Economics 4312

Business Cycles and Forecasting

Dr. Tom Kelly

Office: A.301.2 Hankamer

Phone: 710-4146

Fax: 710-6142

E-Mail: Tom_Kelly@baylor.edu

**Home
Page: http://hsb.baylor.edu/html/kellyt/home.htm**

** **

**Purpose of
the Course**: To introduce you to the concepts, tools, and
techniques used by economists for business forecasting.

**The
Textbook**: Hanke and Wichern, *Business
Forecasting*, (8th^{d} edition)

**General
Requirements**:
All students will be asked to read and work
computer lab assignments based upon the textbook, participate in class
discussions of course content, and perform written examinations based upon
course content. Assignments are due no
more than **two** days after they are assigned. To prepare for each class session, refer to
the schedule below.

**Additional
Graduate Student Requirement**: In order to receive graduate credit each
graduate student in addition to general requirements must also develop a
statistical forecast of the future performance of an assigned industry. Focus will be placed on demand estimation of
industry performance using multiple regression analysis using panel data from
published (or on line) data sources.
Students are expected to write a report to describe their forecasting
methods and findings and how their results may be used with respect to current
and future business strategy of a firm in that industry.

**Computer
Requirements**: We will
use Excel as our primary statistical package, using the MegaStat feature in
addition to normal spread sheet calculations.

**Grades
will be based upon the following requirements:**

·
**Undergraduate
students **

o
Two one-hour in class exams worth 20% each and a
comprehensive final exam worth 30% of your final grade.

o
Five written lab assignments and class discussion
worth 30% for undergraduate students.

·
**Graduate
students**

o
Two hourly exams valued at 20% each and comprehensive
final exam valued at 30%.

o
Completion of all lab assignments and class
participation in order to receive credit in the course.

o
Completion of additional research and report on
estimated demand forecast for selected industry valued at 30%.

**Course Topics**

**Chapter 1: Introduction to Forecasting**

** **The history of forecasting

The need for forecasting

Types of forecasts

Macroeconomic v.
microeconomic forecasting

Choosing a forecasting
method

Steps in forecasting

Managing the forecasting
process

Computer forecasting
packages

Online information

**Chapter 2: A Review of Basic Statistical Concepts**

** **Descriptive statistics

Probability distributions

Sampling distributions

Inference from a sample

Estimation and
hypothesis testing

**Chapter 3: Exploring Data Patterns and Choosing a
Forecasting Technique**

** **Exploring time series data patterns

Using autocorrelation
analysis

Choosing a technique
based on autocorrelation analysis

Measuring forecasting
error

Determining the adequacy
of a forecasting technique

**Lab Assignment 1**: Using Eviews to identify data
patterns

**Chapter 4: Moving Averages and Smoothing Methods**

Naïve models

Simple and moving
averaging models

Double moving average
models

Single exponential smoothing models

Double exponential smoothing models

Holt model to adjust for trend

Holt-Winters model to adjust for trend and seasonal
variation

Application to management

**Lab Assignment 2**:
Using MegaStat to forecast with time series models

**Chapter 5: Time Series and Their Components**

** **Decomposition model

Trend curves and
forecasts

Seasonal adjustment and
forecasting a seasonal time series

Cyclical
and irregular adjustment

The Census II
decomposition method

Application to
management

**Lab Assignment 3**: Using
MegaStat to forecast with a decomposition model.

**Exam I on Chapters 1 - 5 **

**Chapter 6: Simple Linear Regression**

Least squares regression
line specification and estimation

Evaluation of regression
results

Point and interval
forecasts of the dependent variable

Coefficient of
determination

Analysis of residuals

Variable transformations

Growth curves

Application to management

**Chapter 7: Multiple Regression Analysis**

** **Selection of predictor variables

Evaluation of
correlation matrix

Estimation of a multiple
regression model

Interpreting regression
coefficients

Point and interval
forecasts

Dummy variables

Multicollinearity

Diagnostics and residual
analysis

Application to
management

**Lab Assignment 4**: Using
MegaStat to forecast with a multiple regression model.

**Chapter 8: Regression with Time Series Data**

** **The problem of autocorrelation

Durbin-Watson test for
autocorrelation of error terms

Solutions to
autocorrelation problems

Model specification
error

Generalized least
squares

Autoregressive models

The problem of
heteroscedasticity

Application to
management

**Lab Assignment 5**: Using
Excel MegaStat to eliminate autocorrelation.

**Exam II on Chapters 6 - 8**

**Chapter 9: The Box-Jenkins (ARIMA) Methodology**

** **Determining a model using the
Box-Jenkins methodology

Implementing the
model-building strategy

Application to
management

**Chapter 10: Judgmental Forecasting and Forecast
Adjustments**

** **The Dephi Method

Scenario writing

Combining forecasts

Summary of judgmental
forecasting

**Chapter 11: Managing the Forecasting Process**

** **The forecasting process

Monitoring forecasts

Forecasting
responsibility

Forecasting costs

Forecasting and the MIS
system

Selling forecasting to
management

The future of
forecasting

**Final Exam on Chapters 1 - 11**

** **