The late 1980s and early 1990s saw quite a substantial number of SSA countries moving towards the removal of administrative control of the rate of interest and credit, and a shift towards indirect monetary policy (ed. Ncube 2008). However, due to the illiquidity of the financial markets, including secondary bill markets, various governments could not afford to use tools such as open market operations (OMOs), an important element in indirect monetary management, until the late 2000s. Over the past two decades, most SSA nations have made progress in terms of financial development. Financial institutions and financial markets are, nonetheless, underdeveloped in comparison to other developing regions, with the exception of the region’s middle-income countries like South Africa (Mlachila et al. 2016).

When considering private credit provision, as well as financial intermediation, the news is even worse in SSA. In the pre-crisis period of 2007, the average domestic credit to the private sector ratio for commercial banks (as a percent of Gross Domestic Product [GDP]) was only 32.21% in SSA, but the same ratio ranged from 45% to 60% in other developing countries (World Bank 2021). The domestic credit ratio to the private sector by banks during the decade from 2010 to 2019 has been below the pre-2010 levels indicating a declining role of the domestic financial sector in contributing to national income. The commercial banks’ population in every 100 000 adults is still below five in SSA although the figures are gradually rising. Bank liquid reserves to bank assets ratio has been following a steady growth from 2002 to 2019, with figures ranging between 16% and 20%. This gives a clear indication that the region is still underdeveloped in terms of finance.

However, these reported financial development indices fail to highlight crucial new advances in the SSA’s financial systems. Recent changes in the economic and regulatory contexts have been linked to improvements (Allen et al. 2016). There are currently major factors at work to enhance SSA’s chances of integrating into the global financial industry.

For example, global capital markets, including those in developing market economies, are becoming more integrated, resulting in more capital mobility. Barriers to international capital movements have been greatly removed in SSA and the region has experienced the rapid adoption of new financial products, such as cryptocurrency. In addition, information technology (IT) is rapidly linking Africa to the world economy, allowing outside and foreign investors seeking the benefits of international diversification to efficiently access African financial systems (Otchere, Senbet & Simbanegavi 2017). Despite this outstanding achievement in terms of financial sector reforms and economic growth, according to Green (2013), financial systems in SSA are much more underdeveloped than in most other markets around the globe on practically all financial development indicators.

In Africa there are significant development and financial inclusion gaps in both banking and non-banking systems (Allen et al. 2016). In the latter, for example, most African stock markets are quite thin, with low levels of liquidity provision, based on standard metrics of trading activity and capitalisation (Allen, Otchere & Senbet 2011; Senbet & Otchere 2010). African stock markets’ performance was quite remarkable during the pre-crisis period of 2008 in terms of risk-adjusted and absolute returns. Significant problems in terms of liquidity and depth still exist in African stock markets, but increases in capitalisation and trading activity have been realised. Sub-Saharan Africa’s stock markets, with the exception of South Africa and Nigeria, are still small in terms of market capitalisation and the number of listed companies. The data on listed domestic companies and market capitalisation, in relation to GDP from 2009 to 2022, are presented in Table 1. The Southern African region has relatively higher market capitalisation as a percentage of GDP driven mainly by the South African markets. Table 1 also shows that the mean market capitalisation for SSA has been increasing steadily from 2009 to 2019.

According to Green (2013), the SSA experience itself is widely diverse, having South Africa, and to a certain extent, Kenya and Nigeria realising increased maturity in financial market deepening, whereas the rest of the countries have small, fragmented, and relatively underdeveloped financial markets. Even among the more prosperous countries, the pathways taken, appear to be widely varied. In Kenya for example, financial broadening appears to be at the centre of financial sector development, while the South African case is deeply rooted in financial deepening. For all rising and pre-emerging economies, including those in SSA, the global financial crisis and previous crises have created additional concerns. Traditional banking and informal finance dominate the financial systems of SSA, with South Africa doing exceptionally well in terms of finance.

However, as a result of substantial economic reforms, carried out over the past three decades, there have been significant changes in the banking environment with a rise in non-bank financing, notably in the establishment of stock markets that have spread through Africa. These achievements are suspected to be in response to the progress made in reforming the regulatory and economic environments that the entire region has realised in recent years.

