Cover: Methods for Estimating the Volume and Energy Demand of Freight Transport.

Methods for Estimating the Volume and Energy Demand of Freight Transport.

by Dennis P. Tihansky

Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback77 pages $25.00 $20.00 20% Web Discount

Explores methods for discovering what determines freight volume (particularly that of rail, the carrier mode with the largest share of freight traffic) to permit prediction of freight demand and, ultimately, the demand for energy in the future. The methods are (1) graphical analysis, (2) ordinary least-squares regression analysis, (3) stepwise regression analysis, and (4) factor analysis; they are applied to a database of 1939-1968. GNP proved a good predictor of freight volume for all modes except rail. For the latter, coal production and durables manufacture are much better indicators. The volumes of motor vehicle, air, and, to a lesser degree, pipeline transport are particularly sensitive to prices. No single method proved entirely satisfactory; use of all four is probably necessary for making reliable predictions. (See also R-804.) 77 pp. Bibliog.

This report is part of the RAND Corporation Report series. The report was a product of the RAND Corporation from 1948 to 1993 that represented the principal publication documenting and transmitting RAND's major research findings and final research.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.