Office of Planning, Environment, & Realty (HEP)
Planning · Environment · Real Estate
Economic development impacts may be measured through job creation, total or per-capita personal income, business growth and attraction, business productivity, or other means. Transportation investments can provide economic development benefits by reducing the cost of transportation for businesses and by expanding the accessibility of firms to suppliers, labor, and consumer markets. Transportation investments can also induce businesses to locate in areas served by the investment. At the scale regional or national scale, productivity improvements resulting from transportation improvements can result in overall economic growth.
The primary determinants of economic benefits include:
The accessibility benefits of the transportation improvement. Accessibility can be measured through the number of suppliers, buyers, workers, etc., that can be reached within a given travel time or cost.
Safety improvements, which can also reduce travel-related costs to people and businesses and result in corresponding positive economic impacts.
Expenditures on transportation, including capital, operating, and maintenance costs. This category includes consumer expenditures as well as expenditures by the provider of the transportation facility or service. In the short term, construction and operation expenditures may provide a boost to the local economy, especially if project funding flows from outside the region. Long-term economic benefits, however, result primarily from improvements in transportation efficiency rather from than the construction and operation of the project itself.
When measuring economic impacts, it is important to distinguish growth impacts (a net benefit to the economy) from redistribution impacts (where activity is shifted from one location to another). Construction of a new highway, for example, may cause retail activities to locate at the highway's interchanges. This new development may not reflect an increase in total economic activity, however, but rather a shift in the location of the retail establishments following changes in traffic patterns.
Transportation, economic development, and land use form a three-way relationship since land use is driven by economic activity. Measuring or forecasting the impacts of alternative land use policies and development scenarios on economic activity, however, is an issue that has received relatively little attention. Development patterns may have economic implications through their impacts on transportation accessibility. At the same time, policies to channel the location of development to certain areas will have implications for the location and cost of various economic activities.
The regional economic benefits to improvements in a major freight corridor are investigated. User benefits to both truck and business travel are quantified, and a regional economic model is used to translate these benefits into economic measures.
Statistical methods such as multiple regression analysis are first used on time series and cross-sectional data to show the impact of investment on highways and fixed-guideway transit lines on regional job creation, income, and property values. The "elasticities" or "impact factors" found from those regressions are then applied to estimate the expected future impact of highways and transit investments on growth in those regions.
A study for the proposed I-73 in Virginia (Gillespie, 1995) forecast changes in total economic activity based on highway capital expenditures. Coefficients relating investment to economic activity were taken from national studies relating economic activity to highway capital stock. The analysis was at a broad level that did not distinguish how the economic growth would be affected by differences in the highway location and level of use.
Regression models have been applied in a number of studies to estimate the property value impacts of urban transit systems or highways. These models can be used to infer impacts of future transportation investments of a similar nature. Weinberger (2000) describes a study in the San Jose metropolitan area of California in which regression models were developed for an existing light rail system to address the potential property value impacts of planned extensions.
Input-Output (I-O) models contain information on inter-industry relationships, including "multipliers" that are used to forecast impacts as the dollars spent on a transportation investment ripple through the economy. I-O models are well suited for measuring the impacts of expenditures for the construction and operation of transportation facilities. They can also be used with exogenous inputs to calculate how changes in accessibility and transportation costs induce changes in levels of economic activity. For example, if a highway's impact on tourism can be translated into expenditures per new tourist, these expenditures can be fed through an I-O model to measure impacts on the regional economy.
The following examples illustrate the application of I-O models to transportation investments:
Maryland DOT performed a study of the statewide economic growth impacts of statewide highway programs (RESI, 1998). Researchers first applied a statewide I-O model to calculate the total economic activity supported by highway spending and subsequent purchases of labor, goods, and services. Using the results from the I-O modeling, the study then assessed how the state's economy would differ with and without the highway investment. The Maryland study also employed an econometric model to account for changes in business operating costs over time, and industry "cost functions" to capture business productivity growth attributable to highway investment. Similar studies have been done for Texas and Kansas.
