We explore a century-long dataset with a Markov-switching structural VAR to estimate state-dependent government spending multipliers. We show that the multiplier values are statistically larger during recessions than during expansions. However, the multipliers are always smaller than 1. Our...

Wir konstruieren ein neues Modell unbeobachteter Komponenten mit Markov-Switching zur Analyse von Hysterese-Effekten, also der Verfestigung ursprünglich zyklischer Fluktuationen. Das Modell kombiniert die Bestandteile einer Trend-Zyklus Zerlegung, der Identifikation von gegenseitigen...

This paper develops a multivariate regime switching monetary policy model for the US economy. To exploit a large dataset we use a factor-augmented VAR with discrete regime shifts, capturing distinct business cycle phases. The transition probabilities are modelled as time-varying, depending on a...

This paper proposes a Markov-switching framework to endogenously identify periods where economies are more likely to:(i) synchronously enter recessionary and expansionary phases, and (ii) follow independent business cycles. The reliability of the framework is validated with simulated data in...

We investigate whether the United States economy responds negatively to oil price uncertainty and whether oil price shocks exert asymmetric effects on economic activity. In doing so, we relax the assumption in the existing literature that the data are governed by a single process, modifying the...

In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...

We study the comovement of international business cycles in a time series clustering model with regime-switching. We extend the framework of Hamilton and Owyang (2012) to include time-varying transition probabilities to determine what drives similarities in business cycle turning points. We find...

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...

The existing literature on estimated structural News Driven Business Cycle (NDBC) models has focused almost exclusively on macroeconomic data and has largely ignored asset prices. In this paper, we present evidence that including data on asset prices in the estimation of a structural NDBC model...

We develop a multivariate unobserved components model to extract business cycle and financial cycle indicators from a panel of economic and financial time series of four large developed economies. Our model is flexible and allows for the inclusion of cycle components in different selections of...