ABSTRACT
The purpose of this study was to determine the relationship between liquidity and credit risks, and bank spread. It also sought to determine the cyclicality of the effects of liquidity and credit risks. Financial institutions play an important role in the Ghana’s economy. Among other things, the intermediary role they play between entities with surplus funds and those who have a deficit. They do this by accepting surplus funds through savings and other deposits which they then give to deficit entities through loans, overdrafts and other means. Theories such as the theory of financial intermediation assign some activities, also known as qualitative assets transformation, as the fundamental functions of banks. These activities that banks undertake also have associated risks which include liquidity risks and credit risks. The risks affiliated with maturity transformation evolve partly as a result of ensuring a sustainable level of liquidity anytime short- term deposits are used to finance fixed-rate long-term loans. This results in liquidity risks. Also, as intermediaries, banks stand surety for borrowers, since they guarantee repayment to depositors (lenders). To obtain the goals of the study, data was obtained from the Ghana Stock Exchange for banks that had quarterly data from the year 2008 to 2017. Macroeconomic data was taken from the World Bank database and Ghana Statistical Service database. These were analysed using the Generalised Methods of Moments (GMM) estimation technique.
The findings of the study show firstly that, business cycles have a strong positive relationship with bank spread. This relationship is statistically significant, suggesting that there is a strong relationship and correlation between business cycle phases and the interest rate spread of banks, hence bank spread among the sampled banks is procyclical. Also, the findings indicate that credit risk is significant than liquidity risk in explaining bank spreads, but their relative effects differ over the business cycle phases. Credit risk is more significant on spreads in the period of
expansion in the economy, while liquidity risk is more significant on spreads in the period of recession in Ghana. It is recommended that banks should factor the cyclical feature of liquidity risk and credit risk in pricing loans. Future researchers should consider cross-country analysis in Sub Saharan Africa to determine whether our findings can be extended to include other countries in the region.
CHAPTER ONE INTRODUCTION
Background of the Study
The role of banks in any economy is, for the most part, financial intermediation between entities (households or firms) with surplus funds and entities with deficits (Werner, 2015). They accept surplus funds through vehicles such as savings and other short and long-term deposits and offer them to deficit entities through loans, overdrafts and other means (Beckmann, Hake, & Urvova, 2013; Jokipii & Milne, 2008; Werner, 2015). This fundamental role played by banks is also associated with some level of costs incurred by these financial institutions. The theory of financial intermediation features several activities, generally known as qualitative assets transformation and these activities are usually regarded as core functions of banks (Bhattacharya & Thakor, 1993). It must be however be noted that these activities come along with risks specifically liquidity risk, credit risk and other risks associated with the transformation of maturity.
Bhattacharya and Thakor (1993) opined that there is some level of risk related to maturity of assets and liabilities as a result of the arrangement of liquidity when short-term deposits are utilised to finance fixed-rate long-term credits. This creates a gap known as the “maturity gap”, which can be attractive and desirable for banks especially when the associated term premia are lucrative. Term premium refers to the compensation that investors or banks require to bear risks that are associated with short-term treasury yields, since they usually do not evolve as expected. In this instance, banks have an incentive to increase income by being more aggressive in their intermediation role and in the process,
may assume more risks than usual. This is generally referred to as the “lure of interest rate risk” (Greenbaum & Anjan, 2004).
Almeida and Divino (2015) pointed out that credit concession is necessary in the financial sector in order to advance development, through the distribution of financial resources to different sectors of the economy. One of the significant pointers of productivity in financial institutions is the interest rate spread or the loan fee spreads. Interest rate spreads are the differences between the cost of acquiring savings and the profits on these assets from a bank’s point of view; that is, the difference between the financing cost banks charge on advances to their customers and the financing cost that they pay to depositors.
