Methodology for Determining the Economic Development Impacts of Transit Projects

Chatman, Daniel G.; Noland, Robert B.; Tulach, Nicholas K; Grady, Bryan P.; Özbay, Kaan; Rognlien, L; Desautels, A; Alexander, Lauren P.; Graham, Daniel J.; Bilton, Peter; Deka, Deva; Voorhoeve, Niels; Klein, Nick; Berechman, Joseph

doi:10.17226/22765

Cited by 3 publications

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“…Therefore, this paper aims to address the measurement of the relationship between economic growth and highway infrastructure development at local levels in Turkey. One of the most important contributions of this paper is performing our research with the dynamic panel data methodology in the transportation economics literature, where the instrumental variables approach may not always be easy to apply in terms of finding appro-priate instruments for the solution (i.e., suffering from an over-identification problem; see (Chatman et al, 2012)). The dynamic panel data model allows researchers to use both the differenced dependent and independent variables as instruments.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Panel Data Approach for the Analysis of the Growth Impact of Highway Infrastructures on Economic Development

Kalan¹,

Gökaşar²

2020

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Turkey is a developing country where the transportation sector receives a considerable economic share. Roads are the pioneer mode of transportation in Turkey and the common opinion is that increasing highway networks lead to major changes in economic development. This paper focuses on the growth impact of highway infrastructure on economic development and recommends a dynamic panel data approach which is not common in the transportation economics literature. This model is applied to local regions that are located in the eastern and northern parts of Turkey to measure the effects of highway capital stocks on Gross Domestic Product (GDP) change between 2004 and 2016. The analysis reveals that the relationship between GDP and highway capital stock is positive, and statistically significant for local regions in Turkey. It is indicated that the findings of this paper can be a guide for policy and decision-makers and implemented into different regions and locations.

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Section: Introductionmentioning

confidence: 99%

A Dynamic Panel Data Approach for the Analysis of the Growth Impact of Highway Infrastructures on Economic Development

Kalan¹,

Gökaşar²

2020

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“…Various techniques and models can be used to measure the impact of rail transit systems on economic developments, such as cost-benefit analysis, transportation-land use models, economic forecasting models and input-output tables (Litman, 2010, Chatman et al, 2012, Hazledine et al, 2013, Litman, 2015b. Since the evaluation of the impact of the rail system on economic development lies beyond the scope of this research it is assumed that those areas that have potential to bring maximum possible economic growth to the served area have been identified prior to the evaluation process.…”

Section: Londonmentioning

confidence: 99%

GIS and genetic algorithm based integrated optimization for rail transit system planning

Ahmed

Nur²,

Ochieng

2020

Journal of Rail Transport Planning & Management

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The planning of a rail transit system is a complex process involving the determination of station locations and the rail line alignments connecting the stations. There are many requirements and constraints to be considered in the planning process, with complex correlations and interactions, necessitating the application of optimization models in order to realize optimal (i.e. reliable and cost-effective) rail transit systems. Although various optimization models have been developed to address the rail transit system planning problem, they focus mainly on the planning of a single rail line and are therefore, not appropriate in the context of a multi-line rail network. In addition, these models largely neglect the complex interactions between station locations and associated rail lines by treating them in separate optimization processes. This thesis addresses these limitations in the current models by developing an optimal planning method for multiple lines, taking into account the relevant influencing factors, in a single integrated process using a geographic information system (GIS) and a genetic algorithm (GA). The new method considers local factors and the multiple planning requirements that arise from passengers, operators and the community, to simultaneously optimize the locations of stations and the associated line network linking them. The new method consists of three main levels of analysis and decision-making. Level I identifies the requirements that must be accounted for in rail transit system planning. This involves the consideration of the passenger level of service, operator productivity and potential benefits for the community. The analysis and decision making process at level II translates these requirements into effective criteria that can be used to evaluate and compare alternative solutions. Level III formulates mathematical functions for these criteria, and incorporates them into a single planning platform within the context of an integrated optimization model to achieve a rail transit system that best fits the desired requirements identified at level I. This is undertaken in two main stages. Firstly, the development of a GIS based algorithm to screen the study area for a set of feasible station locations. Secondly, the use of a heuristic optimization algorithm, based on GA to identify an optimum set of station locations from the pool of feasible stations, and, together with the GIS system, to generate the line network connecting these stations. The optimization algorithm resolves the essential trade-off between an effective rail system that provides high service quality and benefits for both the passenger and the whole community, and an economically efficient system with acceptable capital and operational costs. Imperial College London vi Chro Ahmed The proposed integrated optimization model is applied to a real world case study of the City of Leicester in the UK. The results show that it can generate optimal station locations and the related line network alignment that satisfy the various stak...

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Firm Births, Access to Transit, and Agglomeration in Portland, Oregon, and Dallas, Texas

Chatman

Noland

Klein

2016

Transportation Research Record: Journal of the Transportation R

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The formation of new firms is one process by which economies grow and innovate. Public transportation services may facilitate the birth of new firms by both providing better access and causing local densification that leads to agglomeration economies. In this study firm births are investigated to determine how they are related to newly provided light rail transit service in two metropolitan areas in the United States. A geocoded time-series database of firm establishments in Dallas, Texas, and Portland, Oregon, from 1991 through 2008 is used. The data set allows the study of spatial patterns by industry and the analysis of the relationship of firm births to rail station proximity, accessibility, and local agglomeration while controlling for a number of potentially confounding factors. Positive, large, and statistically significant relationships are found in Portland between rail station proximity and firm births. The rail proximity results in Dallas are also generally positive, though not as large; this finding is consistent with the smaller accessibility value of rail in Dallas, as well as policies encouraging commercial development near rail in Portland. Rail proximity increases firm births across almost all industrial sectors in both of these metropolitan areas when controlling for the negative effects on firm births of local own-industry employment. Local block-level agglomeration and generalized accessibility are also highly significant but appear to work independently of rail access. These results imply that passenger rail service increases firm births near rail stations by expanding access to the labor market but not by increasing information spillovers or increasing face-to-face interactions.

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Methodology for Determining the Economic Development Impacts of Transit Projects

Cited by 3 publications

References 0 publications

A Dynamic Panel Data Approach for the Analysis of the Growth Impact of Highway Infrastructures on Economic Development

A Dynamic Panel Data Approach for the Analysis of the Growth Impact of Highway Infrastructures on Economic Development

GIS and genetic algorithm based integrated optimization for rail transit system planning

Firm Births, Access to Transit, and Agglomeration in Portland, Oregon, and Dallas, Texas

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