DETERMINANTS OF BANKS’ PROFITABILITY IN A DEVELOPING ECONOMY: EVIDENCE FROM NIGERIA

!e unimpressive banks’ performance in Nigeria over the last decade has remained a source of concern for all and sundry. !is study investigates the e"ects of bank capital, bank size, expense management, interest income and the economic condition on banks’ pro#tability in Nigeria. !e #xed e"ects regression model was employed on a panel data obtained $om the #nancial statements of 20 banks $om 2006 to 2012. !e results indicate that improved bank capital and interest income, as well as e%cient expenses management and favourable economic condition, contribute to higher banks’ performance and growth in Nigeria. !us, government policies in the banking system must encourage banks to regularly raise their capital and provide the enabling environment that will accelerate economic growth in the country. Bank management must e%ciently manage their portfolios in order to protect the long run interest of pro#t-making.


Introduction
Banks' performance in Nigeria over the last decade remained unimpressive. e pro t before tax (PBT) of the banks uctuated, especially between 2002 and 2005, and has declined progressively since 2008. For instance, the pro t before tax which was 80.8% in 2000 fell dramatically and recorded a loss of 13.95%. Although PBT peaked at 287.62% in 2007, it nose-dived to 49.14% in 2008 (see Obamuyi, 2012). is implies that the opportunities for banks in Nigeria to make pro ts are gradually reducing. e declining pro ts could have been caused by the global economic crises, the festering crises in the banking sector and the fact that some of the criteria usually employed to measure the performance of the banks have been compromised by the Central Bank of Nigeria (Obamuyi, 2011). As Olokoyo (2011) argues, the current trend in Nigerian banking and nance sector suggests that the days of cheap pro ts are now over and only banks with well conceptualized lending and credit administration policies and procedures can survive the emerging competition. e implication of all the statements above is that banking habits have been seriously threatened thereby discouraging savings culture and hence reducing the amount of funds that can be mobilized by banks. By extension, the pro tability of the banks, regarded as a key measure of nancial performance for any company, has been negatively a ected. e foregoing con rms the worry of Sharma and Mani (2012) that the performance of banks has become a major concern for economic planners and policy makers due to the fact that the gains of the real sector of the economy depend on how e ciently the banks are performing the function of nancial intermediation. As Saona (2011) argues, an e cient nancial system improves banks' pro tability by increasing the amount of funds available for investment, while enhancing the quality of services provided for the customers. us, important role of banks arises because, by facilitating the use of external nance, they assist in reconciling the nancial interest of the de cit economic units, which invest more than they save, with those of the surplus economic units, which save more than they invest (Ojo, 2010), thereby generating reasonable income in the process.
Although the monetary authorities have taken some measures (such as banks' consolidation, review of prudential guidelines and bail-out strategy) to stabilize the nancial system and build con dence in the banking system, it is still germane to know what factors a ect banks pro tability in order to in uence policy making in the banking sector in Nigeria. us, the study investigates the e ects of capital, size, expenses management and economic condition on banks' pro tability in Nigeria. It is hereby hypothesized that, 'there exists a signi cant relationship between banks' pro tability and each of the banks' capital, size, expenses management and economic condition in Nigeria. e study becomes relevant because it will invoke the a ention of the policy makers and the bank management to pursue policies that have long lasting positive implications on the entire banking system in Nigeria. e study provides additional knowledge for researchers and the general public about factors a ecting banks' pro tability in Nigeria. e outline of the study is as follows: a er the introduction, there is the literature review, which is also followed by the methodology of the study. e results and conclusion are presented in sections four and ve respectively.

