With various governments encouraging people to drive less, economists have wondered if such goals can have the side effect of harming the economy. In most cases, the answer is no, OTREC researcher B. Starr McMullen concluded in a research report.

  • Click here to read more about the research and to download the report.

It’s more than an academic question: driving and the economy do tend to rise and fall together. McMullen, a transportation economics professor at Oregon State University, examined the relationship between the two by looking at which happens first—a change in driving or a change in economic activity.

In general, economic growth leads to more driving, not the other way around, McMullen said. That’s particularly true for metropolitan areas, the very places most likely to pursue policies that reduce driving.

“The more economic activity you have, the more VMT [vehicle miles traveled] you’re going to have,” McMullen said.

On the other hand, if there are policies to reduce VMT and driving decreases, “you’re not going to have the economy fall apart," as some have suggested.

If a state sets a goal to reduce VMT or transportation...

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As metropolitan area governments and others promote density-promoting “smart growth” policies, finer analysis is needed to quantify the impact of such policies on households' transportation and housing costs. Existing research suggests that households in urban areas trade-off between housing costs and transportation costs, but does not explore how policies to increase urban densities might explicitly impact this balance. Furthermore, the research does not adequately distinguish between the effect of urban area density and the effects of other factors associated with urban area density (e.g metropolitan area size and household incomes) on housing costs. This research uses the 2000 Census Public Use Micro Sample (PUMS) person and household data from 23 of the nation's most densely populated states to identify the impact of increased population density on three housing cost measures: household rents, housing unit values, and monthly mortgage payments. Log linear models were estimated for each housing cost measure using least-squares regression. Dependent variables included household, housing unit, and geographic area characteristics, including population density. The models were found to be very similar to one another in terms of the statistical significance...

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Edged Out: Location Efficient Housing and Low Income Households in the Portland Region

Transportation costs are typically a household’s second largest expense after housing. Low income households are especially burdened by transportation costs, with low income households spending up to two times as much of their income on transportation than higher income households (Litman, 2013).

Thus, access to...

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The Myth of Oregon's "Freight Dependent" Economy

Although it is widely claimed that Oregon's economy is dependent on freight movement, economic activity in Oregon has decoupled from physical goods movement. Truck traffic per unit of gross state product has fallen, and even the loss of regular container service to Portland has had no measurable effect on the region's economy.

Oregon's economy has shifted away from freight intensive industries and now depends on knowledge...

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PRESENTATION ARCHIVE

OVERVIEW

Transportation and land use planning, as a field, is shifting away from segregated uses connected by highways and streets to more compact, mixed-use developments connected by high-quality transit. This new paradigm has brought special attention to transit-oriented developments (TOD), which are sometimes touted as being among the most affordable, efficient places to live. But how affordable are they, and who has the power to effect change? This study examines housing costs for households living in TODs.

KEY LEARNING OUTCOMES

  • Learn how many TODs there are currently in the U.S. and what methodology was used to identify them.
  • Learn what share of housing in TODs is affordable, what are the relative shares of designated versus naturally occurring affordable units and whether the level of affordability is the same for families of different sizes.
  • Learn ...
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Smart Cities: Improving the Roadside Environment with Distributed Sensor Systems

The City of Portland is exploring how distributed “Internet of Things” (IoT) sensor systems can be used to improve the available data that is usable by city engineers, planners, and the public to help inform transportation operations, enable assessments of public health and equity, advance Portland’s Climate Action Plan goals, and...

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Webinar: Economic Impacts from Bicycle and Pedestrian Street Improvements

As many cities are investing in street improvements to provide better biking and walking experiences, the economic value and impacts of these active transportation facilities remain areas where many practitioners, planners and policy makers are seeking more conclusive evidence. With various modes competing for scarce resources, planners and transportation agencies often...

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WEBINAR SLIDES
Missed the presentation or want to look back at the slides? View the slides here.

WEBINAR VIDEO

Webinar: The Effects of Demand-Responsive Parking on Transit Usage and Congestion

WEBINAR SUMMARY
Parking is a serious issue in many urban areas, especially those experiencing rapid population growth. To address this problem, some cities have implemented demand-responsive pricing...

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