Applied Econometrics Tutor in Singapore – Syllabus
1. Introduction to Econometrics
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- Nature, scope, and objectives of econometrics
- The role of data in empirical economics
- Types of data: cross-sectional, time series, panel
- Structure of econometric models (deterministic vs. stochastic)
- Classical assumptions and their importance
2. Simple Linear Regression
- Specification of the two-variable regression model
- Ordinary Least Squares (OLS): estimation and interpretation
- Properties of OLS estimators (BLUE)
- Hypothesis testing: t-test, F-test, confidence intervals
- Goodness-of-fit: R² and adjusted R²
3. Multiple Linear Regression
- Extension to multiple regressors
- Interpretation of coefficients
- Multicollinearity: detection and remedies
- Testing joint significance of regressors
- Functional form and model specification
4. Violations of Classical Assumptions
- Heteroscedasticity: nature, detection (Breusch–Pagan, White test), consequences, remedies (robust standard errors, GLS)
- Autocorrelation: sources, detection (Durbin–Watson, Breusch–Godfrey), remedies (Cochrane–Orcutt, Newey–West)
- Multicollinearity revisited with variance inflation factors (VIF)
- Specification errors: omitted variables, irrelevant variables, measurement error
5. Dummy Variables and Qualitative Response Models
Applied Econometrics Tutor in Singapore
- Use of dummy variables in regression
- Interaction effects and structural change
- Linear probability model (LPM), logit, and probit models
6. Time Series Econometrics
- Stationarity and non-stationarity
- Unit root tests (ADF, PP)
- AR, MA, ARMA, and ARIMA models
- Forecasting techniques
- Cointegration and error correction models (ECM)
7. Panel Data Econometrics
- Pooled regression model
- Fixed effects vs. random effects models
- Hausman test
- Applications in microeconomics and policy analysis
- Applied Econometrics Tutor in Singapore
8. Simultaneous Equations Models
- Identification problem
- Two-Stage Least Squares (2SLS)
- Limited Information vs. Full Information methods
9. Applications of Econometrics
- Policy evaluation and impact assessment
- Demand and supply estimation
- Wage equations, education and earnings models
- Growth regressions and development economics applications
10. Software and Practical Component
- Hands-on with statistical/econometric software: Stata, R, EViews, or Python
- Data cleaning and descriptive analysis
- Running regressions and interpreting output
- Project/term paper using real-world datasets
✅ Assessment Methods:
- Midterm and final exams (theory + applications)
- Problem sets using software
- Empirical project/report writing
- we provide Applied Econometrics in singapore all locality.
