- 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
General-to-specific Modeling
General-to-specific Modeling
- Chapter:
- (p.97) 7 General-to-specific Modeling
- Source:
- Empirical Model Discovery and Theory Evaluation
- Author(s):
David F. Hendry
Jurgen A. Doornik
- Publisher:
- The MIT Press
After noting a variety of extant approaches to automatic model selection, we consider the six main stages in formulating and implementing a Gets approach to model discovery. First, a careful formulation of the general unrestricted model (GUM) for the problem under analysis is essential. Second, the measure of congruence must be decided by choosing the mis-specification tests to be used, their forms, and significance levels. Third, the desired null rejection frequencies for selection tests must be set, together with an information criterion to select between mutually encompassing, undominated, congruent models. Fourth, the GUM needs to be appropriately estimated, depending on the weak exogeneity assumptions about the conditioning variables, which then allows congruence to be assessed. Given that is satisfactory, multiplepath reduction searches can be commenced from the GUM, leading to a set (possibly with just one member) of terminal models. These can then be checked for parsimonious encompassing of the GUM. The reliability of the whole process can be investigated by exploring sub-sample outcomes, and simulating the entire selection approach.
Keywords: General-to-specific, general unrestricted model, congruence, mis-specification tests, encompassing, exogeneity
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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
