IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v39y2014icp293-304.html
   My bibliography  Save this article

A multi-period positive mathematical programming approach for assessing economic impact of drought in the Murray–Darling Basin, Australia

Author

Listed:
  • Qureshi, M. Ejaz
  • Ahmad, Mobin-ud-Din
  • Whitten, Stuart M.
  • Kirby, Mac

Abstract

In the last decade, the Murray–Darling Basin (MDB), Australia faced a severe drought which affected its agriculture production. Sustainable diversion limits as proposed in the Australian Government's basin plan together with climate change are expected to impact on future agriculture production and development in the MDB. We developed a biophysical–economic mathematical model calibrated against the observed multi-period land use data utilising the positive mathematical programming (PMP) approach to evaluate the impacts on agricultural production activities of a range of climate events and policy options. This is an extension of our previous work where the model was calibrated against a single year and the focus was on the southern MDB only. The multi-period calibrated model has strong predictive capacity as it matches simulated irrigated area, water use and gross value of irrigated agricultural product (GVIAP) well with the observed irrigated land, water use and GVIAP for all the crops in all the regions of the MDB across the highly variable climatic conditions from 2005 to 2009. The approach will be useful in assessing economic impacts of climate change on irrigation, farmers' adaptation options and/or water policies including water markets and irrigation efficiency improvement.

Suggested Citation

  • Qureshi, M. Ejaz & Ahmad, Mobin-ud-Din & Whitten, Stuart M. & Kirby, Mac, 2014. "A multi-period positive mathematical programming approach for assessing economic impact of drought in the Murray–Darling Basin, Australia," Economic Modelling, Elsevier, vol. 39(C), pages 293-304.
    • Handle: RePEc:eee:ecmode:v:39:y:2014:i:c:p:293-304
    DOI: 10.1016/j.econmod.2014.02.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999314000868
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2014.02.042?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    2. Heckelei, Thomas & Britz, Wolfgang, 2005. "Models Based on Positive Mathematical Programming: State of the Art and Further Extensions," 89th Seminar, February 2-5, 2005, Parma, Italy 234607, European Association of Agricultural Economists.
    3. Kirby, Mac & Connor, Jeffery D. & Bark, Rosalind H. & Qureshi, Muhammad Ejaz & Keyworth, Scott W., 2012. "The economic impact of water reductions during the Millennium Drought in the Murray-Darling Basin," 2012 Conference (56th), February 7-10, 2012, Fremantle, Australia 124490, Australian Agricultural and Resource Economics Society.
    4. Thomas W. Hertel & Stephanie D. Rosch, 2010. "Climate Change, Agriculture, and Poverty," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 32(3), pages 355-385.
    5. Heckelei, Thomas & Britz, Wolfgang, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 57.
    6. Cortignani, Raffaele & Severini, Simone, 2009. "Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming," Agricultural Water Management, Elsevier, vol. 96(12), pages 1785-1791, December.
    7. Ronald C. Griffin, 2006. "Water Resource Economics: The Analysis of Scarcity, Policies, and Projects," MIT Press Books, The MIT Press, edition 1, volume 1, number 026207267x, December.
    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. -, 2009. "The economics of climate change," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 38679, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    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. Pérez-Blanco, C.D. & Gutiérrez-Martín, C., 2017. "Buy me a river: Use of multi-attribute non-linear utility functions to address overcompensation in agricultural water buyback," Agricultural Water Management, Elsevier, vol. 190(C), pages 6-20.
    2. Henderson, Benjamin & Cacho, Oscar & Thornton, Philip & van Wijk, Mark & Herrero, Mario, 2018. "The economic potential of residue management and fertilizer use to address climate change impacts on mixed smallholder farmers in Burkina Faso," Agricultural Systems, Elsevier, vol. 167(C), pages 195-205.
    3. 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.
    4. Rianne van Duinen & Tatiana Filatova & Peter Geurts & Anne van der Veen, 2015. "Empirical Analysis of Farmers' Drought Risk Perception: Objective Factors, Personal Circumstances, and Social Influence," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 741-755, April.
    5. Samira Shayanmehr & Jana Ivanič Porhajašová & Mária Babošová & Mahmood Sabouhi Sabouni & Hosein Mohammadi & Shida Rastegari Henneberry & Naser Shahnoushi Foroushani, 2022. "The Impacts of Climate Change on Water Resources and Crop Production in an Arid Region," Agriculture, MDPI, vol. 12(7), pages 1-22, July.
    6. Paris, Quirino, 2017. "Cost function and positive mathematical programming," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 6(1), May.
    7. Glyn Wittwer & Robert Waschik, 2021. "Estimating the economic impacts of the 2017–2019 drought and 2019–2020 bushfires on regional NSW and the rest of Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(4), pages 918-936, October.

    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. 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(1), pages 1-16, April.
    2. 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.
    3. Kamel Elouhichi & 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," JRC Research Reports JRC118822, Joint Research Centre.
    4. 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.
    5. He, Lixia & Horbulyk, Theodore M. & Ali, Md. Kamar & Le Roy, Danny G. & Klein, K.K., 2012. "Proportional water sharing vs. seniority-based allocation in the Bow River basin of Southern Alberta," Agricultural Water Management, Elsevier, vol. 104(C), pages 21-31.
    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. 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).
    8. Zhou, Wei, 2015. "Three essays on modeling biofuel feedstock supply," ISU General Staff Papers 201501010800005728, Iowa State University, Department of Economics.
    9. 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.
    10. Doole, Graeme J. & Marsh, Dan K., 2014. "Use of positive mathematical programming invalidates the application of the NZFARM model: Response to Daigneault et al. (2014)," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    11. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Montilla-López, Nazaret M., 2021. "Priority water rights. Are they useful for improving water-use efficiency at the irrigation district level?," Agricultural Water Management, Elsevier, vol. 257(C).
    12. Cortignani, Raffaele & Severini, Simone, 2009. "Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming," Agricultural Water Management, Elsevier, vol. 96(12), pages 1785-1791, December.
    13. 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.
    14. Athanasios Petsakos & Stelios Rozakis, 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(3), pages 713-728, July.
    15. Arfini, Filippo & Donati, Michele & Paris, Quirino, 2008. "Innovation in Estimation of Revenue and Cost Functions in PMP Using FADN Information at Regional Level," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44008, European Association of Agricultural Economists.
    16. 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.
    17. Cortignani, Raffaele & Severini, Simone, 2010. "The impact of reforming the Common Agricultural Policy on the sustainability of the irrigated area of Central Italy. An empirical assessment by means of a Positive Mathematical Programming model," 120th Seminar, September 2-4, 2010, Chania, Crete 109318, European Association of Agricultural Economists.
    18. 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.
    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. 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.

    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:eee:ecmode:v:39:y:2014:i:c:p:293-304. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.