Econometrics and Applied Statistics

Course Coordinator: Dr Thomas Chan, BCogSci (HKU), MA, PhD (Boston College)

Aims
This course deals with quantitative model building and statistical skills which students will find useful in economics, marketing, risk management and investment. It aims to teach students how to use statistical techniques to make estimations and test hypotheses in business and economics. Students will learn how to create a statement of theory or a hypothesis, how to collect data, and how to specify economic and business models. Students will also learn how to estimate the parameters of their chosen forecasting model, check for model adequacy, and test the hypotheses derived from the model. The emphasis is on the application of econometric methods to analyse real-world economic data using advanced statistical software.

Contents

• An overview of regression analysis and ordinary least squares
• Learning to use regression analysis and running a regression project
• The classical model and hypothesis testing
• Specification: Choosing the independent variables
• Specification: Choosing a functional form
• Multicollinearity
• Serial correlation
• Heteroskedasticity
• Dummy dependent variable techniques
• Simultaneous equations
• Selected topics in econometrics methodology

Assessment
There will be one assignment, one midterm test and one individual term paper accounting for 50% of the total course score. The final examination will account for the remaining 50%. Students are required to submit assignments via the Online Learning Environment (OLE).

Set Book(s):
Adkins, L C and Hill, R C (2016) Using STATA for Principles of Econometrics, 5th edn, John Wiley & Sons.

Hayashi, F (2000) Econometrics. Princeton, NJ: Princeton University Press.

Joshua, D A and Jörn-Steffen P (2009) Mostly Harmless Econometrics: An Empiricist's Companion, Princeton University Press.