1
Problem Set 5
Economics 103
Due:
Thursday, March 12, 2009
Question 1
True/False/Explain:
1)
The linear probability model is the application of the multiple regression model with a
continuous left-hand side variable and a binary variable as at least one of the regressors.
2)
The linear probability model has predicted values that lie between 0 and 1.
3)
The probit model is the same as the logit model.
4)
In the expression Pr(Y=1)=
(
β
0
+
β
1
X) from a probit model,
1
cannot be negative since
probabilities have to lie between 0 and 1.
5)
In the probit model
1
2
0
1
1
2
Pr(
1|
,
,...,
)
(
...
)
k
x
k
k
Y
X
X
X
X
X
X
, the
slopes tell you the effect of a unit increase in
X
on the probability of
Y
.
6)
In the expression Pr(
deny
= 1|
P/I Ratio
,
black
) =
(–2.26
+ 2.74
P/I ratio
+ 0.71
black
),
the effect of increasing the P/I ratio from 0.3 to 0.4 for a white person is 2.74 percentage
points.
7)
In the binary dependent variable model, a predicted value of 0.6 means that the most
likely value the dependent variable will take on is 60 percent.
8)
In the linear probability model, the interpretation of the slope coefficient is the change in
probability that
Y
=1 associated with a unit change in
X
, holding other regressors constant.
9)
The distinction between endogenous and exogenous variables is that exogenous variables
are determined inside the model and endogenous variables are determined outside the
model.

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