Flashcards in Tutorial 2 - Linear Regression II (Polynomials, Dummy variables, logs...) Deck (8)
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1
Q
How would you add a polynomial into the regression?
A
in addition to linear term, add polinomial term, i.e.:
2
Q
How can you find out the returns to experience in this example (=wage increase for an additional year of experience, holding all other factors fixed)?
A
3
Q
What do you need to consider when interpreting regression coefficients?
A
- Direction of the effect (positive/ negative)?
- Magnitude of the effect? What are the units of measurement of x and y? (e.g. years, Dollars, cm,…)
- Significance
4
Q
How can you interpret a one unit change in x in this regression?
A
5
Q
What is the appriximation of the log effect of a one unit change in variable x? When can you apply this approximation?
A
6
Q
How can you interpret the coefficients of this model?
A
7
Q
Why would you use a log or log-log model?
A
- Some theories in economics predict a certain functional form, e.g. Cobb-Douglas production function in log-log form,
- Using log(y) as dep. var. ensures that predicted values of y are always positive (makes sense for variables like wages, which can only be positive).
- Taking logs of the dependent variable reduces the influence of outliers (alternative to eliminating outliers).
- Taking logs of the dependent variable sometimes reduces heteroskedasticity problems.
8
Q
What does “UNCONDITIONAL estimate” mean? What is a conditional estimate then?
A
- Unconditional: Only one regressor, do not condition on other variables
- Conditional: With other variables