In: Statistics and Probability
Consider a binary response variable y and two
explanatory variables x1 and
x2. The following table contains the parameter
estimates of the linear probability model (LPM) and the logit
model, with the associated p-values shown in
parentheses.
Variable | LPM | Logit | |||
Constant | −0.40 | −2.20 | |||
(0.03 | ) | (0.01 | ) | ||
x1 | 0.32 | 0.98 | |||
(0.04 | ) | (0.06 | ) | ||
x2 | −0.04 | −0.20 | |||
(0.01 | ) | (0.01 | ) | ||
a. At the 5% significance level, comment on the
significance of the variables for both models.
Variable | LPM | Logit |
x1 | (Click to select) Significant Not significant | (Click to select) Significant Not significant |
x2 | (Click to select) Significant Not significant | (Click to select) Significant Not significant |
b. What is the predicted probability implied by
the linear probability model for x1 = 4 with
x2 equal to 10 and 20? (Round
intermediate calculations to at least 4 decimal places and final
answers to 2 decimal places.)
yˆy^ | |
x1 = 4, x2 = 10 | |
x1 = 4, x2 = 20 | |
c. What is the predicted probability implied by
the logit model for x1 = 4 with
x2 equal to 10 and 20? (Round
intermediate calculations to at least 4 decimal places and final
answers to 2 decimal places.)
yˆy^ | |
x1 = 4, x2 = 10 | |
x1 = 4, x2 = 20 | |