IDEAS home Printed from https://ideas.repec.org/p/rep/wpaper/2013-04.html
   My bibliography  Save this paper

Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis

Author

Listed:
  • G. Cornelis van Kooten

Abstract

This paper deals with forest trade modelling from a theoretical, analytic and empirical perspective. An integrated dynamic log-lumber trade model is developed and then used to examine two trade issues, namely, a reduction of Russian taxes on log exports and removal of the taxes on Canadian lumber destined for the United States. To demonstrate the dynamic aspect of the model, both sets of taxes are lowered over a period of time. The trade model consists of five Canadian regions, three U.S. regions, New Zealand, Australia, Chile, Rest of Latin America, Russia, Sweden, Finland, Rest of Europe, Japan, China, Rest of Asia, and Rest of the World – a total of 20 regions. It concerns only coniferous logs and softwood lumber, ignoring hardwoods. The model is also calibrated on 2010 observed bi-lateral flows of logs and lumber using positive mathematical programming. The forest trade model is written using an Excel-GAMS interface, with input data retrieved by GAMS from Excel and GAMS output written to Excel, where final calculations are made.

Suggested Citation

  • G. Cornelis van Kooten, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 2013-04, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
  • Handle: RePEc:rep:wpaper:2013-04
    as

    Download full text from publisher

    File URL: http://web.uvic.ca/~repa/publications/REPA%20working%20papers/WorkingPaper2013-04.pdf
    File Function: Final version, 2013
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Anthony Mogus & Brad Stennes & G. Cornelis van Kooten, 2005. "Canada-US Softwood Lumber Trade Revisited: Examining the Role of Substitution Bias in the Context of a Spatial Price Equilibrium Framework," Working Papers 2005-08, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    2. 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.
    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(1), pages 1-16, April.
    4. John Perez‐Garcia & Bruce Lippke & Janet Baker, 1997. "Trade Barriers In The Pacific Forest Sector: Who Wins And Who Loses," Contemporary Economic Policy, Western Economic Association International, vol. 15(1), pages 87-103, January.
    5. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    6. 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.
    7. Quirino Paris & Richard E. Howitt, 1998. "An Analysis of Ill-Posed Production Problems Using Maximum Entropy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 124-138.
    8. G. C. van Kooten & Henk Folmer, 2004. "Land and Forest Economics," Books, Edward Elgar Publishing, number 3466.
    9. Paris, Quirino & Drogué, Sophie & Anania, Giovanni, 2011. "Calibrating spatial models of trade," Economic Modelling, Elsevier, vol. 28(6), pages 2509-2516.
    10. Jansson, Torbjörn & Heckelei, Thomas, 2009. "A new estimator for trade costs and its small sample properties," Economic Modelling, Elsevier, vol. 26(2), pages 489-498, March.
    11. 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.
    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. 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.

    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. Xuan Liu & Gerrit Cornelis van Kooten & Jun Duan, 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), pages 795-817, July.
    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. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2014. "Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization," Working Papers 197898, University of Victoria, Resource Economics and Policy.
    4. 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.
    5. 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).
    6. 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, December.
    7. Alain CARPENTIER & Alexandre GOHIN & Paolo SCKOKAI & Alban THOMAS, 2015. "Economic modelling of agricultural production:past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 96(1), pages 131-166.
    8. Schmid, Erwin & Sinabell, Franz, 2005. "Evaluation Of Decoupling Scenarios in a Rural Development Context: Results for Austria," 89th Seminar, February 2-5, 2005, Parma, Italy 239278, European Association of Agricultural Economists.
    9. Nunez, H., 2018. "Building a Bioethanol Market in Mexico," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275921, International Association of Agricultural Economists.
    10. Wolfgang Britz & Linda Arata, 2019. "Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 191-206, March.
    11. Umed Temurshoev & Marian Mraz & Luis Delgado Sancho & Peter Eder, 2015. "EU Petroleum Refining Fitness Check: OURSE Modelling and Results," JRC Working Papers JRC96207, Joint Research Centre (Seville site).
    12. Solazzo, Roberto & Pierangeli, Fabio, 2016. "How does greening affect farm behaviour? Trade-off between commitments and sanctions in the Northern Italy," Agricultural Systems, Elsevier, vol. 149(C), pages 88-98.
    13. Robert M'barek & Jesus Barreiro-Hurle & Pierre Boulanger & Arnaldo Caivano & Pavel Ciaian & Hasan Dudu & Maria Espinosa Goded & Thomas Fellmann & Emanuele Ferrari & Sergio Gomez Y Paloma & Celso Gorri, 2017. "Scenar 2030 - Pathways for the European agriculture and food sector beyond 2020," JRC Working Papers JRC108449, Joint Research Centre (Seville site).
    14. Nuñez, Hector M., 2016. "Biofuel Potential in Mexico: Land Use, Economic and Environmental Effects," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236067, Agricultural and Applied Economics Association.
    15. 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.
    16. Franz Sinabell & Martin Schönhart & Erwin Schmid, 2018. "Austrian Agriculture 2020-2050. Scenarios and Sensitivity Analyses on Land Use, Production, Livestock and Production Systems," WIFO Studies, WIFO, number 61571, December.
    17. Roy, René & Baker, Laurie & Thomassin, Paul J., 2013. "Estimating the Cost of Agricultural Pollution Abatement: Establishing Beneficial Management Practices in the Bras d’Henri Watershed," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150956, Agricultural and Applied Economics Association.
    18. Carpentier, Alain & Letort, Elodie, 2009. "Modeling acreage decisions within the multinomial Logit framework," Working Papers 211011, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    19. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2016. "Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems," Center for Agricultural and Rural Development (CARD) Publications 16-wp563, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    20. 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.

    More about this item

    Keywords

    log-lumber trade; spatial price equilibrium model; mathematical programming;
    All these keywords.

    JEL classification:

    • 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
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices

    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:2013-04. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (G.C. van Kooten). General contact details of provider: https://edirc.repec.org/data/devicca.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.