Theoretical Issues
is study examines some of the theories relating to capital and pro tability as well as bank size and pro tability. e theories include the signaling theory, expected bankruptcy cost hypothesis, risk-return hypothesis, market power and e ciency structures hypotheses. e relationship between capital and pro tability is explained by signaling theory (Berger, 1995;Trujillo-Ponce, 2012), expected bankruptcy cost hypothesis and riskreturn hypothesis (Athanasoglou, Brissimis & Delis, 2005;Olweny & Shipho, 2011). e signaling hypothesis suggests that a higher capital is a positive signal to the market of the value of a bank (see Ommeren, 2011). As Berger (1995) and Trujillo-Ponce (2012) observe, under the signaling theory, bank management signals private information that the future prospects are good by increasing capital. us, a lower leverage indicates that banks perform be er than their competitors who cannot raise their equity without further deteriorating the pro tability (Ommeren, 2011). On the other hand, bankruptcy hypothesis argues that in a case where bankruptcy costs are unexpectedly high, a bank holds more equity to avoid period of distress (Berger, 1995). As the literature review pointed out, the signaling hypothesis and bankruptcy cost hypothesis support a positive relationship between capital and pro tability. However, the risk-return hypothesis suggests that increasing risks, by increasing leverage of the rm, leads to higher expected returns. erefore, if a bank expects increased returns (pro tability) and takes up more risks, by increasing leverage, the equity to asset ratio (represented by capital) will be reduced. us, risk-return hypothesis predicts a negative relationship between capital and pro tability (Dietrich and Wanzenrid, 2009;Ommeren, 2011;Saona, 2011;Sharma and Gounder, 2012).
Consequently, the Market Power (MP) and E ciency Structure (ES) theories explain the relationship between the bank size and pro tability. Olweny and Shipho (2011) observe that the market power posits that performance of banks is in uenced by the market structure of the industry and that the E ciency Structure (ES) hypothesis maintains that banks earn high pro ts because they are more e cient than the others. Concluding on the MP and ES theories, Olweny and Shipho (2011) argue that MP theory assumes that the pro tability of a bank is a function of external market factors, while the ES assume that bank pro tability is in uenced by internal e ciencies.

