Does bank concentration stem from financial inclusion in Africa?

ABSTRACT

This paper provides original econometric evidence on whether banking concentration stems from financial inclusion in African countries. In applying a system generalized methods of moments (SGMM) and the panel threshold regression method to a sample of 30 African countries for 2004–2017, we find two main results. First, bank concentration negatively and significantly affects financial inclusion in Africa. Second, as far as the nonlinear relationship is concerned, we find two extreme regimes with a smooth shift characterizing the bank concentration–financial inclusion nexus, with respect to conditional variables; bank concentration effects are negative and significant under the first regime and positive and significant under the second. Furthermore, our findings show that the nonlinear relationship between bank concentration and financial inclusion depends on the levels of financial freedom, mobile phones penetration, protection of property rights, control of corruption and regulatory quality. The results are robust to alternative measures of banking market structure, such as Lerner index and Boone indicator and to the panel smooth transition regression (PSTR).

KEYWORDS:

• Financial Inclusion
• Bank Concentration
• Nonlinear Relationship
• Threshold Regression

JEL:

• G21
• K20
• O16

Disclosure statement

No potential conflict of interest was reportedby the authors.

Notes

¹ In addition, we explore other channels through which bank concentration may affect financial inclusion (financial freedom, bank stability, corruption, and property rights). We test these transmission channels.

² Further details of the method can be found in Seo and Shin (2016) and Seo, Kim, and Kim (2019).

³ Algeria, Botswana, Burundi, Cameroon, Central Africa Republic, Chad, Congo, Egypt, Equatorial Guinea, Eswatini, Gabon, Ghana, Guinea, Kenya, Madagascar, Malawi, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, Seychelles, South Africa, Tanzania, Tunisia, Uganda, Zambia.

⁴ Penetration refers to the percentage of the adult population with financial accounts to total population and life and nonlife insurance policies per 1000 adults.

⁵ Availability includes the number of commercial bank branches and of ATMs per 1000 km² and per 100,000 adults.

⁶ Usage is measured as the share of the adult population who borrowed and saved from a financial institution.