Agricultural Economics and Development

Agricultural Economics and Development

Effect of Climatic and Non-Climatic Variables on Agricultural Production in Iran

Articles in Press

Document Type : Original Article

Authors
ghasem layani 1
Mehdi Karami dehkordi 2
Habib Amini 3
1 Assistant Professor, Department of Management and Rural Development, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran.
2 Associate Professor, Department of Management and Rural Development, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran.
3 MA Student, Department of Management and Rural Development, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran.
10.30490/aead.2026.367527.1695
Abstract
Introduction: Climate change represents one of the pivotal challenges of the 21st century, markedly impacting global food production and security. The interplay of rising temperatures, shifting precipitation dynamics, and increased carbon dioxide levels significantly influences agricultural outputs. These climatic alterations not only diminish agricultural yields but also disrupt the food supply chain, consequently driving up prices and limiting access to essential food resources. Among the various factors impacting food production, carbon dioxide emissions stand out due to their role as a primary greenhouse gas. They contribute to global warming and fundamentally alter plant growth dynamics. While it is documented that elevated CO2 levels can enhance photosynthetic rates, the detrimental effects of increased temperatures and reduced precipitation typically overshadow these potential benefits. The nexus between atmospheric CO2 concentration and agricultural productivity underscores the complexity of climate-related challenges faced by the agricultural sector. Research background indicates that anthropogenic activities, particularly in the agricultural sector, have significantly elevated greenhouse gas concentrations in the atmosphere, directly contributing to global warming. The agricultural industry is vital for both economic and social development globally, and it plays a crucial role in addressing hunger and ensuring food security— objectives that align with the overarching goals of sustainable development as recognized internationally. However, this sector is increasingly vulnerable to the impacts of climate change, which presents an existential threat to agricultural productivity and global food security, particularly over recent decades. The Food and Agriculture Organization of the United Nations (FAO) projects that climate change may reduce agricultural output by 10 to 25 percent in certain at-risk regions by 2050, posing a severe challenge to food security worldwide. Furthermore, in 2020, approximately 33 percent of global agricultural production was adversely impacted by climate change, underscoring the critical need for adaptive strategies in agricultural practices (Florea et al., 2020). This study aimed at creating a comprehensive framework that could link climatic factors (temperature, precipitation, cultivated area) with economic variables (agricultural credit, trade liberalization) and social aspects (agricultural labor force) to analyze their impact on Iran’s agricultural production index. By addressing gaps in previous research, this model would evaluate both long- and short-term relationships, providing valuable insights and policy recommendations to combat the negative effects of climate change on food security in Iran.
Material and Methods: This study analyzed annual data from Iran for 1990-2022 to investigate key determinants affecting the food security. The analysis incorporated both climatic and non-climatic factors, including mean annual temperature (TEM), mean annual precipitation (RAIN), carbon dioxide emissions (CO2), agricultural sector credit allocation (CREDIT), energy consumption (EN), land area dedicated to agricultural crops (LAND), the agricultural labor force metrics (AGEM), trade liberalization indices (TR), and the agricultural production index (API). These variables served as critical indicators to assess the food security within the Iranian context (Soumbara & El Ghini, 2024). The Auto-Regressive with Distributed Lags (ARDL) method allows for the simultaneous examination of long-run and short-run effects between variables, addressing the limitations of the Engel-Granger method. Notably, studies by Pesaran et al. (1996) and Pesaran & Shin (1996) highlight the ARDL approach’s ability to analyze the relationships without needing to determine the direction of causality. It accommodates variables that are stationary at different levels, avoiding the need to separate them into stationary groups. This method can produce unbiased and efficient estimates, as it typically bypasses issues like serial autocorrelation and endogeneity.
