This course aims to provide students with a thorough understanding of theory and application of econometrics in empirical research in economics, accounting and finance. In particular, the course aims to equip students with fundamental statistical methods and techniques to use real-time data to estimate models and make inferences. The main topics include simple and multiple regression models, least squares estimation of the regression model, hypothesis testing and inference procedures, relaxing the underlying assumptions and diagnostic checking, binary choice models (logit and probit) and panel data analysis (pooled regression, fixed and random effects, dynamic panel models, binary choice panel data). Emphasis is placed on time series analysis, such as stationary and non-stationary time-series, unit root testing, cointegration testing and estimating an error-correction model (ECM); vector autoregression analysis and vector error-correction models (VECM). All topics are accompanied with real data examples solved in E-Views and Microfit-5.

After completing this course, the student will be able to:

1. Understand econometrics and describe the econometric methodology
2. Explain the steps involved in empirical research or econometric research;
3. Develop simple and multiple classical regression models and understand the underlying assumptions;
4. Estimate simple and multiple regression models and interpret the results.
5. Apply inference procedures based on t-statistic and F-statistic to test linear restrictions on regression parameters and the goodness of fit;
6. Relax the assumptions of the classical regression model and describe the consequences ofviolation of each assumption;
7. Discuss the conventional econometrics problems of non-normality, heteroscedasticity,autocorrelation, multicollinearity and simultaneous equation bias, explain their consequencesfor the OLS estimators and describe the tests to detect these problems;
8. Apply appropriate methods to remedy the conventional econometric problems;
9. Describe time series models, test a unit root in time series and apply methods to test forcointegration

1. Introduction to econometrics
2. Simple linear regression model
3. Estimation, goodness of fit and hypothesis testing
4. Multiple regression analysis
5. Assumptions, estimation, goodness of fit and hypothesis testing
6. Relaxing assumptions and diagnostic testing
7. Multicollinearity and its implications
8. Heteroskedasticity, consequences, tests and remedies
9. Autocorrelation, consequences, tests and remedies
10. Simultaneous equation models and estimation
11. Model misspecification and tests
12. Time series and cointegration analysis
13. Dynamic models with lagged dependent variables
14. Panel data models

Gujarati, D.N. (2004), “Basic Econometrics”, 4^th Edition, McGraw-Hill.

Wooldridge, J.M. (2012), “Introductory Econometrics: A Modern Approach”, 5^th Edition, CENGAGE Learning Custom Publishing.
Kennedy, P., (2003), “A Guide of Econometrics,” 5^th Edition, Milt Press, USA.
Brooks, C. (2008), “Introductory Econometrics for Finance”, 2^nd Edition, Cambridge: Cambridge University Press.