This paper applies linear and neural network-based "thick" models for forecasting inflation based on Phillips-curve formulations in the USA, Japan and the euro area. Thick models represent "trimmed mean" forecasts from several neural network models. They outperform the best performing linear...

This paper re-examines two data issues concerning euro area money demand: aggregation of national data and measurement of the own rate. The main purpose is to study if euro area money demand is subject to parameter non-constancies using formal tests rather than informal diagnostics. As a...

Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression error as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity....

This paper provides closed-form formulae for computing the asymptotic standard errors of the estimated autocovariance and autocorrelation functions for stable VAR models by means of the d-method. These standard errors can be used to construct asymptotic confidence bands for the estimated...

This paper considers the portfolio problem for high dimensional data when the dimension and size are both large.We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main factor to...