Applied Econometrics

• Model Building: Developing econometric models to analyze economic data.

• Data Analysis: Applying statistical methods to interpret economic data.

• Estimation Techniques: Using techniques like OLS, GLS, and IV for estimating economic relationships.

• Hypothesis Testing: Testing economic theories and hypotheses with statistical methods.

• Forecasting: Predicting future economic conditions based on historical data.

Before learning Applied Econometrics, you should have:

1. Basic Economics: Understanding of economic concepts and theories.

2. Statistics: Knowledge of basic statistical methods and concepts.

3. Mathematics: Familiarity with algebra and calculus, especially for model formulation.

4. Data Analysis: Skills in analyzing and interpreting data.

• The Nature of Applied Econometrics
• Data Considerations and Ordinary Least Squares Estimation of Single-Equation Econometric Models
• Interpretation and Use of Estimated Coefficients and Forecasting with Single-Equation Econometric Models
• Common Tests of Hypotheses in Applied Econometrics
• Use of Dummy (Indicator) Variables in Applied Econometrics
• Diagnostic Checks - Autocorrelation or Serial Correlation
• Diagnostic Checks - Heteroscedasticity