This paper studies the joint dynamics of U.S. inflation and the average inflation predictions of the Survey of Professional Forecasters (SPF) on a sample running from 1968Q4 to 2014Q2. The joint data generating process (DGP) of these data consists of the unobserved components (UC) model of Stock...

Financial time series often exhibit properties that depart from the usual assumptions of serial independence and normality. These include volatility clustering, heavy-tailedness and serial dependence. A voluminous literature on different approaches for modeling these empirical regularities has...

The sustained elevated gold price domestically, hovering persistently above the global market price, underscores the peculiar nature of the gold market in Vietnam and the resiliently strong demand for gold in the local market. In particular, the movements in the price of gold seem to lead a...

This paper discusses estimation of US inflation volatility using time varying parameter models, in particular whether it should be modelled as a stationary or random walk stochastic process. Specifying inflation volatility as an unbounded process, as implied by the random walk, conflicts with...

We argue in this paper that the Great Inflation of the 1970s can be understood as the result of equilibrium indeterminacy in which loose monetary policy engendered excess volatility in macroeconomic aggregates and prices. We show, however, that the Federal Reserve inadvertently pursued policies...

This paper presents evidence on why inflation pass-through from oil shocks in the 21st century relative to the 1970s has dampened. First, results suggest global business cycle demand driven oil shocks are not inflationary. Second, there has been a reduction in inflation pass-through from oil...

The deviance information criterion (DIC) has been widely used for Bayesian model comparison. However, recent studies have cautioned against the use of the DIC for comparing latent variable models. In particular, the DIC calculated using the conditional likelihood (obtained by conditioning on the...

The empirical support for a DSGE type of real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure that makes use of a finite mixture of many models within the class of vector autoregressive (VAR) processes. The linear VAR model is extended to...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...