IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03738928.html
   My bibliography  Save this paper

Impacts of fertilizer subsidy reform options in Iran: an assessment using a Regional Crop Programming model
[Impacts des options de réforme de la subvention des engrais en Iran : une évaluation à l'aide d'un modèle de programmation régionale des cultures]

Author

Listed:
  • Mona Aghabeygi

    (UNIPR - Università degli studi di Parma = University of Parma, JRC - European Commission - Joint Research Centre [Seville])

  • Kamel Louhichi

    (UMR PSAE - Paris-Saclay Applied Economics - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Sergio Gomez y Paloma

    (JRC - European Commission - Joint Research Centre [Seville])

Abstract

The aim of this paper is to assess the potential impacts of different fertilizer subsidy reform options on the performance of the Iranian crops production sector. This is achieved using a Regional Crop Programming (RCP) model, based on Positive Mathematical Programming, which includes in total 14 crop activities and encompasses 31 administrative regions. The RCP model is a collection of micro-economic models, working with exogenous prices, each representing the optimal crop allocation at the regional level. The model is calibrated against observed data on crop acreage, yield responses to nitrogen application, and exogenous supply elasticities. Simulation results show that a total removal of nitrogen fertilizer subsidies would affect the competitiveness of crops with the highest nitrogen application rates and lead to a slight reduction of national agricultural income, at approximately 1%. This effect, which is more pronounced at the regional level, is driven by area reallocation rather than land productivity. The reallocation of nitrogen fertilizer subsidy to only strategic crops boost their production and income but increase disparity among regions and affects negatively welfare compared to the current universal fertilizer program. The transfer efficiency analysis shows that both target and universal simulated options are inefficient with an efficiency score below one.

Suggested Citation

  • Mona Aghabeygi & Kamel Louhichi & Sergio Gomez y Paloma, 2022. "Impacts of fertilizer subsidy reform options in Iran: an assessment using a Regional Crop Programming model [Impacts des options de réforme de la subvention des engrais en Iran : une évaluation à l," Post-Print hal-03738928, HAL.
    • Handle: RePEc:hal:journl:hal-03738928
    DOI: 10.36253/bae-10981
    Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-03738928v1
    as

