Economic Vulnerability Is State Dependent

31 Pages Posted: 20 Apr 2021 Last revised: 6 Mar 2024

See all articles by Leopoldo Catania

Leopoldo Catania

Aarhus University - School of Business and Social Sciences; Aarhus University - CREATES

Alessandra Luati

Imperial College London - Department of Mathematics; University of Bologna - Department of Statistics

Pierluigi Vallarino

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE)

Date Written: April 7, 2021

Abstract

A novel dynamic model for joint estimation of multiple quantiles of a time series conditionally on a set of covariates is presented. The model preserves quantile monotonicity and allows for a clear interpretation of covariate effects across quantiles. Model parameters are estimated using a two-step M-estimator. The resulting estimator is consistent, and its finite sample properties are analysed through simulations. The new model is used to study the impact of different levels of stress in the financial system on GDP growth rate. The analysis shows that worsened financial conditions imply a more pessimistic economic outlook when the financial scenario is already severely distressed, and an overall increased macroeconomic uncertainty. Additionally, past information on GDP growth is found to be critical in studying and predicting economic vulnerability. These findings hold true even when alternative measures of real economic activity are considered.

Keywords: Macro-Finance, Growth-at-Risk, Score-driven models, Dynamic quantiles

JEL Classification: C32, C53, E32, E44

Suggested Citation

Catania, Leopoldo and Luati, Alessandra and Vallarino, Pierluigi, Economic Vulnerability Is State Dependent (April 7, 2021). Available at SSRN: https://ssrn.com/abstract=3821668 or http://dx.doi.org/10.2139/ssrn.3821668

Leopoldo Catania (Contact Author)

Aarhus University - School of Business and Social Sciences ( email )

Fuglesangs Allé 4
Aarhus V, DK-8210
Denmark
+4587165536 (Phone)

HOME PAGE: http://pure.au.dk/portal/en/leopoldo.catania@econ.au.dk

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Alessandra Luati

Imperial College London - Department of Mathematics ( email )

South Kensington Campus
Imperial College
LONDON, SW7 2AZ
United Kingdom

HOME PAGE: http://https://www.imperial.ac.uk/people/a.luati

University of Bologna - Department of Statistics ( email )

via Belle Arti 41
Bologna, 40126
Italy

HOME PAGE: http://https://www.unibo.it/sitoweb/alessandra.luati/en

Pierluigi Vallarino

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE)

P.O. Box 1738
3000 DR Rotterdam, NL 3062 PA
Netherlands

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