In linear specifications, the bias due to the presence of measurement error in a regressor can be entirely avoided when either repeated measurements or instruments are available for the mismeasured regressor. The situation is more complex in nonlinear settings. While identification and root n...

Predictability is time and frequency dependent. We propose a new forecasting method - forecast combination in the frequency domain - that takes this fact into account. With this method we forecast the equity premium and real GDP growth rate. Combining forecasts in the frequency domain produces...

The wavelet transform is used to identify a biannual and an annual seasonality in the Phelix Day Peak and to separate the long-term trend from its short-term motion. The short-term/long-term model for commodity prices of Schwartz & Smith (2000) is applied but generalised to account for weekly...

In this paper, we map the process of synchronization of the Visegrad Four within the framework of the European Union using wavelet techniques. We show that the relationship of among countries is dynamic and that it varies over time and across frequencies. We study the synchronization applying...

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility, and study its properties. Based on an...

This paper studies the dynamics of Mexican inflation by using a wavelet multiresolution analysis on 16 indexes of the Mexican Consumer Price Index. This enables us to estimate the long-term trend, seasonality, and local shocks of the inflation series, even when the series are non-stationary. The...