National Academies Press: OpenBook

Airport Aviation Activity Forecasting (2007)

Chapter: References

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Page 30
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2007. Airport Aviation Activity Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/23192.
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Page 30
Page 31
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2007. Airport Aviation Activity Forecasting. Washington, DC: The National Academies Press. doi: 10.17226/23192.
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Page 31

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

30 Advisory Circular on Airport Capacity and Delay, AC 150/ 5060-5, Federal Aviation Administration, Washington, D.C., 1983, amended 1995. Advisory Circular on Airport Master Plans, AC 150/5070-6B, Federal Aviation Administration, Washington, D.C., 2005. Advisory Circular on the Airport System Planning Process, AC 150/5070-7, Federal Aviation Administration, Wash- ington, D.C., 2004. Aerospace Forecasts, Fiscal Years 1999–2010, Federal Avi- ation Administration, Washington, D.C., 1999. Alonso, W., “Predicting with Imperfect Data,” Journal of the American Institute of Planners, Vol. 34, 1968, pp. 248–255. Armstrong, J.S., Long-Range Forecasting: From Crystal Ball to Computer, John Wiley, New York, N.Y., 1985. Armstrong, J.S., “Extrapolation for Time-Series and Cross- Sectional Data,” In Principles of Forecasting, J.S. Arm- strong, Ed., Springer Science+Business Media, Inc., New York, N.Y., 2001a, pp. 217–243. Armstrong, J.S., “Selecting Forecasting Methods,” In Prin- ciples of Forecasting, J.S. Armstrong, Ed., Springer Science+Business Media, Inc., New York, N.Y., 2001b, pp. 363–386. Armstrong, J.S., “Combining Forecasts,” In Principles of Fore- casting, J.S. Armstrong, Ed., Springer Science+Business Media, Inc., New York, N.Y., 2001c, pp. 417–439. Belsey, D.A., E. Kuh, and R.E. Welsch, Regression Diag- nostics: Identifying Influential Data and Sources of Col- linearity, John Wiley, New York, N.Y., 1980. Brueckner, J.K., “Internalization of Airport Congestion,” Journal of Air Transport Management, Vol. 8, 2002, pp. 141–147. Capacity Needs in the National Airspace System, Federal Aviation Administration, Washington, D.C., 2004. Chatfield, C., “Prediction Intervals for Time-Series Fore- casting,” In Principles of Forecasting, J.S. Armstrong, Ed., Springer Science+Business Media, Inc., New York, N.Y., 2001, pp. 475–494. Department of the Environment, Transport, and the Re- gions, Air Traffic Forecasts for the United Kingdom 2000, Department for Transport, London, United Kingdom, 2000. FAA Aerospace Forecasts, Fiscal Years 2006–2017, Federal Aviation Administration, Washington, D.C., 2006. Findley, D.F., B.C. Monsell, and W.R. Bell, “New Capabil- ities and Methods of the X-12 ARIMA Seasonal Adjust- ment Program,” Journal of Business and Economic Sta- tistics, Vol. 16, 1998, pp. 127–152. Flyvbjerg, B., M.K.S. Holm, and S.L. Buhl, “How (In)accu- rate Are Demand Forecasts in Public Works Projects,” Journal of the American Planning Association, Vol. 71, No. 2, 2005, pp. 131–146. REFERENCES Ford, M.L. and R. Shirack, Statistical Sampling of Aircraft Operations at Non-Towered Airports, Federal Aviation Administration, Washington, D.C., 1985. Ford, M.L. and R. Shirack, “Estimating Aircraft Activity at Nontowered Airports: Results of the Aircraft Activity Counter Demonstration Project,” Transportation Research Record 958, Transportation Research Board, National Re- search Council, Washington, D.C., 1984, pp. 24–29. Forecasting Aviation Activity by Airport, Federal Aviation Administration, Washington, D.C., 2001. Greene, W.H., Econometric Analysis, 2nd ed., MacMillan Publishing Company, New York, N.Y., 1993. Grubb, H. and A. Mason, “Long Lead-Time Forecasting of UK Air Passengers by Holt–Winters Methods with Damped Trend,” International Journal of Forecasting, Vol. 17, 2001, pp. 71–82. Ishii, J., S. Jun, and K. Van Dender, “Air Travel Choices in Multi-Airport Markets,” working paper, Department of Economics, University of California–Irvine, 2006. Kennedy, P., A Guide to Econometrics, 5th ed., The MIT Press, Cambridge, Mass., 2003. Lewis, D., “The Future of Forecasting,” TR News, Vol. 177, 1995, pp. 3–9. Maddala, G.S., Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press, Cambridge, United Kingdom, 1983. Manual on Air Traffic Forecasting, 3rd ed., International Civil Aviation Organization, Montreal, QC, Canada, 2006. Model for Estimating General Aviation Operations at Non- Towered Airports, Federal Aviation Administration, Wash- ington, D.C., 2001. Morrison, S. and C. Winston, “An Econometric Analysis of the Demand for Intercity Passenger Transportation,” In Research in Transportation Economics, Vol. 2, T. Keller, Ed., JAI Press, Greenwich, Conn., 1985, pp. 213–237. Pitfield, D.E., “Predicting Air Transport Demand,” Environ- ment and Planning A, Vol. 25, 1993, pp. 459–466. Revision to Guidance on Review and Approval of Aviation Forecasts, Federal Aviation Administration, Washington, D.C., 2004. Sanders, N.R. and L.P. Ritzman, “Judgmental Adjustment of Statistical Forecasts,” In Principles of Forecasting, J.S. Armstrong, Ed., Springer Science+Business Media, Inc., New York, N.Y., 2001, pp. 405–416. Stock, J.H. and M.W. Watson, Introduction to Econometrics, 2nd ed., Pearson Education, Boston, Mass., 2006, “The Air Transport Industry Since 11 September 2001,” Inter- national Air Transport Association, Montreal, QC, Canada, 2006 [Online]. Available: http://www.iata.org [Dec. 11, 2006]. Transportation Research Circular E-C040: Aviation Demand Forecasting: A Survey of Methodologies, Transportation

31 Research Board, National Research Council, Washington, D.C., 2002., 49 pp. White, H. and G.M. McDonald, “Some Large Sample Tests for Non-Normality in the Linear Regression Model,” Journal of the American Statistical Association, Vol. 75, 1980, pp. 16–28. Yamanaka, S., J. Karlsson, and A. Odoni, “Aviation Infra- structure Taxes and Fees in the United States and the European Union,” Transportation Research Record 1951, Transportation Research Board, National Research Coun- cil, Washington, D.C., 2006, pp. 44–51. Yokum, T. and J.S. Armstrong, “Beyond Accuracy: Com- parison of Criteria Used to Select Forecasting Methods,” International Journal of Forecasting, Vol. 11, 1995, pp. 591–597.

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The TRB Airport Cooperative Research Program's ACRP Synthesis 2: Airport Aviation Activity Forecasting examines how airport forecasts are used and identifies common aviation metrics, aviation data sources, issues in data collection and preparation, and special data issues at nontowered airports. The report also explores available forecasting methods, including the primary statistical methods; market share analysis; econometric modeling; and time series modeling. In addition the report reviews forecast uncertainty, accuracy, issues of optimism bias, and options for resolving differences when multiple forecast are available.

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