Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows

We introduce a regression-based gravity model for commodity flows between 35 regions in Austria. We incorporate information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We find that our approach produces improved model fit and higher likelihood values. The model accounts for spatial dependence in the origin-destination flows by introducing a spatial connectivity matrix that allows for three types of spatial dependence in the origins to destinations flows. We modify this origin-destination connectivity structure that was introduced by LeSage and Pace (2005) to include information regarding the presence or absence of a major highway/train corridor that passes through the regions. Empirical estimates indicate that the strongest spatial autoregressive effects arise when both origin and destination regions have neighboring regions located on the highway network. Our approach provides a formal spatial econometric methodology that can easily incorporate network connectivity information in spatial autoregressive models.Commodity flows, Spatial autoregression, Bayesian, Maximum likelihood, Spatial connectivity of origin-destination flows

A BI-LEVEL SCHEME FOR ASSESSING THE IMPACT OF AIR TRANSPORTATION ON LOCAL DEVELOPMENT

An approach to assess the impact of the creation or expansion of an air transport infrastructure over regional development is proposed in this paper. Effective long term planning of this costly investment requires performing an overall analysis of socio-economic consequences through long term forecasting, scenario generation and risk analysis. One of main aspects of this task is related with the estimation of future demand over the modified transportation network which attends the considered region. The proposed approach makes use of two complementary models: One model is devoted to demand forecasting taking into account the modified accessibility of the multimodal transportation network, the other one defines the global transport supply according to a profit maximization behavior for the involved transport system. The demand forecasting process is based on an entropy maximization approach with flexible origin-destination levels to determine the intensity and the distribution of new origin-destination vectors. A two level solution technique considering vehicle flows at the first level and the payload/passengers flows at the second level is introduced. The proposed solution scheme is composed of an iterative process between the current solution for demand forecasting and the supply optimization problem: the entropy maximizing distribution problem provides the origin-destination matrix given a cost/capacity structure, while the supply optimization problem provides this cost/capacity structure resulting from the accessibility level, given the updated origin-destination vectors. The proposed approach is illustrated in the case of a fast developing rural agro-industrial area in central Brazil, where the consequences of the installation of a medium size airport are assessed.

Changes in transport and non transport costs: local vs. global impacts in a spatial network

We develop a multi-country Dixit-Stiglitz trade model and analyze how industry location and welfare respond to changes in: (i) transport frictions (e.g., infrastructure, transportation technology); and (ii) non-transport frictions (e.g., tariffs, standards and regulations). We show that changes in non-transport frictions, which are usually origin-destination specific, do not allow for any clear prediction as to changes in industry location and welfare; whereas changes in transport frictions, which are usually not origin-destination specific, may allow for such predictions. In particular, we show that reductions in transport frictions occurring at links around which the spatial network is locally a tree are Pareto welfare improving.trade frictions; multi-country trade models; monopolistic competition; spatial networks; international integration

Interaction Data Sets In The UK: An Audit

Interaction or flow data involves counts of flows between origin and destination areas and can be extracted from a range of sources. The Centre for Interaction Data Estimation and Research (CIDER) maintains a web-based system (WICID) that allows academic researchers to access and extract migration and commuting flow data (the so-called Origin-Destination Statistics) from the last three censuses. However, there are many other sources of interaction data other than the decadal census, including national administrative or registration procedures and large scale social surveys. This paper contains an audit of interaction data sets in the UK, providing detailed description and exemplification in each case and outlining the advantages and shortcomings of the different types of data where appropriate. The Census Origin-Destination Statistics have been described elsewhere in detail and only a short synopsis is provided here together with review of the interaction data that can be derived from other census products. The primary aims of the audit are to identify those interaction data sets that exist that might complement the census origin-destination statistics currently contained in WICID and to assess their suitability and availability as potential data sets to be held in an expanded version of WICID. Tables or flow data sets are included for exemplification. The paper concludes with a series of recommendations as to which of these data sets should be incorporated into a new information system for interaction flows that complement the census data and also provide opportunities for new research projects

A Primal-Dual Algorithm for Link Dependent Origin Destination Matrix Estimation

Origin-Destination Matrix (ODM) estimation is a classical problem in transport engineering aiming to recover flows from every Origin to every Destination from measured traffic counts and a priori model information. In addition to traffic counts, the present contribution takes advantage of probe trajectories, whose capture is made possible by new measurement technologies. It extends the concept of ODM to that of Link dependent ODM (LODM), keeping the information about the flow distribution on links and containing inherently the ODM assignment. Further, an original formulation of LODM estimation, from traffic counts and probe trajectories is presented as an optimisation problem, where the functional to be minimized consists of five convex functions, each modelling a constraint or property of the transport problem: consistency with traffic counts, consistency with sampled probe trajectories, consistency with traffic conservation (Kirchhoff's law), similarity of flows having close origins and destinations, positivity of traffic flows. A primal-dual algorithm is devised to minimize the designed functional, as the corresponding objective functions are not necessarily differentiable. A case study, on a simulated network and traffic, validates the feasibility of the procedure and details its benefits for the estimation of an LODM matching real-network constraints and observations