Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis

  • Authors: Jeuck, J; Cubbage, F.; Abt, R.; Bardon, R.; McCarter, J.; Coulston, J.; Renkow, M.
  • Publication Year: 2014
  • Publication Series: Scientific Journal (JRNL)
  • Source: International Journal: Forests 2014, 5/7
  • DOI: 10.3390/f5071532

Abstract

: We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratios estimates were developed based on (1) proportion of times the independent variables had statistical significance and (2) proportion of times independent variables met the original study authors’ expectations. In F2D models, we confirmed the success of popular independent variables such as population, income, and urban proximity estimates but found timber rents and site productivity variables less successful. In F2A models, we confirmed success of popular explanatory variables such as forest and agricultural rents and costs, governmental programs, and site quality, but we found population, income, and urban proximity estimates less successful. In U2D models, successful independent variables found were urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. In F2NF models, we found poor success using timber rents but high success using agricultural rents, site quality, population, and income. Success ratios and discussion of new or less popular, but promising, variables was also included. This meta-analysis provided insight into the general success of econometric independent variables for future forest-use or -cover change research.

  • Citation: Jeuck, James A.; Cubbage, Frederick W.; Abt, Robert C.; Bardon, Robert E.; McCarter, James B.; Coulston, John W.; and Renkow, Mitch A. 2014. Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis.
  • Keywords: forestland use change; meta-analysis; econometric modeling
  • Posted Date: October 10, 2014
  • Modified Date: November 13, 2014
  • Print Publications Are No Longer Available

    In an ongoing effort to be fiscally responsible, the Southern Research Station (SRS) will no longer produce and distribute hard copies of our publications. Many SRS publications are available at cost via the Government Printing Office (GPO). Electronic versions of publications may be downloaded, printed, and distributed.

    Publication Notes

    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
    • Our online publications are scanned and captured using Adobe Acrobat. During the capture process some typographical errors may occur. Please contact the SRS webmaster if you notice any errors which make this publication unusable.
    • To view this article, download the latest version of Adobe Acrobat Reader.