Central banks and deposit-taking institutions make up the SSA banking system. Although central banks are technically independent of government control, they collaborate mostly with their individual Ministries of Finance to assist in the establishment and implementation of government policies (Allen et al. 2011). In most SSA countries, state-owned banks or a few major, sometimes global, institutions lead the banking system. However, as part of the African countries’ restructuring agenda, the banking sector in Africa is undertaking reforms centred on transforming state-owned banks into privately owned ones so as to increase the quality of the banks. The banks in Nigeria and the Southern African Development Community’s (SADC) countries of Botswana, Malawi, Seychelles, and South Africa are well-capitalised and dynamic, and they pursue banking practices in a highly innovative way. The Seychelles’ banking sector is extremely modernised and somewhat similar to those in most advanced economies.

Western and Eastern African countries, such as Cameroon, are part of monetary union, as well as members of the Southern Africa Currency Union (SACU), such as South Africa and Namibia. Member countries in most of the monetary arrangements in Africa, such as SACU, and the Franc Zones, have almost similar financial systems. Except for Botswana, all SACU member states form the common monetary area, which allows the South African Rand to be fully convertible in these countries. This implies that South Africa’s exchange rate and monetary policy is conveyed across SACU. The financial sectors in these countries and the local legal systems follow Roman-Dutch and Common Law backgrounds. Countries in West Africa such as Cameroon, Chad, and Equatorial Guinea are affiliated with one or two monetary unions. The form of monetary integration within these regional groupings presents opportunities for deeper monetary integration in Africa with the operation of the African Continental Free Trade Area (AfCFTA).

Until recently, Africa has realised unhindered expansion and has been one of the world’s fastest-growing areas in many years (Rotberg 2013). Sub-Saharan Africa has long been the world’s most economically underdeveloped region, but its economies appear to be growing, though growth was subdued in 2019 and 2020 due to the global coronavirus pandemic. Figure 1 indicates that the 2019 GDP growth rate in SSA was 2.28% (down from 2.41% in 2018), while the average regional growth rate during the period from 2009 to 2019 was 3.47%. The inflation rate averaged 4.43% from 2009 to 2019 and depicts a relatively downward trend from 1976 to 2019. The inflation rate was at an all-time high of 27.45% in 1994 and has recorded figures below 10% from 1996 to 2019, except in 2008 when 10.46% was recorded. However, the outlook is quite different at the country level with places like Zimbabwe recording inflation rates as high as 231 million percent in 2008. Broad money grew steadily in SSA from 1984 to 2019, while total reserves, as a percentage of total external debt, has been subject to wide fluctuations during the period between 1971 and 1982, and also 2003 and 2017. Figure 1 shows the trend in broad money, GDP growth, total reserves as a percentage of total external debt, and the inflation rate for SSA from 1970 to 2022.

Furthermore, monetary policy plays a significant role in the majority of SSA countries, although in most instances, in a submissive way to fiscal policy in influencing aggregate demand. While the primary goal is maintaining price stability, monetary authorities do work closely with the fiscal authorities, and in some countries, they are not entirely independent of the central government’s control, except for a few countries like South Africa and Mauritius. The control of money supply rests upon the monetary authorities and credit expansion has a more far- reaching impact on aggregate demand and inflation in developing countries. However, expansive monetary policy involving an increase in money supply has to be well-targeted to guard against fierce inflationary pressures and rapid exchange-rate depreciation. Well-functioning financial markets with links to the international settlement system have evolved over the past decade in SSA and so has financial sector regulation. Mobile money services in countries like Kenya have replaced conventional financial transaction channels, while financial deregulation has been fundamental in enabling new developments that have raised the standards of living of the populace and significantly reduced transaction costs.

The financial system in SSA is thin and its role in the growth of the economy is still minimal (Adelegan & Radzewicz-Bak 2009; Effiong et al. 2017; Mlachila et al. 2016). The banking sector in developing economies is generally small, the banking competition level is low combined with feeble financial intermediation, and the legal setup for financial activities is constantly moving in these economies. Additionally, a well-developed financial system could lessen the effectiveness of monetary policy as new innovations may be introduced to hedge against unanticipated monetary shocks. Some common features combine to render SSA countries’ financial systems highly susceptible to internal and external shocks.

