Document Type : Original Article
Authors
1
FERDOWSI UNIVERSITY OF MASHHAD
2
PhD candidate, Department of Agricultural Economics, Ferdowsi University of Mashhad
3
Professor, Department of Agricultural Economics, Ferdowsi University of Mashhad
4
Department of Agricultural Economics/ Faculty of Agriculture/ Ferdowsi University of Mashhad
10.48308/envs.2024.1393
Abstract
Introduction: Meeting the food demands of a rapidly growing global population is a substantial challenge for the agricultural industry, which requires a significant increase in food production. However, such expansion often triggers adverse environmental consequences, including ecosystem degradation, biodiversity loss, soil erosion, water contamination, and increased greenhouse gas emissions. Furthermore, environmental degradation poses a threat to agricultural stability, affecting incomes and food security, a particularly concerning issue in leading agricultural nations. This underscores the critical need to link agricultural development with environmental conservation for sustainable growth.
Material and Methods: This study investigates the potential role of income in the relationship between agricultural production and the ecological footprint—an indicator of environmental degradation—using panel data from the ten countries with the highest agricultural value added from 1996 to 2021. The research begins by assessing cross-section dependence through the Breusch-Godfrey test and examines the time series data for stationarity using the Levin, Lin, and Chu, and the Im, Pesaran, and Shin unit root tests. Subsequent panel cointegration tests by Pedroni and Kao determine the presence of a long-term equilibrium relationship among the variables. The study employs Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) cointegration techniques to explore the effects of agricultural production. The analysis also considers other variables such as adjusted net national income, renewable energy consumption, population size, the regulatory quality index, and the interactive impact of adjusted net national income on the agricultural production's ecological footprint.
Results and Discussion: Pesaran's test confirms the independence of the cross-sections. Although all variables become highly significant when differenced, they do not all exhibit stationarity in their levels. The empirical findings indicate the presence of cointegration between the dependent variable (ecological footprint) and the independent variables (adjusted net national income, renewable energy consumption, population size, regulatory quality index, and the interaction between adjusted net national income and agricultural production). The FMOLS and DOLS models reveal a positive relationship between the ecological footprint and both adjusted net national income and agricultural production. However, the interaction between these variables shows a negative and significant impact on environmental degradation, suggesting that income plays a mediating role in the relationship between agricultural production and ecological footprint. This indicates that higher income levels have the potential to mitigate the negative effects of agricultural production on environmental degradation. The findings also confirm the expected positive influence of population size and the negative impact of renewable energy consumption on environmental degradation. Furthermore, the regulatory quality index is found to inversely affect the ecological footprint.
Conclusion: Governments and policymakers should prioritize the elimination of poverty, raising income levels, and promoting financial solutions to encourage sustainable and environmentally responsible agricultural practices. Tax incentive policies, such as reductions in income tax for organic products, can enhance sustainable production methods. The enforcement of the rule of law and maintenance of public order are critical for the successful implementation of agricultural policies. Within this framework, policymakers can leverage electronic government systems to optimize management processes, reduce costs, increase competitiveness, and foster environmental responsibility in the agricultural sector.
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