Demand responsive transport: towards the emergence of a new market segment

This paper focuses on recent British experience with telematics-based Demand Responsive Transport (DRT) services in rural areas. In recent years, the ability of DRT concepts to provide efficient, viable transport services has been greatly enhanced by the use of transport telematics as demonstrated in a variety of environments across Europe. The success of British local authorities in winning substantial funding under the Rural and Urban Bus Challenge programmes for the implementation of DRT has resulted in widespread interest in flexible forms of transport. It is thus timely to evaluate the impact of this substantial investment. Drawing on the experience of a number of UK schemes, the paper assesses the reasons for the new-found success of what is becoming a relatively well-accepted mode by concentrating on a variety of factors including: service characteristics (particularly route flexibility, flexibility of booking method and pre-booking regime), emerging markets and the overall contribution of DRT to increased social inclusion and intermodality. Impediments to the development of DRT services are highlighted. The paper also discusses current research into the next generation of DRT services and concludes by identifying some key issues for policy-makers concerned with the future implementation of DRT services.     

The evaluation of demand responsive transport services in Europe

Over the last decade Demand Responsive Transport (DRT) services have grown in popularity for several reasons including: the shortcomings of conventional regular bus and taxi services; shortcomings of special transport services; and new developments in community transport. Traditional dial-a-ride services have often been criticised because of their relatively high cost of provision, their lack of flexibility in route planning and their inability to manage high demand. The potential for overcoming these limitations may be realised through the introduction of telematics-based DRT and this has been widely demonstrated, for example, in recent research funded by the European Commission (e.g. the DGXIII-funded SAMPO and SAMPLUS projects). This paper provides an introduction to the concept of telematics-based DRT services and presents the results of the evaluation of a set of DRT technologies and operations at urban and rural sites across Europe. The paper offers discussion in terms of the key issues that influence the introduction of DRT services.     

International Evidence on the Stability of the Optimizing IS Equation*

We provide international evidence on the issue of whether the optimizing IS equation is more stable than a backward‐looking alternative. This evidence consists of estimates of IS equations on quarterly data for the UK and Australia, both for the full sample of the last 40 years and for the period following major monetary policy shifts in 1979–80. Results suggest the parameters in the optimizing IS equations are more empirically stable than those of the backward‐looking alternative. The use of dynamic general equilibrium modelling in empirical work does deliver material benefits, in the form of equations more suitable for policy analysis.     

A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’

This paper introduces a general procedure for decomposition of non-stationary time series into a permanent and transitory component allowing both components to be stochastic. The permanent component is shown to be a random walk with drift and the transitory or cyclical component is a stationary process with mean zero. The decomposition methodology, which depends only on past data and therefore is computable in ‘real time’, is applied to the problem of measuring and dating business ‘cycles’ in the portwar U.S. economy. We find that measured expansions and contractions are of roughly equivalent duration and that our dating of cyclical episodes tends to lead the traditional NBER dating and, to a lesser extent, the ‘growth cycle’ chronology of Zarnowitz and Boschan (1977).     

Modelling Deforestation and Land‐Use Change: Sparse Data Environments

Land‐use change in developing countries is of great interest to policy‐makers and researchers with diverse interests. Concerns about consequences of deforestation for global climate change and biodiversity have received the most publicity, but loss of wetlands, declining land productivity and watershed management are also problems facing developing countries. Analyses of these problems are especially constrained by lack of data. This article reviews modelling approaches for data‐constrained environments that involve discrete choice methods including neural nets and dynamic programming, and research results that link individual household survey data with satellite images using geographic positioning systems.