. & Rosegrant, Mark W. & Koo, Jawoo & Robertson, Richard & Sulser, Timothy & Zhu, Tingju & Ringler, Claudia & Msangi, Siwa & Palazzo, Amanda & Batka, Miroslav & Magalhaes, Marilia & Va, 2009. "Climate change: Impact on agriculture and costs of adaptation," Food policy reports 21, International Food Policy Research Institute (IFPRI).
    21. Junpeng Li & Wanglin Ma & Alan Renwick & Hongyun Zheng, 2020. "The impact of access to irrigation on rural incomes and diversification: evidence from China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 12(4), pages 705-725, September.
    22. A. J. Challinor & J. Watson & D. B. Lobell & S. M. Howden & D. R. Smith & N. Chhetri, 2014. "A meta-analysis of crop yield under climate change and adaptation," Nature Climate Change, Nature, vol. 4(4), pages 287-291, April.
    23. Brandon Koch & David M. Vock & Julian Wolfson, 2018. "Covariate selection with group lasso and doubly robust estimation of causal effects," Biometrics, The International Biometric Society, vol. 74(1), pages 8-17, March.
    24. Abdul Nafeo Abdulai, 2016. "Impact of conservation agriculture technology on household welfare in Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 729-741, November.
    25. Deepak Ghimire & Dinesh Panday, 2016. "Interconnection of Climate Change, Agriculture and Climate Justice: Complexities for Feeding the World Under Changing Climate," Development, Palgrave Macmillan;Society for International Deveopment, vol. 59(3), pages 270-273, December.
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