1. Automobile Sales and the General Economy ECON240A Group #1 Deepti Goyal Rory Tyler Hofstatter Hairuo Hu Joel Benjamin Lindenberg Sooyeon Angela Shin Michael John Stromberg Kathy Zha Ling Zhu

2. Introduction Dependent Variable ◦Amount of Auto Sales Independent Variables ◦Unemployment ◦Price of Oil ◦Average Mileage per Gallon ◦Income per Capita

3. Why Study Such Variables? Trend towards vehicles with better fuel efficiency Automobile sales have been decreasing, particularly for bigger vehicles notably in the past couple of years Impact of current recession on the auto sales industry

4. Auto Sales by Make

5. Trucks vs. Cars

6. How the Study is Conducted Exploratory Data Analysis ◦Histograms ◦Box Plots ◦Scatter Diagram ◦Time Series Trend Regression Analysis ◦Correlation Diagram ◦Bi-variate Regression using OLS method ◦Normality test using Jarque-Bera Statistics ◦Heteroskedasticity

7. Data Gathering Auto Sales: Ward’s Automotive Group Unemployment Rate: US Bureau of Labor Statistics Annual Crude Oil Prices: US Bureau of Labor Statistics Income per Capita: US Department of Commerce, Bureau of Economic Analysis 35 Years (1974-2008) ‏

8. Variable Histograms

9. Variable Boxplots

10. Auto Sales vs. Time

11. Unemployment Rate vs. Time

12. Oil Price vs. Time

13. Income per Capita vs. Time

14. Average Mileage vs. Time

15. Correlation between Variables

17. Correlation – Auto Sales and Other Variables Negative Slope!

18. Regression Equation Auto Sales = c1*Avgmpg + c2*Income+c3*oilprice + c4 * Unemployment + constant

19. Regression I Highly Significant F-statistic Barely Significant at 5% level All other variables are significant at 5% level

20. Diagnostic of Regression I Residual vs. Fitted Values Slightly skewed to the left But still normally distributed

21. Heteroskedasticity? White Heteroskedasticity test: F-statistics 1.409723 Probability 0.239025 Obs*R-squared 10.58868 Probability 0.226112

22. Regression II Highly Significant F-statistic All variables are significant at 5% level with income as highly significant

23. Diagnostic of Regression II

24. Correcting the autocorrelation function

25. Error Term Regression

26. Durbin Watson Correction

27. Conclusion Significant Factors Affecting Automobile Sales:  Unemployment Rate  Income per Capita  Fuel Economy (Avg. Mileage per Gallon)  Avg. Price of Crude Oil Forecasting ◦Automobile Sales, when unemployment rate and income per capita. Room for Future Studies: ◦For stronger R 2 (0.74 for Reg. #1 and 0.69 for Reg. #2), additional variables should be studied

28. Questions ?