EC490 Business Forecasting
SOUTHEAST MISSOURI STATE UNIVERSITY
Department of Economics and Finance
COURSE SYLLABUS, EC490, Business Forecasting
Revised in October 1989
I. Catalog Description and Credit Hours of Course
Introduction to the various econometric forecasting techniques available to deal with economic and business prediction. (3)
MA134 College Algebra
EC215 Principles of Microeconomics
EC225 Principles of Macroeconomics
III. Purposes or Objectives of the Course
A. To introduce the various forecasting theories and techniques available in the areas of economics and business
B. To familiarize students with the application of statistics and the use of packaged computer programs for the forecasting purpose.
C. To provide students with basic skills that are commonly used in the field.
IV. Expectations of Students
A. Students will be expected to attend class regularly and participate in discussion
B. Students will also be expected to accomplish their own forecasting projects with actual economic and business data
C. Students will be required to use mainframe or personal computers.
V. Course Outline
A. Introduction to Forecasting
1. Characteristics of Forecasts
2. Essential materials of forecasting
a. data sources - public, private and international
b. data bases
3. Choice of appropriate techniques
B. Trend Analysis
1. Moving averages models
2. Smoothing models (e.g., exponential models)
3. Seasonal Models
C. Regressions Procedures and Analysis
1. Simple linear regression
2. Multiple linear regression
3. Nonlinear regression
4. Further topics
D. Advanced Forecasting Techniques
1. Time series models
2. The Box-Jenkins Models
3. Subjective information model
4. Technological forecasting
5. Forecasting errors and Tracking signals
6. Recent developments
VI. Textbook(s) and/or Other Required Materials or Equipment
Forecasting Principles and Applications, SAtephen A. DeLurgio, McGraw-Hill, 1998.
SAS/ETS: Statistical Analysis System/Econometric Time Series
VII. Basis of Student Evaluation
A. Performance on regular in-class exams and the final exam.
B. Participation in class discussion and performance on class assignments.
C. Performance on the student's own forecasting project.