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 ◦Price of Oil ◦Average Mileage per Gallon ◦Income per Capita

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

Auto Sales by Make

Trucks vs. Cars

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

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 ( ) ‏

Variable Histograms

Variable Boxplots

Auto Sales vs. Time

Unemployment Rate vs. Time

Oil Price vs. Time

Income per Capita vs. Time

Average Mileage vs. Time

Correlation between Variables

Correlation – Auto Sales and Other Variables Negative Slope!

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

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

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

Heteroskedasticity? White Heteroskedasticity test: F-statistics Probability Obs*R-squared Probability

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

Diagnostic of Regression II

Correcting the autocorrelation function

Error Term Regression

Durbin Watson Correction

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

Questions ?