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September 28, 2006
Left-Out Variables
We considered the consequences of mistakenly leaving out a regressor.
Set up for the two-variable regression model:
Consider two possibilities:
If the truth is I and we pick I, we are in good shape:
An important proposition:
If the truth is II and we pick I, we have a left-out variable, which effectively becomes part of the error term.
We can derive an expression for the resulting left-out variable bias.
Posted by bparke at 09:29 PM | Comments (0)
September 26, 2006
Functional Form
Somebody forgot his camera today, but the material we discussed resembled a Fall 2005 lecture and a Spring 2005 lecture.
Posted by bparke at 08:24 PM | Comments (0)
September 21, 2006
The F Test
We can use an F test to test a hypothesis involving more than one restriction.
We created rvm2 = rvm*rvm to show that an F test for one linear restriction is equivalent to a t test.
Posted by bparke at 10:52 PM | Comments (0)
September 19, 2006
Multiple Regression
Posted by bparke at 10:29 PM | Comments (0)
September 14, 2006
Ordinary Least Squares
What is better, large n or small n? What is better, big V(x) or small V(x)?
Supplement -- a way to think about the model:
Posted by bparke at 10:32 PM | Comments (0)
September 12, 2006
Random Numbers
Stata generates random numbers uniformly distributed between 0 and 1 if you use "gen x = uniform()". To generate standard normal random variables use "gen e = invnorm(uniform())".
Posted by bparke at 10:23 PM | Comments (0)
Ordinary Least Squares
Posted by bparke at 09:52 PM | Comments (0)
Monte Carlo "do" File
The following "do" file will probably be used in today's lecture.
mc1.do
Posted by bparke at 12:13 AM | Comments (0)
September 07, 2006
Hypothesis Testing
The basic strategy
One-tail test
Two-tail test
Posted by bparke at 05:49 PM | Comments (0)
September 05, 2006
Bayesian vs. Classical Statistics, including Confidence Intervals
A fairly innovative approach via Bayesian statistics reviewed confidence intervals (of classical statistics).
If you were in class, you know that the last diagram illustrates a point of profound importance.
Posted by bparke at 09:27 PM | Comments (0)