Introduction: Over recent decades, growing concerns over climate change and the environmental consequences of economic growth have made the reassessment of sectoral policies a key priority for governments. The agricultural sector, due to its central role in food security, employment, and rural development, has traditionally been at the core of public support policies. At the same time, agriculture is a significant source of greenhouse gas emissions, particularly carbon dioxide, as a result of intensive energy use, reliance on chemical inputs, and extensive exploitation of natural resources. In Iran, agricultural support policies implemented across successive development plans have largely focused on increasing production and achieving self-sufficiency, while environmental considerations have received relatively limited and unsystematic attention. Against this background, empirically examining the relationship between government support for agriculture and carbon dioxide emissions can provide valuable insights into the extent to which existing support policies are aligned with the objectives of sustainable development. This study aimed at investigating the dynamics of the relationship between total support to the agricultural sector and the carbon dioxide emissions in Iran.
Materials and Methods: In order to analyze the dynamic relationship between the agricultural support policies and the environmental performance, this study adopted a set of dynamic econometric methods. The empirical analysis was basedon a time-series dataset covering the period from the First to the Fifth Economic, Social and Cultural Development Plans of Iran. Government support to the agricultural sector was measured using the Total Support Estimate (TSE), which provided a comprehensive indicator of policy-induced transfers to agriculture, while environmental pressure was proxied by carbon dioxide emissions. The econometric analysis was implemented in two main stages. In the first stage, the Toda- Yamamoto augmented Granger causality approach was employed to investigate the direction of causality between the agricultural support and the carbon dioxide emissions. In the second stage, a Vector Autoregression (VAR) framework was estimated to capture the dynamic interactions between the variables and to assess their responses to exogenous shocks over time. The appropriate lag length of the VAR model was determined using standard information criteria, including the Akaike and Schwarz criteria. To ensure the validity and robustness of the results, several diagnostic tests, such as tests for serial correlation, heteroskedasticity, and model stability, were conducted.
Results and Discussion: The results of the Toda-Yamamoto Granger causality test indicated the existence of bidirectional causality between total agricultural support and carbon dioxide emissions in Iran. This finding suggests that changes in the level and composition of government support to agriculture can significantly influence the trajectory of carbon dioxide emissions. More specifically, increases in production-oriented support—particularly those that encourage greater use of energy-intensive and chemical inputs— tend to exacerbate the environmental pressures and contribute to higher emissions. Conversely, the results also showed that variations in carbon dioxide emissions were, to some extent, associated with changes in agricultural support policies; however, the magnitude and statistical strength of this effect were considerably weaker than the reverse relationship. The estimation of the VAR model and the analysis of impulse response functions provided further evidence of this asymmetry. A positive shock to total agricultural support generated a statistically significant and relatively persistent response in the carbon dioxide emissions, with the effects extending over several periods. This pattern indicated that support policies influenced the environmental outcomes through their impact on production structures, input use, and energy intensity in agriculture. In contrast, shocks associated with rising the carbon dioxide emissions exerted only a limited and short-lived influence on the level of agricultural support and did not lead to substantial or lasting adjustments in policy orientation. Taken together, these results clearly demonstrate that environmental considerations have not yet been fully internalized into the agricultural policy-making process in Iran. Policy responses to signals of environmental degradation appear weak and largely non-systematic. In other words, although the environmental consequences of agricultural activities are observable, they rarely translate into meaningful revisions of support objectives or instruments. This pattern reflects the dominance of short-term production, economic, and food security objectives over long-term environmental sustainability goals, a bias that may ultimately result in higher social and economic costs associated with environmental degradation.
Conclusion and Suggestions: Overall, the study findings suggest that while agricultural support policies in Iran have a significant impact on carbon dioxide emissions, they have not been designed within a coherent framework consistent with the principles of sustainable development. The presence of bidirectional causality between support measures and emissions highlights the potential of agricultural support policies as an effective leverage for steering the sector toward a low-carbon development pathway— a potential that has so far remained largely underutilized. Accordingly, there is a clear need to systematically integrate environmental considerations into the design and implementation of agricultural support policies. Establishing comprehensive systems for monitoring and evaluating the environmental impacts of support measures, reforming the composition of support in favor of low-carbon technologies and environmentally friendly production practices, and expanding education and extension programs on sustainable agriculture alongside financial support can all contribute to reducing the environmental pressures.