1. Group 4 | Presentation on June 20, 2012 | 1 TERMPROJECT TERM PROJECT: Determinants of Fatal Car Accidents in the United States MBA 555: Managerial Economics Presentation on June 20, 2012 Group 4:Henning Andrees, Chelsey Hawes, Martin Kumke, Paula Monteiro, Charly von Wiedersperg

2. Group 4 | Presentation on June 20, 2012 | 2 TERMPROJECT Agenda 1.Introduction 2.Research History 3.Data and Variables 4.Econometric Model 5.Results 6.Policy Implications 7.Summary and Conclusion

3. Group 4 | Presentation on June 20, 2012 | 3 TERMPROJECT INTRODUCTION Car Fatalities Are Devastating to Society  Car crashes are the leading cause of death in ages 5–34 in the US  2.3 million adults treated in the ER as a result of crashes  $41 billion in medical and loss of labor costs  32,788 traffic fatalities in 2010  Causes: aggressive driving, alcohol, weather, equipment failure 1 death per 10,000 people per year Examining the determinants of fatal car accidents in the US STUDY OBJECTIVE

4. Group 4 | Presentation on June 20, 2012 | 4 TERMPROJECT RESEARCH HISTORY Many Models Have Been Developed over the Years  Loeb (1987) –Drinking beer, age, speed, vehicle inspection  O’Donnell et al. (1996): –Age, speed, alcohol, vehicle type, seating position  Fridstrom (1999): –Impact of multiple variables on severity of accidents  Ulfarsson et al. (2002): –Impact of gender and type of vehicle on car accident severity  Milton (2006): –Weather, traffic, road conditions, curves

5. Group 4 | Presentation on June 20, 2012 | 5 TERMPROJECT HYPOTHESES Testing Hypotheses in Four Different Categories H 1 The number of fatal car accidents is explained by … weather and climatic conditions. H 2 The number of fatal car accidents is explained by … the degree of drug and alcohol use. H 3 The number of fatal car accidents is explained by … demographic factors. H 4 The number of fatal car accidents is explained by … driving-related factors.

6. Group 4 | Presentation on June 20, 2012 | 6 TERMPROJECT DATA AND VARIABLES Diverse Variables Based on Hypothesis Categories 1: Weather and climate  Temperature (average)  Precipitation (annual)  Snowfall (annual)  Wind speed (average)  Time between sunrise and sunset 3: Demographic factor  Average age  Sex ratio (male/female)  Student population (percent)  Number of foreign born (percent)  Median income  Average family size  Population density 2: Drug and alcohol use  Beer consumption (per capita)  Cigarette use (percentage)  Prescription drugs sold (kg per capita) 4: Driving-related factors  Number of motor vehicles (per capita)  Driving age (full license)  Interstate miles (per vehicle)  Speed limit (mph)  Fine for speeding  Suspension for drunk driving  Police officers (per capita) Number of fatal car accidents per 100,000 inhabitants DEPENDENT INDEPENDENT

7. Group 4 | Presentation on June 20, 2012 | 7 TERMPROJECT  Narrow down the significant variables METHODOLOGY Multiple Steps to Create the Best Production Model Basic Assumption: Cobb-Douglas Production Function: Stepwise  Test for regression assumptions  Eliminate variables with multicollinearity OLS  No regression parameter for intercept No Intercept BEST MODEL: No intercept multiplicative model DATA:  Cross- sectional  50 states of the USA  Year: 2010  23 variables SOFTWARE:  WinORS

8. Group 4 | Presentation on June 20, 2012 | 8 TERMPROJECT ECONOMETRIC MODEL Cobb-Douglas Production Function VariableDescriptionParameter Estimate FAFatal Car Accidents per 100,000 PeopleDEPENDENT TAverage Annual Temperature1.309 CPercent Cigarette Use in Adults 18+0.296 AAverage Age0.699 FBNumber of Foreign Born in Percent–0.169 VNumber of Motor Vehicles per Person0.442 DDrive Age (Full License)–1.994 MInterstate Miles per 1,000 Vehicles0.250 ELaw Enforcement Employees per 1,000 People0.298

9. Group 4 | Presentation on June 20, 2012 | 9 TERMPROJECT RESULTS Is the Model Trustworthy? F-Value2,473.843 P-Value0.00001 R² (adjusted)99.753% EXPLANATORY POWER AUTOCORRELATION Does not exist in Ln model (No Durbin Watson) Average VIF 2.302 MULTICOLLINEARITY

