Financial Development and Economic Growth in Emerging Markets: Structural Changes in Causality

İlhan Küçükkaplan, Hüseyin Ağır, Muhsin Kar

Abstract


The relationship between financial development and economic growth has been one of the hotly debated issues of whether the financial sector actually contributes to the real sector in the process of economic development. There is a great deal of empirical literature that has scrutinized the experiences of the developed and developing economies. This special interest comes from the intermediary role of financial markets between savers and investors in the process of economic development. The emerging markets economies, over the last two decades, have experienced a wave of liberalization in the financial sector with an expectation that lifting government restrictions on the banking system in terms of interest rate ceiling, high reserve requirement, and directed credit programs which enhance financial development and, in turn, expected to promote economic growth. A careful investigation of the results from these experiences provides additional evidence of whether the financial sector actually causes to economic growth.

This paper investigates the direction of causality between financial development and economic growth in the emerging market countries. We employ a new causality approach proposed by Nazlioglu et al. (2016 and 2018) which augments the Toda-Yamamoto method with a Fourier approximation. This approach is capable of capturing gradual or smooth shifts and does not require a prior knowledge regarding the number, dates, and form of structural breaks. The so-called Fourier Toda-Yamamoto causality test is applied to the panel of emerging countries. Traditional causality procedures that seek abrupt shifts are inadequate in capturing gradually developing structural changes. To that effect, we modify the Toda-Yamamoto Granger causality procedure by embedding a Fourier approximation. The Fourier approximation is capable in capturing gradual or smoothing shifts and does not require a prior knowledge regarding the number, dates, and form of breaks.

Since financial development is a multi-dimensional concept, there is not a single variable that can capture the extent of financial development. This multidimensionality, however, leads to close interrelations between the financial development indicators and results in higher correlations among them to the extent that using several indicators can provide some redundancy of information. In particular, the close interrelations are likely to cause a multicollinearity problem which can lead to misleading inferences. To overcome these problems, we also construct a comprehensive financial development index based on principal component analysis from six financial development indicators.


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