Trend growth in total factor productivity (TFP) is unobserved; it is frequently assumed to evolved continuously over time. That assumption is inherent in the use of the Hodrick-Prescott or Bandpass filter to extract trend. Similarly, the Kalman filter/unobserved-components approach assumes that...

Demonstration that our noise filtering procedure is extremely robust on the basis of the following experiment. The noise filtering procedure was applied first to an empirical correlation matrix and, second, to the matrix built from the same time series deliberately contaminated with noise. The...

Demonstration that our noise filtering procedure is extremely robust on the basis of the following experiment. The noise filtering procedure was applied first to an empirical correlation matrix and, second, to the same matrix deliberately contaminated with noise. The final, noise filtered...

This paper proposes a parsimonious threshold stochastic volatility (SV) model for financial asset returns. Instead of imposing a threshold value on the dynamics of the latent volatility process of the SV model, we assume that the innovation of the mean equation follows a threshold distribution...

Particle filtering is a useful statistical tool which can be used to make inference on the latent variables and the structural parameters of state space models by employing it inside MCMC algorithms (Flury and Shephard, 2011). It only relies on two assumptions (Gordon et al, 1993): a: The...

Estimating regional integration faces challenges because of incomplete data from missing values and insufficient time spans. A key advantage of a dynamic factor model estimated using the Bayesian state-space approach is its ability to handle missing values and aggregation of the regional...

Changes in net positions of foreign and local investors in the forward market may have differential effects on the spot exchange rate. This paper assesses the role of different sectors in the derivatives market and their potential impact with other fundamentals on the spot exchange rate in...

This paper develops a wavelet (spectral) approach to test the presence of a unit root in a stochastic process. The wavelet approach is appealing, since it is based directly on the different behavior of the spectra of a unit root process and that of a short memory stationary process. By...

We investigate the time-scale relationships between the ten S&P sectors and the market through the use of wavelet analysis, a methodology that has widespread acceptance for investigating multi-horizon properties of time series. Our analysis of the data highlights that variation in the pattern of...

This paper develops a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require instruments and yields...