Abstract
The paper examines the long-run relationship between banking sector development and economic growth in 25 ARF countries for the period 1960–2012. Using principal component analysis for the construction of development index and vector auto-regressive model for testing the Granger causalities, the study finds the presence of both unidirectional and bidirectional causality between banking sector development and economic growth. The policy implication of this study is that the economic policies should recognize the differences in the banking sector development and economic growth in order to maintain sustainable development in the 25 ARF countries.
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Notes
ASEAN stands for Association of South-East Asian Nations.
We observe only nine countries, which are used for our analysis. To include the European Union, the tenth member, would have meant double-counting of a couple of countries like Australia, Canada and Japan.
Pedroni (1999) suggests two types of test to determine the existence of heterogeneity of the cointegration vector. The first is a test which uses the within-dimension approach (a panel test). It uses four statistics, namely a panel v-statistic, a panel ρ-statistic, a panel PP-statistic and a panel ADF-statistic. These statistics pool the auto-regressive coefficients across different panel members for the unit root tests to be performed on the estimated residuals. The second is a test based on the between-dimensions approach (a group test). It includes three statistics: a group ρ-statistic, a group PP-statistic and a group ADF-statistic. These statistics are based on estimators that simply average the individually estimated auto-regressive coefficients for each panel member. There are basically five steps to obtain these cointegration statistics. The mathematical exposition and the asymptotic distributions of these panel cointegration statistics are contained in Pedroni (1999). Under an appropriate standardization, based on the moments of the vector of Brownian motion function, these statistics are distributed as standard normal. Accordingly, the null of no cointegration is then tested, based on the above description of standard normal distribution. The detailed discussions of these tests are available in Pedroni (2000).
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Pradhan, R.P., Tripathy, S., Chatterjee, D. et al. Development of banking sector and economic growth: the ARF experience. Decision 41, 245–259 (2014). https://doi.org/10.1007/s40622-014-0056-y
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DOI: https://doi.org/10.1007/s40622-014-0056-y