This paper provides key findings from NCHRP Study 2-21, which examined how urban traffic congestion imposes economic costs within metropolitan areas. Specifically, the study applied data from Chicago and Philadelphia to examine how various producers of economic goods and services are sensitive to congestion, through its impacts on business costs, productivity and output levels. The data analysis showed that sensitivity to traffic congestion varies by industry sector, and is attributable to differences in each industry sector's mix of required inputs and hence its reliance on access to skilled labor, access to specialized inputs and access to a large, transportation-based market area. Statistical analysis models were applied with the local data to demonstrate how congestion effectively shrinks business market areas and reduces the "agglomeration economies" of businesses operating in large urban areas, thus raising production costs. Overall, this research illustrates how it is possible to estimate the economic implications of congestion, an approach that may in the future be applied for benefit-cost analysis of urban congestion reduction strategies or for development of congestion pricing strategies. The analysis also shows how congestion reduction strategies can induce additional traffic as a result of economic benefits. OVERVIEWWhile it is clear that increasing traffic congestion does impose costs upon travelers and affect broader business operations, it has been difficult to develop and apply empirical measures of the extent of those economic costs. This paper describes a new modeling approach for analyzing how urban traffic congestion affects businesses and metropolitan-wide economic activity, based on results of NCHRP project 2-21. The paper is organized into five parts: (a) background on the nature of the analysis problem, (b) general approach for analyzing congestion costs, (c) calibration of statistical analysis models, (d) application of scenarios to assess the nature of congestion impacts, and (e) conclusions. BACKGROUND Defining Congestion.Traffic congestion is defined as a condition of traffic delay (i.e., when traffic flow is slowed below reasonable speeds) because the number of vehicles trying to use a road exceeds the design capacity of the traffic network to handle it. Traffic congestion is widely viewed as a growing problem in many urban areas because the overall volume of vehicular traffic in many areas (as reflected by aggregate measures of vehicle-miles or vehicle-kilometers of travel) continues to grow faster than the overall capacity of the transportation system. The resulting traffic slowdowns can have a wide range of negative impacts on people and on the business economy, including impacts on air quality (due to additional vehicle emissions), quality of life (due to personal time delays), and business activity (due to the additional costs and reduced service areas for workforce, supplier and customer markets). This study focuses specifically on the latter type of impact --how roadway traffic...

O10, O18, R15, R40,

Past research has shown that transportation system improvements can affect economic growth and productivity by changing access to markets and connectivity to intermodal terminals. However, most past research has adopted singular measures of market access and business productivity. This study demonstrates how various transportation projects can have larger or smaller impacts on business concentration and productivity by affecting different aspects of market access in areas with different business mixes. The study demonstrates these relationships through a two-step process. First, it defines seven types of access and connectivity measures, including access to labor markets, truck delivery markets, and intermodal terminals. The process then develops econometric models of the relationship between access and connectivity characteristics of local areas and relative levels of business productivity, job concentration, and export base. These relationships are estimated with simultaneous, nonlinear equations that allow access threshold effects to be recognized and for different relationships to apply for 54 industry sectors. The results confirm that different types of access are relevant to different industry sectors. As a consequence, the productivity and agglomeration of a given industry in a given area can be related to more than one dimension of accessibility. These results can have important implications for estimating the wider economic benefits of transportation investment and suggest the need to consider both industry detail and forms of accessibility in order to calculate accurately the relative impact of specific project proposals.

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