Indeed, financial institutions are susceptible to diverse risks such as operational risks, credit and liquidity risks, because they serve as a risk dealer (Ho & Saunders, 1981) by creating liquidity from savers and investors and providing funds to borrowers, and they are always expected to provide funds to their savers and investors whenever the need arises. This becomes more perilous because the banks do not know the timing needs of their savers and also there is likelihood that their borrowers will also not be capable to fulfil their obligations when their repayment of funds is due. Hence, banks are more cautious about liquidity and credit risk. Arif and Nauman Anees (2012) defined liquidity risk as a situation where banks are not capable of fulfilling their financial obligations without mislaying assets or incurring unexpected expenditure. In order to have a sound financial stability to compact unforeseen withdrawals, banks need to have a sufficient liquidity buffer. If banks need to hold or maintain a sufficient buffer to avoid future occurrences of panic withdrawals as suggested by ( Arif and Nauman Anees, 2012), then
they would always be disadvantaged on the cost of holding too much money even when customers do not need their monies at that particular period. Following this conversation in the literature, we argue that, banks need to be aware of and understand the state of the economy in which they operate and what each state of the economy may demand. For instance, if the economy is at a boom period, the question of whether or not customers will need more money for consumption or the banks will invest customers’ deposit needs to be asked. In a period where banks give funds to borrowers on the assumption that they will redeem repayments when due but the borrowers fail to repay the loans granted them, it results in credit risk. So, the timing for holding more liquidity and investing customers’ savings is a crucial decision for the banks. The economy grows when the banks are able to give credit to borrowers to take risky ventures. It is for this reason that, banks need to have a comprehensive facts and understanding of the business cycle and know how liquidity and credit risks responds to a specific phase of the cycle and its effects. In order for banks to compensate all costs attributed to their financial intermediary roles, having considered all the necessary risks, they charge a rate of interest on loans and also pay a depositor rate of interest to depositors.
Market analysts consider bank spread (the difference between deposit rate and lending rate) to be an indication of banks’ efficiency in their financial intermediation role. Aydemir and Guloglu (2017) indicated that when competition is weak in the financial institution sector, bank spreads are relatively to be high and this would be symptomatic of inefficiency in financial intermediation. High bank spreads will dampen investment in the economy as a consequence of high costs of borrowing. Moreover, if deposit rates are low,
relative to lending rates, savings level will decline and further distort the macro economy along various phases of the business cycle (Ndung’u & Ngugi, 2000).
When interest rates are countercyclical, that is, high during recessions, businesses will struggle to find cheap financing to make investments. This would lead to lower investments and production which will further deepen the recession. This cyclical impact of spreads is known as the financial accelerator principle or mechanism. Because of this accelerator effect, it is very necessary to examine the cyclical behaviour of spreads so as to understand how banking sector stability impacts on the real economy ( Bernanke, Gertler, & Gilchrist, 1996; Kasekende, 2010; Mlachila, Park, & Yabara, 2013). Studies on business cycles have spanned more than a century, and the concept has been variously defined. One of the important definitions is by Burns and Mitchell (1946) who defined business cycles as follows:
Business cycles are a type of fluctuation found in the aggregate economic activity of nations that organise their work mainly in business enterprises: a cycle consists of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions, and revivals which merge into the expansion phase of the next cycle (p. 3).
Business cycle thus refers to the phases that an economy goes through over time with respect to fluctuations around its activities, often measured by the GDP. This study also determines “business cycle” as real GDP growth rate following (Gilchrist & Zakrajsek, 2012), and Hamiton, 1989). These phases of the economic cycles have implications for businesses and banks (Bernauer & Koubi, 2002; Diebold & Rudebusch, 1996; Goldberg, 2007; Machado, 2001). For instance, during periods of contractions, there is generally a
slowdown of activities and reduced income, this leads to higher unemployment rates and business losses. Banks are more likely to record higher non-performing loans during this period, thus higher credit risk. In order to accommodate this type of risk, banks may charge exorbitant interest on loans and widen the spread. By this conventional wisdom, it will be expected that bank spread would be wider during contractions and smaller during expansions, reaching its lowest and highest at the trough and peak, respectively ( Nikitin & Smith, 2009). Some studies have however suggested a countercyclical relationship between spreads and the business cycle (Hasan, Liu, & Zhang, 2015; Liu, 2013; Nikitin & Smith, 2009). Banks may also face other classifications of risks like liquidity risk during contractions and expansions in the economy ( Bernauer & Koubi, 2002; Guidara, Lai, Soumaré, & Tchana, 2013; Nikitin & Smith, 2009).
