This Paper proposes a method to conduct inference in panel VAR models with cross-unit interdependencies and time variations in the coefficients. The set-up used is Bayesian, and Markov chain Monte Carlo (MCMC) methods are used to estimate the posterior distribution of the features of interest....

Managers in the fundraising and public sectors face the constant challenge of soliciting donations from a population who may or may not have donated before. Rather than merely asking respondents what they wish to donate, it is standard practice to present a set of suggested amounts – the...

I study whether and how US shocks are transmitted to eight Latin American countries. US shocks are identified using the procedure of Canova and De Nicolo’ (2002) and treated as exogenous with respect to Latin American economies. Posterior estimates for individual and average effects are...

We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in the U.S. unemployment rates. We extract the common dynamics amongst unemployment rates disaggregated for 7 age groups. The framework allows analysis of the contribution of demographic...

In this paper we consider inference procedures for two types of dynamic linear panel data models with fixed effects. First, we show that the closure of the stationary ARMA panel model with fixed effects can be consistently estimated by the First Difference Maximum Likelihood Estimator and we...

Continuous-time stochastic volatility models are becoming a more and more popular way to describe moderate and high-frequency financial data. Recently, Barndorff-Nielsen and Shephard (2001a) proposed a class of models where the volatility behaves according to an Ornstein-Uhlenbeck process,...

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model that accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for...

This paper considers inference procedures for two types of dynamic linear panel data models with fixed effects (FE). First, it shows that the closures of stationary ARMAFE models can be consistently estimated by Conditional Maximum Likelihood Estimators and it derives their asymptotic...