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Institutional Repository of Vilnius University

An early warning indicatοrs fοr cyclical systemic risk crοss cοuntry analysis /

Abstract

dc:description

Consistent with the research of the Bank of Lithuania (N. Valinskytė and G. Rupeika, 2015), this master’s thesis presents application of one-sided Hodrick-Prescott filter augmented with 5-year ahead random walk forecasts method and analysis of quarterly the Credit-to-GDP ratio gap as main indicator that could signal of systemic risk in countries during the periods of credit expansion. Research reveals, all twenty countries are homogenous and one-sided Hodrick-Prescott filter augmented with random walk forecast identifies periods of increased cyclical systemic risk, event for countries with small observations but comparisons of results for countries have to be interpreted carefully because of the small number of crisis events per country (1 or 2) and because of the different macroeconomic vulnerabilities. The results of signalling in all nineteen euro area countries and Sweden could be useful for further studies of early warning indicators for the identification of cyclical systemic risks. It could serve as a starting point in considerations whether here is a possibility to have a better early warning indicator.

Degree

thesis:*
Grantor dc:publisher
Institutional Repository of Vilnius University
Year dc:date
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Šiaulytė, Arūnė,
Contributors dc:contributor
  • Celov, Dmitrij

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • info:eu-repo/semantics/openAccess
Language dc:language
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:vu.lt:elaba:81590029

Chain of custody

source
Harvested from
Vilnius University
Base URL
epublications.vu.lt/oai
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Šiaulytė, Arūnė,. An early warning indicatοrs fοr cyclical systemic risk crοss cοuntry analysis /. Institutional Repository of Vilnius University, 2021. https://repository.vu.lt/VU:ELABAETD81590029&prefLang=en_US