Linear Regression Model

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Econ 122B Problem Set 2 Name(Print)______________________
Due in class Feb 6 UCI ID_____________________________ Multiple­Choice Questions (Choose the best answer, and briefly explain your reasoning.) 1. Assume we have a simple linear regression model: . Given a random sample from the population, which of the following statement is true? a. OLS estimators are biased when BMI do not vary much in the sample.
b. OLS estimators are biased when the sample size is small (say 20 observations).
c. OLS estimators are biased when the error u captures perseverance and self‐ control, and you believe that
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b. be unbiased if using a large enough sample.
c. be biased, because the variance of efficienc/ability depends on training.
d. be unbiased, as long as both prod and training are recorded correctly.

8. Suppose you have the following estimated equation,
500 84 , where Burger refers to weekly number of burgers sold on average in In&In Burger joint and price is in US dollars. What would be your estimate of the slope if price were in GB pounds (assuming 1 GB pound = 2 US dollars) AND you use daily number of burgers sold rather than weekly? a.
‐12
b.
‐84
c.
‐168
d. ‐24

9. Using data on 4,137 college students, the following equation was estimated by
OLS:
1.392
4,137,

0.0135

0.00148

0.273

where colGPA is measured on a four‐point scale, hsperc is the percentile in the high school graduating class (defined so that, for example, hsperc = 5 means the top 5%

3

of the class), and SAT is the combined math and verbal scores on the student achievement test.
1)

How would you interpret the estimated slope for hsperc?

How would you interpret the R2?

2) 3)

Suppose that two high school graduates, A and B, graduated in the same percentile from high school, but Student A’s SAT score was 140 points higher (about one standard deviation in the sample). What is the predicted difference in
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