10. Group 4 | Presentation on June 20, 2012 | 10 TERMPROJECT Average Annual Temperature0.00001 Cigarette Use in Adults 18+ (%)0.02066 Average Age0.02066 Number of Foreign Born (%)0.00379 Number of Motor Vehicles per Person0.00500 Driving Age (Full License)0.00011 Interstate Miles per Vehicle0.00011 Law Enforcement Employees per Person0.00001 RESULTS Is the Model Trustworthy? STATISTICAL SIGNIFICANCE P-Value

11. Group 4 | Presentation on June 20, 2012 | 11 TERMPROJECT RESULTS Is the Model Trustworthy? HOMOSKEDASTICITY White’s Test: 48.221 P-Value: 0.30597

12. Group 4 | Presentation on June 20, 2012 | 12 TERMPROJECT RESULTS Is the Model Trustworthy? NORMALITY Correl. For Normality:0.9935 Critical Value:0.9840

13. Group 4 | Presentation on June 20, 2012 | 13 TERMPROJECT RESULTS No Hypothesis Has Been Rejected H 1 The number of fatal car accidents is explained by … weather and climatic conditions. NOT REJECTED H 2 The number of fatal car accidents is explained by … the degree of drug and alcohol use. NOT REJECTED H 3 The number of fatal car accidents is explained by … demographic factors. NOT REJECTED H 4 The number of fatal car accidents is explained by … driving-related factors. NOT REJECTED

14. Group 4 | Presentation on June 20, 2012 | 14 TERMPROJECT 1 0 -2 CONCLUSIONS Elasticities Explain Impact on Fatal Car Accidents ELASTICITY Interstate Miles per Vehicle Average Annual Temperature Average Age Number of Foreign Born # of Motor Vehicles per Person Cigarette Use in Adults 18+ Driving Age (Full License) Law Enforcement Employees

15. Group 4 | Presentation on June 20, 2012 | 15 TERMPROJECT POLICY IMPLICATIONS How to Survive in the US M O V E T O A C O L D S T A T E … … W H E R E Y O U N G P E O P L E L I V E T O G E T H E R … … W I T H L O T S O F I M M I G R A N T S … … T O O C O O L F O R C O P S … A LASKA M AINE U TAH C ALIFORNIA … A N D N O O N E S M O K E S ! T EXAS

16. Group 4 | Presentation on June 20, 2012 | 16 TERMPROJECT SUMMARY AND CONCLUSIONS How to Survive in the US A LASKA M AINE U TAH C ALIFORNIA T EXAS Whatever you do: Leave Rhode Island; wicked dangerous! And move to:

17. Group 4 | Presentation on June 20, 2012 | 17 TERMPROJECT Thank you for your attention! Determinants of Fatal Car Accidents in the United States

18. Group 4 | Presentation on June 20, 2012 | 18 TERMPROJECT References  Injury Prevention and Control: Motor Vehicle Safety. Centers for Disease control and Prevetion. http://www.cdc.gov/motorvehiclesafety/http://www.cdc.gov/motorvehiclesafety/  Traffic safety facts: Crash Stats. US department of Transportation: National Highway Traffic Safety Administratio; 4/11. http://www-nrd.nhtsa.dot.gov/Pubs/811451.pdfhttp://www-nrd.nhtsa.dot.gov/Pubs/811451.pdf  Loeb,P. The Determinants of Automobile Accidents. Journal of Transport Economics and Policy; London School of Economics and Political Science. 21(3);1987:279-287  O’Donnell, C.J.Connor D. Predicting the severity of vehicle accident injuries using models of ordered multiple choice. Accident and Analysis Prevention; 28(6);1996:739-753  Fridstrom,L. Econometric models of road use, accidents, and road investment decisions. Institute of Transport Economics.1999:1-292  Ulfarsson, G; Mannering, F. Differences in male and female injury severity in sport utility vehicle, minivan, pickup, and passenger car accidents. Accident Analysis and Prevention. 36(2);2004:135-147  Milton, J; Shankar, V; Mannering, f. Highway accident severities and the mixed logit model: An explanatory empirical analysis. Accident Analysis and Prevention. 40(1);2008:260-266