By: Chau The Vinh - VNP 18
Supervisor: Dr. Nguyen Trong Hoai
The thesis estimates a logit regression model by fixed effect with a combination of some macroeconomic and financial indicators from the work of Hagen and Ho (2007) and Worldwide Governance Indicators (WGI) from the updated database of Kaufmann (2013) as explanatory variables for binary dependent variable banking crises generated from the approach of money market pressure index (Hagen and Ho, 2007). The monthly panel dataset, which is available in full range and easy of approach from International Financial Statistics CD-ROM (2011), of 18 countries from Latin America and Asian over the scope of 2001 – 2010is applied. Some specific lag lengths of indicators are also applied according to the suggestion of “flexibility in forecast horizon” of Drehmann et al. (2011). The crisis phenomenon of banking system seems to be well-described in light of the present of depreciation, former year crisis, high real interest rate in prior of 36 months, growth of credit to GDP in prior 12 months. Moreover, impact of inflation seems to support the school of thought that it is negative effect to crisis. Simultaneously, growth rate of bank deposits to GDP is likely useful to prevent banking systems from profitability risks exposure that leads to banking crisis probability. However, unfortunately, the indicators of growth of monetary base and growth of M2 to reserves give incorrect expected sign and negligible effect on banking crisis. Furthermore, the included institutional variables from WGI give insignificant statistic meaning. Hence, another set of institutional indicators such as that from International Country Risk Guide (ICRG) should be considered in future analysis to test for the relationship between Government health and banking crisis probability. Despite, on one hand, there should be a more adequate research to be examined in the future, this thesis attempts to contribute so-called new updates information on the would-be banking crisis determinants. Nevertheless, on the other hand, there is likely no proper explanation on the tranquil periods of banking system. Hence, it is suggested that thereshould be some assessment ofsuch time of banking system, which over a long time has beenneglected (Kauko, 2014).
Keywords: Banking crisis, Tranquiltime, Determinants, Institutional indicators, Fixed effect logitregression.