Empirical Evidence
e empirical review of the study is done by identifying similarities and di erences across the various economies studied by previous researchers. e factors a ecting banks' pro tability have been empirically examined by many authors, especially in the developed countries. Demirgüç-Kunt and Huizinga (1999), using bank level data for 80 countries in the 1988-1995 periods, showed that di erences in interest margins and banks' pro tability re ect a variety of determinants: the characteristics of the bank, macroeconomic conditions, explicit and implicit bank taxation, deposit insurance regulation, overall nancial structure, and several underlying legal and institutional indicators. Athanasoglou et al. (2005) studied the e ect of bank-speci c, industry-speci c and macroeconomic determinants of bank pro tability, using an empirical framework that incorporates the traditional Structure-Conduct-Performance (SCP) hypothesis. e results indicated that all bank-speci c determinants, with the exception of size, a ect bank pro tability signi cantly in the anticipated way. Saona (2011) examined the determinants of the pro tability of the US banks during the period 1995-2007. e empirical analysis combined bank speci c (endogenous) and macroeconomic (exogenous) variables through the GMM system estimator. He found a negative link between the capital ratio and the pro tability, which supports the notion that banks are operating over-cautiously and ignoring potentially pro table trading opportunities. Sco and Arias (2011) also investigated the primary determinants of pro tability of the top ve bank holding companies in the United States. e ndings of Sco and Arias (2011), which were also highlighted by Rahman and Farah (2012), show that pro tability determinants for the banking industry include capital to asset ratio, annual percentage changes in the external per capita income and internal factor of size (as measured by an organization's total assets). Staikouras and Wood (2004) constructed the OLS and xed e ect models to examine the determinants of European bank pro tability from 1994 -1998. e authors found that the pro tability of European banks is in uenced not only by factors related to their management decisions but also to changes in the external macroeconomic environment. Khrawish (2011) accessed the Jordanian commercial bank pro tability from 2000 through 2010, and categorised the factors a ecting pro tability into internal and external factors. e author found that there is signi cant and positive relationship between return on asset (ROA) and the bank size, total liabilities/ total assets, total equity/ total assets, net interest margin and exchange rate of the commercial banks and that there is signi cant and negative relationship between ROA of the commercial banks and annual growth rate for gross domestic product and in ation rate. Dietrich and Wanzenrid (2009) analysed the pro tability of commercial banks in Switzerland over the period 1999 to 2006. eir ndings revealed that the most important factors are the GDP growth variable, which a ects the bank pro tability positively, and the e ective tax rate and the market concentration rate, which both have a signi cantly negative impact on bank pro tability. Macit (2011) investigated the bank speci c and macroeconomic determinants of pro tability in participation banks for Turkish banking sector using ROA and ROE. He found that for the bank speci c determinants of pro tability, the ratio of non-performing loans to total loans has a signi cant negative e ect on pro tability. e result is consistent with the study by Davydenko (2010) in the Ukraine. Macit (2011) also found that the log of real assets has a signi cant positive e ect on pro tability. Riaz (2013) investigated the impact of the bank speci c variables and macroeconomic indicators on the pro tability of banks in Pakistan during the period of 2006-2010. When ROA is taken as a dependent variable, he determined that the credit risk as well as the interest rate has a signi cant in uence on the commercial banks' pro tability in Pakistan. Flamini, McDonald and Schumacher (2009) investigated the determinants of bank pro tability in 41 Sub-Saharan African (SSA) countries, using a sample of 389 banks. e study proved that apart from credit risk, higher returns on assets are associated with larger bank size, activity diversi cation, and private ownership. e results also indicate that bank returns are a ected by macroeconomic variables, suggesting that macroeconomic policies that promote low in ation and stable output growth do boost credit expansion. Sharma and Gounder (2012) investigated the pro tability determinants of deposit-taking institutions in Fiji, over the 2000-2010 period. e study used panel data techniques of xed e ects estimation and generalized method of moments (GMM). e authors discovered that Market power (measured by the Lerner Index) is a key determinant of pro tability. us, institutions were allowed to pass on to their clients the interest costs of raising deposit liabilities and the overall cost of operations. Naceur and Goaied (2008) observed a positive relationship between capital and net interest margin or pro tability in Tunisia, but determined that the bank size impacts negatively on pro tability, which implies that Tunisia banks are operating above their optimal level. Olweny and Shipho (2011) evaluated the e ects of banking sectoral-factors on the pro tability of commercial banks in Kenya, using panel data from 2002 to 2008 of 38 commercial banks. e authors concluded that the bank-speci c factors are more signi cant factors in uencing the pro tability of commercial banks in Kenya than market factors. e study revealed that pro table commercial banks are those that strive to improve their capital bases, reduce operational costs, improve assets quality by reducing the rate of non-performing loans, employ revenue diversi cation strategies as opposed to focused strategies and keep the right amount of liquid assets. Aburime (2008) investigated the determinants of bank pro tability in Nigeria, using a panel data from 1980-2006. He found that real interest rates, in ation, monetary policy, and exchange rate regime are signi cant macroeconomic determinants of bank pro tability in Nigeria, while banking sector development, stock market development, and nancial structure are insigni cant. Also, Oladele, Sulaimon and Akeke (2012) found that operating expense, relationship between cost and income, and equity to total assets signi cantly a ects the performance of banks in Nigeria. Ani et al. (2012) established that capital and asset composition positively a ect bank pro tability, while bank size has negative e ect on pro tability in Nigeria. Also, Babalola (2012) used four models (an aggregated model coupled with three other decomposed models) to investigate the determinants of pro tability in Nigeria. His ndings showed that in the short run, capital adequacy ratio is the determining factor for bank pro tability. e literature reviewed above has shown the consistency of some of the internal (bankspeci c) factors like capital, size and credit risks in determining bank pro tability across di erent economies of the world. e external (macroeconomic) factors of gross domestic product growth rate and interest rate have also been prominent in the determination of bank pro tability. Consequently, the review shows that return on assets (ROA) and return on equity (ROE) are the most common criteria employed as measures of pro tability by most researchers. However, a search in the literature on the determinants of banks' pro tability indicates that only scanty empirical research, using few banks and/or economic variables, can be found in Nigeria. erefore, the study contributes to the literature by empirically re-con rming (or otherwise) the results of the previous studies, especially with regard to Nigeria's situation.