Results and Discussion: The study results revealed that the climate change was affecting food production in Iran differently; in addition, increased temperatures had a significant negative impact on agriculture, with a coefficient of -0.445, aligning with findings that suggested higher temps would reduce crop yields due to increased evapotranspiration, lower soil moisture, and heat stress. Conversely, as shown by the results, precipitation had a positive impact, with a significant coefficient of 0.556, emphasizing the importance of water resources for agriculture; also, carbon dioxide emissions negatively affected agricultural production, with estimates indicating that one percent increase in emissions could decrease production by 0.011 percent; agricultural labor (with the coefficient of 1.540) remained crucial for Iran’s agricultural production index. However, declining employment in this sector underscores the need for mechanization and improved labor productivity. The study also revealed a negative impact of trade liberalization (with the coefficient of -1.081) on food production, indicating a 1.081 percent decrease in the agricultural production index with increased trade relations, assuming other conditions would remain constant. Short-term changes in crop area, credit, energy consumption, precipitation, temperature, labor force, and trade liberalization would significantly impact the food production. The coefficient of crop cultivated area (0.955) highlighted the importance of enhancing agricultural infrastructure. Additionally, the positive effect of credit (0.198) underscored the vital role of financial policies in supporting agriculture. Access to credit helps farmers expand operations and improve productivity through investments in machinery and technology. In Iran, where agriculture is crucial for the food security, targeted credit policies can strengthen production capacities and reduce reliance on imports. These findings are consistent with existing literature on the food security and agricultural development. The precipitation coefficient was 0.146, indicating a significant positive effect on agricultural yields, particularly in arid regions of Iran, where it could be considered as a key water source. Conversely, the temperature coefficient was -0.428, suggesting that higher temperatures would negatively impact the food production. The error correction term (with a coefficient of -0.605) suggested that approximately 60 percent of the short-run imbalance would adjust towards long-run equilibrium each period.
Conclusion and Suggestions: The analysis revealed that rising temperatures and increased carbon dioxide levels adversely affected agricultural production in the long term. Notably, while the temperature coefficient was not statistically significant over extended periods, this might suggest the presence of nonlinear dynamics or the moderating effects of additional variables. Conversely, precipitation demonstrated a positive and statistically significant effect on agricultural output in both the short and long terms. The findings underscore that the influence of climatic variables on agricultural production intensifies over time, likely attributable to cumulative mechanisms such as progressive soil degradation, loss of biodiversity, and heightened environmental stressors. In light of these outcomes, it is imperative to pursue adaptive strategies in agriculture that address the climate change. This includes the implementation of advanced irrigation systems, promotion of sustainable agricultural practices to mitigate alterations in precipitation patterns, investment in climate-resilient research aimed at developing heat- and drought-resistant crop varieties, and the modification of crop patterns to manage pollution emissions. Such measures are essential for alleviating the adverse impacts of climate change on the food security.
Keywords
Climate Change
Energy Consumption
CO2 Emissions
Agricultural Production
Trade Liberalization
Iran.
Subjects
1.      Ahmed, M., Shuai, J., & Ali, H. (2024). The effects of climate change on food production in India: evidence from the ARDL model. Environment, Development and Sustainability, 26(6), 14601-14619.
2.      Ahsan, F., Chandio, A. A., & Fang, W. (2020). Climate change impacts on cereal crops production in Pakistan: evidence from cointegration analysis. International Journal of Climate Change Strategies and Management, 12(2), 257-269.
3.      Asghar, N., & Salman, A. (2018). Impact of agriculture credit on food production and food security in Pakistan. Pakistan Journal of Commerce and Social Sciences (PJCSS), 12(3), 851-864.
4.      Ayyildiz, M., & Erdal, G. (2021). The relationship between carbon dioxide emission and crop and livestock production indexes: a dynamic common correlated effects approach. Environmental Science and Pollution Research, 28(1), 597-610.
5.      Bhuyan, B., Mohanty, R. K., & Patra, S. (2023). Impact of climate change on food security in India: an evidence from autoregressive distributed lag model. Environment, Development and Sustainability, 27, 6349–6369.
6.      Chandio, A. A., Gokmenoglu, K. K., Ahmad, M., & Jiang, Y. (2022a). Towards sustainable rice production in Asia: the role of climatic factors. Earth Systems and Environment, 6, 1-14.
7.      Chandio, A. A., Jiang, Y., Fatima, T., Ahmad, F., Ahmad, M., & Li, J. (2022b). Assessing the impacts of climate change on cereal production in Bangladesh: evidence from ARDL modeling approach. International Journal of Climate Change Strategies and Management, 14(2), 125-147.
8.      Demirhan, H. (2020). Impact of increasing temperature anomalies and carbon dioxide emissions on wheat production. Science of the Total Environment, 741, 139616.
9.      Deressa, T. T., & Hassan, R. M. (2009). Economic impact of climate change on crop production in Ethiopia: evidence from cross-section measures. Journal of Africa Economics, 18, 529-554.
