Econ 302
Econometrics
Bilkent University
Department of Economics
Taskin
Review List for Midterm
Following are the concepts that you should know and be familiar with.
This is not designed to be a comprehensive list of all the items covered in class, but it is
just a reminder of topics.
Time Series:
- Stationary and non-stationary time series,
- Random walk model (pure, with drift, with time trend)
- Unit Root
- Testing for unit root, Dickey Fuller Test,
- Augmented Dickey Fuller test (ADF),
- Integrated of order 0 or higher; I(0), I(1) or I(2),
- Co-integration
- Error correction model
- Spurious regression.
Panel data:
- Common coefficient,
- Fixed effect models
- Entity or country fixed effect
- Time fixed effect
- GLS corrections and forms of Cov (u) matrix,
- Random Effects models
- Hausman Test
- Significance testing
- Restriction testing across different specification
Quantitative Response Models: (binary response models):
- Linear probability model
- Problems with LPM,
- Interpretation of the LPM
- Heteroschedasticity problem in LPM
- Logit model- its form and its intuition
- Interpretation of the coefficients and computation of the partial effects at the
averages.
- Likelihood ratio test
- Pseudo R square (Mc Fadden’s)
- Restriction testing
- Correct forecast ratio measures
Background information from Econ 301
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Simple linear regression model, population regression function, Sample
regression function (fitted regression equation),
Coefficients, interpretations.
disturbance term (error term)
residuals,
Ordinary Least Squares, derivation
Assumptions about the explanatory variables, and error term
Properties of OLS,
SST, SSR, SSE
R2, adjusted R2
Sampling distribution,
Unbiasedness, Efficiency,
Confidence interval
Hypothesis testing
o Single hypothesis –t test
o Two sided and one sided tests
o Joint hypothesis – F test
o Restriction testing identification of the restrictions
Assessing the joint significance of the explanatory variables,
Omitted variable and irrelevant variables,
Measurement Errors in variables
Nonlinear regression; quadratic variables and logarithmic variables,
Large sample properties of the OLS
Dummy Variables, (one category and multiple categories, and dummies for
multiple groups in one category)
Heteroscedasticity, (definition, consequences, detection methods, correction)
Autocorrelation, , (definition, consequences, detection methods, correction)