Financial cycle synchronization in the advanced and systemic middle-income economies: evidence from a dynamic factor model

Khwazi Magubane, Phocenah Nyatanga and Ntokozo Nzimande
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Khwazi Magubane: Finance and Economics, University of KwaZulu Natal, South Africa
Phocenah Nyatanga: University of KwaZulu Natal, South Africa

International Journal of Research in Business and Social Science (2147-4478), 2024, vol. 13, issue 7, 301-314

Abstract: Financial cycles are widely regarded as key drivers of global financial conditions and major contributors to international financial crises. Understanding the extent to which these cycles are interconnected is essential for developing early warning systems to predict financial crises and for informing the design of macroprudential and monetary policies. In this context, a dynamic factor model and time-varying Granger causality (TVGC) are employed to assess the degree of financial cycle synchronization between advanced economies and systemic middle-income countries (SMICs). Our data spans the period from 1980Q1 to 2023Q4. The analysis reveals that a common factor—shared by both advanced and systemic middle-income economies—plays a significant and persistent role in driving financial cycles across these regions. Notably, the influence of this common factor intensified following the 2007–2009 global financial crisis, highlighting the growing financial interconnectedness between these economies. These results strongly support the argument for closer coordination of macroprudential policies between advanced economies and SMICs. The findings from the TVGC analysis further reinforce the conclusions drawn from the dynamic factor model. Specifically, the TVGC results indicate a bidirectional causality between the financial cycles of advanced economies and SMICs, suggesting mutual influence. This bidirectional relationship underscores the importance of enhanced policy coordination across these economies to mitigate systemic risks. Key Words:financial cycles, macroprudential policy, financial stability, dynamic factor model

Date: 2024
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