In this paper, we show the interest of the time-varying coefficient model in hedge fund performance assessment and selection. We argue that the alpha of hedge funds is dynamic and that the time-varying alpha captures this dynamic behavior. Therefore, forming portfolios based on their...

This article studies inflation persistence with time-varying coefficient autoregressions for twelve central European countries, in comparison with the United States and the euro area. Inflation persistence tends to be higher in times of high inflation. Since the oil price shocks, inflation...

This paper studies inflation persistence with time-varying coefficient autoregressions for twelve central European countries,in comparison with the United States and the euro area. Inflation persistence tends to be higher in times of high inflation. Since the oil price shocks, inflation...

This article studies inflation persistence with time-varying coefficient autoregressions for twelve central European countries, in comparison with the United States and the euro area. Inflation persistence tends to be higher in times of high inflation. Since the oil price shocks, inflation...

On the basis of a disaggregated data set, we study inflation persistence in Hungary by focusing on regional cross-sectional variation. To this end, we use regional inflation series constructed from individual store-level price quotes. The price observations were collected for the CPI database at...

We propose an extension of a seasonal modulation smooth model with P-splines for times series data using a mixed model formulation. A smooth trend with seasonality decomposition can be estimated simultaneously. We extend the model to consider the forecasting of new future observations in the...

This paper provides a method to estimate time varying coefficients structural VARs which are non-recursive and potentially overidentified. The procedure allows for linear and non-linear restrictions on the parameters, maintains the multi-move structure of standard algorithms and can be used to...

Using Monte Carlo methods, we compare the ability of the Kalman-filter, the Kalman-smoother and the flexible least squares (FLS) to uncover the parameters of an autoregression. We find that the ordinary least squares (OLS) estimator performs much better that the time-varying coefficient methods...