Skip to main content
SpringerLink
Log in

The potential role of a carbon tax on CO2 emission reduction in the agriculture sector of Iran

  • Original Paper
  • Published:
International Journal of Environmental Science and Technology Aims and scope Submit manuscript

Abstract

A carbon tax is one of the fundamental cost-effective market tools to limit global temperature and reduce greenhouse gases emissions. In this study, using the provisions of the Paris Agreement and the shadow price of carbon, the potential role of the carbon tax on carbon emission reduction in the agricultural sector of Iran is investigated. To this end, the GMM (generalized method of moments) approach and data for 28 provinces of Iran during 2001–2017 is implemented. The own price and income elasticity of diesel are calculated at −0.26 and 0.32, respectively. Results indicated that each 300 Rial ($0.0.0071) increase in diesel price led to a 44 kg/capita decrease in carbon emission. Each 10% decrease in electricity price led to a 1.5% decrease in diesel consumption and a 0.21% decrease in per capita carbon emission. To comply with Paris Agreement, the recommended carbon tax will be 0.360 Dollar/liter. According to carbon shadow price in the agriculture sector of Iran, to cover external costs from agriculture products, the carbon tax should be determined at 1.459 Dollar/liter. In the short term, such a high tax rate may affect the welfare of producers. Hence, moderating fuel prices, transferring fossil fuel subsidies to providing clean energy sources, electrification of agricultural wells, use of solar panels in the agricultural sector, modernization of agricultural machinery, and equipment that use less fuel are recommended.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability and materials

The data set analyzed during this study are available in: “https://pep.moe.gov.ir/” and “https://www.amar.org.ir/”.

References

  • Abler D (2015) Economic evaluation of agricultural pollution control options for China. J Integr Agric 14(6):1045–1056

    Article  Google Scholar 

  • Agheli L (2015) Estimating the demand for diesel in agriculture sector of Iran. Int J Energy Econ Policy 5(3):660–667

    Google Scholar 

  • Alam MM, Murad MW, Noman AHM, Ozturk I (2016) Relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental Kuznets Curve hypothesis for Brazil, China, India and Indonesia. Ecol Indic 70:466–479

    Article  Google Scholar 

  • Apergis N, Payne J (2009) CO2 emissions, energy usage and output in Central America. Energy Policy 37:3282–3286

    Article  Google Scholar 

  • Anderson TW, Hsiao C (1981) Estimation of dynamic models with error components. J Am Stat Assoc 76:589–606

    Article  Google Scholar 

  • Arellano M, Bond S (1991) Some test of specification for panel data: Monte Carlo evidence and application to employment equations. Rev Econ Stud 58:277–297

    Article  Google Scholar 

  • Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error component models. J Econ 68:29–51

    Article  Google Scholar 

  • Atasoy BS (2017) Testing the environmental Kuznets curve hypothesis across the U.S.: evidence from panel mean group estimators. Renew Sustain Energy Rev 77:731–747

    Article  Google Scholar 

  • Baltagi B (2005) Econometric analysis of panel data, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  • Baltagi B (2008) Econometrics analyses of panel data, vol 1. John Wiley, New York

    Google Scholar 

  • Ben Jebli M, Ben Youssef S, Ozturk I (2016) Testing environmental Kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in OECD countries. Ecol Ind 60:824–831

    Article  Google Scholar 

  • Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econ 87:115–143

    Article  Google Scholar 

  • Breitung J (2000) The local power of some unit root tests for panel data. Adv Econ 15:161–177

    Google Scholar 

  • Carroll DA, Stevens KA (2021) The short-term impact on emissions and federal tax revenue of a carbon tax in the U.S. electricity sector. Energy Policy 158:112526. https://doi.org/10.1016/j.enpol.2021.112526

    Article  Google Scholar 

  • Coondoo D, Dinda S (2002) Causality between income and emission: a country-group specific econometric analysis. Ecol Econ 40(3):351–367

    Article  Google Scholar 

  • Chen PY, Chen BY, Tsai PH, Chen Ch (2015) Evaluating the impacts of a carbon tax on imported forest products: evidence from Taiwan. Forest Policy Econ 50:45–52

    Article  Google Scholar 

  • Churchill SA, Inekwe J, Ivanovski K, Smyth R (2018) The Environmental Kuznets Curve in the OECD: 1870–2014. Energy Econ 75:389–399

