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Municipal Non-Residential Real Property Valuation Forecast Accuracy

  • Arnold Cote, K. Nicole
  • Smith, Wm. Doyle
  • Fullerton, Thomas M., Jr.

The objective of this study is to estimate the accuracy and/or reliability of alternative methods of forecasting property valuations of non-residential real commercial and industrial property in El Paso to improve municipal revenue forecasting. This study seeks to identify and evaluate four econometric and statistical alternatives to present forecasting practices for nonresidential property valuation forecasts: (1) a traditional income elasticity method, (2) a regional structural econometric model, (3) a statistical ARIMA method, and (4) trend analysis. In order to evaluate the four models, ex ante forecast simulations are created for each modeling approach and then compared to random walk and random walk with drift models for both commercial and industrial property values. Results indicate that the random walk with drift model outperformed all four models for both commercial and industrial property values. In addition, results also indicate that the random walk model outperformed all four models for industrial property values.

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File URL: http://mpra.ub.uni-muenchen.de/32116/1/MPRA_paper_32116.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 32116.

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Date of creation: 22 Oct 2010
Date of revision: 11 Feb 2011
Publication status: Published in International Journal of Business & Economics Perspectives 1.6(2011): pp. 56-77
Handle: RePEc:pra:mprapa:32116
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Phone: +49-(0)89-2180-2219
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Web page: http://mpra.ub.uni-muenchen.de

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  1. Fullerton, Thomas & Aragones-Zamudio, Victor, 2006. "El Paso Property Tax Abatement Ineffectiveness," MPRA Paper 626, University Library of Munich, Germany, revised 2006.
  2. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  3. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, June.
  4. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
  5. Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
  6. Thomas M. Fullerton Jr. & George Novela, 2010. "Metropolitan Maquiladora Econometric Forecast Accuracy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 124-140, September.
  7. Roy H. Webb, 1984. "Vector autoregressions as a tool for forecast evaluations," Economic Review, Federal Reserve Bank of Richmond, issue Jan, pages 3-11.
  8. Fullerton, Thomas M., Jr. & Kelley, Brian W., 2008. "El Paso Housing Sector Econometric Forecast Accuracy," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(01), April.
  9. Thomas M Fullerton Jr, 2004. "Specification of a Borderplex Econometric Forecasting Model," Urban/Regional 0405006, EconWPA.
  10. Thomas M Fullerton Jr, 2005. "Borderplex Bridge and Air Econometric Forecast Accuracy," Urban/Regional 0501005, EconWPA.
  11. Thomas M Fullerton Jr & Arturo Elias, 2004. "Short-Term Water Consumption Dynamics in El Paso, Texas," Others 0410005, EconWPA.
  12. Terri Erickson Sexton & Richard J. Sexton, 1986. "Re-Evaluating the Income Elasticity of the Property Tax Base," Land Economics, University of Wisconsin Press, vol. 62(2), pages 182-191.
  13. Fullerton, Thomas Jr., 1989. "A composite approach to forecasting state government revenues: Case study of the Idaho sales tax," International Journal of Forecasting, Elsevier, vol. 5(3), pages 373-380.
  14. Fullerton, Thomas & Barraza de Anda, Martha, 2008. "Borderplex Population Modeling," MPRA Paper 7032, University Library of Munich, Germany.
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