Published cost estimates of impaired-driving crashes do not describe their effects on the economy. For example, when an injured person buys domestic medical care rather than an imported South African diamond or a television set produced in China that affects the domestic economy. The published cost estimates can be compared to the Gross Domestic Product (GDP) or some other measure of economic activity. However, computing the effects of crashes on the economy requires tracing the waves of expenditure shifts that result from injuries. It also requires carefully accounting for spending directed at impaired-driving enforcement, adjudication, and sanctioning, costs that surprisingly have never been estimated in the United States. A 20% rise or fall in impaired-driving crash rates doubtless would affect national economic output, gross domestic product (GDP), national income, and employment. This study is a first attempt to measure these effects. To do so, we will use input-output model software developed by Rutgers University. The national input-output model underlying this software has 517 sectors. Its national input-output accounts are from the 2005 annual accounts produced by the U.S. Bureau of Economic Analysis and extra detail in the retail trade, agriculture, water transportation, and household consumption sectors. The goals of this study are to estimate the drag impaired driving currently places on the economy and to simulate how much worse the economy would have fared if impaired driving had not been reduced. To achieve these goals we will: 1 - Estimate the monetary costs of impaired-driving crashes in 2008 to employers, employees, and government in the United States. The costs to employers will be detailed by industry. Costs will include medical costs, productivity (work) losses, property damage, and other resource costs. To estimate these costs we will follow methods used in our previous crash cost studies. We also will estimate impaired driving cost per drink by driver demographics. 2 - Estimate the costs of nationwide impaired-driving prevention, enforcement, adjudication, and sanctioning efforts during 2008. 3 - Introduce all the costs and benefits associated with the reduction in impaired-driving crashes into an input-output model of the United States economy to assess the net effects of impaired-driving crashes on national economic output, GDP, national income, and employment. To estimate the economic effects of reducing the impaired-driving crash rate, we will run input-output models on the current impaired-driving crash rates and prevention, enforcement, adjudication, and sanctioning costs and on a range of higher and lower rates. Keeping everything else constant, these runs will let us isolate the effects of rate changes on the economy.

Public Health Relevance

This project will provide a new perspective on the economic impact of alcohol impaired-driving crashes by looking at their effect on the economy as a whole. It will provide the first estimates of impaired driving costs per drink by drinker age group and gender and the first national estimate of law enforcement and sanctioning costs related to impaired driving.

National Institute of Health (NIH)
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Exploratory/Developmental Grants (R21)
Project #
Application #
Study Section
Health Services Research Review Subcommittee (AA)
Program Officer
Bloss, Gregory
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Pacific Institute for Research and Evaluation
United States
Zip Code
Zaloshnja, Eduard; Miller, Ted R; Lawrence, Bruce A (2016) Economics of alcohol-involved traffic crashes in the USA: an input-output analysis. Inj Prev 22:19-24
Zaloshnja, Eduard; Miller, Ted R; Blincoe, Lawrence J (2013) Costs of alcohol-involved crashes, United States, 2010. Ann Adv Automot Med 57:3-12
Miller, Ted R; Gibson, Rekaya; Zaloshnja, Eduard et al. (2012) Underreporting of driver alcohol involvement in United States police and hospital records: capture-recapture estimates. Ann Adv Automot Med 56:87-96