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Forecasting for Environmental Decision Making

  • JS Armstrong

    (The Wharton School - University of Pennsylvania)

Those making environmental decisions must not only characterize the present, they must also forecast the future. They must do so for at least two reasons. First, if a no-action alternative is pursued, they must consider whether current trends will be favorable or unfavorable in the future. Second, if an intervention is pursued instead, they must evaluate both its probable success given future trends and its impacts on the human and natural environment. Forecasting, by which I mean explicit processes for determining what is likely to happen in the future, can help address each of these areas.

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File URL: http://128.118.178.162/eps/get/papers/0412/0412023.pdf
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Paper provided by EconWPA in its series General Economics and Teaching with number 0412023.

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Length: 25 pages
Date of creation: 10 Dec 2004
Date of revision:
Handle: RePEc:wpa:wuwpgt:0412023
Note: Type of Document - pdf; pages: 25
Contact details of provider: Web page: http://128.118.178.162

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  1. JS Armstrong, 2004. "Forecasting Methods for Conflict Situations," General Economics and Teaching 0412025, EconWPA.
  2. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
  3. JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, EconWPA.
  4. Winston, Clifford, 1993. "Economic Deregulation: Days of Reckoning for Microeconomists," Journal of Economic Literature, American Economic Association, vol. 31(3), pages 1263-89, September.
  5. JS Armstrong & Philip D. Hutcherson, 2005. "Predicting The Outcome of Marketing Negotiations: Role-Playing versus Unaided Opinions," General Economics and Teaching 0502040, EconWPA.
  6. 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.
  7. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
  8. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, EconWPA.
  9. Chatfield, Chris, 1995. "Positive or negative?," International Journal of Forecasting, Elsevier, vol. 11(4), pages 501-502, December.
  10. Collopy, Fred & Armstrong, J. Scott, 1992. "Expert opinions about extrapolation and the mystery of the overlooked discontinuities," International Journal of Forecasting, Elsevier, vol. 8(4), pages 575-582, December.
  11. Fred Collopy & J. Scott Armstrong, 1992. "Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations," Management Science, INFORMS, vol. 38(10), pages 1394-1414, October.
  12. JS Armstrong & Terry Overton, 2005. "Estimating Nonresponse Bias in Mail Surveys," General Economics and Teaching 0502044, EconWPA.
  13. Don Fullerton & Thomas C. Kinnaman, 1994. "Household Responses to Pricing Garbage by the Bag," CARE Working Papers 9402, The University of Texas at Austin, Center for Applied Research in Economics.
  14. Bretschneider, Stuart I. & Gorr, Wilpen L. & Grizzle, Gloria & Klay, Earle, 1989. "Political and organizational influences on the accuracy of forecasting state government revenues," International Journal of Forecasting, Elsevier, vol. 5(3), pages 307-319.
  15. J. S. Armstrong, 2005. "Forecasting by Extrapolation: Conclusions from 25 Years of Research," General Economics and Teaching 0502025, EconWPA.
  16. Yokuma, J. Thomas & Armstrong, J. Scott, 1995. "Beyond accuracy: Comparison of criteria used to select forecasting methods," International Journal of Forecasting, Elsevier, vol. 11(4), pages 591-597, December.
  17. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  18. Adya, Monica & Collopy, Fred & Armstrong, J. Scott & Kennedy, Miles, 2001. "Automatic identification of time series features for rule-based forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 143-157.
  19. Dalrymple, Douglas J., 1987. "Sales forecasting practices: Results from a United States survey," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 379-391.
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