Maintaining a steady price level and stable growth is key to long-term prosperity and when these variables become too volatile, there are unforeseen consequences for and effects on the economy that keep financial markets from functioning at their optimal level of efficiency. Financial markets are characterised by information asymmetry and the Central Bank often has instruments to achieve the set objectives (Gertler & Gilchrist 1994). The instruments do not directly affect the goals but the variables, such as reserves and loans, which in turn affect goal variables such as output and inflation with a lag. Policymakers face difficulties in predicting the precise effect of monetary policy actions on the real economy and price level, since the monetary transmission mechanism is characterised by long, variable, and uncertain time lags. In this regard, analysing the nexus between financial structure and monetary policy impulses empirically is crucial to understand how the various financial indicators contribute to monetary policy effectiveness in influencing economic activity. Financial sector inefficiencies are predicted to play a crucial role in the monetary policy transmission mechanism by amplifying and propagating the influence of monetary policy on the real economy (Bernanke, Gertler & Gilchrist 1999; Gertler & Gilchrist 1993).

However, due to a lack of clear understanding of such mechanisms in developing countries, there is a need to study the nexus between financial structure and monetary policy impulses in SSA.

The key objective is to investigate the nexus between financial structure and monetary policy impulses in SSA. The specific objectives are to:

The article is based on the following hypotheses:

The debate over the relationship between financial structure and monetary policy impulses has raged for a long time, and has piqued the interest of academics in both rich and developing countries. Effiong et al. (2017) carried out an investigation to check if financial development has an influence on monetary policy effectiveness in Africa. Panel data techniques were employed on annual data covering 39 African countries spanning the period from 1990 to 2015. The analysis discovered a weak link between the efficiency of monetary policy and financial development. In the case of inflation, a negative association was discovered, but only at their contemporaneous levels. The research suggested that deepening financial sector growth is necessary to boost the monetary transmission mechanism in African economies. Most African countries’ financial systems are claimed to be underdeveloped, having structural flaws that undermine the efficiency of monetary policy.

Mishra and Montiel (2012) reviewed the monetary transmission mechanism in low-income nations, with focus on the implications of financial market structure on the monetary transmission. With a small number of macro-economic variables such as interest rates, inflation, and output, the researchers employed variance decomposition and the impulse response functions (IRFs), based on VAR, to analyse the monetary transmission mechanism. According to the article, transmission channels are very country-specific and heavily dependent on each economy’s financial structure. Also, a wide range of empirical methodologies were said to have failed to produce evidence of successful monetary transmission in developing nations. The bank lending channel was determined to be the most common and dominant means of monetary transmission.

Carranza, Galdon-Sanchez and Gomez-Biscarri (2010) analysed the relationship between financial development and monetary policy by estimating a set of dynamic panels that test the significance of relationships between the indicators of financial development and monetary policy effectiveness. Factor analysis was used to obtain meaningful measures of financial development and several VAR-based measures of the effectiveness of monetary policy across several developed and developing nations. However, the researchers failed to rationalise either a positive or negative relationship between financial development and monetary policy effectiveness. The theoretical arguments were suggested to rationalise both a positive and a negative relationship. The conclusion was that monetary policy has a greater influence when the financial system is underdeveloped. The size of the central bank was found to be positively related to the effectiveness of monetary policy. However, the results were presented in the form of a list of stylised facts which require further attention.

Assenmacher-Wesche and Gerlach (2008) studied the effects of monetary policy shocks on residential property and equity prices, inflation, and economic activity. The researchers used single-country VARs and panel VARs to assess the nature of the responses, which were based on a panel of 17 countries for the period from 1986 to 2007. The findings show that monetary policy has significant and predictable effects on residential property values, which are approximately in line with its effects on the real economy. According to the paper, monetary policy could be utilised to tamp down property price booms. However, the use of the VAR methodology alone has drawbacks in terms of providing efficient estimates since the VAR model is not based on any economic theory and use of wrong lag lengths has dire consequences such as biased estimates.

Ferreira (2009) confirmed the relevance of the tendencies in the financial system in the European Union’s (EU) credit channel of monetary policy. For the period from 1999 to 2006, the researcher employed panel fixed-effect estimation using quarterly data from 26 EU countries. The importance of financial systems was examined, using the Bernanke and Blinder (1988) model. According to the article’s findings, bank performance conditions are particularly important for the expansion of bank lending in the European Union.

Ncube (2008) examined the importance of the financial system in the evolution and conduct of monetary policy in Africa where capital markets, non-banking financial institutions, and the banking system make up the financial system. According to their study, the effectiveness and operation of indirect monetary policy are influenced by the financial structure. The extent of competition between banks and non-bank financial firms, the balance sheet structure of financial and non-financial institutions, and the regulatory environment were suggested as the financial system’s main features that may influence the operation of monetary policy. The researcher established that the banking system’s structure, notably the lack of competition between banks, hinders the transmission mechanism, causing lending and deposits to respond slowly to changes in monetary policy stance. Furthermore, the impact of financial structure on monetary policy impulses varies greatly across countries. However, the findings from this article are not sufficient to warrant that the financial structure inhibits monetary policy transmission since it is purely narrative.

