IDEAS home Printed from https://ideas.repec.org/p/rep/wpaper/2014-04.html
   My bibliography  Save this paper

Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization

Author

Listed:
  • Craig Johnston
  • G. Cornelis van Kooten

Abstract

This paper serves to document the REPA Forest Trade Model – a global model of forest trade that consists of ten products across two horizontal layers in a vertical chain. The model includes 20 regions: Five Canadian regions (Atlantic Canada, Central Canada, Alberta, BC Interior and BC Coast), three U.S. regions (South, North and West), China, Japan, Rest of Asia, Chile, Rest of Latin America, Australia, New Zealand, Finland, Sweden, Russia, Rest of Europe, and the Rest of the World. The underlying economic theory upon which the model is built is discussed in detail; we demonstrate that changes in region-level forest management policies (e.g., related to harvests) and/or trade policies have a larger impact on income transfers among regions and agents than they have on global welfare. The objective function and constraints to the quadratic programming implementation of the model are developed, and the method used to calibrate the model to existing bilateral trade flows via positive mathematical programming is discussed. Finally, the data sources and actual data are provided, as are the corrections to shipping and handling costs needed to calibrate the model.

Suggested Citation

  • Craig Johnston & G. Cornelis van Kooten, 2014. "Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization," Working Papers 2014-04, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    • Handle: RePEc:rep:wpaper:2014-04
    as

    Download full text from publisher

    File URL: http://web.uvic.ca/~repa/publications/REPA%20working%20papers/WorkingPaper2014-04.pdf
    File Function: Final version, 2014
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hayri Önal & Bruce A. McCarl, 1991. "Exact Aggregation in Mathematical Programming Sector Models," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 39(2), pages 319-334, July.
    2. 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.
    3. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    4. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    5. Bruno Henry Frahan & Jeroen Buysse & Philippe Polomé & Bruno Fernagut & Olivier Harmignie & Ludwig Lauwers & Guido Huylenbroeck & Jef Meensel, 2007. "Positive Mathematical Programming for Agricultural and Environmental Policy Analysis: Review and Practice," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 129-154, Springer.
    6. van Kooten, G. Cornelis & Johnston, Craig, 2014. "Global impacts of Russian log export restrictions and the Canada–U.S. lumber dispute: Modeling trade in logs and lumber," Forest Policy and Economics, Elsevier, vol. 39(C), pages 54-66.
    7. Xiaoguang Chen & Hayri Önal, 2012. "Modeling Agricultural Supply Response Using Mathematical Programming and Crop Mixes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(3), pages 674-686.
    8. G. C. van Kooten & Henk Folmer, 2004. "Land and Forest Economics," Books, Edward Elgar Publishing, number 3466.
    9. D. L. Holley, 1970. "Location of the Softwood Plywood and Lumber Industries: A Regional Programming Analysis," Land Economics, University of Wisconsin Press, vol. 46(2), pages 127-137.
    10. Buongiorno, Joseph, 1996. "Forest sector modeling: a synthesis of econometrics, mathematical programming, and system dynamics methods," International Journal of Forecasting, Elsevier, vol. 12(3), pages 329-343, September.
    11. Paris,Quirino, 2011. "Economic Foundations of Symmetric Programming," Cambridge Books, Cambridge University Press, number 9780521123020.
    12. T. Takayama & G. G. Judge, 1964. "Spatial Equilibrium and Quadratic Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 46(1), pages 67-93.
    13. Bruce A. McCarl, 1982. "Cropping Activities in Agricultural Sector Models: A Methodological Proposal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 64(4), pages 768-772.
    14. Paris,Quirino, 2011. "Economic Foundations of Symmetric Programming," Cambridge Books, Cambridge University Press, number 9780521194723.
    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. Miguel Riviere & Sylvain Caurla & Philippe Delacote, 2020. "Evolving Integrated Models From Narrower Economic Tools : the Example of Forest Sector Models," Post-Print hal-02512330, HAL.
    2. Johnston, Craig M.T. & Parajuli, Rajan, 2017. "What's next in the U.S.-Canada softwood lumber dispute? An economic analysis of restrictive trade policy measures," Forest Policy and Economics, Elsevier, vol. 85(P1), pages 135-146.
    3. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2016. "Global trade impacts of increasing Europe's bioenergy demand," Journal of Forest Economics, Elsevier, vol. 23(C), pages 27-44.
    4. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2017. "Impact of inefficient quota allocation under the Canada-U.S. softwood lumber dispute: A calibrated mixed complementarity approach," Forest Policy and Economics, Elsevier, vol. 74(C), pages 71-80.

    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. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    2. van Kooten, G. Cornelis & Johnston, Craig, 2014. "Global impacts of Russian log export restrictions and the Canada–U.S. lumber dispute: Modeling trade in logs and lumber," Forest Policy and Economics, Elsevier, vol. 39(C), pages 54-66.
    3. 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.
    4. 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.
    5. 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.
    6. Doole, Graeme J. & Marsh, Dan K., 2014. "Methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(1), January.
    7. Arata, Linda & Donati, Michele & Sckokai, Paolo & Arfini, Filippo, 2014. "Incorporating risk in a positive mathematical programming framework: a new methodological approach," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182659, European Association of Agricultural Economists.
    8. 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.
    9. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Research Reports JRC108693, Joint Research Centre.
    10. 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.
    11. Affuso, Ermanno & Hite, Diane, 2013. "A model for sustainable land use in biofuel production: An application to the state of Alabama," Energy Economics, Elsevier, vol. 37(C), pages 29-39.
    12. 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.
    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. Daigneault, Adam & Greenhalgh, Suzie & Samarasinghe, Oshadhi, 2014. "A response to Doole and Marsh (2013) article: methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    15. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    16. Franz Sinabell & Martin Schönhart & Erwin Schmid, 2015. "Austrian Agriculture 2010-2050. Quantitative Effects of Climate Change Mitigation Measures – An Analysis of the Scenarios WEM, WAM and a Sensitivity Analysis of the Scenario WEM," WIFO Studies, WIFO, number 58400, Juni.
    17. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.
    18. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    19. Lisa Baldi & Filippo Arfini & Sara Calzolai & Michele Donati, 2023. "An Impact Assessment of GHG Taxation on Emilia-Romagna Dairy Farms through an Agent-Based Model Based on PMP," Land, MDPI, vol. 12(7), pages 1-24, July.
    20. van Kooten, G. Cornelis, 2014. "Benefits and costs of impeding free trade: Revisiting British Columbia's restrictions on log exports," Journal of Forest Economics, Elsevier, vol. 20(4), pages 333-347.

    More about this item

    Keywords

    Forest trade modeling; vertical chains; welfare measurement; mathematical programming; model calibration;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D60 - Microeconomics - - Welfare Economics - - - General
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q27 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Issues in International Trade
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    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:rep:wpaper:2014-04. 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: G.C. van Kooten (email available below). General contact details of provider: https://edirc.repec.org/data/devicca.html .

    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.