DSGE models are typically estimated using Bayesian methods, but a researcher may want to estimate a DSGE model with full information maximum likelihood (FIML) so as to avoid the use of prior distributions. A very robust algorithm is needed to find the global maximum within the relevant parameter...

We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil using a combination of probabilistic individual model forecasts. Our combination method extends earlier approaches that have been applied to oil price forecasting, by allowing...

This paper studies the role of global and regional variations in economic activity and policy in developed world in driving portfolio capital flows (PCF) to emerging markets (EMs) in a Factor Augmented Vector Autoregressive (FAVAR) framework. Results suggest that PCFs to EMs depend mainly on...

Central banks have usually employed short-term rates as the main instrument of monetary policy. In the last decades, however, forward guidance has also become a central tool for monetary policy. In an innovative way this paper combines two sources of extraneous information - high frequency...

We estimate output growth rate spectra for 58 countries. The spectra exhibit diverse shapes. To study the sources of this diversity, we estimate the short-run, business cycle, and long-run frequency components of the sampled series. For most OECD countries the bulk of the spectral mass is in the...

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

We study how the output gap affects potential output over time-i.e., the dynamic hysteresis effect. To do so, we introduce novel unobserved components (UC) models that consider hysteresis as a sequence of lagged effects, thus separating the long-run recession-induced adverse effects from other...

We study the time-varying effects of Tobin's q and cash flow on investment dynamics in the USA using a vector autoregression model with drifting parameters and stochastic volatilities estimated via Bayesian methods. We find significant variation over time of the response of investment to shocks...