Zakaria (2007) specifically investigated whether monetary policy actions hinge on the countries’ financial structure for both the common-law countries and civil-law countries. A VAR model was estimated for each country by employing quarterly data for the period from 1980 to 2003. In civil-law nations, the effect of an increase in the rate of interest on output was found to be higher and to respond faster than in common-law nations. This was attributed to the fact that most financial arrangements in common-law countries are more market-based. The study concluded that in common-law nations, the greater the availability of substitutes for bank loans, the lesser the contractionary effect of monetary policy following a reduction in credit supply.

A panel data model which is meant to relate a measure of monetary policy impulses (MPI) to financial structure (FS) will be estimated, while at the same time controlling for macro-economic heterogeneity. The dynamic panel data model (DPD) takes the form specified by Carranza et al. (2010) when analysing the relationship between financial development and monetary policy (MP) (see Equation 1): mpiit=αmpiit−1+θjFSj,it+β′zit+εit[Eqn 1] where mpi_it is the specific MPI measure for country i in year t, FS_j,it is the value of the FS factor j for country i in year t, z_it is a vector of control variables and ε_it is an independently and identically distributed (i.i.d) error. The study employs Arellano and Bond’s (AB) (1991) General Method of Moments (GMM) estimator for the DPD model in which the measure of mpi is a continuous variable. The AB estimator is chosen because it takes all the orthogonality conditions into account and addresses the endogeneity problem through the use of instrumental variables.

The GMM is employed in this study since the dependent variable (MPI) is assumed to be dynamic and depends on its realisation in the past. Also, the right-hand variables (FS indicators such as competition in the banking industry) are considered to be not strictly exogenous (Hildebrand 2006). As already mentioned, financial market pricing reflects market expectations about future economic events such as output, inflation, and the future path of MP, to the extent that financial market activities influence MP. Financial contracts and institutions, according to Bernanke et al. (1999), are endogenous, and outcomes based on arbitrary constraints on financial ties may be misleading. Also, the panel dataset consists of a small number of time periods (2011–2018) and many individual units (21 SSA countries). Therefore, the AB estimator is suitable to estimate the functional relationship in Equation 1.

The econometric analysis is based on annual data observations of a number of selected macro-economic variables: output growth, inflation, reserves, broad money, and FS indicators, including the number of bank branches per 100 000 inhabitants, net acquisition of financial assets, and the bank liquid reserves to bank assets ratio. Therefore, a sample of 21 SSA countries was analysed, for which data observations on the mentioned variables were collected during the period spanning from 1985 to 2018 for the VAR model and the period from 2011 to 2018 for the panel data model. The data for each individual country were collected from the World Development Indicators database. Also, some missing data were collected from the respective countries’ central banks. The sub-Saharan African countries included for investigation were: Angola, Botswana, Burkina Faso, Cameroon, Congo Republic, Cote d’Ivoire, Equatorial Guinea, Ghana, Kenya, Lesotho, Madagascar, Mauritius, Namibia, Nigeria, Rwanda, Seychelles, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe. These countries, and the time periods under consideration, were selected on the basis of the availability of reliable and comprehensive macro-economic data. The STATA Software package was used to analyse the data.

The data analysis was carried out in stages following the methodology outlined in this section.

The preliminary investigation steps involved employing country-specific VAR models to generate a reliable measure of monetary policy impulses. Table 2 shows the list of the 21 SSA countries and their averages over the period from 1985 to 2018 for each measure of inflation, reserve growth, output growth, and broad money as a percentage of GDP.

A cursory examination of the data exposes major disparities across countries among the variables under consideration. The rate of annual inflation ranged from an average of 2.696% for Burkina Faso and an average of 39.105% for Zambia. Also, the average annual growth in broad money as a percentage of GDP ranged from a record of 14.032% for Equatorial Guinea and a record of 84.151% for Mauritius among the cross-sectional units. The relatively large disparities in the observations suggest that monetary policy may have asymmetrical effects on prices and output across countries. As a result, the price and output reactions to an unexpected monetary policy shock vary significantly throughout SSA. Congo Republic has the lowest output growth rate average of 1.625%. However, we do not comment on the results from the VAR estimation for the separate countries. The VAR model was only used to estimate IRFs for each country in order to obtain a measure of monetary policy instrument. It should be highlighted that monetary policy in most of the countries under examination is often relatively short-term, and in some cases, even ineffective. The data to support this are presented in Appendix 1.

