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Choosing the Right Type of Forecasting Model | |
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Introduction | |
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Statistics, Econometrics, and Forecasting | |
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Concept of Forecast Accuracy: Compared to What? | |
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Structural Shifts in Parameters | |
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Model Misspecification | |
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Missing, Smoothed, Preliminary, or Inaccurate Data | |
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Changing Expectations by Economic Agents | |
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Policy Shifts.Unexpected Changes in Exogenous Variables | |
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Incorrect Assumptions about Exogenity | |
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Error Buildup in Multi-Period Forecasts | |
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Alternative Types of Forecasts | |
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Point or Interval | |
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Absolute or Conditional | |
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Alternative Scenarios Weighed by Probabilities | |
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Asymmetric | |
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Single or Multi Period | |
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Short Run or Long Range | |
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Forecasting Single or Multiple Variables | |
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Some Common Pitfalls in Building Forecasting Equations | |
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Useful Tools for Practical Business Forecasting | |
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Introduction | |
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Types and Sources of Data | |
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Time Series, Cross Section, and Panel Data | |
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Basic Sources of U.S. Government Data | |
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Major Sources of International Government Data | |
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Principal Sources of Key Private Sector Data | |
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Collecting Data from the Internet | |
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Forecasting Under Uncertainty | |
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Utilizing Graphs and Charts | |
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Mean and Variance | |
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Goodness of Fit Statistics | |
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Covariance and Correlation Coefficients | |
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Standard Errors and t-ratios.F-ratios and Adjusted R-squared | |
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Using the EViews Statistical Package | |
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Utilizing Graphs and Charts | |
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Checklist Before Analyzing Data | |
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Adjusting for Seasonal Factors | |
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Checking for Outlying Values | |
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Using Logarithms and Elasticities | |
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The General Linear Regression Model | |
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Introduction | |
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The General Linear Model | |
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The Bivariate Case.Desirable Properties of Estimators | |
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Expanding to the Multivariate Case | |
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Uses and Misuses of R-Bar Squared | |
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Differences Between R-Square and R-Bar Square | |
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Pitfalls in Trying to Maximize R-Bar Square | |
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An Example: the Simple Consumption Function | |
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Measuring And Understanding Partial Correlation | |
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Covariance and the Correlation Matrix | |
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Partial Correlation Coefficients | |
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Pitfalls Of Stepwise Regression | |
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Testing and Adjusting for Autocorrelation | |
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Why Autocorrelation Occurs and What it Means | |
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Durbin-Watson Statistic to Measure Autocorrelation | |
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Autocorrelation Adjustments: Cochrane-Orcutt and Hildreth-Lu | |
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Higher Order Autocorrelation | |
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Overstatement of t-ratios When Autocorrelation is Present | |
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Pitfalls of Using the Lagged Dependent Variable | |
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Testing and Adjusting for Heteroscedasticity | |
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Causes of Heteroscedasticity in Cross-Section and Time-Series Data | |
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Measuring and Testing for Heteroscedasticity | |
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Getting Started: An Example in Eviews | |
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Predicting Retail Sales for Hardware Stores | |
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German Short-Term Interest Rates | |
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Lumber Prices | |
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Additional Topics for Single-Equation Regression Models | |
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Introduction | |
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Problems Caused by Multicollinearity | |
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Eliminating or Reducing Spurious Trends | |
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Demand for Airline Travel | |
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Log-Linear Transformation | |
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Percentage First Differences | |
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Ratios | |
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Deviations Around Trends | |
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Weighted Least Squares | |
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Summary and Comparison of Methods | |
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Distributed Lags | |
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General Discussion of Distributed Lags | |
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Polynomial Distributed Lags | |
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General Guidelines for Using PDLs | |
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Treatment of Outliers and Issues of Data Adequacy | |
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Outliers | |
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Missing Observations | |
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General Comments of Data Adequacy | |
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Uses and Misuses of Dummy Variables | |
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Single-Event Dummy Variables | |
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Changes in Dummy Variables for Institutional Structure | |
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Changes in Slope Coefficients | |
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Nonlinear Regressions | |
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Log-Linear Regressions | |
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Quadratic and Other Powers, Including Inverse | |
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Ceilings, Floors, and Kronecker Deltas: Linearizing with Dummy Variables | |
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General Steps For Formulating A Multiple Regression Equation | |
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The Consumption Function | |
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Case | |