This paper surveys the techniques of wavelets analysis and the associated methods of denoising. The Discrete Wavelet Transform and its undecimated version, the Maximum Overlapping Discrete Wavelet Transform, are described. The methods of wavelets analysis can be used to show how the frequency...

This paper introduces a new model of structural breaks which assumes that structural breaks are driven by large economic shocks. The model specifies that both the timing and size of breaks are stochastic and it can be used to investigate the impact of large economic shocks on the stability of...

In this paper we suggest a number of statistical tests based on neural network models, that are designed to be powerful against structural breaks in otherwise stationary time series processes while allowing for a variety of nonlinear specifications for the dynamic model underlying them. It is...

This paper applies a new model of structural breaks developed by Kapetanios and Tzavalis (2004) to investigate if there exist structural changes in the mean reversion parameter of US macroeconomic series. Ignoring such type of breaks may lead to spurious evidence of unit roots in the...

This paper presents a new model of stochastic volatility which allows for infrequent shifts in the mean of volatility, known as structural breaks. These are endogenously driven from large innovations in stock returns arriving in the market. The model has a number of interesting properties. Among...

In this paper, a Bayesian approach is suggested to compare unit root models with stationary models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. The paper utilizes analytic and Monte Carlo integration techniques for calculating...

This paper revisits a number of data-rich prediction methods, like factor models, Bayesian ridge regression and forecast combinations, which are widely used in macroeconomic forecasting, and compares these with a lesser known alternative method: partial least squares regression. Under the...

This paper provides a review which focuses on forecasting using statistical/econometric methods designed for dealing with large data sets.

The paper provides a proof of consistency of the ridge estimator for regressions where the number of regressors tends to infinity. Such result is obtained without assuming a factor structure. A Monte Carlo study suggests that shrinkage autoregressive models can lead to very substantial...

This paper proposes a new regression model - a smooth transition mixed data sampling (STMIDAS) approach - that captures recurrent changes in the ability of a high frequency variable in predicting a low frequency variable. The STMIDAS regression is employed for testing changes in the ability of...