Notwithstanding the extant literature on bank risks, bank spreads and business cycles, very few studies have examined how these variables relate among themselves, and the direction of any such relationship. Different studies on bank spreads have likewise been focused on the prime determinants of financing costs (Ho & Saunders, 1981), causes of net interest margins (Maudos & De Guevara, 2004), the impact of maturity transformation (Drechsler, Savov, & Schnabl, 2017; Paligorova & Santos, 2014; Sher & Loiacono, 2013), comprehending the behaviour cycle of bank spreads (Angbazo, 1997), interest-rate risk, default risk and off-balance sheet banking (Angbazo, 1997). This current study seeks to investigate the effects of liquidity risk and credit risk on bank spreads amid the different phases of the business cycle.
This piece adds to literature in two ways. First and foremost, it is one of the initial studies that examine credit, liquidity risks, business cycle and bank spread in the Sub Saharan
African region. This study is important in this region because Africa is a growing continent aiming for development. As shown by Levine (1997) the fiscal development of a nation can be attributed to the efficacy of financial intermediation in the country. Moreover, a good understanding of the business cycle will help in making correct analysis of economic activities and anticipating future movement of the cycles because the behaviour of every economy is also described by an interaction between growth and cycles (Calderón & Fuentes, 2014; Machado, 2001). Secondly, many of the existing studies on bank spread have also been geared towards the determinants of bank spread without linking these determinants to the business cycles in which they operate to ascertain whether it has any effect. This study contributes to literature by linking bank risks with spread over business cycle. This will inform policy makers, financial institutions and other users as to how bank risk (credit and liquidity) affects their spread at various phases of the business cycle. These gaps in the literature are what the researcher seeks to fill.
The approach adapted for measuring bank spread in this study is the ex-post approach instead of the controversial ex-ante approach. Thus, our measure of bank spread is more forward looking. The ex-ante is computed from the expectation of financial institutions for granting credit, hitherto the realisation of its after-effect. The ex-ante spread is believed to be more responsive to changes in the economy because of its quick reaction to changes in the macroeconomic scenario, but this approach comes with some problems. Earlier researchers have argued that banks can give different loans to their customers at different rates depending on the risk assessment or level of the customer. Therefore, this may lead to ambiguity in determining the rates at which a particular bank offers a facility
to its customers over a period of time. However, ex-post spread has the tendency of being less responsive and hence more stable, given that it is a representation of the effective outcome of financial intermediation. The ex-post approach is believed to have captured all the various rates at which loans were given to customers, because it deals with the interest accrued from the loans. Also, the study investigates how liquidity risk and credit risk have various effects on bank spreads during business cycles in Ghana. This is important, given that the relationship between spreads and the cyclical behaviour of credit and liquidity risks has not been studied in the Sub-Saharan African (SSA) region to the best of our knowledge.
Statement of Problem
Currently, most studies have in the past found that interest rate spreads have persistently been high in Ghana and other developing countries in Africa, the Caribbean and Latin America compared to OECD countries (Chirwa & Mlachila, 2004; Brock & Rojas- Suárez, 2000; Crowley, 2007; Gelos, 2009; Randall, 1998). Notwithstanding its persistence, research on this problem is scanty though the problem has dominated economic discussions in these countries for many years. The few studies on this topic have focused mainly on the causes of interest margins. Ho and Saunders (1981) found that given certain assumptions, the pure spread could be identified empirically. Saunders and Schumacher (2000) results also shows that, there is a significant and positive direction between spreads and the variance on bond rates as has been predicted by theoretical models (Saunders & Schumacher, 2000).
