It is common in empirical macroeconomics to fit vector autoregressive (VAR) models to construct estimates of impulse responses. An important preliminary step in impulse response analysis is the selection of the VAR lag order. In this paper, we compare the six lag-order selection criteria most...

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

In this paper, we propose a new Empirical Information Criterion (EIC) for model selection which penalizes the likelihood of the data by a function of the number of parameters in the model. It is designed to be used where there are a large number of time series to be forecast. However, a...

A new method, called relevant transformation of the inputs network approach (RETINA) is proposed as a tool for model building and selection. It is designed to improve on some of the shortcomings of neural networks. RETINA has the flexibility of neural network models, the concavity of the...

In Perez-Amaral, Gallo, and White (2003), the authors proposed an automatic predictive modelling tool called Relevant Transformation of the Inputs Network Approach (RETINA). It is designed to embody flexibility (using nonlinear transformations of the predictors of interest), selective search...

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

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 addresses the growing gulf between traditional macroeconometrics and the increasingly dominant preference among macroeconomists to use DSGE models and to estimate them using Bayesian estimation with strong priors but not to test them as they are likely to fail conventional statistical...