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  • Statistical Analysis of Relationship Between Globalization and Level of Banking Sector Development in Different Countries

Statistical Analysis of Relationship Between Globalization and Level of Banking Sector Development in Different Countries

Student: Massarskaya Anna

Supervisor: Elena Kopnova

Faculty: Faculty of Economic Sciences

Educational Programme: Economics and Statistics (Bachelor)

Year of Graduation: 2019

The research had a purpose to scrutiny interconnections between globalization process and banking sector development. During analysis, relationships with different types of globalization were checked and this allowed to identify unidirectional interdependence between banking industry development and financial globalization using recursive systems of simultaneous equations. After this, all countries were classified into three groups according to world specific banking systems metrics. Based on literature review for the further econometric modelling the most exposed to globalization clusters were selected. For cluster of the least developed banking systems panel cointegration model and VECM were estimated. They allowed to determine statistically significant long-run and short-run interconnections between banking development and globalization processes. Causal Granger test defined unidirectionality of interconnection from financial globalization to banking sector development. Impulse response function indicated one-time increase in banking development level in reaction to occasional shock in globalization. After the expiry of 4 years banking development moves to a new equilibrium path. For cluster of the most developed banking systems statistically significant unidirectional interdependence also was detected using panel VAR(1) model and Granger test. In this case, impulse response function has revealed leap in banking development in response to globalization change by 1ε. However, in 5,5 years effect from one-way shock is graded and equilibrium comes to the primary situation. In both groups dynamic forecasts were constructed which designated positive tendency of two studied parameters.

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