Batey, Madden, and Scholefield (1992) utilize an input-output model to assess the regional impacts of an airport expansion in the United Kingdom. Economic inputs include expenditures on construction and operation, income from employment, local expenditures from additional passengers, and relocation of airline headquarters.
Macroeconomic simulation models are integrated modeling systems that include both an I-O model and a production function. These model components are integrated, and allow for the researcher to calculate how changes in policy decisions will impact economic conditions. Unlike I-O models which are static and allow only a one-time snapshot of the impacts of a transportation investment, simulation models allow the researcher to track the regional economic impacts of an investment over time. Some models can also estimate how changes in business operating costs and household living costs affect regional business expansion and population growth.
The REMI Model, developed by Regional Economic Models, Inc., is a well-known simulation model that has been applied to a number of regional highway and transit investment scenarios. User benefits from each scenario, including time, operating cost, and accident cost savings, are entered as cost savings or productivity improvements to businesses. Construction and operating costs are entered as expenditures by business category. Specific applications include the evaluation of freight projects in Portland, Oregon (see case study) and Columbus, Ohio; a comparison of regional highway versus transit investment plans in New York and Los Angeles; and evaluations of transit investments or disinvestments in Chicago, Philadelphia, and Rochester, NY; and evaluation of intercity highway corridor improvements in Wisconsin, Indiana, and Maine
Some land use models contain economic relationships, such as input-output matrices, as part of their underlying foundation. These models are capable of measuring the three-way relationship among transportation, land use, and the economy. At the heart of the MEPLAN model, for example, are input-output relationships that specify each sector's consumption from other sectors as well as its consumption of land and generation of trips by type. These models are typically used to measure forecast the distribution of economic activity within a region. Compared to an economic simulation model such as REMI, they are much more limited in their economic detail, as their primary purpose is to forecast land use changes rather than overall regional economic effects.
Examples of applications include:
The land use models MEPLAN and TRANUS have been applied in a number of metropolitan areas in the U.S. and Europe (see Sacramento and SPARTACUS case studies). The MEPLAN model has been used to forecast impacts of local projects on urban areas (such as improvements to the A7/A68 motorway in southeast Scotland), and broader regional impacts of larger projects (such as the Channel Tunnel). The local urban applications have typically featured small area zones and very limited industry detail, while the larger regional applications have typically featured broader zones and a greater level of industry detail.
The METROSIM model is a custom model now being tested in New York metro area (Anas, 1999). It combines a market-oriented economic (labor market) model with a transportation and land use model. The model takes into account how transportation projects are affected by the locational pattern of demand for land uses, and also allows basic and service employment to respond to transportation changes through labor market and businesses location decisions.
The TELUS system was developed by the New Jersey Transportation Institute, Rutgers University, and the North New Jersey Transportation Planning Authority to help MPOs select projects for their TIPs (Transportation Improvement Plans). TELUS has three components: a) a data base with key information about projects; b) an I-O model for estimating jobs created and the income and tax impacts of projects; and c) a land use model for estimating property tax impacts. The research team used national inter-industry relationships as well as relationships developed from New Jersey bid sheets to develop impact factors and economic multipliers for the I-O model. Multipliers reflect the ratio of total/direct effects, and are expressed in terms of jobs (by industry), income, and GRP per million dollars of original investment.
Hagler Bailly (2000) contains a toolbox of software models for forecasting economic development impacts as well as user economic impacts (i.e., benefit-cost analysis). The toolbox also includes case studies of applications and a diagnostic tool to assist in choosing a model.
Cambridge Systematics (1998) includes a categorization, description, and case studies of a wide range of methods for forecasting the economic impacts of transportation projects. While the focus is on measuring the impacts of transit projects, the methods are generally applicable to highway and other transportation modes.
Transportation Research Record 1274 (1990) contains a number of articles resulting from a conference on identifying and measuring the impacts of transportation on economic development.
