The fixed effects transformation Consider the following simple unobserved effects regression model for each i: yit = Beta1xit + ai + uit
where
yit = value of the dependent variable for individual i at time t
xit = value of the independent variable for individual ai at time t
ai = unobserved, time-constant effect
uit = idiosyncratic error
Therefore, the average value ofa; over time (-) is equal to.
This ispresents the time-demeaned data on a variable, performing the fixed effects transformation on the original model yields which of the variesover time.
Therefore, the average value of ai over time (a,) is equal to.
Therefore, if represents the time-demeaned data on a variable, performing the fixed effectinformation on the original model yields which of the following?
a. yit = Beta1xit + ai + uit
b. yit - yi = Beta1(xit - xi) + (uit + ui)
c. yit - yi - Beta1(xit - xi) - (uit + ui)
d. yit = Beta1xit + uit
Suppose, in the original unobserved effects model, it -sat is the SAT score, (with the highest score used if there were multiple attempts).
Beta1 can be estimated by using the within transformation on the unobserved effects model and then using OLS. A. True
B. False