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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. Term Project: Determinants of Fatal Car Accidents in the United States. Agenda. Introduction Research History Data and Variables

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Term Project: Determinants of Fatal Car Accidents in the United States

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  1. MBA 555: Managerial Economics Presentation on June 20, 2012 Group 4: Henning Andrees, Chelsey Hawes, Martin Kumke, Paula Monteiro, Charly von Wiedersperg Term Project:Determinants of Fatal Car Accidentsin the United States

  2. Agenda • Introduction • Research History • Data and Variables • Econometric Model • Results • Policy Implications • Summary and Conclusion

  3. IntroductionCar 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 STUDY OBJECTIVE • Examining the determinants of fatal car accidents in the US 1 death per 10,000 people per year

  4. Research HistoryMany 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. HypothesesTesting Hypotheses in Four Different Categories H1 The number of fatal car accidents is explained by …weather and climatic conditions. H2 The number of fatal car accidents is explained by … the degree of drug and alcohol use. H3 The number of fatal car accidents is explained by … demographic factors. H4 The number of fatal car accidents is explained by … driving-related factors.

  6. Data and VariablesDiverse Variables Based on Hypothesis Categories Number of fatal car accidents per 100,000 inhabitants DEPENDENT INDEPENDENT • 1: Weather and climate • Temperature (average) • Precipitation (annual) • Snowfall (annual) • Wind speed (average) • Time between sunrise and sunset • 2: Drug and alcohol use • Beer consumption (per capita) • Cigarette use (percentage) • Prescription drugs sold (kg per capita) • 3: Demographic factor • Average age • Sex ratio (male/female) • Student population (percent) • Number of foreign born (percent) • Median income • Average family size • Population density • 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)

  7. MethodologyMultiple Steps to Create the Best Production Model Basic Assumption: Cobb-Douglas Production Function: Stepwise • Narrow down the significant variables • DATA: • Cross-sectional • 50 states of the USA • Year: 2010 • 23 variables • SOFTWARE: • WinORS OLS • Test for regression assumptions • Eliminate variables with multicollinearity No Intercept • No regression parameter for intercept • BEST MODEL: • No intercept multiplicative model

  8. Econometric ModelCobb-Douglas Production Function

  9. ResultsIs the Model Trustworthy? F-Value2,473.843 P-Value 0.00001 R² (adjusted) 99.753% Explanatory power Autocorrelation Does not exist in Ln model (NoDurbin Watson) Average VIF 2.302 Multicollinearity

  10. ResultsIs the Model Trustworthy? Statistical Significance P-Value

  11. ResultsIs the Model Trustworthy? HOMOSKEDASTICITY White’s Test: 48.221 P-Value: 0.30597

  12. ResultsIs the Model Trustworthy? Normality Correl. For Normality: 0.9935 Critical Value: 0.9840

  13. ResultsNo Hypothesis Has Been Rejected H1 The number of fatal car accidents is explained by … weather and climatic conditions. NOT REJECTED H2 The number of fatal car accidents is explained by … the degree of drug and alcohol use. NOT REJECTED H3 The number of fatal car accidents is explained by … demographic factors. NOT REJECTED H4 The number of fatal car accidents is explained by … driving-related factors. NOT REJECTED

  14. ConclusionsElasticities Explain Impact on Fatal Car Accidents Elasticity Average Annual Temperature 1 Average Age # of Motor Vehicles per Person Cigarette Use in Adults 18+ Interstate Miles per Vehicle 0 Number of Foreign Born Law Enforcement Employees -1 -2 Driving Age (Full License)

  15. Policy ImplicationsHow to Survive in the US Alaska Maine Move to a Cold State… Utah … too Cool For Cops … … where Young People Live Together … California … with Lots of Immigrants … Texas … and No One Smokes!

  16. Summary and ConclusionsHow to Survive in the US Alaska Maine Utah Whatever you do: Leave Rhode Island; wicked dangerous! And move to: California Texas

  17. Determinants of Fatal Car Accidents in the United States Thank you for your attention!

  18. References • Injury Prevention and Control: Motor Vehicle Safety. Centers for Disease control and Prevetion. 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.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

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