Abstract

To achieve sustainability, agricultural insurance is one of the main tools capable of reducing the vul-nerability of farmers. This is the reason it is important to investigate the different factors that affect the farmers’ agricultural insurance decision-making. The paper, using Regional panel data from Italy Regions and the GMM dynamic panel data model, examines the effect of different group variables on agricultural insurance decision making: risk perception and management, agricultural insurance recognition, trust and affordability. The aim of this paper is: (1) to analyze, through a systematic liter-ature review, which are the main problems regarding agricultural insurance diffusion, (2) to measure which category of variables influences agricultural insurance adoption, (3) to provide different policy solutions to improve the diffusion of agricultural insurance in Italy. The results show that agricultural insurance affordability, risk perception and management are the major influencing factors; a possible solution to improve the agricultural insurance demands would be to raise household net income and find an alternative solution to subsidies.

Highlights

  • The agricultural sector plays a key role in economic development and the reduction of poverty in the world (Christiaensen et al, 2011)

  • The results show that agricultural insurance affordability, risk perception and management are the major influencing factors; a possible solution to improve the agricultural insurance demands would be to raise household net income and find an alternative solution to subsidies

  • The results show that the stochastic discount factor is appropriate for calculating a farmer’s willingness to pay for a crop insurance product

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Summary

Introduction

The agricultural sector plays a key role in economic development and the reduction of poverty in the world (Christiaensen et al, 2011). The damage produced by climate change has the potential to turn into disastrous and devastating situations for human communities in the absence of risk reduction systems (Beilfuss and Nhemachena, 2017). For this reason, it has become fundamental to develop an approach oriented to reducing vulnerability and to increasing resilience to disasters (Capitanio and Adinolfi, 2009; Speranza et al, 2014; Javadinejad et al, 2020a). It has become fundamental to develop an approach oriented to reducing vulnerability and to increasing resilience to disasters (Capitanio and Adinolfi, 2009; Speranza et al, 2014; Javadinejad et al, 2020a) Based on this approach, hazard reduction pro-

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