    Download full text from publisher

    File URL: https://hal.inrae.fr/hal-03738928v1/document
    Download Restriction: no
    File URL: https://libkey.io/10.36253/bae-10981?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(01), pages 1-16, April.
    2. Eruygur, H.O. & Cakmak, Erol H., 2008. "EU Integration of Turkey: Implications for Turkish Agriculture," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44213, European Association of Agricultural Economists.
    3. Godard, C. & Roger-Estrade, J. & Jayet, P.A. & Brisson, N. & Le Bas, C., 2008. "Use of available information at a European level to construct crop nitrogen response curves for the regions of the EU," Agricultural Systems, Elsevier, vol. 97(1-2), pages 68-82, April.
    4. Cloé Garnache & Pierre Mérel & Richard Howitt & Juhwan Lee, 2017. "Calibration of shadow values in constrained optimisation models of agricultural supply," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(3), pages 363-397.
    5. Nina Graveline & Pierre Mérel, 2014. "Intensive and extensive margin adjustments to water scarcity in France's Cereal Belt," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(5), pages 707-743.
    6. Horner, G.L. & Corman, J. & Howitt, R.E. & Carter, C.A. & MacGregor, R.J., 1992. "The Canadian Regional Agriculture Model Structure, Operation and Development," Papers 1-92, Gouvernement du Canada - Agriculture Canada.
    7. Kamel Louhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez y Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies Insights from three country case studies using LSMS-ISA data [Modélisation des moyens de subsistance des ménages agricoles dans les écon," Post-Print hal-02544905, HAL.
    8. Pierre Mérel & Santiago Bucaram, 2010. "Exact calibration of programming models of agricultural supply against exogenous supply elasticities," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(3), pages 395-418, September.
    9. Garshasbi, Alireza & Khosropour, Hossein & Rahimian, Narges & Behrooz, Aref & Sedighi, Somaye, 2014. "Determining the Role of Inefficiency on Elasticity of Output Supply and Input Demand: A Case Study of Irrigated Wheat in 27 provinces of Iran," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 4(01), pages 1-14, January.
    10. Alireza Garshasbi & Hossein Khosropour & Narges Rahimian & Aref Behrooz & Somaye Sedighi, 2014. "Determining the Role of Inefficiency on Elasticity of Output Supply and Input Demand: A Case Study of Irrigated Wheat in 27 provinces of Iran," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society, vol. 4(1), pages 82-95.
    11. Gardner, Bruce L, 1992. "Changing Economic Perspectives on the Farm Problem," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 62-101, March.
    12. Pierre Mérel & Leo K. Simon & Fujin Yi, 2011. "A Fully Calibrated Generalized Constant-Elasticity-of-Substitution Programming Model of Agricultural Supply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 936-948.
    13. Thomas Heckelei & Hendrik Wolff, 2003. "Estimation of constrained optimisation models for agricultural supply analysis based on generalised maximum entropy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 30(1), pages 27-50, March.
    14. Kamel Louhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez y Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies Insights from three country case studies using LSMS-ISA data [Modélisation des moyens de subsistance des ménages agricoles dans les écon," Working Papers hal-02544905, HAL.
    15. Louhichi, Kamel & Gomez y Paloma, Sergio, 2014. "A farm household model for agri-food policy analysis in developing countries: Application to smallholder farmers in Sierra Leone," Food Policy, Elsevier, vol. 45(C), pages 1-13.
    16. Johansson, Robert & Peters, Mark & House, Robert, 2007. "Regional Environment and Agriculture Programming Model," Technical Bulletins 184314, United States Department of Agriculture, Economic Research Service.
    17. Chibwana, Christopher & Shively, Gerald & Fisher, Monica & Jumbe, Charles & Masters, William A., 2014. "Measuring the impacts of Malawi’s farm input subsidy programme," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 9(2), pages 1-16, April.
    18. Bruno Henry de Frahan, 2019. "Towards Econometric Mathematical Programming for Policy Analysis," Natural Resource Management and Policy, in: Siwa Msangi & Duncan MacEwan (ed.), Applied Methods for Agriculture and Natural Resource Management, chapter 0, pages 11-36, Springer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Jing Jing & Salleh, Norlida Hanim Mohd & Nor, Nor Ghani Md, 2024. "The economy-wide impact of cooking oil subsidy reforms and compensation to the oil palm industry," Journal of Policy Modeling, Elsevier, vol. 46(6), pages 1228-1242.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kamel Louhichi & Pavel Ciaian & Maria Espinosa & Angel Perni & Sergio Gomez y Paloma, 2018. "Economic impacts of CAP greening: application of an EU-wide individual farm model for CAP analysis (IFM-CAP)," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(2), pages 205-238.
    2. Jonathan R. Sweeney & Richard E. Howitt & Hing Ling Chan & Minling Pan & PingSun Leung, 2017. "How do fishery policies affect Hawaii's longline fishing industry? Calibrating a positive mathematical programming model," Papers 1707.03960, arXiv.org.
    3. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(01), pages 1-16, April.
    4. Pascal Tillie & Kamel Louhichi & Sergio Gomez-Y-Paloma, 2018. "La culture attelée dans le bassin cotonnier en Côte d'Ivoire. Analyse et modélisation des impacts d'un programme de relance de la culture attelée," JRC Research Reports JRC111027, Joint Research Centre.
    5. Garnache, Cloe & Merel, Pierre R., 2011. "Calibrating a regional PMP model of agricultural supply under multiple constraints: a set of matryoshka doll conditions," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114630, European Association of Agricultural Economists.
    6. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Paloma, Sergio, 2015. "The Impact of Crop Diversification Measure: EU-wide Evidence Based on IFM-CAP Model," 2015 Conference, August 9-14, 2015, Milan, Italy 211542, International Association of Agricultural Economists.
    7. Kamel Louhichi & Aymeric Ricome & Sergio Gomez y Paloma, 2022. "Impacts of agricultural taxation in Sub‐Saharan Africa: Insights from agricultural produce cess in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 671-686, September.
    8. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.
    9. Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    10. Umed Temurshoev & Marian Mraz & Luis Delgado Sancho & Peter Eder, 2015. "EU Petroleum Refining Fitness Check: OURSE Modelling and Results," JRC Research Reports JRC96207, Joint Research Centre.
    11. Liu, Xuan & van Kooten, Gerrit Cornelis & Duan, Jun, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    12. Siwa Msangi & Sarah Ann Cline, 2016. "Improving Groundwater Management for Indian Agriculture: Assessing Tradeoffs Across Policy Instruments," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-33, September.
    13. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
    14. Aymeric Ricome & Kamel Louhichi & Sergio Gomez y Paloma, 2020. "Impacts of agricultural produce cess (tax) reform options in Tanzania [Impacts des options de réforme des taxes sur les produits agricoles en Tanzanie]," Working Papers hal-02535711, HAL.
    15. Umed Temurshoev & Fréderic Lantz, 2016. "Long-term petroleum product supply analysis through a robust modelling approach," Working Papers 2016-003, Universidad Loyola Andalucía, Department of Economics.
    16. Britz, Wolfgang & Linda, Arata, "undated". "How Important Are Crop Shares In Managing Risk For Specialized Arable Farms? A Panel Estimation Of A Programming Model For Three European Regions," 56th Annual Conference, Bonn, Germany, September 28-30, 2016 244801, German Association of Agricultural Economists (GEWISOLA).
    17. Petsakos, Athanasios & Rozakis, Stelios, 2022. "Models and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(03), January.
    18. Lee, Hwarang & Eom, Jiyong & Cho, Cheolhung & Koo, Yoonmo, 2019. "A bottom-up model of industrial energy system with positive mathematical programming," Energy, Elsevier, vol. 173(C), pages 679-690.
    19. Adam Daigneault & Suzie Greenhalgh & Oshadhi Samarasinghe, 2018. "Economic Impacts of Multiple Agro-Environmental Policies on New Zealand Land Use," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(4), pages 763-785, April.
    20. Torbjörn Jansson & Staffan Waldo, 2022. "Managing Marine Mammals and Fisheries: A Calibrated Programming Model for the Seal-Fishery Interaction in Sweden," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 501-530, March.

    More about this item

    Keywords

    agricultural policy; fertilizer subsidy; land use effect; Regional Crop Model; Positive Mathematical Programing (PMP); Iran;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-03738928. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.