Economic Forces on Motor Carrier Safety: Impact and Strategies

1. The Effects of Economic Forces on Motor Carrier Safety Motor Carrier Safety Advisory Committee Federal Motor Carrier Safety Administration December 7, 2009 Michael H. Belzer, Ph.D. Department of Economics Wayne State University - Detroit

2. Competition is a key latent safety factor • Freight and passenger transport is a business activity • Cannot abstract fatigue management from work and business process • Focus on industrial organization rather than on technology • Focusing on technology and engineering ignores economic forces — and competition — that drive the work process • Competitors will do whatever they must to make a profit • Without regulatory limits • Shippers will make carriers do whatever it takes to be lowest cost providers • Carriers will make operators do whatever it takes to be lowest cost providers • With regulatory limits • Carriers can compete on safety and service • Safety management can become a strategic advantage • Risk-shifting and subcontracting to least powerful people pushes competition to the bottom of the food chain

3. Features of This Labor Market • Widespread subcontracting and as many as 500,000 carriers • Perhaps 300,000 owner-drivers (no accurate measures exist) • 75% are “lease-operators” (owner-drivers leased to motor carriers) • 25% are owner-operators (operating on their own authority) • Owner-operators are the most competitive drivers • Net $21,267/year on average, total pay and profit • Most have no health insurance and none have pensions • Common law treats all of them as independent contractors • They may not organize, unlike in Canada or Australia • Marginal cost pricing in transportation leads to cobweb (“cutthroat”) pricing and destructive competition • Teamster drivers earn average of about $50,000/year, mostly in LTL • Non-union drivers average about $36,000/year, mostly in TL

4. Three Studies Show How Pay Drives Safety • Using driver level data from J.B. Hunt, we determined the probability of driver crashes using 11,540 drivers and 93,000 driver-month observations • Using carrier level data from the National Survey of Driver Wages, we determined the extent to which compensation factors predict carrier crash rates • Using the UMTIP random survey of over-the-road drivers, we determined that driver pay predicts safety outcomes

5. Backward-bending Labor Supply Curve “Safety Pay Rate” • Mean rate: 36¢/mile • Below mean, drivers work more hours • Above the mean drivers work fewer hours • Creates “Safe Pay” function

6. Study 1: Effect of pay level in one firm The Problem • J. B. Hunt: The nation’s second largest truckload carrier in 1995 • Experiencing 96% driver turnover • Carrier had driver safety and reliability problems The Solution • Raised wages by 38% in one major move • Closed down training schools & hired experience • Focused on driver retention

7. Results:Higher Pay => Lower Crash Rates

8. At the mean, 10% higher driver pay rate resulted in40% lower crash probability At the mean, every one cent more in first observed pay led to 11.1% lower crash probability At the mean pay rate of 34 cents per mile, every 10% higher first-observed pay is associated with a34% lower crash probability A 10% pay increase is associated with a 6% lower crash probability At the mean, each year of tenure reduces crash by 16% Higher pay reduces turnover and increases age, experience, and unmeasured characteristics Hunt Pay Level Findings

9. Study 2:The Effect of CompensationLevel and Methodfor 102 Truckload Carriers Data Sources: National Survey of Driver WagesUMTIP Survey of Carriers SAFER System

10. Carrier Level Descriptive Statistics

11. Negative Binomial Regression Results Log-likelihood: -454.996 Restricted Log-likelihood: -4648.659 Likelihood Ratio Statistic: -8387.326 Significance Level: 0.000 Chi-Square Statistic 465.016 Significance Level: 0.000

13. Overall Compensation Effect • For every 10% more that they compensate drivers, carriers have a 9.2% lower crash rate • Significant components include • Mileage rate for drivers with 3 years experience 5.2% • Drivers’ anticipated annual pay raise 0.6% • Amount ofunpaid non-driving time per mile driven1.0% • Safety bonus 1.0% • Amount driver pays for family health insurance 0.8% • Amortized value of life insurance provided by carrier 0.6% • Total 9.2%

14. Study 3Effect of Pay Level on Safety:Individual Driver Level Data Sloan Foundation Trucking Industry ProgramUMTIP Truck Driver Survey • Based on 1,000 drivers surveyed in 1997-98 • Regression results based on 247 of these who are mileage employee drivers working in the for-hire trucking industry • These data were the basis for the backward-bending labor supply curve

15. Mean Compensation Variables

16. Workplace Variables

17. Probit Regression Estimates(significant variables only) N = 247 Log-likelihood: -85.706 Restricted Log-likelihood: 98.967 Chi-Square Statistic: 26.522 Significance Level: .380

18. Driver Survey:Effect of Pay on Safety At the mean pay rate, for every 10% more that drivers earn, their probability of reporting having had a crash last year is 25.0% lower Significant components include • For every 10% higher mileage rate that driver earns, the probability of a crash is 18.7% lower • For every 10% more paid days off, the probability of a crash is 6.3% lower

19. Human capital and incentivesmay not be independent • Labor markets work. • Better jobs go to those with best overall record. • For beginning drivers, hiring depends on factors other than commercial truck driving experience. • Subsequent performance on the job determines future opportunities. • Drivers are careful not to damage their record in order to maintain their labor market position. • Further incentives include defined-benefit pensions, which act as performance bonds.

20. Study 4Large Truck Crash Causation Study • Strength • Comprehensive study of about 1,000 truck crashes • Evaluation of data quality • Data quality on compensation too poor to analyze • Data quality on work pressure is excellent • Dependent Variable: Assigned Critical Reason • Logistic regression included all usable questions on the economics of the workplace • Results • Work pressure and fatigue are strong crash predictors

23. Fatigued, pressured, aggressive drivers likely to be involved in crashes they could have prevented • Assignment of the critical reason to the truck is associated positively with • WorkPressureTotal • AggressionCount • Fatigue • Assignment of the critical reason to the truck is associated negatively with • ClassYears • SafetyBonus • HoursDriving • MileagePay

24. Health and Safety Risk and Work Hours Dembe, Allard E., Rachel Delbos, J. Bianca Erickson, and Steven M. Banks. 2005. "The impact of overtime and long work hours on occupational injuries and illnesses: new evidence from the United States." Occupational and Environmental Medicine Vol. 62: pp 588–97.

25. Economic Pressure Drives Australian Policy • Chain of Responsibility • Everyone in the supply chain is responsible for taking responsible action in support of driver safety • Shippers cannot transfer responsibility to truckers by requiring unrealistic delivery schedules, overloading trucks, or pressuring drivers • Criminal sanctions for flagrant violators • Safe pay standards create minimum compensation • Establishes level playing field • Stop running rates into the ground

26. Future Research • Use the Longitudinal Employer Household Dynamics survey to measure unobserved human capital attributable to both workers and firms, and analyze the effects of these factors on safety • Use the LEHD to determine impact of work organization and competition on health and mortality • Develop a safety benchmarking program, like the Trucking Industry Benchmarking Program, to create a market for safety. • This innovative approach might be able at least to supplement some of the current rule-based framework and achieve greater safety more efficiently.

27. Further Resources Available by Request Michael H. Belzer, Ph.D. Department of Economics Wayne State University (313) 577-3345 michael.h.belzer@wayne.edu http://www.clas.wayne.edu/unit-faculty-detail.asp?FacultyID=595 http://myprofile.cos.com/mbelzer Benchmarking: http://www.ilir.umich.edu/TIBP/