📖 ABSTRACT/OVERVIEW
The persistent non-adoption of crop insurance by Nigerian smallholder farmers, even when products are subsidised and actively promoted, represents a significant puzzle for agricultural risk management policy. Classical expected utility theory predicts adoption whenever actuarially fair insurance is available to risk-averse agents, yet adoption rates remain below 5 percent in most trial programmes. This study investigates the behavioural foundations of crop insurance non-adoption in rural Nigeria using a combination of experimental methods and structural survey data collected from 600 farm households across Niger, Kwara, and Adamawa States in the North Central and North East geopolitical zones. The theoretical framework integrates prospect theory, narrow bracketing, basis risk aversion, and trust as behavioural explanations for the adoption puzzle, generating empirically distinguishable predictions about the relative contribution of each mechanism. A laboratory-in-the-field experiment elicits loss aversion parameters, probability weighting functions, and trust indices for each respondent. Structural estimation of a prospect theory agricultural household insurance demand model is conducted using maximum likelihood. Randomised information treatments varying transparency of payout rules and farmer control over claim assessment are implemented. Results indicate that loss aversion and probability distortion together explain approximately 45 percent of the adoption shortfall. Basis risk aversion accounts for an additional 28 percent, particularly for index insurance products. Trust in insurance providers is the strongest single predictor of adoption probability. The randomised information treatment significantly increased adoption rates among the lowest-trust quartile of respondents. The study contributes an original structural behavioural model of crop insurance demand for the Nigerian context. Keywords: crop insurance, behavioural economics, prospect theory, non-adoption, rural Nigeria
Need Complete Chapters of the Above Topic?
Get high-quality, Zero-AI research materials with current citations.
Request via WhatsApp 💬