Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose...

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose...

This paper argues that the sometimes-conflicting results of a modern revisionist literature on data mining in econometrics reflect different approaches to solving the central problem of model uncertainty in a science of non-experimental data. The literature has entered an exciting phase with...

In principle, making credit decisions under uncertainty can be approached by estimating the potential future outcomes that will result from the various decision alternatives. In practice, estimation difficulties may arise as a result of selection bias and limited historic testing. We review some...

The objective of this study is to compare alternative computerized model-selection strategies in the context of the vector autoregressive (VAR) modeling framework. The focus is on a comparison of subset modeling strategies with the general-to-specific reduction approach automated by PcGets....

The Hoover?Perez description of the LSE [London School of Economics] general-to-specific methodology of model selection is formalized and analysed using the the-ory of model selection. Numerical evidence is provided to justify the claim that simple and elegant information criteria (which are...

The objective of this study is to compare alternative computerized model-selection strategies in the context of the vector autoregressive (VAR) modeling framework. The focus is on a comparison of subset modeling strategies with the general-to-specific reduction approach automated by PcGets....

Kevin Hoover and Stephen Perez take important steps towards resolving some key issues in econometric methodology. They simulate general-to-specific selection for linear, dynamic regression models, and find that their algorithm performs well in re-mining the ?Lovell database?. We discuss...

Unrestricted reduced form vector autoregressive (VAR) models have become a dominant research strategy in empirical macroeconomics since Sims (1980) critique of traditional macroeconometric modeling. They are however subjected to the curse of dimensionality. In this paper we propose...

In this paper we face the fitting versus forecasting paradox with the objective of realizing an optimal Early Warning System to better describe and predict past and future sovereign defaults. We do this by proposing a new Regression Tree-based model that signals a potential crisis whenever...