1
ECN 425
EXERCISE 3
DR. AHN
ECONOMETRICS
FALL 2011
Q1.
(32 pts.; 4 pts. on each.)
Choose the best
answer for each of the following questions.
Mark
on your choices.
Answers
for 1):
; for 2):
;
for 3):
;
for 4):
for 5):
; for 6):
;
for 7):
;
for 8):
1)
Omitted variable bias
a.
will always be present if
2
1
R
.
b.
is always there but is negligible in almost all economic examples.
c.
exists if the omitted variable is correlated with the included regressor but is not a
determinant of the dependent variable.
d.
exists if the omitted variable is correlated with the included regressor and is a
determinant of the dependent variable.
2)
The adjusted
2
R
, or
2
R
, is given by
a.
2
1
1
nR
S
S
nk T
S
S
; b.
1
1
1
nE
S
S
S
S
; c.
1
1
1
S
S
S
S
; d.
ESS
TSS
.
3)
Imagine you regressed earnings of individuals on a constant (for
0
ˆ
), a binary variable
(“
Male
”) which takes on the value 1 for males and is 0 otherwise, and another binary
variable (“
Female
”) which takes on the value 1 for females and is 0 otherwise.
Because
females typically earn less than males, you would expect
a.
the coefficient for
Male
to have a positive sign, and for
Female
a negative sign.
b.
both coefficients to be the same distance from the constant, one above and the other
below.
c.
none of the OLS estimators to exist because there is perfect multicollinearity.
d.
this to yield a difference in means statistic.
4)
The confidence interval for a single coefficient in a multiple regression
a.
makes little sense because the population parameter is unknown.
b.
should not be computed because there are other coefficients present in the model.
c.
can be used to test a large number of hypotheses related to the coefficient.
d.
should only be calculated if the regression
R
2
is identical to the adjusted
R
2
.
5)
The interpretation of the slope coefficient in the model
01
ln( )
ln(
)
ii
i
YX
u
is as
follows:
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a. 1% change in
X
is associated with a
1
% change in
Y
.
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 Fall '09
 Statistics, Econometrics, Regression Analysis, Statistical hypothesis testing, Statistical significance, significance level, binary variable

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