Model Comparisons in Unstable Environments
AbstractThe goal of this paper is to develop formal techniques for analyzing the relative in-sample performance of two competing, misspecified models in the presence of possible data instability. The central idea of our methodology is to propose a measure of the models' local relative performance: the "local Kullback-Leibler Information Criterion" (KLIC), which measures the relative distance of the two models' (misspecified) likelihoods from the true likelihood at a particular point in time. We discuss estimation and inference about the local relative KLIC; in particular, we propose statistical tests to investigate its stability over time. Compared to previous approaches to model selection, which are based on measures of "global performance," our focus is on the entire time path of the models' relative performance, which may contain useful information that is lost when looking for a globally best model. The empirical application provides insights into the time variation in the performance of a representative DSGE model of the European economy relative to that of VARs.
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Bibliographic InfoPaper provided by Duke University, Department of Economics in its series Working Papers with number 10-29.
Date of creation: 2010
Date of revision:
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Model Selection Tests; Misspecification; Structural Change; Kullback-Leibler Information Criterion;
Other versions of this item:
- Raffaella Giacomini & Barbara Rossi, 2009. "Model Comparisons in Unstable Environments," Working Papers 09-10, Duke University, Department of Economics.
- Raffaella Giacomini & Barbara Rossi, 2012. "Model comparisons in unstable environments," CeMMAP working papers CWP13/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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