- Title Pages
- About the Arne Ryde Foundation
- Preface
- Acknowledgments
- Glossary
- Data and Software
-
1 Introduction -
2 Discovery -
3 Background to Automatic Model Selection -
4 Empirical Modeling Illustrated -
5 Evaluating Model Selection -
6 The Theory of Reduction -
7 General-to-specific Modeling -
8 Selecting a Model in One Decision -
9 The 2-variable DGP -
10 Bias Correcting Selection Effects -
11 Comparisons of 1-cut Selection with Autometrics -
12 Impact of Diagnostic Tests -
13 Role of Encompassing -
14 Retaining a Theory Model During Selection -
15 Detecting Outliers and Breaks Using IIS -
16 Re-modeling UK Real Consumers' Expenditure -
17 . Comparisons of Autometrics with Other Approaches -
18. Model Selection in Underspecified Settings -
19 More Variables than Observations -
20 Impulse-indicator Saturation for Multiple Breaks -
21 Selecting Non-linear Models -
22 Testing Super Exogeneity -
23 Selecting Forecasting Models -
24 Epilogue - References
- Author Index
- Index
Retaining a Theory Model During Selection
Retaining a Theory Model During Selection
- Chapter:
- (p.167) 14 Retaining a Theory Model During Selection
- Source:
- Empirical Model Discovery and Theory Evaluation
- Author(s):
David F. Hendry
- Publisher:
- The MIT Press
Economic theories are often fitted directly to data to avoid any issues of model selection. This is an excellent strategy when the theory is complete and correct, but less successful otherwise. We consider embedding a theory model that specifies the set of n relevant exogenous variables, xt, within a larger set of n+k candidate variables, (xt; wt), but only select over the wt. When the theory model is complete and correct, so the wtare in fact irrelevant, by orthogonalizing them with respect to the xt, selection over the orthogonalized components can be undertaken without affecting the theory parameters’ estimator distributions. This strategy keeps the theory-parameter estimates when the theory is correct, yet protects against the theory being underspecified when some wt are relevant
Keywords: Retaining theory models, orthogonalizing candidate variables, theory evaluation
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- Title Pages
- About the Arne Ryde Foundation
- Preface
- Acknowledgments
- Glossary
- Data and Software
-
1 Introduction -
2 Discovery -
3 Background to Automatic Model Selection -
4 Empirical Modeling Illustrated -
5 Evaluating Model Selection -
6 The Theory of Reduction -
7 General-to-specific Modeling -
8 Selecting a Model in One Decision -
9 The 2-variable DGP -
10 Bias Correcting Selection Effects -
11 Comparisons of 1-cut Selection with Autometrics -
12 Impact of Diagnostic Tests -
13 Role of Encompassing -
14 Retaining a Theory Model During Selection -
15 Detecting Outliers and Breaks Using IIS -
16 Re-modeling UK Real Consumers' Expenditure -
17 . Comparisons of Autometrics with Other Approaches -
18. Model Selection in Underspecified Settings -
19 More Variables than Observations -
20 Impulse-indicator Saturation for Multiple Breaks -
21 Selecting Non-linear Models -
22 Testing Super Exogeneity -
23 Selecting Forecasting Models -
24 Epilogue - References
- Author Index
- Index