The descriptive statistics were based on a panel consisting of 21 SSA countries and 8 time periods. Table 3 shows the mean, standard deviation, minimum and the maximum on each variable under consideration.

The ‘overall’ statistics are ordinary statistics that were based on 168 observations. ‘Between’ statistics are calculated on the basis of summary statistics of the 21 countries, regardless of the time period, while ‘within’ statistics by summary statistics of eight time periods regardless of the country. The variables mpi, finsecsiz, findev, and centrbanksiz have means of: -0.0275%, 25.4969%, 0.8732%, and 21.4764, respectively; exchratereg is a qualitative indicator taking two values: a minimum of zero and a maximum of one; whereas mpi has an overall minimum of 4.45%, while the average number of bank branches per 100 000 (marketcon) is 8.53 in SSA. The average number of bank branches indicates a low level of banking sector competition in SSA. Most countries in SSA have a fixed exchange-rate regime with a low variation in findev as compared to finsecsiz between groups. The average ratio of 21.48 for centrbanksiz indicates that central banks in SSA hold more reserves in relation to central bank assets.

The LLC’s (2002) test results are presented in Table 4. The STATA output is inserted in Appendix 1.

In all cases, the null hypothesis that the panels contain unit roots, is rejected and the conclusion is that all the panels are stationary. All the variables under consideration are stationary at the 1% level of significance, except centrbanksiz which is stationary at the 5% significance level. In addition to the stationarity tests, the Kao test for co-integration was conducted and results are presented in Appendix 1.

The results of the dynamic panel data model estimated using the AB estimator are presented in Table 5. The STATA output is also inserted in Appendix 2.

The Wald Chi-Square statistic is significant at the 1% level and this confirms that at least one of the coefficients in not equivalent to zero. The Sargan test’s null for the validity of over-identifying restrictions was rejected and the conclusion was that there was no need to impose over-identification restrictions. The results in Table 5 indicate that MPI in the previous two periods, as well as competition in the banking system in the previous period are significant at the 1% level (p-value < 0.001). Financial development is significant at the 5% level (p-value < 0.05), while the size of the central bank is economically and statistically significant at the 10% level (p-value < 0.10).

The positive coefficient of markconc (L1) implies that an increase in the number of commercial bank branches per 100 000 people by one bank in the previous period will result in a 0.7% increase in the response of the economic activity to monetary policy in the current period. The result is in line with the expected results since a move towards a more competitive banking system, coupled with financial inclusion, is more likely to increase the responses of economic activity to monetary policy, as this will possibly accelerate credit expansion and reduce collusive tendencies by commercial banks when allocating financial resources. According to Mlachila et al. (2016), most countries in SSA have underdeveloped financial systems categorised by low competition and usually only a small number financial intermediaries. As competition within the banking system increases, commercial banks’ practices will respond better to market incentives and monetary policy becomes more effective. In line with Ncube (2008), lack of bank competition weakens the transmission mechanism resulting to the moderately sluggish correction of deposit and lending rates to alterations in the monetary policy stance.

Monetary policy tends to have a significant cumulative impact on real economic activity when the financial system is less developed. The results indicate that a 1% rise in the net acquisition of financial assets (as a percentage of GDP) in the previous period will induce a 0.17% decline in the responsiveness of economic activity to monetary policy in the current period. As the financial system develops, private agents can devise new instruments such as crypto currency which allow them to safeguard against unpredicted monetary shocks and thus, reduce the volatility of their expenditure patterns (De Bondt 2000; Effiong et al. 2017). The finding confirms the expected results and the conclusion by Ma and Lin (2016) according to which the effects of monetary policy on output and inflation are negatively and significantly related to financial development.

The larger the central bank, the higher is the prospect that its actions will meaningfully affect economic agents’ actions and effectively influence economic activity in SSA. The coefficient of centrbanksiz indicates that an increase in the ratio of bank liquid reserves to bank assets, held by monetary authorities by 1%, will result in an increase in the cumulative impact of monetary policy on economic activity by 0.0448%. In conformity with the findings by Carranza et al. (2010), an increase in the size of the central bank results in an increase in the power of the central bank to conduct and implement effective monetary policy. The result is also in line with the expected results from the study.