ECON 164
Lecture 13
Hypothesis testing, III
p-values: alternative to t-stats
p-value means probability value
Your t-statistic and your p-value are both indicators of the
likelihood of finding what you
ECON 164
Lecture 20
Review of functional forms
Recall: Dummy X variable
A way of including a non-numerical variable in
your regression model.
How many values can a dummy variable take?
2: Think of it
ECON 164
Lecture 17
Specification: Functional
Form
Sensitivity analysis
Most empirical studies report more than one
regression
When you deliberately run (and report) a set of
alternative specification
ECON 164
Lecture 16
Specification: Choosing Explanators, III
Menu for today
Omitted vs irrelevant variables
4 specification criteria
Misusing the criteria: An example
Searching for the best specificat
ECON 164
Lecture 19
Specification: Functional
Form, III
Recall: Quadratic form
Another form that allows the impact on Y of a
change in X to depend on the level of X:
Y = 0 + 1X + 2 X2 +
Advantage ove
ECON 164
Lecture 15
Specification: Choosing Explanators, II
Recall: Omitted variable bias
When we leave out an explanator, we worry that the
coefficients we estimate will be biased.
Our concern is not
ECON 164
Lectures 11 and 12
Hypothesis testing
The null hypothesis: H0
The null hypothesis: A statement about what you
think is not true about the value of
The most common null?
Therefore, what you d
ECON 164
Lecture 14
Specification:
Choosing your explanators
Thinking about variables
No chapter devoted to choosing your Y variable
In practice, this is an extremely important choice, can make or
bre
Lecture 2
Econometrics
Overview of regression
analysis
Recall: What constitutes econometrics?
About measuring correlations
Relatively few new statistical concepts
How much do these two variables co-va
ECON 164
Lecture 18
Specification: Functional
Form, II
Recall: Linear in the coefficients
OLS requires only that
f(Y)= 0 + 1f(X)
Recall: Natural logarithm
Natural log mean your base is e
ln X = b mean