    Article  Google Scholar 

  • Coalition of Finance Ministers for Climate Action [WWW Document], (2021). https://www.financeministersforclimate.org. Accessed 24 Mar 2021

  • Cong RG, Wei YM (2010) Potential impact of CET carbon emission trading on chines power sector: a perspective difference from allowance allocation options. Energy 35(9):3921–3131

    Article  Google Scholar 

  • Davis LW, Kilian L (2009) Estimating the Effect of a gasoline tax on carbon emission. NBER Working Paper No. 14685

  • De Cillia B, McCurdy P (2020) No Surrender. No Challenge. No Protest Paradigm: a content analysis of the canadian news media coverage of the “Yellow Vest Movement” and the “United We Roll Convoy.” Can Rev Sociol 57(4):656–680

    Article  Google Scholar 

  • Dogan N (2016) Agriculture and environmental Kuznets curves in the case of Turkey: evidence from the ARDL and bounds test. Agric Econ-Czech 62:566–574

    Article  Google Scholar 

  • Energy balance sheet of Iran (2018) is available in: http://pep.moe.gov.ir/

  • Erol U, Yu ESH (1987) Time series analysis of the causal relationships between US energy and employment. Resour Energy 9:75–89

    Article  Google Scholar 

  • Fang D, Zhang X, Yu Q, Jin TCh, Tian L (2018) A novel method for carbon dioxide emission forecasting based on improved Gaussian processes regression. J Clean Prod 173:143–150

    Article  CAS  Google Scholar 

  • Farajian L, Moghaddasi R, Hosseini S (2018) Agriculture energy demand in Iran: approaching for more sustainable situation. Energy Rep 4:260–265

    Article  Google Scholar 

  • Fiorito G (2018) Studies in environmental, production and transport economics. Institute Environmental Science and Technology, Universitat Autonoma Barcelona. Ph.D. thesis

  • Frees EW (1995) Assessing cross-sectional correlations in panel data. J Econ 69:393–414

    Article  Google Scholar 

  • Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J Am Stat Assoc 32:675–701

    Article  Google Scholar 

  • Galeotti M, Manera M, Lanza A (2009) On the robustness of robustness checks of the environmental Kuznets curve hypothesis. Environ Resource Econ 42(4):551–574

    Article  Google Scholar 

  • Gokhale H (2021) Japan’s carbon tax policy: limitations and policy suggestions. Curr Res Environ Sustain 3:100082. https://doi.org/10.1016/j.crsust.2021.100082

    Article  Google Scholar 

  • Gokmenoglu KK, Taspinar N (2018) Testing the agriculture-induced EKC hypothesis: the case of Pakistan. Environ Sci Pollut Resour Int 25:22829–22841

    Article  Google Scholar 

  • Grossman GM, Kruger AB (1996) The inverted-U: what does it mean? Environ Dev Econ 1:119–122

    Article  Google Scholar 

  • Hadri K (2000) Testing for stationary in heterogeneous panel data. Econ J 3:148–161

    Google Scholar 

  • Hao Y, Chen H, Zhang Q (2016) Will income inequality affect environmental quality? Analysis based on China’s provincial panel data. Ecol Ind 67:533–542

    Article  Google Scholar 

  • Hailemariam A, Dzhumashev R, Shahbaz M (2019) Carbon emissions, income inequality, and economic development. Empir Econ. https://doi.org/10.1007/s00181-019-01664-x

    Article  Google Scholar 

  • Harrison K, Peet C (2012) Historical legacies and policy reform: diverse regional reactions to British Columbia’s carbon tax BC Studies. Br Columbian Qrly 173(97):122

    Google Scholar 

  • He J, Richard P (2010) Environmental Kuznets curve for CO2 in Canada. Ecol Econ 69:1083–1093

    Article  Google Scholar 

  • Hu H, Dong W, Zhou Q (2021) A comparative study on the environmental and economic effects of a resource tax and carbon tax in China: analysis based on the computable general equilibrium model. Energy Policy 156:112460. https://doi.org/10.1016/j.enpol.2021.112460

    Article  CAS  Google Scholar 

  • Huang Zh, Duan H (2020) Estimating the threshold interactions between income inequality and carbon emissions. J Environ Manag 263:110393

    Article  Google Scholar 

  • Im KS, Pesaran M, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115(1):53–74

