IDEAS home Printed from https://ideas.repec.org/a/eee/foreco/v20y2014i3p305-315.html
   My bibliography  Save this article

Projecting county pulpwood production with historical production and macro-economic variables

Author

Listed:
  • Brandeis, Consuelo
  • Lambert, Dayton M.

Abstract

We explored forecasting of county roundwood pulpwood production with county-vector autoregressive (CVAR) and spatial panel vector autoregressive (SPVAR) methods. The analysis used timber products output data for the state of Florida, together with a set of macro-economic variables. Overall, we found the SPVAR specification produced forecasts with lower error rates compared to CVAR specifications. Nonetheless, high forecast errors across counties revealed the uncertainty associated with projecting volumes of county pulpwood production.

Suggested Citation

  • Brandeis, Consuelo & Lambert, Dayton M., 2014. "Projecting county pulpwood production with historical production and macro-economic variables," Journal of Forest Economics, Elsevier, vol. 20(3), pages 305-315.
  • Handle: RePEc:eee:foreco:v:20:y:2014:i:3:p:305-315
    DOI: 10.1016/j.jfe.2014.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1104689914000324
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jfe.2014.09.002?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation," MPRA Paper 11569, University Library of Munich, Germany, revised Nov 2008.
    2. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    3. Damiaan Persyn & Joakim Westerlund, 2008. "Error-correction–based cointegration tests for panel data," Stata Journal, StataCorp LP, vol. 8(2), pages 232-241, June.
    4. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    5. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    6. Buongiorno, Joseph & Kang, Young & Connaughton, Kent, 1988. "Predicting the effects of macro-economic variables on timber harvest in small regions: Method and application," Agricultural Systems, Elsevier, vol. 28(4), pages 241-257.
    7. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    8. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    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. Peñasco, Cristina & del Río, Pablo & Romero-Jordán, Desiderio, 2017. "Gas and electricity demand in Spanish manufacturing industries: An analysis using homogeneous and heterogeneous estimators," Utilities Policy, Elsevier, vol. 45(C), pages 45-60.
    2. Markus Eberhardt, 2012. "Estimating panel time-series models with heterogeneous slopes," Stata Journal, StataCorp LP, vol. 12(1), pages 61-71, March.
    3. Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    4. Scott, K. Rebecca, 2011. "Demand and Price Volatility: Rational Habits in International Gasoline Demand," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2q87432b, Department of Agricultural & Resource Economics, UC Berkeley.
    5. Tzu-Ming Liu, 2020. "Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?," Tourism Economics, , vol. 26(3), pages 461-474, May.
    6. Roberto Dell'Anno & Adalgiso Amendola, 2015. "Social Exclusion and Economic Growth: An Empirical Investigation in European Economies," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(2), pages 274-301, June.
    7. Daniel Weimar & Markus Schauberger, 2018. "The impact of sporting success on student enrollment," Journal of Business Economics, Springer, vol. 88(6), pages 731-764, August.
    8. Colin Wren & Jonathan Jones, 2011. "Assessing The Regional Impact Of Grants On Fdi Location: Evidence From U.K. Regional Policy, 1985–2005," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 497-517, August.
    9. Vu, K.M., 2017. "Structural change and economic growth: Empirical evidence and policy insights from Asian economies," Structural Change and Economic Dynamics, Elsevier, vol. 41(C), pages 64-77.
    10. Meri Davlasheridze & Pinar C. Geylani, 2017. "Small Business vulnerability to floods and the effects of disaster loans," Small Business Economics, Springer, vol. 49(4), pages 865-888, December.
    11. Eicher, Theo S. & Schreiber, Till, 2010. "Structural policies and growth: Time series evidence from a natural experiment," Journal of Development Economics, Elsevier, vol. 91(1), pages 169-179, January.
    12. Zheng, Xinye & Li, Fanghua & Song, Shunfeng & Yu, Yihua, 2013. "Central government's infrastructure investment across Chinese regions: A dynamic spatial panel data approach," China Economic Review, Elsevier, vol. 27(C), pages 264-276.
    13. Alexander Klemm & Stefan Parys, 2012. "Empirical evidence on the effects of tax incentives," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(3), pages 393-423, June.
    14. Giovanni S F Bruno & Enrico Marelli & Marcello Signorelli, 2014. "The Rise of NEET and Youth Unemployment in EU Regions after the Crisis," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 56(4), pages 592-615, December.
    15. Ronald MacDonald & Flávio Vieira, "undated". "A panel data investigation of real exchange rate misalignment and growth," Working Papers 2010_13, Business School - Economics, University of Glasgow.
    16. DELL'ANNO, Roberto & VILLA, Stefania, 2012. "Growth in Transition Countries: Big Bang versus Gradualism," CELPE Discussion Papers 122, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    17. Murtin, Fabrice & de Serres, Alain & Hijzen, Alexander, 2014. "Unemployment and the coverage extension of collective wage agreements," European Economic Review, Elsevier, vol. 71(C), pages 52-66.
    18. Bertacchini, Enrico & Dalle Nogare, Chiara, 2014. "Public provision vs. outsourcing of cultural services: Evidence from Italian cities," European Journal of Political Economy, Elsevier, vol. 35(C), pages 168-182.
    19. Mohanty, Biswajit & Bhanumurthy, N. R. & Dastidar, Ananya Ghosh, 2017. "What explains Regional Imbalances in Infrastructure?: Evidence from Indian States," Working Papers 17/197, National Institute of Public Finance and Policy.
    20. Njangang, Henri & Asongu, Simplice A. & Tadadjeu, Sosson & Nounamo, Yann & Kamguia, Brice, 2022. "Governance in mitigating the effect of oil wealth on wealth inequality: A cross-country analysis of policy thresholds," Resources Policy, Elsevier, vol. 76(C).

    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:foreco:v:20:y:2014:i:3:p:305-315. 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/wps/find/journaldescription.cws_home/701775/description#description .

    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.