We propose an extended time-varying parameter Vector Autoregression that allows for an evolving relationship between the variances of the shocks. Using this model, we show that the relationship between the conditional variance of GDP growth and the long-term interest rate has become weaker over...

We study the impact of climate volatility on economic growth exploiting data on 133 countries between 1960 and 2005. We show that the conditional (ex ante) volatility of annual temperatures increased steadily over time, rendering climate conditions less predictable across countries, with...

We use a factor model with stochastic volatility to decompose the time-varying variance of Macro economic and Financial variables into contributions from country-specific uncertainty and uncertainty common to all countries. We find that the common component plays an important role in driving the...

We confirm that standard time-series models for US output growth, inflation, interest rates and stock market returns feature non-Gaussian error structure. We build a 4-variable VAR model where the orthogonolised shocks have a Student t-distribution with a time-varying variance. We find that in...

This paper uses a FAVAR model with stochastic volatility to estimate the impact of uncertainty shocks on real income growth in US states. The results suggest that there is a large degree of heterogeneity in the magnitude and the persistence of the response to uncertainty shocks across states....

We present a weekly structural Vector Autoregressive (VAR) model of the US crude oil market. Exploiting weekly data we can explain short-run crude oil price dynamics, including those related with the COVID-19 pandemic and with the Russia's invasion of Ukraine. The model is set identified with a...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

In this work, we propose an analysis of the global market for crude oil based on a revised version of the Structural Vector Autoregressive (SVAR) model introduced by Kilian and Murphy (2014). On this respect, we replace the global proxy for above-ground crude oil inventories with the oil...

This paper develops a two-block Structural Vector Autoregression featuring time-varying parameters and stochastic volatility to estimate the changing spillover of global oil shocks into the Maltese economy during the period that goes from January 2008 to March 2022. The model is estimated by...