Data Collection
e panel secondary data (comprising cross-sectional and time-series data) for the study were obtained from the reports of the 20 banks in existence as at the end of 2012. e cross-sectional element is re ected by the di erent Nigerian banks and the time series element is re ected in the period of study (2006 -2012). As Saona (2011)

Dependent Variable
Researchers have employed di erent measures of pro tability to determine the factors a ecting banks' performance. For instance, the measures of pro tability employed (and the authors) include: return on assets (Flamini et al., 2009;Sco & Arias, 2011;Oladele et al, 2012;Babalola, 2012); return on equity (Saona, 2011); return on assets and return on equity (Athanasoglou et al., 2005;Dietrich & Wanzenrid, 2009;Rasiah, 2010b;Khrawish, 2011;Ali, Akhtar & Ahmed, 2011;Macit, 2012;Sharma & Gounder, 2012;Riaz, 2013); return on assets, return on equity and return on deposits ( Jahan, 2012); return on assets and net interest margins (Demirgüç-Kunt & Huizinga, 1999;Naceur & Goaied, 2008); return on assets, return on equity and net interest margins (Su an & Habibullah, 2009;Naceur & Omran, 2011;Qin & Pastory, 2012); return on assets, return on equity, pro t margin (BTP/TA) and net interest margins (Hassan & Bashir, 2005). e return on assets (ROA) is a nancial ratio used to measure the relationship of earnings to total assets. ROA is regarded as the best and widely used indicator of earnings and pro tability supplemented by return on equity (ROE) and return on deposits (ROD) ( Jahan, 2012). Studies have shown that ROA assesses how e ciently a bank is managing its revenues and expenses, and also re ects the ability of the management of the bank to generate pro ts by using the available nancial and real assets (see Jahan, 2012). e net interest income (NIM) refers to the net income accruing to the bank from non-interest activities (including fees, service charges, foreign exchange, and direct investment) divided by total assets. e bank's before-tax pro t over total assets (BTP/TA), as a measure of the bank's pro t margin, is calculated from the bank's income statement as the sum of non-interest income over total assets minus overhead over total assets minus loan loss provision over total assets minus other operating income (Hassan & Bashir, 2005).
For this study, bank pro tability is proxied by return on assets (ROA), de ned as the banks' a er tax pro t over total assets. ROA is considered as the key proxy for bank pro tability, instead of the alternative return on equity (ROE), because an analysis of ROE disregards nancial leverage and the risks associated with it (Flamini et al., 2009).

Bank-Speci c Determinants
Most of the studies on bank pro tability have categorized the determinants of pro tability into internal and external factors (Rasiah, 2010b;Naceur & Omran, 2011;and Khrawish, 2011). Furthermore, Sastrossuwito and Suzuki (2012) refer to the internal factors as the bank-speci c determinants of pro tability, while the external factors refer to the macroeconomic determinants of pro tability.
Capital: Capital refers to the amount of own funds available to support a bank's business and, therefore, bank capital acts as a safety net in the case of adverse development (Athanasoglou et al., 2005). Capital is calculated as the ratio of equity to total assets. e ratio measures how much of the banks' assets are funded with owners' fund and is a proxy for capital adequacy of a bank by estimating the ability to absorb losses (Ommeren, 2011). Based on past literature, the relationship between capital and pro table is said to be unpredictable (Sharma & Gounder, 2005). is is because while positive relationship had been found by some studies (Berger 1995;Demirgüç-Kunt & Huizinga, 1999;Hassan & Bashir, 2005;Athanasoglou et al. 2005;Dietrich & Wanzenrid, 2009;Davydenko (2010); Olweny & Shipho, 2011;Ommeren, 2011;Ani et al., 2012;and Rao & Lakew, 2012), other studies found a negative relationship between capital and pro tability (Saona, 2011;Ali et al., 2011;Qin & Pastory, 2012). Staikouras and Wood (2004) argue that a positive (negative) coe cient estimate for capital indicates an e cient (ine cient) management of banks' capital structure.
Bank Size: Bank size accounts for the existence of economies or diseconomies of scale (Naceur & Goaied, 2008). e variable is measured as the natural log of total assets (Saona, 2011). Economic theory suggests that market structure a ects rm performance (Haron, 1996) and that if an industry is subject to economies of scale, larger institutions would be more e cient and could provide service at a lower cost (Rasiah, 2010a). Also, the theory of the banking rm asserts that a rm enjoys economies of scale up to a certain level, beyond which diseconomies of scale set in. is implies that pro tability increases with increase in size, and decreases as soon as there are diseconomies of scale. us, literature has shown that the relationship between the bank size and pro tability can be positive or negative (Staikouras & Wood, 2004;Athanasoglou et al., 2005;Flamini et al., 2009;Dietrich & Wanzenrid, 2009;Naceur & Omran, 2011).
Expenses Management: Expenses management relates to the idea of e cient management of banks' resources. For this study, the variable measures the ratio of operating expenses to total assets. As Athanasoglou et al. (2005) observe, a negative relationship is expected between expenses management and pro tability, since improved management of the expenses will increase e ciently and hence raise pro ts.

