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The common bean is an important staple food in Colombia with diverse nutritional content and environmental benefits. The most important climatic risk confronted by common bean production in Colombia is El Niño Southern Oscillation (ENSO) since its two extreme phases —El Niño and La Niña— increase the intensity and variety of abiotic and biotic stresses in the region. Using information from the Food and Agricultural Organization (FAO) for the period 1991–2018, we test whether pre-2030 ENSO has had a negative impact on common bean production in Colombia using a Prais–Winsten regression model. We find that common beans’ yields have been negatively affected by El Niño, but not by La Niña. Moreover, short-run ENSO-induced deviations in the growth rate of precipitation with respect to its long-run value reduce yields and increase farmers’ income from common bean production. These results have two important implications. From a modelling standpoint, we find that precipitation has a non-linear relationship with yields and incomes, implying that second-order effects should be incorporated in any analysis of the effects of climatic variables on agricultural production. From a policy perspective, our results suggest a need for countercyclical polices to counteract price spikes of common beans in the Colombian market since, when they occur, they tend to over-compensate the reduction in yields, which reduce common bean consumers’ purchasing power and food security.

Variety selection and diversification are climate change adaptation practices pursued by Colombian common bean producers. We investigate the drivers behind common bean variety selection and diversification in one of the most important common bean production regions in Colombia —Santander. The effects of climate change on this region are expected to be elevation driven. Exploiting the relationship between elevation-driven weather variations and climate change perception in Santander, we estimate an alternative-specific conditional logistic regression model to identify the determinants of common bean variety selection from a survey of producers. Using an ordered-logistic regression model, we also investigate the drivers behind common bean variety diversification within this farming community. We find that farms' elevation, household composition, and seed certification are some of the most important drivers behind farmers' common bean variety selection in Santander. We also find that varieties that sell at higher prices and have shorter vegetative cycles tend to be more preferred by farmers. Finally, farmers who receive more help from family members and own a tractor tend to grow more than one variety in the same production cycle. Common bean breeding programmes can exploit these drivers to design communication strategies to maximize uptake of newly developed common bean phenotypes.

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