Commission proposes a production function methodology that involves the estimation of two classes of Gaussian state space models … unobserved component models and offers frequentist as well as Bayesian estimation techniques. Additional functionalities include … preparation, model specification, and estimation processes using RGAP. …

methods applied for their estimation are as accurate as possible. A bivariate Kalman Filter (KF) model using capacity … the first-best approach for future TFP cycle estimation. This paper compares the existing method to an approach which uses …, and that this new approach leads to a reduction in the total estimation error variance and revisions required to TFP cycle …

Short-term analysis is generally performed with seasonally adjusted data from which further estimation of the business …, because seasonal adjustment and trend-cycle estimation do not share the same methodological framework, a fact which could … Nelson decompositions. We show that estimation of the various components of a given time series is feasible once the location …

model specifications for the parameters are therefore not required. Parameter estimation is carried out in the frequency …

need to use nonlinear models to describe business cycle dynamic behaviour. Their approach is model (estimation)-free, based …

develop a robust estimation approach for these slow-moving trend processes, which is guided by a judicious choice of priors … structure of the estimation procedure. The general version of the proposed Bayesian estimator with a slab-and-spike prior …