A multivariate cointegrating vector auto regressive model of freight transport demand: evidence from Indian railways

In this paper long run structural relationship for freight transport demand is derived for railways in India using annual time series data for 1960–1995. Some of the recent developments in multivariate dynamic econometric time series modelling have been employed such as estimation of long-run structural cointegrating relationship, short-run dynamics and measurement of the effects of shocks and their persistence during the evolution of dynamic freight transport demand system. The models are estimated using a cointegrating vector autoregressive (VAR) modelling framework, which allows for endogeneity of regressors. Results indicate high GDP elasticity and low price elasticity, with real freight rate, i.e. the price variable behaving exogenously with respect to the system. Any disequilibrium in the short-run is likely to be corrected in the long run via adjustments in freight transport demand and GDP. Further, the demand system seems to be stable in the long run and converges to equilibrium in a period of around 3 years after a typical system-wide shock.     

A Review of Pseudo Panel Data Approach in Estimating Short-run and Long-run Public Transport Demand Elasticities

Abstract

The distinctions between short-run and long-run public transport demand elasticities have been highlighted in the literature, but the identification of long-run travel demand has been constrained by existing research methodology and the unavailability of longitudinal travel survey data. The pseudo panel data approach using repeated cross-sectional data has been suggested as an alternative to conducting a longitudinal travel demand analysis when genuine panel data are not available. This paper comprehensively reviews the background and the current practices of pseudo panel data research, and introduces the challenges in applied research that need further investigation, particularly for public transport. A case study using the Sydney Household Travel Survey data is presented to demonstrate pseudo panel data construction and to identify the short-run and long-run public transport demand elasticities using a pseudo panel data approach. The research findings suggest that the public transport demand elasticity of price in Sydney is ?0.22 in the short run and ?0.29 in the long run.     

High-Speed Rail Operations on an Existing Network: An Assessment Model for China

High-speed rail operations have the potential to reduce the long-term decline in rail passenger travel demand for the medium to long distance inter-urban markets. Such decline has been evident through most of the industrialized countries where air and road transport tend to be the dominant modes. In China, the operations of long distance high-speed rail on fully dedicated track is not very easy to implement, due to the high proportion of passengers who travel between high-speed and conventional railways. An alternative approach would be to allow for mixed operations with trains of various speeds on the same track. This article puts forward a simulation model designed to allow an evaluation of the most efficient distance for high-speed rail operations under mixed train speed scenarios. The model takes into account the main operating parameters such as passenger volumes, train speeds, capital and maintenance costs, train operating costs and energy consumption. The distance of high-speed train running on conventional rail that will yield the most economic benefit can be estimated using the model. The article includes the results of using the model for a specific example. It is concluded that large-scale high-speed trains have the potential to be successfully operated on conventional rail networks.     

A survey of Hungarian transport policy

Abstract

In its introductory part this article discusses the principles of the transport policy approved in 1968, followed by the reasons behind the advances on this policy approved in 1978.

It then goes on to review the Hungarian transport pattern and organization, including the roles played by the railways, the road transport companies, the state‐owned enterprises as well as cooperatives, urban transport, shipping, air transport, pipelines, and private transport.

In discussing the division of labour (or market sharing) in transport it concludes that passenger transport is increasing slowly, while the proportion of private transport is continuing to rise. A moderate increase is expected in goods transport with a decline in the share of the railways and a rise in that of the other transport branches. This division of labour is being influenced by economic, not administrative, means.

The main target of the advanced transport policy is to shape a transport system which corresponds to socioeconomic requirements. This means that goods transport capacities must be put to more efficient use, which involves improving development, organizational and planning operations. In passenger transport priority must go to public transport while the proportion of private transport must be defined in keeping with demand and economic possibilities.

In the development of the infrastructure and investments, the need to improve energy use and protect the environment must be stressed.

The rest of the article presents the detailed reasoning behind the measures already taken and scheduled to be taken to achieve these main targets.     

Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway

We estimate the elasticities of fuel and travel demand with respect to fuel prices and income in the case of Norway. Furthermore, we derive the direct rebound effects that explain the degree to which a fuel price increase is “offset” in the form of greater fuel use and/or travel due to improvements in vehicle fuel efficiency. For this purpose, we use and compare two alternative econometric approaches: the error correction model (ECM) and the dynamic model. Our initial assumption is that one should not be indifferent with respect to the approach used to derive elasticities. The data used are for the period 1980–2011. Our results indicate the following: (1) the dynamic model fits the data better than the ECM model does; (2) the estimated elasticities of fuel demand with respect to price and income are −0.26 and 0.06 in the short run and −0.36 and 0.09 in the long run. For travel demand, the respective elasticities are −0.11 and 0.06 in the short run and −0.24 and 0.13 in the long run, implying inelastic demands for fuel and travel demand; and (3) rebound effects indicate that 0.26% and 0.06% of fuel savings as a result of fuel price increase will be offset in the form of more fuel use in the short run and in the long run, respectively, if fuel efficiency increases by 1%. Our policy recommendations are that policies should not be indifferent to the methods used to derive elasticities. We contend that it is crucial to seriously consider rebound effects in policy making because basic elasticity estimates exaggerate the impact of fuel price increases.     

Environmental impacts of transformative land use and transport developments in the Greater Beijing Region: Insights from a new dynamic spatial equilibrium model

This paper reports the insights into environmental impacts of the ongoing transformative land use and transport developments in Greater Beijing, from a new suite of dynamic land use, spatial equilibrium and strategic transport models that is calibrated for medium to long term land use and transport predictions. The model tests are focused on urban passenger travel demand and associated emissions within the municipality of Beijing, accounting for Beijing’s land use and transport interactions with Tianjin, Hebei and beyond. The findings suggests that background trends of urbanization, economic growth and income rises will continue to be very powerful drivers for urban passenger travel demand across all main modes of transport beyond 2030. In order to achieve the dual policy aims for a moderately affluent and equitable nation and reducing the absolute levels of urban transport emissions by 2030, road charging and careful micro-level coordination between land use, built form and public transport provision may need to be considered together for policy implementation in the near future.     

Environmental benefits from better freight transport management: freight traffic in a VAR model

Most macro empirical studies on the price elasticity in the freight transport sector focus on the demand for transport. However, most of the external costs from the freight transport sector are more closely linked with the traffic volumes. In the paper an explicit distinction between traffic and transport demand is made by regarding traffic as an input in the shippers’ production of transport services, while transport demand is derived from firms’ production of output. An empirical analysis based on aggregate time series is carried out in a VAR model, where the stationary long run relationships are estimated using the so-called ‘Johansen Procedure’. The estimated price elasticity with respect to traffic (−0.81) is considerably higher than the elasticity with respect to transport (−0.47).     

An exploration of the competitive relationship between intercity transport systems

A suitable model that enables the analysis of dynamic relationships between transport systems is important for managers to make real-time reaction strategies. This study proposes an autoregressive distributed lag modeling approach that can point a way to interpret the long- and short-term relationships between intercity transport systems. To test the applicability of the approach with regard to evaluating the dynamic competitive relationships between intercity transport systems, an empirical study sample is adopted in evaluating competition between high-speed rail (HSR) and intercity bus services. The results indicate that HSR has a long-run impact on intercity bus transport and the intercity bus transport market is positively affected by its previous operations and negatively influenced by the previous performance of HSR. However, in the short-run, the current period performance of HSR positively affects the intercity bus transport market.     

The long-run behaviour of transport performance in India: a cointegration approach

The long-run relationships between variables representing transport performance and other macro-economic variables in India are analysed in this paper using the concepts of cointegration and error correction. The results show that passenger-kilometres (PKM) in India are likely to increase faster than gross domestic product (GDP), and much faster than urbanisation. The tonne-kilometres (TKM) are highly correlated to industrial growth, and are likely to increase faster than the index of industrial production. Both the passenger and freight performances are relatively inelastic to price changes. The error correction model (ECM) shows that both passenger and tonne-kilometres adjust to their respective long-run equilibrium at a moderate rate, with about 35% of adjustment in PKM and 40% of adjustment in TKMs occurring in the first year.     

The systemic,long-run relation among gasoline demand,gasoline price,income, and vehicle ownership in OECD countries: Evidence from panel cointegration and causality modeling

This paper looks at relationships between gasoline consumption per capita, income, gasoline price, and car ownership for a panel of OECD countries. Estimated long-run and short-run income elasticities are smaller than typically found and gasoline consumption is Granger-caused by gasoline price, but not by car ownership or income. Car ownership is Granger-caused by income and at the margin by gasoline consumption, but not by gasoline price.     

Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area

This paper estimates fuel demand models for the Lisbon Metropolitan Area (AML) and uses the demand elasticities obtained to predict future levels of road transport CO₂ greenhouse gas emissions. Data for the municipalities constituting the AML and the period 1993–2010 are analysed using static and dynamic panel data models to measure the relative importance of fuel price, income, vehicle stock, the price of public transport, and the availability of urban and suburban rail networks on fuel demand. To the best of our knowledge, this is the first study in the Portuguese context to produce fuel demand elasticities for a specific metropolitan area, as opposed to the estimation of country-level aggregate elasticities. Our findings indicate that the elasticity of fuel demand with respect to fuel price ranges between −0.48 and −0.72 in the short run and between −1.19 and −1.82 in the long run. Income elasticities are found to range between 0.51 and 0.54 in the short run and between 1.26 and 1.37 in the long run. The elasticity of fuel demand with respect to vehicle stock (keeping population constant) is 0.57 in the short run and 1.43 in the long run. There is only weak evidence of a reduction in fuel demand as a result of a decrease in the price of public transport, and no effect of greater availability of rail networks. Based on the elasticities estimated, we predict road transport CO₂ emissions for the AML according to different macroeconomic scenarios. The results indicate that the emissions target is only achieved in the scenario of poor economic performance. In the presence of medium and strong economic growth, fuel prices would need to increase by about 7% and 11% per year respectively in order to meet the emissions target.     

Long-run relationship among transport demand,income, and gasoline price for the US

Energy used in transport is a particularly important focus for environment-development studies because it is increasing in both developed and developing countries and is largely carbon-intensive. This paper examines whether a systemic, mutually causal, cointegrated relationship exists among mobility demand, gasoline price, income, and vehicle ownership using US data from 1946 to 2006. We find that those variables co-evolve in a transport system; and thus, they cannot be easily disentangled in the short-run. However, estimating a long-run relationship for motor fuel use per capita was difficult because of the efficacy of the CAFE standards to influence fleet fuel economy. The analysis shows that the fuel standards program was effective in improving the fuel economy of the US vehicle fleet and in temporarily lessening the impact on fuel use of increased mobility demand. Among the policy implications are a role for efficiency standards, a limited impact for fuel tax, and the necessity of using a number of levers simultaneously to influence transport systems.     

The asymmetric effects of income and fuel price on air transport demand

Forecasts of passenger demand are an important parameter for aviation planners. Air transport demand models typically assume a perfectly reversible impact of the demand drivers. However, there are reasons to believe that the impacts of some of the demand drivers such as fuel price or income on air transport demand may not be perfectly reversible. Two types of imperfect reversibility, namely asymmetry and hysteresis, are possible. Asymmetry refers to the differences in the demand impacts of a rising price or income from that of a falling price or income. Hysteresis refers to the dependence of the impacts of changing price or income on previous history, especially on previous maximum price or income. We use US time series data and decompose each of fuel price and income into three component series to develop an econometric model for air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find statistical evidence of asymmetry and hysteresis – for both, prices and income – in air transport demand. Implications for policy and practice are then discussed.     

Equilibrium at a bottleneck when long-run and short-run scheduling preferences diverge

We consider the use of a Vickrey road bottleneck in the context of repetitive scheduling choices, distinguishing between long-run and short-run scheduling preferences. The preference structure reflects that there is a distinction between the (exogenous) ‘long-run preferred arrival time’, which would be relevant if consumers were unconstrained in the scheduling of their activities, and the ‘short-run preferred arrival time’, which is the result of an adaptation of travel routines in the face of constraints caused by, in particular, time-varying congestion levels. We characterize the unpriced equilibrium, the social optimum as well as second-best situations where the availability of the pricing instruments is restricted. All of them entail a dispersed distribution of short-run preferred arrival times. We obtain the intriguing results that the dispersion is lower in the social optimum than in the unpriced equilibrium, and that the application of first-best short-run tolls does not induce efficient long-run choices of travel routines.     

Behavioral monitoring of public transport users through a mobile communication system

There are various activities now taking place in ITS research and development in Japan. Advanced information and communication technologies have been applied to improve public transport systems, as well as automated highway systems. In the first part of this paper, we show three examples of public transport systems recently developed in ITS environment. These transport systems are operated in local cities and towns in Japan: the travel information system for tram users in Hiroshima, the demand responsive bus system in Nakamura and the co‐operative use of electric vehicle in Ebina. In the second part of the paper, we explain how we have monitored individual passenger on public transport using cellular phones for location positioning. Location positioning technology for mobile object is essential for the operation and management of ITS supported public transport systems. Furthermore, such accurate and detailed positioning data can be utilized for travel behaviour analysis in demand modeling. The mobile instrument and monitoring systems shown in this paper can be combined with any of the case studies of ITS application to public transport systems.     

