Sustainability Standards, Gender, and Nutrition among Smallholder Farmers in Uganda

Abstract

Sustainability standards are gaining in importance in global markets for high-value foods. While previous research has shown that participating farmers in developing countries may benefit through income gains, nutrition impacts have hardly been analysed. We use survey data from smallholder coffee farmers in Uganda – certified under Fairtrade, Organic, and UTZ – to analyse impacts on food security and dietary quality. Estimates of instrumental variable models and simultaneous equation systems show that certification increases calorie and micronutrient consumption, mainly through higher incomes and improved gender equity. In certified households, women have greater control of coffee production and monetary revenues from sales.

Acknowledgements

This research was financially supported by the German Research Foundation (DFG). We thank two anonymous reviewers and the editors of this journal for useful comments. The data used in this research and related details can be made available upon request.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The data from Uganda are the same as those used by Chiputwa et al. (2015), but the focus and methodological approaches are different. Chiputwa et al. (2015) analysed effects of certification on income and poverty with a propensity score matching approach. They did not look at nutrition and gender, nor did they examine impact pathways with structural models, as we do here.

2. General principles of these three sustainability standards are described in the Online Appendix.

3. In their study on the income and poverty effects, Chiputwa et al. (2015) included a few additional asset and market access variables in a logit model to estimate propensity scores for certification. Here, we concentrate on a smaller set of key variables for two reasons. First, the simultaneous equation system is more sensitive to changes in the specification and less robust when more variables are added. Second, possible issues of endogeneity are more relevant here than they are in logit models used for the calculation of propensity scores.

4. As these assets may be influenced by certification, which could lead to issues of reverse causality, we use values lagged by five years, thus referring to 2007 (the other values refer to 2012 when the survey was conducted). Most households in the sample were not certified before 2007.