10.   Dithmer, J., & Abdulai, A. (2017). Does trade openness contribute to food security? A dynamic panel analysis. Food policy, 69, 218-230.
11.   FAO (2024). FAO STAT, Iran, the Islamic Republic. Food and Agriculture Organization (FAO), Rome, Italy. Available at https://www.fao.org/faostat/en/#data.
12.   Florea, N. M., Badircea, R. M., Pirvu, R. C., Manta, A. G., Doran, M. D., & Jianu, E. (2020). The impact of agriculture and renewable energy on climate change in Central and East European Countries. Agricultural Economics, 66(10), 444-457. 
13.   Ghosh, B. C., Eyasmin, F., & Adeleye, B. N. (2023). Climate change and agriculture nexus in Bangladesh: evidence from ARDL and ECM techniques. PLOS Climate, 2(7), e0000244.
14.   Global Data Lab. (2024). Global Data Lab. https://globaldatalab.org/
15.   Haji-Rahimi, M., Asaadi, M. A., & Sharaifi, F. (2024). The impact of climate change on cereal production and food security in Iran. Climate Change Research, 5(20), 65-78. [In Persian]
16.   Hosseini, S., Pakravan, M., & Etghaei, M. (2013). Effects of agriculture sector total support estimate on food security in Iran. Iranian Journal of Agricultural Economics and Development Research, 44(4), 533-544. [In Persian]
17.   Huq, N., Huge, J., Boon, E. E., & Gain, A. K. (2015). Climate change impacts in agricultural communities in rural areas of coastal Bangladesh: a tale of many stories. Sustainability, 7(7), 1-24.
18.   Javadi, A., Ghahremanzadeh, M., Sassi, M., Javanbakht, O., & Hayati, B. (2023). Economic evaluation of the climate changes on food security in Iran: application of CGE model. Theoretical and Applied Climatology, 151(1), 567-585.
19.   Li, Y., Li, X., Tan, M., Wang, X., & Xin, L. (2018). The impact of cultivated land spatial shift on food crop production in China, 1990-2010. Land Degradation and Development, 29(6), 1652-1659.
20.   Mahdavian, S. M., Askari, F., Kioumarsi, H., Naseri Harsini, R., Dehghanzadeh, H., & Saboori, B. (2024). Modeling the linkage between climate change, CH4 emissions, and land use with Iran’s livestock production: a food security perspective. Proceedings of Natural Resources Forum. Oxford, UK, Blackwell Publishing Ltd.
21.   Malawi, A. I., & AlMansi, M. (2014). Economic Globalization and Labor Productivity: An Application of Autoregressive Distributed Lag (ARDL) Bounds Testing Approach. International Journal of Business and Statistical Analysis, 1(01), 254-278.
22.   Mendelsohn, R., Dinar, A., & Williams, L. (2006). The distributional impact of climate change on rich and poor countries. Environment, Development, Economics, 11, 159-178.
23.   Nonhebel, S. (2005). Renewable energy and food supply: Will there be enough land?. Renewable and Sustainable Energy Reviews, 9(2), 191-201.
24.   Our World in Data (2023). Agriculture share in GDP, Iran, the Islamic Republic. Available at https://ourworldindata.org/grapher/agriculture-share-gdp?tab=chart&country=~IRN.
25.   Pesaran, M. H., & Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs, 31, 371-413.
26.   Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
27.   Pickson, R. B., He, G., Ntiamoah, E. B., & Li, C. (2020). Cereal production in the presence of climate change in China. Environmental Science and Pollution Research, 27(36), 45802-45813.
28.   Praveen, B., & Sharma, P. (2019). A review of literature on climate change and its impacts on agriculture productivity, Journal of Public Affairs, 19(4), e1960.
29.   Shahbaz, M., Shahbaz Shabbir, M., & Sabihuddin Butt, M. (2013). Effect of financial development on agricultural growth in Pakistan: new extensions from bounds test to level relationships and Granger causality tests. International Journal of Social Economics, 40(8), 707-728.
30.   Soumbara, S. A., & El Ghini, A. (2024). Asymmetric effects of climate variability on food security in Morocco: evidence from the nonlinear ARDL model. Journal of Agribusiness in Developing and Emerging Economies, 14(5), 1109-1126.
31.   Tagwi, A. (2022). The impacts of climate change, carbon dioxide emissions (CO2) and renewable energy consumption on agricultural economic growth in South Africa: ARDL approach. Sustainability, 14(24), 16468.
32.   Van Huong, N., Nguyet, B. T. M., Van Hung, H., Duc, H. M., Van Chuong, N., Tri, D. M., & Van Hien, P. (2022). Economic impact of climate change on agriculture: a case of Vietnam. AgBioForum, 24(1), 1-12.
33.   Warsame, A. A., Sheik-Ali, I. A., Ali, A. O., & Sarkodie, S. A. (2021). Climate change and crop production nexus in Somalia: an empirical evidence from ARDL technique. Environmental Science and Pollution Research,  28(16), 19838-19850.
34.   World Bank (2023). Agriculture share in employment. Available at https://data.worldbank.org/indicator/SL.AGR.EMPL.ZS.
35.   World Bank. (2024). World Development Indicators. https://datatopics.worldbank.org/world-development-indicators/
36.   Xu, N., Zhang, L., & Leng, X. (2022). Sustainable food production from a labor supply perspective: policies and implications. Sustainability, 14(23), 15935.
37.   Zakaria, M., Jun, W. T., & Khan, M. F. (2019). Impact of financial development on agricultural productivity in South Asia. Agricultural Economics, 65(5), 232-239.
Agricultural Economics and Development

Articles in Press, Accepted Manuscript
Available Online from 28 April 2026