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The purpose of this paper is to develop a method for predicting fluctuations in thetransportation sector using leading indicators. From twenty-five initial candidates, we selectseven leading indicators using various screening techniques and modern time series models.A composite leading index is constructed and found to perform well in predicting theirreference cycles. The leading index signals downturns in the transportation sector by 9months and upturns by 6 months, on average. The former predicted the latest recession intransportation 20 months ahead. We also confirm the predictive contents of the CLI inrelation to transportation growth cycles. These evaluation criteria ensure accurate forecastsof the general state of the transportation sector in a timely fashion.

Subject(s): Research and Development/Tech Change/Emerging Technologies

Research Methods/ Statistical Methods

Issue Date: 2005-03

Publication Type: Conference Paper/ Presentation

PURL Identifier: http://purl.umn.edu/208159

Total Pages: 18

Record appears in: Transportation Research Forum > 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005





Autor: Yao, Vincent W. ; Solboda, Brian

Fuente: http://ageconsearch.umn.edu/record/208159?ln=en







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