Title: A Time Series Analysis of Rail Demand in Great Britain
Abstract: The paper explores the characteristics of time-series data in order to help better understand how best to model the demand for rail travel. More specifically, the paper: (1) explores the relationship between rail demand and economic performance, considering the influence short and long term trends, and the existence of asymmetric effects (e.g. gains and losses); (2) examines the impact of long-term trends in economic, demographic and competition variables; (3) examines the impact of long-term trends in endogenous factors such as fares and service quality; (4) identifies and assess the influence of structural breaks on demand whether as a result of a single event or a process evolving over time; and (5) considers the constraints to passenger demand growth brought about by demand (market saturation) and supply (capacity restriction) side factors. The methodological approach includes the use of univariate time-series and multivariate econometric approaches as well as a new application of unobserved component models. Each model specification has advantages and disadvantages, but on balance the unobserved components model is the preferred approach as it allows for trend and seasonal components to evolve over time allowing for changes to omitted variables and changes to consumer tastes and preferences. The unobserved components approach is thought to generate more robust elasticity estimates but it also identifies an unexplained trend that will need to be accommodated in the production of forecasts. In addition to fares and economic performance, the models also included a range of other significant influences including: rail performance as measured by the Public Performance Measure (PPM), an index of the cost of motoring/price of fuel, an index of Bus & Coach fares and a series of dummy variables to account for accidents, strikes and regulatory interventions.
Publication Year: 2010
Publication Date: 2010-01-01
Language: en
Type: article
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Cited By Count: 4
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