This paper studies the predictive distribution of Italian GDP growth, taking account of various risk factors, both at global and national level. The methodology adopted (known as expectile regression) allows us to quantify the risks for GDP growth based on the impact of different factors on the tails of the distribution - the strongly negative scenarios on the left tail and positive ones on the right.
The analysis confirms that the financial conditions are correlated with the left tail of the distribution. The indicators of global trade trends and uncertainty, on the other hand, have an impact on both tails. According to these estimates, the risks for the GDP growth in Italy were driven mostly by international trade developments throughout the global recession of 2008-09, by the domestic financial conditions at the time of sovereign debt crisis and by the uncertainty in more recent years.
Published in 2021 in: Economic Modelling, v. 101
