Measuring Farm Sustainability Using Data Envelope Analysis with Principal Components: The Case of the Wisconsin Cranberry

Measuring farm sustainability performance is a crucial component for improving agricultural sustainability. While extensive assessments and indicators exist that reflect the different facets of agricultural sustainability, because of the relatively large number of measures and interactions among them, a composite indicator that integrates and aggregates over several variables is particularly useful. This paper describes and empirically evaluates a method for constructing a composite sustainability indicator that individually scores and ranks farm sustainability performance. The method first uses non-negative polychoric principal component analysis to reduce the number of variables, to remove correlation among variables and to transform categorical variables to continuous variables, and then applies common-weight data envelope analysis to these principal components to individually score each farm. An empirical application to Wisconsin cranberry farms finds heterogeneity in terms of sustainability practice adoption, implying that some farms could adopt better practices to improve the overall sustainability performance of the industry.