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Automobile Sales and the General Economy ECON240A

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. Introduction. Dependent Variable Amount of Auto Sales Independent Variables Unemployment

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Automobile Sales and the General Economy ECON240A

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  1. Automobile Sales and the General EconomyECON240A 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. 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 Why Study Such Variables?

  4. Auto Sales by Make

  5. Trucks vs. Cars

  6. 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 How the Study is Conducted

  7. 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)‏ Data Gathering

  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

  16. Correlation between Variables

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

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

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

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

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

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

  23. Diagnostic of Regression II

  24. Correcting the autocorrelation function

  25. Error Term Regression

  26. Durbin Watson Correction

  27. 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 R2 (0.74 for Reg. #1 and 0.69 for Reg. #2), additional variables should be studied Conclusion

  28. Questions?

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