Willingness to pay for crop insurance in Tolon District of Ghana: Application of an endogenous treatment effect model

Joshua Anamsigiya Nyaaba; Kwame Nkrumah-Ennin; Benjamin Tetteh Anang; Joshua Anamsigiya Nyaaba; Kwame Nkrumah-Ennin; Benjamin Tetteh Anang

doi:10.3934/agrfood.2019.2.362

AIMS Agriculture and Food

2019, Volume 4, Issue 2: 362-375. doi: 10.3934/agrfood.2019.2.362

Previous Article Next Article

Research article

Willingness to pay for crop insurance in Tolon District of Ghana: Application of an endogenous treatment effect model

Department of Agricultural Economics and Extension, Faculty of Agriculture, University for Development Studies, Tamale, Ghana

Received: 23 January 2019 Accepted: 22 March 2019 Published: 26 April 2019

The purpose of this study was to assess the factors affecting farmers’ awareness of and willingness to pay for crop insurance in Tolon District of Ghana. The study was guided by the following objectives: (1) to determine farmers’ level of awareness of crop insurance, (2) to analyse the factors affecting awareness of crop insurance and (3) to identify the factors that affect willingness to pay for crop insurance. Data was collected from 150 respondents from three farming communities in the Tolon District. Questionnaires were used as instruments for data collection. The computer software package STATA version 15 was used to analyse the quantitative data. Farmers’ level of awareness of crop insurance was described descriptively while an endogenous treatment effect model was used to analyse the factors affecting awareness and willingness to pay. The result indicated that 48% of the respondents were aware of crop insurance. The results showed that sex of the farmer, extension training and adoption of good agriculture practices were significant factors affecting awareness of crop insurance. Also, willingness to pay for crop insurance was influenced by household size, years of farming experience, farm size and respondent’s awareness of crop insurance. The study concluded that increasing awareness of crop insurance is an effective way to enhance farmers’ willingness to pay. Hence, any intervention to promote adoption of crop insurance should target awareness campaign in order to increase the level of awareness especially among male farmers.
- awareness,
- willingness to pay,
- crop insurance,
- small-scale maize farmers,
- Ghana
Citation: Joshua Anamsigiya Nyaaba, Kwame Nkrumah-Ennin, Benjamin Tetteh Anang. Willingness to pay for crop insurance in Tolon District of Ghana: Application of an endogenous treatment effect model[J]. AIMS Agriculture and Food, 2019, 4(2): 362-375. doi: 10.3934/agrfood.2019.2.362

Related Papers:

Abstract

The purpose of this study was to assess the factors affecting farmers’ awareness of and willingness to pay for crop insurance in Tolon District of Ghana. The study was guided by the following objectives: (1) to determine farmers’ level of awareness of crop insurance, (2) to analyse the factors affecting awareness of crop insurance and (3) to identify the factors that affect willingness to pay for crop insurance. Data was collected from 150 respondents from three farming communities in the Tolon District. Questionnaires were used as instruments for data collection. The computer software package STATA version 15 was used to analyse the quantitative data. Farmers’ level of awareness of crop insurance was described descriptively while an endogenous treatment effect model was used to analyse the factors affecting awareness and willingness to pay. The result indicated that 48% of the respondents were aware of crop insurance. The results showed that sex of the farmer, extension training and adoption of good agriculture practices were significant factors affecting awareness of crop insurance. Also, willingness to pay for crop insurance was influenced by household size, years of farming experience, farm size and respondent’s awareness of crop insurance. The study concluded that increasing awareness of crop insurance is an effective way to enhance farmers’ willingness to pay. Hence, any intervention to promote adoption of crop insurance should target awareness campaign in order to increase the level of awareness especially among male farmers.

