nach oben

Transportation

Erschienen in:

01.01.2008

The impact of high-speed technology on railway demand

verfasst von: Antonio Couto, Daniel J. Graham

Erschienen in: Transportation | Ausgabe 1/2008

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.

Vorheriger Artikel Estimation of the determinants of bicycle mode share for the journey to work using census data

Nächster Artikel Assessing asymmetric response effect of behavioral intention to service quality in an integrated psychological decision-making process model of intercity bus passengers: a case of Taiwan

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

Surveys of transport demand elasticities are provided by Oum and Yong (1992) and Goodwin (1992).

The cross-section data is unbalanced with yearly observations covering the whole period for some companies but other companies with reduced number of observations, mainly those from the Eastern countries.

Constant price data for the sample have been calculated using the World Bank country price deflators and the OECD country PPPs.

The traditional application of the perpetual inventory method requires the direct estimation of depreciation from which the net capital stock is obtained indirectly. The alternative approach, suggested in OECD-Statistics (2001), which was used in this study, is to use the age price profiles to directly estimate the net capital stock from which depreciation is obtained indirectly. This alternative method has the advantage of all stock data being necessarily consistent with each other because the age-efficiency profiles (used to estimate the productive capital stock) determine the age–price profiles (used to estimate the net capital stock and depreciation).

The number of aircraft departures includes inter-continental departures. The International Civil Aviation Organization (ICAO) does allows us to distinguish between domestic and continental departures but not inter-continental. A measure of domestic departures would be unlike to improve the accuracy of our proxy variable.

To compute 2SLS we use the following set of instrumental variables: all exogenous variables specified in the demand equation (except LTKMP), population country density and productive transport infrastructure capital stock.

Although there is a serious evidence of first order autocorrelation, with Durbin–Watson statistics of 0.56 (which renders the 2SLS inefficient, though the parameter estimates themselves remain unbiased), we did not proceed to correct for this given the high level of precision with which the coefficients were estimated.

The large differences between Western and Eastern railways suggest that an Eastern Europe dummy variable could be useful in this context. However, in practice we find that this additional dummy variable does not substantially improve the model fit and is in fact found to be statistically insignificant. The main difference in results obtained with the inclusion of this dummy was in the GDP coefficient which decreased to a value of 0.62.

The social characteristic attributes used were: AGL, DENSITY, AREA, SNOW and SURVEY. The economic capacity attributes used were: GDP per capita, productive transport equipment capital stock and productive transport infrastructure capital stock.

Brinkhoff, T.: The principal agglomerations of the world (www.citypopulation.de) (2002)

Button, K.J.: Demand for transport. In: Transport economics. Edward Elgar Publishing Company, Cambridge (1993)

ECIS: The state of European infrastructure, European Centre for Infrastructure Studies (1996)

ECMT: Trends in transport sector (1970–2003). Paris, European Conference of Ministers of Transport (2005)

ECMT/OECD: Evolution des transports (1970–1994). Paris, European Conference of Ministers of Transport (1996)

ESRI: ArcAtlas: Our Earth–snow cover (www.nationalgeographic.com) (2002)

FitzRoy, F., Smith, I.: The demand for rail transport in European countries. Transp. Policy 2(3), 153–158 (1995)CrossRef

FitzRoy, F., Smith, I. Passenger rail demand in 14 Western European countries: a comparative time series study. Int. J. Transp. Econ. XXV(3), 299–312 (1998)

Fowkes, T., Nash, C.: The aggregate approach. In: Analysing demand for rail travel. Institute for Transport Studies, Avebury (1991)

Goodwin, P.B.: A review of new demand elasticities with special reference to short and long run effects of price changes. J. Transp. Econ. Policy 26(2), 155–169 (1992)

IEA: Energy prices and taxes. International Energy Agency (http://www.iea.org) (2003)

Jane’s World Railways: Railway Systems, 16th edn. In: Abbott, J. (ed.) Surrey (1995)

Jones, I.S., Nichols, A.J.: The demand for inter-city rail travel in the United Kingdom. J. Transp. Econ. Policy 17(2), 133–153 (1983)

Kennedy, P.: Interpreting dummy variables. Rev. Econ. Stat. 68(1), 174–175 (1986)CrossRef

Maps.com: World Elevation (www.maps.com) (1999)

McGeehan, H.: Forecasting the demand for inter-urban railway travel in the Republic of Ireland. J. Transp. Econ. Policy 18(3), 275–291 (1984)

OECD-Statistics: Measuring capital—OECD manual: measurement of capital stocks, consumption of fixed capital and capital services (http://www.SourceOECD.org), pp. 1–132 (2001)

Oum, T.H.: Alternative demand models and their elasticity estimates. J. Transp. Econ. Policy 23, 163–187 (1989)

Oum, T.H., W.G.W. II, Yong, J.: Concepts of price elasticities of transport demand and recent empirical estimates—an interpretative survey. J. Transp. Econ. Policy 26(2), 139–154 (1992)

Owen, A.D., Phillips G.D.A.: The characteristics of railway passenger demand: an econometric investigation. J. Transp. Econ. Policy 21(3), 231–251 (1987)

Preston, J.: Demand forecasting foe new local rail stations and services. J. Transp. Econ. Policy 25(2), 183–202 (1991)

Queralt, G.B.: Intermodal competition on inter-urban rail. Int. J. Transp. Econ. XXII(2), 181–198 (1995)

Suits, D.B.: Dummy variables: mechanics v. interpretation. Rev. Econ. Stat. 66(1), 177–180 (1984)CrossRef

Uden, M.v.: The European railway stock lists, The European Railway Server (http://mercurio.iet.unipi.it) (2001)

Wardman, M.: Forecasting the impact of service quality changes on the demand for Inter-urban rail travel J. Transp. Econ. Policy 28(3), 287–306 (1994)

Wardman, M.: Demand for rail travel and the effects of external factors. Transp. Res. Part E 42, 129–148 (2006)CrossRef

WorldBank: World Development Indicators (http://www.worldbank.org/data/) (2002)

Ying, J.S.: On calculating cost elasticities. Logist. Transp. Rev. 28(3), 231–235 (1992)

Titel: The impact of high-speed technology on railway demand
verfasst von: Antonio Couto
Daniel J. Graham
Publikationsdatum: 01.01.2008
Verlag: Springer US
Erschienen in: Transportation / Ausgabe 1/2008
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI: https://doi.org/10.1007/s11116-007-9138-4

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 1/2008

Estimation of the determinants of bicycle mode share for the journey to work using census data

Assessing asymmetric response effect of behavioral intention to service quality in an integrated psychological decision-making process model of intercity bus passengers: a case of Taiwan

Children’s mode choice for the school trip: the role of distance and school location in walking to school

Urban form, travel time, and cost relationships with tour complexity and mode choice

Correlations between industrial demands (direct and total) for communications and transportation in the U.S. economy 1947–1997

Defining and understanding trip chaining behaviour

Premium Partner