Macroeconomic Determinants
Interest Rate: e bank lending rate is expected to have a positive impact on bank pro tability. is is because interest rate directly impacts bank interest income and expenses, and the net result that further a ects pro tability.
Dummy of Real GDP Growth: the real GDP growth is used as a proxy of business cycle in which banks operate, and controls for variance in pro tability due to di erences in business cycles which in uence the supply and demand for loans and deposits (Staikouras & Wood, 2004;Ommeren, 2011). In this study, GDP is used as a dummy in de ning favourable/unfavourable conditions, i.e., a dummy of the shi in economic activities (GDP) from favourable (1) to unfavourable (0) conditions. us, higher (lower) GDP indicates favourable (unfavourable) business opportunities under which a bank can achieve higher (lower) pro tability. is is because an increase in economic activities of the country signals that customers' demand for loans will increase, and with improved lending activities, banks are able to generate more pro ts.

Method of Analysis
e paper made use of both descriptive and econometric analyses. e descriptive approach was used to analyze the means and further shows the normality of the distribution. A preliminary estimation of the correlation coe cients of the variables was carried out in order to determine the explanatory variables that would nally appear in the regression model. e econometric approach examines the main factors a ecting banks' pro tability in Nigeria by applying xed e ects model. e results of the xed e ects would be compared to that obtained from the random e ects through the Hausman (1978) speci cation test. e speci cation of the model for the study is based on the empirical works of Demirgüç-Kunt and Huizinga (1999), Athanasoglou et al. (2005), Flamini et al. (2009) andSaona (2011). Five explanatory variables are included in the regression analysis. e empirical model takes the following form: where ROA it is the return on asset (bank pro t over total assets) and represents the pro tability of bank i at time t, with i = 1, 2, ..., N, t = 1, 2, ..., T, α is a constant term, Y it is a vector of k explanatory variables and ε it is the disturbance with v i the unobserved bank-speci c e ect and u it the idiosyncratic error.
Based on the reviewed literature, vector Y consists of some independent variables, categorized as internal factors (Y p it ), and external factors (Y q it ). Hence, Y it can be divided into two groups as: it e internal (bank-speci c) control variables (Y p it ) are bank capital (ratio of equity to total assets), bank size (natural log of total assets) and expenses management (ratio of operating expenses to total assets). e external (macroeconomic) control variables (Y q it ) refer to the variables of bank interest (lending) rate and the dummy of the GDP growth rate.
Meanwhile, some reliability tests were also carried out in the study. e coe cient of determination (R 2 ), also known as the goodness of t that describes how well the model ts a set of observation, was employed to measure the degree of relationship existing among the variables. e statistic would show the percentage of total variation in dependent variable that is explained by the independent variables. e Durbin-Watson (D-W) statistic was also used to nd out whether there is the incidence of autocorrelation among the variables in the model. Table 1 presents the results of the descriptive statistics of both the dependent and independent variables for the panel data analysis of the study.

