Evaluating Automatic Model Selection
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We outline a range of criteria for evaluating model selection approaches that have been used in the literature. Focusing on three key criteria, we evaluate automatically selecting the relevant variables in an econometric model from a large candidate set. General-to-specific selection is outlined for a regression model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors. Comparisons with an automated model selection algorithm, Autometrics (Doornik, 2009), show similar properties, but not restricted to orthogonal cases. Monte Carlo experiments examine the roles of post-selection bias corrections and diagnostic testing as well as evaluate selection in dynamic models by costs of search versus costs of inference.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Periodicity, Non-stationarity, and Forecasting of Economic and Financial Time Series: Editors' Introduction
- Consideration of Trends in Time Series
- Detecting Common Dynamics in Transitory Components
- Nonparametric Tests for Periodic Integration
- Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots
- Econometric Modelling of Time Series with Outlying Observations
- Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index
- Evaluating Automatic Model Selection
- On a Graphical Technique for Evaluating Some Rational Expectations Models
- Modeling the Volatility-Return Trade-Off When Volatility May Be Nonstationary
- HYBRID GARCH Models and Intra-Daily Return Periodicity
Articles in the same Issue
- Article
- Periodicity, Non-stationarity, and Forecasting of Economic and Financial Time Series: Editors' Introduction
- Consideration of Trends in Time Series
- Detecting Common Dynamics in Transitory Components
- Nonparametric Tests for Periodic Integration
- Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots
- Econometric Modelling of Time Series with Outlying Observations
- Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index
- Evaluating Automatic Model Selection
- On a Graphical Technique for Evaluating Some Rational Expectations Models
- Modeling the Volatility-Return Trade-Off When Volatility May Be Nonstationary
- HYBRID GARCH Models and Intra-Daily Return Periodicity
