HONG KONG BAPTIST UNIVERSITY
Department of Economics

ECON 3600 Econometric Modeling and Analysis
1st Semester 2004/05
Instructor Dr. Bill Wan-Sing Hung
(Email: billhung@hkbu.edu.hk)
Office/Office Hours  WLB626, Tel: 3411-7574
W 11:30-12:20; T 9:30-11:20; TH 15:30-17:20; F 10:30-11:20 or by appointment
Lecture Hours/Room 12:30 - 13:20 Tuesday (WLB303)
Tutorial Hours/Room 11:30 - 12:20 Friday (WLB506)
Lecture Notes: note#01 , note#02 , note#03 , note#04 , note#05 , note#06 , note#07 , note#08 , note#08a , note#09 , note#10 , note#11
 

Tutorial examples and Applications 

Supplementary Tutorial on Website

Start to use EVIEWS

Subject objectives: This course aims to introduce relevant quantitative methods for time-series analysis, modeling and forecasting. Topics include economic fluctuation and cycle, seasonality, time trend modeling, unit roots and stationary tests, distributed lag model, ARIMA model, logit model, Probit model, simultaneous-equations model, VAR model, ARCH and GARCH model, etc. Emphasis will be put on the applications in economics, finance and business related areas. Computing is an integral part of this course. All students are required to practice data analyzing, modeling and forecasting by using computer software EVIEWS.

Pre-requisite: ECON 2170 Applied Econometrics or equivalence

Textbook:  DeLurgio, Stephen A. Forecasting principles and Applications, Irwin/McGraw-Hill, 1998.

References:

    1. Clements and Herny , Forecasting Economic Times Series, Cambridge, 1998.
    2. Diebold, Elements of Forecasting, South-Western, 3/edition, 2004
    3. Franses,Time series models for business and economic forecasting, Cambridge, 1998.
    4. Gujarati, Basic Econometrics, 4/e., McGraw-Hill, 2002.
    5. Hall, Applied Economic Forecasting Techniques, Harvester-Wheatsheaf, 1994.
    6. Koop, Analysis of Economic Data, Wiley, 2000.
    7. Pindyck & Rubinfeld, Econometric Models & Economic Forecasts, 4/e., McGraw-Hill, 1998.
    8. Wallis, Time Series Analysis and Macroeconometric Modelling, Edward Elgar, 1995.
    9. Wooldridge, Introductory Econometrics, South-Western, 2000.
    10. Verbeek,  A Guide to Modern Econometrics, Wiley, 2000.
Assessment:
Class Participation and Discussion 10%
Assignment(s)  20%
Test(s) 20%
Examination 50% Course content:
1. Univariate Time Series Analysis  
    1.1 The autocorrelation function
    1.2 The autoregressive model for univariate time series
    1.3 Nonstationary versus stationary time series
    1.4 Testing Unit Roots and Extensions of the AR model
    1.5 Testing in the AR(p) with deterministic trend model
2. Applications of Econometric Models I: Time-series Models and Analysis

    2.1 Moving-average and Exponential Smoothing Methods
    2.2 Decomposition Methods and Seasonal Indexs
    2.3 Autoregressive Integrated Moving Average (ARIMA) Models
     2.4 ARIMA Intervention Analysis

3. Applications of Econometric Models II: Limited Dependent Variable Models
    3.1 Dummy Dependent Variable
    3.2 The Linear Probability Model
    3.3 The Logit Model and Probit Model

4. Applications of Econometric Models III: Multi-equation Analysis

    4.1 Simultaneous-Equations Regression Models
    4.2 The problem of Identification
    4.3 Causality, Exogeneity, Specification and Simultaneity Tests
    4.4 Two-Stage Least Squares (2SLS) and Instrument Methods
5. Applications of Econometric Models V: Dynamic System Analysis

    5.1 Autoregressive and Distributed lag models 
    5.2 Vector autoregressive model (VAR)
    5.3 Cointegration and Error Correction Model

6. Applications of Econometric Models IV: Conditional Time Varying Analysis
    6.1 ARCH model and tests
    6.2 GARCH model and tests
     

 

Teaching Methods: There are two hours of lecture and one hour of tutorial and computer exercise per week. Students are required to attend all lectures, tutorials and computer workshops. Students are also expected to read the assigned reading materials (or chapters) prior to the lecture and complete their assignments. In the one hour tutorial, there will be discussions based on topics related to the materials in the preceding lectures and will be in the form of examples, discussions and computing exercises, etc. The tutorial will be held in computer room and students will be explored to the uses of statistical software EVIEWS for practicing data analyzing, modeling and forecasting.