Affiliation:
1. School of Business Anhui University of Technology Ma'anshan China
2. School of English Studies Beijing International Studies University Beijing China
3. Chinese Society for Sustainable Development Beijing China
4. School of Business Jinggangshan University Ji’an China
5. College of Applied Business Administration, King Saud University Riyadh Saudi Arabia
6. Department of Quantitative Methods Rzeszow University of Technology Rzeszów Poland
Abstract
AbstractThere is a notable scarcity of literature addressing the complex affiliation amidst natural resources, water productivity (WPROD), and the food production index (FPI). Existing research focuses on emerging and developing countries, primarily centering on the initial objectives of sustainable development. To bridge this literature gap, our research delves into the nexus of WPROD, FPI, and total land resources (TLRS). Additionally, the study explores the persuasive roles of income (GDP) and renewable energy consumption (REC). Employing time series methodologies, we utilize the DF‐GLS unit root assessment to assess the variable static method and the Bayer‐Hanck test to scrutinize long‐term equilibrium. The primary analysis employs the least squares approach with breakpoints, supplemented by the Robust least squares method for validation. For causal relationships between variables, we deployed the Granger causality approach. Our outcomes disclose that variables are static at the first difference, indicating long‐run equilibrium among all variables. Empirical outcomes suggest a resource curse associated with TLRS, as it negatively influences both WPROD and FPI, regardless of breaks. The increase in coefficients of land resources by 1% causes decrease in water productivity and food production by −0.35% and −0.185%. In contrast, GDP and renewable energy positively impact water productivity and food production index, even in the presence of structural breaks. Robustness checks yield‐mixed outcomes, though the overall results remain significant and consistent with the main methods. Causality analysis indicates a bi‐directional linkage between natural resources, renewable energy, and water productivity, and food production, while GDP demonstrates a uni‐directional linkage in the study. We provide relevant policies under the targets of COP 27 to manage land resources in the USA.