    Article  Google Scholar 

  • IPCC Climate Change (2014) Synthesis Report Summary for Policymakers

  • Jagers SC, Martinsson J, Matti S (2019) The impact of compensatory measures on public support for carbon taxation: an experimental study in Sweden. Clim Policy 19(2):147–160

    Article  Google Scholar 

  • Jalil A, Mahmud S (2009) Environment Kuznets curve for CO2 emissions: a cointegration analysis for China. Energy Policy 37:5167–5172

    Article  Google Scholar 

  • Kahn JR, Franceschi D (2006) Beyond Kyoto: a tax-based system for global reduction of greenhouse gas emissions. Ecol Econ 58(4):778–787

    Article  Google Scholar 

  • Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90:1–44

    Article  Google Scholar 

  • Kasman A, Duman Y (2015) CO2 emission, economic growth, energy consumption, trade and urbanization in new member and candidate countries: a panel data analysis. Econ Model 44:97–103

    Article  Google Scholar 

  • Kacprzyk A, Kuchta Z (2020) Shining a new light on the environmental Kuznets curve for CO2 emissions. Energy Econ. https://doi.org/10.1016/j.eneco.2020.104704

    Article  Google Scholar 

  • Lee CC, Lee JD (2009) Income and CO2 emissions: evidence from panel unit root and cointegration tests. Energy Policy 37:413–423

    Article  Google Scholar 

  • Levin ACF, Lin CS, Chu J (2002) Unit root tests in panel data: Asymptotic and finite-sample properties. J Econ 108:1–24

    Article  Google Scholar 

  • Lopez LA, Cadarso MA, Gomez N, Tobarra MA (2015) Food miles, carbon footprint and global value chains for Spanish agriculture: assessing the impact of a carbon border tax. J Clean Prod 103:423–436

    Article  Google Scholar 

  • Marron D, Toder E, Austin L (2015) Taxing carbon: what, why, and how. Tax Policy Center- Urban institute & Brooking institution: 1–27

  • Martins PMG (2010) Aid absorption and spending in Africa: a panel cointegration approach, CREDIT Research Paper, No. 10/06

  • Maestre-Andrés S, Drews S, van den Bergh J (2019) Perceived fairness and public acceptability of carbon pricing: a review of the literature. Clim Policy 19(9):1186–1204

    Article  Google Scholar 

  • Mousavi MH, Ghavidel S (2019) Structural time series model for energy demand in Iran’s transportation sector. Case Stud Transp Policy 7(2):423–432

    Article  Google Scholar 

  • Najafi Alamdarlo H (2019) The economic impact of agricultural pollutions in Iran, spatial distance function approach. Sci Total Environ 616–617:1656–1663

    Google Scholar 

  • Nong D (2020) Development of the electricity-environmental policy CGE model (GTAP-E-Power S): a case of the carbon tax in South Africa. Energy Policy 140:111375

    Article  Google Scholar 

  • Nong D, Simshauser P, Nguyen DB (2021) Greenhouse gas emissions vs CO2 emissions: comparative analysis of a global carbon tax. Appl Energy 298:117223. https://doi.org/10.1016/j.apenergy.2021.117223

    Article  Google Scholar 

  • Ozcan B (2013) The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: a panel data analysis. Energy Policy 62:1138–1147

    Article  Google Scholar 

  • Patt A, Lilliestam J (2018) The case against carbon prices. Joule 2(12):2494–2498

    Article  Google Scholar 

  • Pedroni P (2004) Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. J Econ Theory 20:597–625

    Google Scholar 

  • Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. University of Cambridge, Faculty of Economics. Cambridge Working Papers in Economics No. 0435

  • Philips PCB, Perron P (1988) Testing for a unit root in time series regression. Biometrica 75(2):335–346

    Article  Google Scholar 

  • Pigou AC (2013) The economics of welfare. Palgrave Macmillan, London

    Google Scholar 

  • Povitkina M, Jagers SC, Matti S, Martinsson J (2021) Why are carbon taxes unfair? Disentangling public perceptions of fairness. Glob Environ Chang 70:102356. https://doi.org/10.1016/j.gloenvcha.2021.102356

    Article  Google Scholar 

  • Ridzuan S (2019) Inequality and the environmental Kuznets curve. J Clean Prod. https://doi.org/10.1016/j.jclepro.2019.04.284

    Article  Google Scholar 

  • Schaffitzel F, Jakob M, Soria R, Vogt-Schilb A, Ward H (2020) Can government transfers make energy subsidy reform socially acceptable? A case study on Ecuador. Energy Policy 137:111120. https://doi.org/10.1016/j.enpol.2019.111120

