Abstract
This study assesses the role of ICT (internet and mobile phone penetration) in complementing financial sector development (financial formalization and informalization) for financial access. The empirical evidence is based on generalized method of moments with 53 African countries for the period 2004–2011. The following findings are established from linkages between ICT, financial sector development and financial activity. First, the interaction between ICT and financial formalization (informalization) decreases (increases) financial activity. Second, with regard to net effects, the expected signs are established for the most part. In spite of the negative marginal effects from financial informalization, the overall net effects are positive. Third, the potentially appealing interaction between ICT and informalization produces positive thresholds that are within ranges. Policy implications are discussed in three main strands. They include implications for (i) mobile/internet banking, (ii) a quiet life and (iii) ICT in reducing information asymmetry and surplus liquidity.
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Notes
Of the 54 existing African countries, only South Sudan is not included because data for the country is not available before the year 2011.
There are two additional explanations for the choice of the periodicity: (i) The financial development variables used to compute the financial sector development propositions are from the Financial Development and Structure Database (FDSD) of the World Bank. The FDSD of the World Bank is computed 1 year or 2 years after the World Development Indicators (WDI) of the World Bank have been published. There is usually a two year lag when WDI are published. This implies that when the 2017 WDI will be released, the most updated year will be 2015, i.e. data points for the years 2016 and 2017 cannot be available in WDI published in 2017. When the data was collected in 2015 from WDI, the most updated year from WDI was 2013 while the most updated year from the FDSD was 2011. (ii) The data used by Asongu (2015b, c) to propose the indicators is not up to the year 2011. Hence, we computed new indicators to reflect current reality.
“First, the null hypothesis of the second-order Arellano and Bond autocorrelation test (AR(2)) in difference for the absence of autocorrelation in the residuals should not be rejected. Second the Sargan and Hansen overidentification restrictions (OIR) tests should not be significant because their null hypotheses are the positions that instruments are valid or not correlated with the error terms. In essence, while the Sargan OIR test is not robust but not weakened by instruments, the Hansen OIR is robust but weakened by instruments. In order to restrict identification or limit the proliferation of instruments, we have ensured that instruments are lower than the number of cross-sections in most specifications. Third, the Difference in Hansen Test (DHT) for exogeneity of instruments isalso employed to assess the validity of results from the Hansen OIR test. Fourth, a Fischer test for the joint validity of estimated coefficients is also provided” (Asongu and De Moor 2017, p.200).
6.822 is the mean value of internet penetration.
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Asongu, S.A., Nwachukwu, J.C. ICT, Financial Sector Development and Financial Access. J Knowl Econ 10, 465–490 (2019). https://doi.org/10.1007/s13132-017-0477-x
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DOI: https://doi.org/10.1007/s13132-017-0477-x