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Risk Optimality and, Subscription and Subscription Intensity of Weather Index Insurance: Application of T-MOTAD and Negative Binomial Double Hurdle Model

Author

Listed:
  • Koufie, Augustine
  • Acquah, Henry de-Graft
  • Dadzie, Samuel Kwesi Ndzebah

Abstract

This study sought to analyze risk efficient income and examine its effect on subscription and subscription intensity of weather index insurance (WII). Data was obtained from food crop farmers who were randomly sampled from the Upper West Region; and further, the T-MOTAD and Negative binomial hurdle model were estimated to arrive at the study findings. The study fills methodological gap by estimating the negative binomial hurdle and Zero-inflated negative binomial models as advancement of the Poisson regression model. Further, AIC, BIC, Log-likelihood, rootogram as well as the Vuong test were employed to ascertain the empirical superiorities of the estimated models to the data set. Results show that the risk efficient plans’ incomes of GHS9403.42 ($854.08) and GHS9835.10 ($893.29) are higher than that of the income of GHS7412.97 ($673.29) from the farmer’s optimal plans. Also, about two-third of farmers have subscribed to the weather index insurance in the study area; for intensity of subscription, 0.39ha on average out of every hectare of land cultivated is covered with the weather index insurance. The negative binomial hurdle model showed empirical superiority for the fit of the data set. The farmer’s decision to subscribe and their subscription intensity of the weather index insurance are significantly influence by age, sex, farm size, experience, education, insurance prompt payment, extension service, credit access and risk efficient income. It is recommended that farmers should adopt the risk efficient plan to earn higher income to be able to afford WII premium, as this will increase their subscription intensity.

Suggested Citation

  • Koufie, Augustine & Acquah, Henry de-Graft & Dadzie, Samuel Kwesi Ndzebah, 2024. "Risk Optimality and, Subscription and Subscription Intensity of Weather Index Insurance: Application of T-MOTAD and Negative Binomial Double Hurdle Model," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 16(4), December.
    • Handle: RePEc:ags:aolpei:349001
    DOI: 10.22004/ag.econ.349001
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    References listed on IDEAS

    as
    1. Ellis, Emmanuella, 2017. "Farmers’ Willingness to Pay for Crop Insurance: Evidence from Eastern Ghana," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 7(4), September.
    2. Kwame Asiam Addey & John Baptist D. Jatoe & George Tsey-Mensah Kwadzo, 2020. "Adoption of crop insurance in Ghana: an application of the complementary log-log truncated Poisson double-hurdle model," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 81(1), pages 76-93, June.
    3. Feng, Shuaizhang & Han, Yujie & Qiu, Huanguang, 2021. "Does crop insurance reduce pesticide usage? Evidence from China," China Economic Review, Elsevier, vol. 69(C).
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