    Article  Google Scholar 

  • Shabani E, Hayati B, Pishbahar E, Ghorbani MA, Ghahremanzadeh M (2021) The relationship between CO2 emission, economic growth, energy consumption, and urbanization in the ECO member countries. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-021-03319-w

    Article  Google Scholar 

  • Soytas U, Sari R (2009) Energy consumption, economic growth, and carbon emissions: challenges faced by an EU candidate member. Ecol Econ 68(6):1667–1675

    Article  Google Scholar 

  • Stern N (2007) The economics of climate change: the Stern review. Cambridge University Press, UK

    Book  Google Scholar 

  • Stevens KA, Carroll DA (2020) comparison of different carbon taxes on utilization of natural gas. Energy Clim Change. https://doi.org/10.1016/j.egycc.2020.100005

    Article  Google Scholar 

  • Tan R, Lin B (2020) The influence of carbon tax on the ecological efficiency of China’s energy intensive industries—a inter-fuel and inter-factor substitution perspective. J Environ Manage 261:110252

    Article  Google Scholar 

  • Turkekul B, Unaktin G (2011) A cointegration analysis of the price and income elasticities of energy demand in Turkish agriculture. Energy Policy 39:2416–2433

    Article  Google Scholar 

  • Uddin MdM, Mishra V, Smyth R (2020) Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling. Energy Econ. https://doi.org/10.1016/j.eneco.2020.104780

    Article  Google Scholar 

  • Uzar U, Eyuboglu K (2019) The nexus between income inequality and CO2 emission in Turkey. J Clean Prod 227:149–157

    Article  Google Scholar 

  • Wang ZhX, Li Q (2019) Modeling the nonlinear relationship between CO2 emissions and economic growth using a PSO algorithm-based grey Verhulst model. J Clean Prod 207:214–224

    Article  Google Scholar 

  • Westerlund J (2007) Testing for error correction in panel data. Oxford Bull Econ Stat 69:0305–9049

    Article  Google Scholar 

  • Yang M, Fan Y, Yang F, Hu H (2014) Regional disparities in carbon dioxide reduction from China’s uniform carbon tax: a perspective on inter-factor/inter-fuel substitution. Energy 74:131–139

    Article  Google Scholar 

  • Zafeirious E, Sofios S, Partalidou X (2017) Environmental Kuznets curve for EU agriculture: empirical evidence from new entrant EU countries. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-017-9090-6

    Article  Google Scholar 

  • Zhang K, Wang Q, Liang Q, Chen H (2016) A bibliometric analysis of research on carbon tax from 1989 to 2014. Renew Sustain Energy Rev 58:297–310

    Article  Google Scholar 

  • Zhang H, Li P, Zheng H, Zhang Y (2020) Impact of carbon tax on enterprise operation and production strategy for low-carbon products in a co-opetition supply chain. J Clean Prod. https://doi.org/10.1016/j.jclepro.2020.125058

    Article  Google Scholar 

  • Zhang L, Pang J, Cheng X, Lu Zh (2019) Carbon emissions, energy consumption and economic growth: evidence from the agricultural sector of China’s main grain-producing areas. Sci Total Environ 665:1017–1025

    Article  CAS  Google Scholar 

Download references

Funding

No funds, grants, or other support was received.

Author information

Authors and Affiliations

  1. Department of Agriculture Economics, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

    E. Shabani, B. Hayati, E. Pishbahar & M. Ghahremanzadeh

  2. Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

    M. A. Ghorbani

Authors
  1. E. Shabani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Hayati
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Pishbahar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. A. Ghorbani
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Ghahremanzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.SH: Conceptualization, Methodology, Software, Writing - original draft. B.H.: Project administration, Supervision, Data curation. E.P.: Methodology,Validation. M.A.GH.: Investigation, review and editing. M.GH.: Conceptualization, Software, Formal analysis, Writing - review & editing.

Corresponding author

Correspondence to E. Shabani.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Editorial responsibility: Dai-Viet N. Vo.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shabani, E., Hayati, B., Pishbahar, E. et al. The potential role of a carbon tax on CO2 emission reduction in the agriculture sector of Iran. Int. J. Environ. Sci. Technol. 21, 6965–6980 (2024). https://doi.org/10.1007/s13762-024-05485-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13762-024-05485-z

Keywords

Search

Navigation