Assessing Productivity Impacts of Transportation Investments

Weisbrod, Glen; Stein, Naomi; Williges, Christopher; Mackie, Peter; Laird, James; Johnson, D.; Simmonds, David; Ogard, Elizabeth; Gillen, David; Vickerman, Roger

doi:10.17226/22294

Cited by 9 publications

(11 citation statements)

References 22 publications

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“…As a result, one cannot be certain that the coefficients which were statistically derived to reflect their impacts adequately control for those correlations. This same issue was examined in a US guide to measurement of transport impacts on productivity, and the position that was taken in that report is that correlation does not necessarily translate into double counting (Weisbrod et al, 2014). But if research studies derive valuation or elasticity factors separately for each effect without controlling for other correlated effects, some impacts may be under-or overestimated.…”

Section: Measurement Issues: Additionality and Double Countingmentioning

confidence: 99%

Estimating wider economic impacts in transport project prioritisation using ex-post analysis

Weisbrod¹

2017

ITF Roundtable Reports

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Section: Measurement Issues: Additionality and Double Countingmentioning

confidence: 99%

Estimating wider economic impacts in transport project prioritisation using ex-post analysis

Weisbrod¹

2017

ITF Roundtable Reports

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“…Typically, SHRP 2 Project C11 tools have been used for corridorlevel analysis and have not accounted for the network effects in the broader regions that surround the investment locations. A recent report on the use of the SHRP 2 Project C11 tools in three case studies indicated that these analyses were all performed on a restricted, corridor-level scale, without the capture of the benefits of a full-scale travel demand model, unlike the proposed seven-level integrated framework (9). Thus the work presented here differed significantly from past research on multiple levels.…”

mentioning

confidence: 93%

Statewide Assessment of Broader Economic Benefits from Transportation Investment: Integration of Travel Demand Models and SHRP 2 Project C11 Tools in Maryland

Kastrouni

Shayanfar

Schonfeld

et al. 2015

Transportation Research Record

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Project selection and prioritization are of utmost importance to federal, state, and local agencies and should be performed cautiously on the basis of expected project costs and benefits. Informed resource allocation decisions with respect to project candidates not only maximize public investment benefits but create economic opportunities and ultimately improve quality of life. With the use of tools readily available to most state agencies (e.g., travel demand models), along with the open-source SHRP 2 Project C11 tools, planners and engineers can proceed with informed statewide assessments of investment projects that yield benefits in market accessibility, travel time reliability, and connectivity. In this study, a seven-level framework was proposed to integrate a travel demand model with the SHRP 2 Project C11 tools and to showcase its functionality with the Intercounty Connector (ICC) MD-200 in Maryland as a case study. After a customized version of the SHRP 2 tools was developed in which Maryland-specific values were used in lieu of the default SHRP 2 parameters, the results suggested that, in the year 2030, a total increase of approximately 1% in buyer–supplier market accessibility would be achieved in the counties that surrounded the ICC as a result of the new construction. Also, all three corridors parallel to the ICC, which served similar origin–destination pairs, would experience a decrease in recurring and incident delays attributable to the ICC. In dollar terms, the value of the total annual benefits from the ICC construction in the year 2030 would amount to approximately $200 million.

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“…For this reason, the amount of research assessing the links between regional economic output and investments in different types of infrastructure, including transportation, is significant. Moreover, in the literature focusing on evaluating transportation investments, efforts have been made to account for the impacts of transportation projects on firms' productivity as part of the decision-making processes [e.g., Weisbrod et al (5)].…”

mentioning

confidence: 99%

Investigating the Spatial Distribution of Manufacturing Employment

Chacon-Hurtado

Pyrialakou

Gkritza

2017

Transportation Research Record

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An extensive body of research examines the relationship between transportation and economic activity in a region; however, many of the studies ignore the possible spatial interdependencies between regions. As a result, these studies may over- or underestimate the role that transportation plays on the economic activity of a region. This paper contributes to the literature by exploring the relationship between the supply of transportation infrastructure and manufacturing employment concentration through a model that accounts for the spatial structure of the data at the zip code level. The modeling approach, which is demonstrated with a case study in Indiana, accounts for spillovers across areas by using a spatial autoregressive model with autoregressive disturbances. The results indicate that the high concentration of manufacturing employment in Indiana has been strongly associated with proximity to industrial parks, low commuting time, a higher percentages of firms with more than 100 employees, lower highway density, and proximity to intermodal facilities. The results of this study could benefit metropolitan or rural planning organizations and economic development groups that aim to design policies or plans to attract manufacturing activity to their regions.

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Assessing Productivity Impacts of Transportation Investments

Cited by 9 publications

References 22 publications

Estimating wider economic impacts in transport project prioritisation using ex-post analysis

Estimating wider economic impacts in transport project prioritisation using ex-post analysis

Statewide Assessment of Broader Economic Benefits from Transportation Investment: Integration of Travel Demand Models and SHRP 2 Project C11 Tools in Maryland

Investigating the Spatial Distribution of Manufacturing Employment

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