Do Farmers Dislike Risk?

The estimation of the risk attitudes of poor farmers has been of continuing interest in the development literature.  Two different approaches have generally guided attempts to estimate risk attitudes.  First, many researchers have had farmers participate in risky choice experiments.  In these experiments, farmers are asked to make choices over a variety of binary lotteries.  For example, farmers might be asked to choose between (i) an equal chance of $100 and nothing or (ii) an equal chance of $60 and $30.  The choices offered to farmers are carefully constructed so researchers can identify risk attitudes based on specific assumptions regarding how farmers make risky choices.

Alternatively, researches have used detailed farm household survey data to infer farmers’ risk attitudes based on their production decisions and specific assumptions regarding how farmers make risky choices.  For example, expected utility theory predicts that more risk averse farmers will produce less of a marketable crop if the price of the crop is characterized by risk.  Therefore, the theory predicts that differences in how much farmers choose to produce can be used to compare their risk attitudes.

Regardless of which approach is used, the vast majority of studies have found that farmers in the developing world are risk averse, though the degree of risk aversion is heterogeneous and often systematically related to observable individual circumstances or characteristics.  Risk aversion is typically found to be negatively related to age, education, risk pooling, luck, household size, and liquidity.  It is typically found to be positively related to the size of the gamble, proportion of children in the household, age of the household head, and perceived vulnerability.  There is emerging evidence that this risk aversion is sensitive to how risk is framed as hypothesized by prospect and cumulative prospect theory.  This emerging evidence suggests that farmers may in fact be risk preferring when risk is framed in terms of losses rather than gains (e.g., by using fertilizer crop yield losses can be reduced by 10 percent versus by using fertilizer crop yields can be increased by 10 percent).  It also suggests that these farmers are loss averse (i.e. are more sensitive to losses than gains), ambiguity averse (i.e. avoid risk when the probability of chance outcomes is unknown), and overweight the probability of unlikely outcomes, while underweighting the probability of likely outcomes.