- Demonstrate a familiarity with the properties and applications of several families of statistical distributions to econometric problems.
- Demonstrate an understanding of variations and generalizations of the basic regression model including
Generalized least squares
Generalized autoregressive conditional heteroskedasticity models
Seemingly unrelated regression models
Hausman specification tests.
- Demonstrate an understanding of estimation frameworks in econometric models including
Parametric, semiparametric, and non parametric specifications
Maximum likelihood, M-, generalized method of moments, kernel, empirical likelihood, and extremum estimation.
- Formulate and estimate various nonlinear models.
- Identify and estimate autoregressive integrated moving average (ARIMA) models and obtain forecasts of economic variables.
- Demonstrate an understanding of dynamic (and static) structural econometric models including being able to discuss
Reduced form, structural, and transfer function representations
The identification problem
Issues of estimation and statistical inference
Vector autoregression models.
- Complete a research project in which they formulate a research question, apply appropriate methods to answer the question, and prepare a paper summarizing their results.