References

[1]	Musonda MB (2012) Socio-Economic Factors that Influence Adoption of Crop Insurance Among farmers in Lusaka Province, Zambia. B.Sc. dissertation, Department of Agricultural Economics, University of Zambia.
[2]	Kumar DS, Barah BC, Ranganathan CR, et al. (2011) An analysis of farmers' perception and awareness towards crop insurance as a tool for risk management in Tamil Nadu. Agri Econ Res Rev 24: 37–46.
[3]	Kumari M, Singh KM, Sinha DK, et al. (2017) Role of socio-economic variables in adoption of crop insurance: A Discriminant Function Approach. Available from: https://mpra.ub.uni- muenchen.de/80271/1/MPRA_paper_80271.pdf.
[4]	Rola ACC, Aragon CT (2013) Crop insurance participation decisions and their impact on net farm income loss of rice farmers in the lakeshore municipalities of Laguna, Philippines. Paper presented during Annual Meeting of the Philippine Economic Society, Intercontinental Hotel Manila, and November 15, 2013.
[5]	Mahul O, Stutley C (2010) Government Support to Agricultural Insurance: Challenges and Options for Developing Countries, World Bank publications.
[6]	Dragos SL, Mare C (2014) An econometric approach to factors affecting crop insurance in Romania. E&M Econo Manage 17: 93–104.
[7]	Estacio BF, Mordeno NB (2001) Agricultural insurance: The Philippine experience. Paper presented at the corporate planning conference Philippine crop insurance corporation. Available from: http://www.scribd.com/doc/27511384/Crop-Insurance-in-the-Philippines.
[8]	Cooper PJM, Dimes J, Rao KPC, et al. (2008) Coping better with current climatic variability in the rain-fed farming systems of Sub Saharan-Africa: An essential first step in adapting to future climate change. Agri Ecosyst Environ 126: 24–35. doi: 10.1016/j.agee.2008.01.007
[9]	Kunreuther HC, Michel-Kerjan OE (2008) A framework for reducing vulnerability to natural disasters: Ex Ante and Ex post considerations, World Bank publications.
[10]	Mechler R, Linnerooth-Bayer J, Peppiatt D (2006) Disaster insurance for the poor? A review of microinsurance for natural disaster risks in developing countries. ProVention/IIASA, Geneva. Available from: http://www.proventionconsortium.org/ themes/default/pdfs/Microinsurance_study_July06.pdf].
[11]	Fu H, Li J, Li Y, et al. (2018) Risk transfer mechanism for agricultural products supply chain based on weather index insurance. Complexity 2018: 1–17.
[12]	Raucci GL, Silveira RLF, Capitani DH (2018) Development of weather derivatives: Evidence from Brazilian Soybean market. Agricultural and applied economics association annual meeting at: Washington, D.C, 2018: 1–16.
[13]	Khan S, Rennie M, Charlebois S (2013) Weather risk management by Saskatchewan agriculture producers. Agri Finance Rev 73: 161–178. doi: 10.1108/00021461311321375
[14]	Spicka J, Hnilica J (2013) A methodical approach to design and valuation of weather derivatives in agriculture. Adv Meteorol 2013: 1–8.
[15]	Nyamekye I (2016) Area yield crop insurance and diversification in Ghana: An agricultural household programming model. Master thesis. Canada: University of Alberta.
[16]	Issaka YB, Wumbei BL, Buckner J, et al. (2016) Willingness to participate in the market for crop drought index insurance among farmers in Ghana. Afr J Agri Res 11: 1257–1265. doi: 10.5897/AJAR2015.10326
[17]	Ellis E (2017) Farmers willingness to pay for crop insurance: Evidence from Eastern Ghana. Int J Agri Manage Dev 7: 447–463.
[18]	Sherrick BJ, Barry PJ, Ellinger PN, et al. (2004) Factors influencing farmers' crop insurance decisions. Am J Agri Econ 86: 103–114. doi: 10.1111/j.0092-5853.2004.00565.x
[19]	Ghadirian M, Ahmadi B (2002) Efficient factors to tendency for Soya from Golestan province. Papers presented in the meeting of agricultural products insurance development and investment protection. Tehran, Iran, 152–158.
[20]	Makki SS, Somwaru A (2001) Evidence of adverse selection in crop insurance markets, J Risk Insur 68: 685–708.
[21]	Coble KH, Knight TO, Pope RD, et al. (1996) Modeling farm-level crop insurance demand with panel data. Am J Agri Econ 78: 439–447. doi: 10.2307/1243715
[22]	Smith V, Watts M (2009) Index based agricultural insurance in developing countries: Feasibility, scalability and sustainability. Gates Foundation, 1–40.
[23]	Danso-Abbeam G, Addai KN, Ehiakpor D (2014) Willingness to pay for farm insurance by smallholder cocoa farmers in Ghana. J Soc Sci Policy Implic 2: 163–183.
[24]	Falola A, Ayinde OE, Agboola BO (2014) Willingness to take agricultural insurance by cocoa farmers in Nigeria. Int J Food Agri Econ 1: 97–107.
[25]	Abebe TH, Bogale A (2014) Willingness to pay for rainfall based insurance by smallholder farmers in Central Rift Valley of Ethiopia: The case of Dugda and Mieso Woredas. Asia Pac J Energy Environ 1: 121–155. doi: 10.15590/apjee/2014/v1i2/53750
[26]	Enjolras G, Sentis P (2011) Crop insurance policies and purchases in France. Agri Econ 42: 475–486. doi: 10.1111/j.1574-0862.2011.00535.x
[27]	Barrieu P, Scaillet O (2010) A primer on weather derivatives. In: Filar JA, Haurie A, Eds.Uncertainty and Environmental Decision Making, International Series in Operations Research and Management Science, 138.
[28]	Smith VH, Goodwin BK (1996) Crop insurance, moral hazard, and agricultural chemical use.Am J Agri Econ 78: 428–438. doi: 10.2307/1243714
[29]	Miranda MJ, Glauber JW (1997) Systemic risk, reinsurance, and the failure of crop insurance markets. Am J Agri Econ 79: 206–215. doi: 10.2307/1243954
[30]	Just RE, Calvin L, Quiggin J (1999) Adverse selection in crop insurance: Actuarial and asymmetric information incentives. Am J Agri Econ 81: 834–849. doi: 10.2307/1244328
[31]	Lindholm A (2014) The (re)emergence of contract farming in Sub-Saharan Africa: Moving from land grab to power grab? Analysis of multilateral institutions' discourse from 1980 to present. Master's thesis in socio-economics, University of Geneva.
[32]	Strohm K, Hoeffler H (2006) Contract farming in Kenya: Theory, evidence from selected value chains and implications for development cooperation. Unpublished Working Document prepared for GTZ, Nairobi, Kenya.
[33]	Ghana Statistical Service (2014) 2010 Population and Housing Census. District Analytical Report. Tolon District. Available from: www.statsghana.gov.gh/docfiles/2010_District_Report/Northern/TOLON.pdf.
[34]	Kwadzo T-MG, Kuwornu JKM, Amadu ISB (2013) Food crop farmers' willingness to participate in market-based crop insurance scheme: Evidence from Ghana. Res Appl Econ 5: 1–21.
[35]	Okoffo ED, Denkyirah EK, Adu DT, et al. (2016) A double‑hurdle model estimation of cocoa farmers' willingness to pay for crop insurance in Ghana. Springer Plus 5: 873. doi: 10.1186/s40064-016-2561-2
[36]	Abdullah MA, Auwal AG, Darham S, et al. (2014) Farmers willingness to pay for crop insurance in North West Selangor irrigated agricultural development area (IADA), Malaysia.Int Soc Southeast Asian Agri Sci 20: 19–30.

Reader Comments

Your name:*

Email:*
© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)