Forestry insurance preference among tree growers in the Ashanti Region of Ghana: a tobit and multi-nomial regression approach

PurposeThe study analyses the preference for forestry insurance amongst tree growers in the Ashanti Region of Ghana. Specifically, the authors examine the factors influencing the amount of forestry insurance and the choice for forestry insurance types.Design/methodology/approachA total of one hundred and seventy (170) tree growers were sampled for the study. The tobit model, multi-nomial regression and Kendall's tau were employed to analyse the factors affecting the amount for forestry insurance, the choice for forestry insurance types and the perils to forest quality, respectively.FindingsThe results of the study indicate that the incidence of bush fire and theft were the key perils that affect forest quality. In total, 52.94% of respondents preferred forest plantation fire insurance as named-peril insurance whereas 70.59% preferred a combination of forest plantation fire, windstorm and consequential loss insurance as multi-peril insurance. The majority (89.4%) of the respondents were willing to pay an amount between Ghc 10.00–49.00 (US$ 2–8) per stand. On the one hand, results of the tobit model reveal age, income, experience in forest management, land ownership and the previous occurrence of fire as the factors affecting the amount for forestry insurance. On the other hand, the multi-nomial results indicate the previous occurrence of fire, gender, forest size, income and risk aversion significantly influenced the choice for forestry insurance types, namely named peril and multi-peril.Originality/valueSeveral studies exist for forestry insurance in the developed countries. However, in West Africa specifically, Ghana, studies on forestry insurance appear to be non-existent. Above and beyond, this study, therefore, adds to the paucity of research on forestry insurance in Ghana and serves as a framework for agricultural insurance institutions such as the Ghana Agricultural Insurance Pool (GAIP) and World cover and other agricultural insurance institutions globally.