Abstract
Growth-at-Risk modelling has been a cornerstone for research and policymaking recently as a way to model tail risk in the macroeconomy. However, the majority of the research has been almost exclusively been done on US data. The aim of this paper is to utilise a variable selection framework to identify which variables are key in capturing the different parts of the GDP distribution for the Euro Area. Importantly this paper uses a methodology that can handle variable selection task in small sample settings.
Original language | English |
---|---|
Article number | 110990 |
Journal | Economics Letters |
Volume | 223 |
Early online date | 14 Jan 2023 |
DOIs | |
Publication status | Published - Feb 2023 |
Keywords
- Downside risk
- Growth-at-risk
- LASSO
- Non-crossing constraints
- Quantile regression
ASJC Scopus subject areas
- Finance
- Economics and Econometrics