Using gret l for Principles of Econometrics, 4th Edition
Using Linear Probability to Verify Random Assignment
A number of variables are omitted from the model and it is safe to do so as long as they are not correlated with regressors. This would be evidence of assignments to the control group that
are systematic. This can be checked using a regression. Since small is an indicator, we use a linear probability regression.
The independent variables include a constant, boy white_asian, tchexper and freelunch.
The result is
OLS, using observations 1-3743
Dependent variable: small
Heteroskedasticity-robust standard errors, variant HC3
|
Coefficient Std. Error |
t-ratio |
p-value |
||
|
const |
0.4665 |
0.0253 |
18.46 |
7.33e-073 |
|
boy |
0.0014 |
0.0163 |
0.09 |
0.931 |
|
white_asian |
0.0044 |
0.0197 |
0.22 |
0.823 |
|
tchexper |
-0.0006 |
0.0014 |
-0.42 |
0.676 |
|
freelunch |
-0.0009 |
0.0183 |
-0.05 |
0.961 |
|
Sum squared resid 930.9297 |
S. E. of |
regression |
0.499044 |
|
|
R[52] |
0.000063 |
Adjusted R2 |
-0.001007 |
|
|
F(4, 3738) |
0.059396 |
P-value(F) |
0.993476 |
The overall-F statistic is not significant at 10%. None of the individual t-ratios are significant. Finally, a test of the hypothesis that the constant is ві = 0.5 cannot be rejected. A value of 0.5 would be consistent with assigning children to a small or large class by a fair coin flip. I think it is safe to omit these regressors from the model.
