Taking as data-generation process a standard DSGE model, we show via Monte Carlo that reliably detecting hysteresis, defined as the presence of aggregate demand shocks with a permanent impact on output, is a significant challenge, as model-consistent identification schemes (i) spuriously detect...

We search for the presence of hysteresis, which we define as aggregate demand shocks that have a permanent impact on real GDP, in the U.S., the Euro Area, and the U.K. Working with cointegrated structural VARs, we find essentially no evidence of such effects. Within a Classical statistical...

We study whether the response of the economy to structural shocks changes at the zero lower bound. Monte Carlo evidence suggests that VARs have a limited ability to detect changes in impulse response functions at the ZLB compared to the standard environment with positive interest rates. This...

I use Bayesian VARs with stochastic volatility to forecast global temperatures and sea level and ice cover in the Northerin emisphere until 2010, by exploiting (i) their long-run equilibrium relationship with climate change drivers (CCDs) and (ii) the relationship between world GDP and...

I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a ‘no change’ scenario, the most favorable median forecast predicts the land...