A global food–energy–water nexus with heterogeneity, non-stationarity and cross-sectional dependence

We estimate the Food–Energy–Water (FEW) nexus for 21 countries worldwide, with data available from year 1990–2000 in order to investigate the relationship between food production and two scarce resources: energy and water. Food production is proxied by four alternative variables: The index of agricultural production, the index of crops production, the index of livestock production and the value added from agriculture. Water and energy as independent variables are controlled by methane and nitrogen emissions, capital, labor and five versions of fertilizer proxy: pesticides, insecticides, fungicides, herbicide and other. For robust estimation, we have perused a number of standard and novel panel estimators such as the common correlated effects mean group estimator and the augmented mean group estimator (AMG). These estimators can account both for non-stationarity and the cross-dependence problems. Based on standard estimators such as the generalized least squares estimator or the Arellano-Bond generalized method of moments GMM, they reveal the existence of a significant FEW nexus while the mean group estimator, the group mean DOLS estimator, the common correlated effects and the augmented mean group estimator (AMG) do not yield significant coefficients for water and energy. In the latter models only labor and pesticides are significant at 5%. Also, the unobserved total factor productivity appears significant at 5% under the AMG estimation. When significant, energy and water elasticities ranged from − 0.001 to − 0.256 and from − 0.014 to − 0.084 respectively.