Assesing Early Warning System Model for Banking Crisis in ASEAN Countries
Musdholifah Musdholifah and
Ulil Hartono
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Musdholifah Musdholifah: Department of Management, Faculty of Economics, Universitas Negeri Surabaya, Surabaya, Indonesia
Ulil Hartono: Department of Management, Faculty of Economics, Universitas Negeri Surabaya, Surabaya, Indonesia
International Journal of Economics and Financial Issues, 2017, vol. 7, issue 4, 358-364
Abstract:
It is really necessary to understand that the banking sector is one of important part in the economy of a country. Banking acted as intermediary institutions between the parties with the excess funds were underfunded and the role of banking sector as part of the payment system, it needs to be maintained stability. If the banking industry has problems, then it will affect stability of economy in a country. The study aimed to develop an early warning system of banking crisis in Asian. This is necessary due to the detection of early symptoms of a banking crisis the losses caused by the crisis can be minimized. Moreover, it also can be done countermeasures so that a crisis can be avoided. The research used an ex-pose facto approach in constructing the models of early warning system is combining econometric techniques and signalling method. Sample of this research are ASEAN countries, namely Indonesia, Malaysia and Thailand. The study period was divided into two periods that are in-sample and out-sample. The important results persuasively show, that the predictive models were able to provide predictive power for the possibility of a crisis in out-sample period. This implies that the better the predictive, the better the banking system to avoid banking crisis system in ASEAN countries. In practically, banking in ASEAN countries should apply the Early Warning System.
Keywords: Early Warning System; Banking Crisis; Asean (search for similar items in EconPapers)
JEL-codes: F45 G2 H12 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ1:2017-04-45
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