4 resultados para full Bayes (FB) hierarchical
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of different dimensions establishes the usefulness of the proposed approach.
Resumo:
Using new linked employee-employer data for Britain in 2004, this paper shows that, on average, full-time male public sector employees earn 11.7 log wage points more than their private sector counterparts. Decomposition analysis reveals that the majority of this pay premium is associated with public sector employees having individual characteristics associated with higher pay and to their working in higher paid occupations. Further focussing analysis on the highly skilled and unskilled occupations in both sectors, reveals evidence of workplace segregation positively impacting on earnings in the private sector for the highly skilled, and in the public sector for the unskilled. Substantial earnings gaps between the highly skilled and unskilled are found, and the unexplained components in these gaps are very similar regardless of sector.
Resumo:
We analyze and quantify co-movements in real effective exchange rates while considering the regional location of countries. More specifically, using the dynamic hierarchical factor model (Moench et al. (2011)), we decompose exchange rate movements into several latent components; worldwide and two regional factors as well as country-specific elements. Then, we provide evidence that the worldwide common factor is closely related to monetary policies in large advanced countries while regional common factors tend to be captured by those in the rest of the countries in a region. However, a substantial proportion of the variation in the real exchange rates is reported to be country-specific; even in Europe country-specific movements exceed worldwide and regional common factors.
Resumo:
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.