Part
I: Choosing the
Right Type of Forecasting Model: 
(001.pdf, size 203KB)
Introduction
1. Statistics, Econometrics, and Forecasting
2. Concept of Forecast Accuracy: Compared to What?
3. Alternative Types of Forecasts
4. Some Common Pitfalls in Building Forecasting Equations |
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Part
II: Useful Tools
for Practical Business Forecasting:
(002.pdf, size 326KB)
Introduction
5. Types and Sources of Data
6. Collecting Data from the Internet
7. Forecasting Under Uncertainty
8. Utilizing Graphs and Charts
9. Mean and Variance
10. Goodness of Fit Statistics
11. Using the EViews Statistical Package
12. Utilizing Graphs and Charts
13. Checklist Before Analyzing Data
14. Using Logarithms and Elasticities |
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Part
III: The General Linear Regression Model:
Introduction
15. The General Linear Model
16. Uses and Misuses of R-Bar Squared
17. Measuring And Understanding Partial Correlation
18. Testing and Adjusting for Autocorrelation
19. Testing and Adjusting for Heteroscedasticity
20. Getting Started: An Example in Eviews |
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Part
IV: Additional Topics for Single-Equation
Regression Models:
Introduction
21. Problems Caused by Multicollinearity
22. Eliminating or Reducing Spurious Trends
23. Distributed Lags
24. Treatment of Outliers and Issues of Data Adequacy
25. Uses and Misuses of Dummy Variables
26. Nonlinear Regressions
27. General Steps For Formulating A Multiple Regression
Equation |
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Part
V: Forecasting with a Single-Equation
Regression Model:
Introduction
28. Checking for Normally Distributed Residuals
29. Testing for Equation Stability and Robustness
30. Evaluating Forecast Accuracy
31. The Effect of Forecasting Errors in the Independent
Variables
32. Comparison with Naïve Models
33. Adjusting the Coefficients of the Model When Forecasting
34. Buildup of Forecast Error Outside the Sample Period |
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Part
VI: Elements Of Univariate Time-Series
Methods:
Introduction
35. The Basic Time-Series Decomposition Model
36. Linear and Nonlinear Trends
37. Methods of Smoothing Data
38. Methods of Seasonal Adjustment |
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Part
VII: Univariate Time Series Modeling
and Forecasting:
Introduction
39. Box-Jenkins Philosophy: Combining Theoretical and
Practical Forecasts
40. ARIMA Models
41. Stationary and Integrated Series
42. Identification
43. Seasonal Factors in ARMA Modeling
44. Estimation of ARMA Models
45. Diagnostic Checking and Forecasting |
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Part
VIII: Combining Forecasts:
Introduction
46. Outline of the Theory of Forecast Combination
47. Major Sources of Forecast Error
48. Combining Methods of Nonstructural Estimation
49. Combining Structural and Nonstructural Methods
50. The Role of Judgment in Forecasting
51. The Role of Consensus Forecasts
52. Adjusting Constant Terms and Slope Coefficients
53. Combining Forecasts: Summary |
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Part
IX: Building and Presenting Short-Term
Sales Forecasting Models:
Introduction
54. Organizing the Sales Forecasting Procedure
55. Endogenous and Exogenous Variables in Sales Forecasting
56. The Role of Judgment
57. Presenting Sales Forecasts |
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Part
X: Methods of Long-Term Forecasting:
Introduction
58. Nonparametric Methods of Long-Term Forecasting
59. Statistical Methods of Determining Nonlinear Trends:
Nonlinear Growth and Decline, Logistics, and Saturation
Curves
60. Predicting Trends Where Cyclical Influences are Important
61. Projecting Long-Run Trends in Real Growth
62. Forecasting Very Long-Range Trends: Population and
Natural Resource Trends |
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Part
XI: Simultaneous Equation Models:
Introduction
63. Simultaneity Bias in a Single Equation
64. Estimating Simultaneous Equation Models
65. Further Issues in Simultaneous Equation Model Forecasting
66. Summary |
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Part
XII: Alternative Methods of Macroeconomic
Forecasting:
Introduction
67. Structural vs. VAR Models
68. Solving Structural Macroeconomic Models
69. A Prototype Macroeconomic Model
70. Simulating the Model
71. Preparing the Model for Forecasting
72. Using the Leading Indicators for Macroeconomic Forecasting
73. Using Indexes of Consumer and Business Sentiment
for Forecasting
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