We bring the notion of connectedness (Diebold and Yilmaz, 2012) to a set of two critical macroeconomic variables as inflation and unemployment. We focus on the G7 economies plus Spain, and use monthly data –high-frequency data in a macro setting– to explore the extent and consequences of...

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...

Recessions and expansions are often caused or reinforced by developments in private consumption - the largest component of aggregate demand - which, as a result, varies over the business cycle. As such, an accurate measurement of the cyclical component of consumption and an understanding of its...

The conventional wisdom that inflation and unemployment are unrelated in the long-run implies the compartmentalisation of macroeconomics. While one branch of the literature models inflation dynamics and estimates the unemployment rate compatible with inflation stability, another one determines...

This paper provides new evidence on the effects of government spending shocks and the fiscal transmission mechanism in the euro area for the period 1980-2008. Our contribution is two-fold. First, we investigate changes in the macroeconomic impact of government spending shocks using time-varying...

We propose using sign restrictions to identify regional labor demand shocks in a panel VAR of US federal states. Observed migration responds significantly, but less persistently than the residual-based migration measure constructed by Blanchard and Katz (1992)

We introduce a new and general methodology for analyzing vector autoregressive models with time-varying coefficient matrices and conditionally heteroskedastic disturbances. Our proposed method is able to jointly treat a dynamic latent factor model for the autoregressive coefficient matrices and...