Agriculture is highly impacted by different sources of risk. There is a wide variety of management instruments that farmers can use to cover these risks. The objective of this paper is to analyze the explanatory variables for the simultaneous adoption of a large set of risk management instruments. The main innovation is the methodological approach: first, we apply a hierarchical cluster analysis to identify the groups of instruments whose adoption is correlated; second, we use multivariate probit models to analyze the influence of different factors on the simultaneous adoption of the instruments included in each cluster. Explanatory variables capture farmers’ socio-demographic features, perception of risks, risk aversion and subjective perception of past risk experience; farms’ technical-economic characteristics; and perception of local-level climate change. The results show that there are significant differences in the variables influencing the adoption of the risk management instruments. ...
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