The effect of the price of gasoline on the urban economy: From route choice to general equilibrium

RELU-TRAN2, a spatial computable general equilibrium (CGE) model of the Chicago MSA is used to understand how gasoline use, car-VMT, on-the-road fuel intensity, trips and location patterns, housing, labor and product markets respond to a gas price increase. We find a long-run elasticity of gasoline demand (with congestion endogenous) of ?0.081, keeping constant car prices and the TFI (technological fuel intensity) of car types but allowing consumers to choose from car types. 43% of this long run elasticity is from switching to transit; 15% from trip, car-type and location choice; 38% from price, wage and rent equilibration, and 4% from building stock changes. 79% of the long run elasticity is from changes in car-VMT (the extensive margin) and 21% from savings in gasoline per mile (the intensive margin); with 83% of this intensive margin from changes in congestion and 17% from the substitution in favor of lower TFI. An exogenous trend-line improvement of the TFI of the car-types available for choice raises the long-run response to a percent increase in the gas price from ?0.081 to ?0.251. Thus, only 1/3 of the long-run response to the gas price stems from consumer choices and 2/3 from progress in fuel intensity. From 2000 to 2007, real gas prices rose 53.7%, the average car fuel intensity improved 2.7% and car prices fell 20%. The model predicts that from these changes alone, keeping constant population, income, etc. aggregate gasoline use in this period would have fallen by 5.2%.     

Telecommunications and travel demand and supply: Aggregate structural equation models for the US

Disaggregate studies of the impacts of telecommunications applications (e.g. telecommuting) on travel have generally found a net substitution effect. However, such studies have all been short-term and small-scale, and there is reason to believe that when more indirect and longer-term effects are accounted for, complementarity is the likely outcome. At least two aggregate studies have focused on the relationships between telecommunications and travel from economic perspectives (consumer and industry). However, both use the monetary value of consumption or transactions rather than actual activity measures (e.g. miles, number of calls), and neither fully explains the direct and indirect causal relationships between the two. The purpose of this study is to develop a conceptual model in a comprehensive framework, considering causal relationships among travel, telecommunications, land use, economic activity, and socio-demographics, and to explore the aggregate relationships between telecommunications and travel, using structural equation modeling of national time series data spanning 1950–2000 in the US. In this paper we focus on number of telephone calls as the measure of telecommunications, and passenger vehicle–miles traveled as the measure of transportation. Future research will investigate additional measures of these two constructs. Our empirical results strongly support the hypothesis that telecommunications and travel are complementary. That is, as telecommunications demand increases, travel demand increases, and vice versa. These results offer a more realistic picture to policy makers and transportation planners than has been available till now, and suggest useful directions for them to develop transportation or telecommunications strategies designed to reduce traffic congestion, air pollution, and energy consumption.     

A hierarchical line planning approach for a large-scale high speed rail network: The China case

Planning a set of train lines in a large-scale high speed rail (HSR) network is typically influenced by issues of longer travel distance, high transport demand, track capacity constraints, and a non-periodic timetable. In this paper, we describe an integrated hierarchical approach to determine line plans by defining the stations and trains according to two classes. Based on a bi-level programming model, heuristics are developed for two consecutive stages corresponding to each classification. The approach determines day-period based train line frequencies as well as a combination of various stopping patterns for a mix of fast trunk line services between major stations and a variety of slower body lines that offer service to intermediate stations, so as to satisfy the predicted passenger transport demand. Efficiencies of the line plans described herein concern passenger travel times, train capacity occupancy, and the number of transfers. Moreover, our heuristics allow for combining many additional conflicting demand–supply factors to design a line plan with predominantly cost-oriented and/or customer-oriented objectives. A range of scenarios are developed to generate three line plans for a real-world example of the HSR network in China using a decision support system. The performance of potential train schedules is evaluated to further examine the feasibility of the obtained line plans through graphical timetables.     

Estimating the demand responses for different sizes of air passenger groups

This paper investigates the sensitivity of demand for air travel by singleton passengers, couples, and families. It examines how the demand for air travel by these groups is potentially different. In this study, a compound Poisson structure of the demand of different passenger groups is considered, and aggregate demand observations and maximum likelihood procedures are used to decompound the processes and estimate demand sensitivity of each group of customers to price, time, season, and the economic cycle. The methodology is applied to Canadian market data and the results indicate there are significant differences among the different groups of customers.     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.