A TIME SERIES ANALYSIS OF MONTHLY RIDERSHIP FOR AN URBAN RAIL RAPID TRANSIT LINE

This paper presents two time series regression models, one in linear form and the other in logarithmic form, to estimate the monthly ridership of a single urban rail rapid transit line. The model was calibrated for a time period of about six and a half years (from 1978-1984) based on ridership data provided by a transit authority, gasoline prices provided by a state energy department, and other data. The major findings from these models are: (1) seasonal variations of ridership are minus 6.26%, or minus 6.20% for the summer period, and 4.77%, or 4.62% for the October period; (2) ridership loss due to a station closure is 2.46% or 2.41%; and (3) elasticities of monthly ridership are minus 0.233 or minus 0.245 with respect to real fare, 0.113 or 0.112 with respect to real gasoline price, and 0.167 or 0.185 with respect to real bridge tolls for the competing automobile trips. Such route specific application results of this inexpensive approach provide significant implications for policymaking of individual programs in pricing, train operation, budgeting, system changes, etc, as they are in the case reported herein and would be in many other cities.

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• Corporate Authors:

  Elsevier Publishing Company, Incorporated

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• Authors:
  • Doi, M
  • Allen, W B
• Publication Date: 1986

Media Info

• Pagination: p. 257-269
• Serial:
  • Transportation (Netherlands)
  • Volume: 13
  • Issue Number: 3
  • Publisher: Martinus Nijhoff Publishers
  • ISSN: 0049-4488

Subject/Index Terms

• TRT Terms: Gasoline; Linear regression analysis; Logarithms; Mathematical models; Rapid transit; Regression analysis; Ridership; Routes; Time series analysis; Urban areas
• Old TRIS Terms: Route specific
• Subject Areas: Data and Information Technology; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 00462909
• Record Type: Publication
• Source Agency: British Railways
• Files: TRIS
• Created Date: Aug 28 2004 4:48AM