Practical business forecasting

523 Pages·2002·3.118 MB·English

by  Evans, Michael K

P B
RACTICAL USINESS
F
ORECASTING
Michael K. Evans
Blackwell
Publishers

PRACTICAL BUSINESS FORECASTING

P B
RACTICAL USINESS
F
ORECASTING
Michael K. Evans
Blackwell
Publishers
© Michael K.Evans 2003
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First published 2002 by Blackwell Publishers Ltd,a Blackwell Publishing company
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ISBN 0-631-22066-6 (pbk)
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To Sophie Evans Brill

C
ONTENTS
Acknowledgments xv
Preface xvi
PART I 1
1. Choosing the Right Type of Forecasting Model 3
Introduction 3
1.1 Statistics, Econometrics, and Forecasting 4
1.2 The Concept of Forecasting Accuracy:
Compared to What? 5
1.2.1 Structural Shifts in Parameters 8
1.2.2 Model Misspecification 9
1.2.3 Missing,Smoothed,Preliminary,or Inaccurate
Data 10
1.2.4 Changing Expectations by Economic Agents 13
1.2.5 Policy Shifts 14
1.2.6 Unexpected Changes in Exogenous Variables 15
1.2.7 Incorrect Assumptions about Exogeneity 17
1.2.8 Error Buildup in Multi-period Forecasts 17
1.3 Alternative Types of Forecasts 18
1.3.1 Point or Interval 18
1.3.2 Absolute or Conditional 19
1.3.3 Alternative Scenarios Weighed by Probabilities 19
1.3.4 Asymmetric Gains and Losses 20
1.3.5 Single-period or Multi-period 21
1.3.6 Short Run or Long Range 21
1.3.7 Forecasting Single or Multiple Variables 22
1.4 Some Common Pitfalls in Building
Forecasting Equations 22
Problems and Questions 25
viii CONTENTS
2. Useful Tools for Practical Business Forecasting 29
Introduction 29
2.1 Types and Sources of Data 30
2.1.1 Time-series,Cross-section,and Panel Data 30
2.1.2 Basic Sources of US Government Data 32
2.1.3 Major Sources of International Government
Data 34
2.1.4 Principal Sources of Key Private Sector Data 35
2.2 Collecting Data from the Internet 37
2.3 Forecasting Under Uncertainty 38
2.4 Mean and Variance 40
2.5 Goodness-of-Fit Statistics 42
2.5.1 Covariance and Correlation Coefficients 42
2.5.2 Standard Errors and t-ratios 43
2.5.3 F-ratios and Adjusted R-squared 44
2.6 Using the EViews Statistical Package 46
2.7 Utilizing Graphs and Charts 49
2.8 Checklist Before Analyzing Data 55
2.8.1 Adjusting for Seasonal Factors 56
2.8.2 Checking for Outlying Values 56
2.9 Using Logarithms and Elasticities 58
Problems and Questions 60
PART II 65
3. The General Linear Regression Model 67
Introduction 67
3.1 The General Linear Model 68
3.1.1 The Bivariate Case 68
3.1.2 Desirable Properties of Estimators 69
3.1.3 Expanding to the Multivariate Case 70
3.2 Uses and Misuses of R2 70
3.2.1 Differences Between R2 and R2 71
3.2.2 Pitfalls in Trying to Maximize R2 71
3.2.3 An Example:The Simple Consumption Function 72
3.3 Measuring and Understanding Partial
Correlation 75
3.3.1 Covariance and the Correlation Matrix 75
3.3.2 Partial Correlation Coefficients 76
3.3.3 Pitfalls of Stepwise Regression 77
3.4 Testing and Adjusting for Autocorrelation 77
3.4.1 Why Autocorrelation Occurs and What it Means 78
3.4.2 Durbin–Watson Statistic to Measure
Autocorrelation 79