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What decides the price of used cars?. Group 1 Jessica Aguirre Keith Cody Rui Feng Jennifer Griffeth Joonhee Lee Hans-Jakob Lothe Teng Wang. How we got data. Collected from kbb.com (Kelley Blue Book) Used random number generator
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What decides the price of used cars? Group 1 Jessica Aguirre Keith Cody Rui Feng Jennifer Griffeth Joonhee Lee Hans-Jakob Lothe Teng Wang
How we got data • Collected from kbb.com (Kelley Blue Book) • Used random number generator • First collected 140 sets of data from various types of cars • Then collected 160 sets of data from Toyota Camrys
Assumptions • Random sample is representative of population • All prices are the selling price • Residuals are homoskedastic • Residuals are normally distributed • The variables we choose affect the price of used cars: age, color, etc
Preparations • Created dummy variables • e.g. Transmission, automatic = 0, manual = 1 • Color • Type • Engine (V4 = 4, V8 = 8, etc)
All Cars: Regression of price against independent variables (age, color, engine, miles and transmission)
All Cars: Regression of price against significant independent variables (p<0.05) Price = -631.9880*AGE + 949.8378* ENGINE -0.051251* MILEAGE + 1977.688*TRIM + 18866.11
Some reasons why this model fails • Color is randomly assigned a number (red = 9, blue = 7, etc) • Engines: e.g. 4 cylinder = 4, V8 = 8 assumes the V8 is twice the price of 4 cylinder • We suspect that many models leads to low R-Square
Our solution: New model • New model where we look at one model and brand (Toyota Camry), only two engines (4 cylinder and 6 cylinder), and disregard color • Dummy variable for engine: 6 cylinder = 1, 4 cylinder = 0 • We also introduce a new variable called trim • Dummy variable for trim: luxury = 1, standard = 0 • Toyota Camry • Most Popular Car in America* * Motor Trendhttp://www.motortrend.com/features/auto_news/2010/112_1004_america_top_10_best_selling_vehicle_comparison_2009_2000/index.html
Toyota Camry: Regression of price against independent variables (age, engine, mileage, trim and transmission)
Toyota Camry: Regression of price against independent variables (age, engine, mileage and trim) Price = -631.9880 * AGE + 949.8378 * ENGINE -0.051251 * MILEAGE + 1977.688 * TRIM + 18866.11
All Cars: mileage against price R-Square ≈ 22%
Toyota Camrys: mileage against price R Square ≈ 66%
Alternative ModelPRICE^(1/2) = -0.0002263673136*MILEAGE + 4.59824795*ENGINE - 2.952776402*AGE + 7.704044111*TRIM + 139.1536581
Conclusions • As expected, older, higher mileage cars are worth less than newer cars. • Bigger engines and nicer levels of trim cost more • Our model explains 82% of price variations
What we learned from this project • Communication can be difficult • EViews is amazingly fun and can be useful in analyzing social and economic phenomena • Thanks!