The

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: n the multiple regression model because a) many economic variables are perfectly correlated. b) the OLS estimator cannot be computed in this situation. c) in real life, economic variables change together all the time. d) with perfect collinearity, R2 is equal to 1. 2 7. Suppose a researcher is interested in the impact of on‐the‐job training on productivity, and plans to estimate the following model: , where prod is a measure of labor productivity, and training represents number of hours a worker has spent in a training program. The researcher believes that less efficient or less able workers tend to spend more time on training. If this is true, then OLS estimates of this model will most likely a. be biased, because training is correlated with efficiency/ability, which is in the error term. 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 equati...
View Full Document

Ask a homework question - tutors are online