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Beyond borders: Decoding the influence of economic development, money confidence, financial market, and purchasing
Zibin Cao1,2, Weini Soh2, Nazrul Hisyam Ab Razak2
1School of Economics and Management, Zhoukou Normal University, Zhoukou City, Henan Province, China.
Abstract:
Due to dedollarization and deglobalization trends, countries are pursuing currency diversification to reduce reliance on the U.S. dollar and mitigate currency risks. The research on the drivers of currency internationalization still faces problems such as small sample sizes, fewer methods, and incomplete theoretical frameworks. This study aims to investigate the effects of economic development, money confidence, and the financial market on currency internationalization. It also explores whether purchasing power mediates the relationships between the first two exogenous variables and currency internationalization. The Partial least squares structural equation modeling (PLS-SEM) method is used to analyze secondary data from 9 of the 10 most used currencies (excluding the euro) from 2000 to 2020 to examine these relationships. The findings show that economic development and money confidence have negative and significant relationships with currency internationalization, while financial market and purchasing power have positive and significant relationships with currency internationalization. The relationships between economic development and currency internationalization, as well as between money confidence and currency internationalization, are both mediated by purchasing power. These mediation effects are partially complementary mediation effects. Accordingly, to promote currency internationalization, this study recommends governments should adopt policies to develop the financial market, increase openness, and reduce capital controls. It also highlights the importance of managing inflation, diversifying reserve assets, and maintaining a flexible exchange rate to prevent currency depreciation. This study is limited by the exclusion of the euro, reliance on hard data, a small sample size, and a narrow focus on economic factors.
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