Results of the Descriptive Statistics
From the results in Table 1, the analysis of the means shows the following descriptive statistics: pro tability (M = 0.018, SD = .008); capital (M = 0.185, SD = 0.058); bank size (M = 5.803, SD = 0.298); expenses management (M = 0.036, SD = 0.013); interest rate (M = 0.216, SD = 0.023); and GDP dummy (M = 0.429, SD = 0.495). e analysis indicates that the bank size has the highest means (M = 5.503), with the deviation from the mean at 29.8%. e lowest standard deviation for pro tability (0.008) indicates that the data are clustered around the mean and thus more reliable.
e Jargue-Bera statistic indicates that all the data series are normally distributed. is is indicated by the probability values of JB statistic which for those series are signi cantly di erent from zero at 1% signi cant level. In any case, evaluating normality indicates that the acceptable range of -1.0 to + 1.0 was satis ed for all the variables.

Discussions of Econometric Results
Table 2 below presents the results of the correlation analysis for the study in order to determine the level of association among the variables.  Table 2 indicate that a positive correlation exists between pro tability and each of the independent variables (capital, bank size, expenses management, interest rate and the economic condition of the country).
us, the correlation coe cients indicate that an improvement in bank capital, bank size, expense management, interest rate and the economic condition of the country leads to higher pro ts for the banks. e results of the correlated random e ects -Hausman test (not shown here), performed to decide between xed or random e ects, indicate that the xed e ects model is more suitable than the random e ects model (chi2 = 0.001). e regression results in Table 3 are based on the xed e ects model. From the results in Table 3, the xed e ects coe cients of the regressors indicate how much pro tability changes when there is a change in the capital of each bank, bank size, expenses management, interest rate and economic condition of a country. From Table 3, the overall regression is statistically signi cant, F = 48.40, p = .001, thus supporting the fact that capital, size, expenses management, interest rate and the economic situation of a country are important factors in determining the pro tability of the banks in Nigeria. e coe cient of multiple determinations (R 2 ), which indicates the quality of tness of the model, shows that about 89.30% of the changes in pro tability of the banks in Nigeria are caused by the combined in uence of the independent variables of the bank capital, bank size, expenses management, interest rate and the economic situation of the country. With a value of 89.30%, the strong positive relationship between pro tability and its determinants is further con rmed. e results of the Durbin Watson Statistics of 2.026 indicates that there is no autocorrelation among the variables included in the model, making the model more reliable. e relationship between pro tability and capital is positive and statistically signi cant. e results imply that the banks with larger capital are able to diversify their business operations by strengthening their ability to assume risk and a ract funds at low cost, which will enhance their liquidity position. e overall e ect will be an improvement of their lending, with positive e ect on pro tability. As Athanasoglou et al. (2005) observe, a bank with a sound capital position is able to pursue business opportunities more e ectively and has more time and exibility to deal with problems arising from unexpected losses, thus achieving increased pro tability. e results con rm the study by Saona (2011) and Bourke (1989). For instance, Bourke (1989) found that capital ratios are positively related to pro tability under the assumption that well capitalized banks may enjoy access to cheaper and less risky sources of funds and be er quality asset markets. Berger (1995) and Saona (2011) a ribute the two potential explanations for the positive relationship between the bank's pro ts and the capital ratios to the expected bankruptcy costs hypothesis and the signaling hypothesis. e result is consistent with the works of Naceur and Goaied (2008), Sco andArias (2011), andOladele et al. (2012).
Bank size has a negative but statistically signi cant e ect on banks' pro tability (ROA). e results indicate that banks are likely to earn fewer pro ts as compared to small banks. e negative relationship could be that, as the banks are becoming extremely large, the bureaucratic procedures have negatively a ected their performances. For instance, the forced mergers and acquisitions of banks in Nigeria in 2006, where the number of banks were reduced from 89 banks to 24 groups of banks in 2006, could have caused the returns of the banks to decline. us, policy makers should be cautious and understand, as Shih (2003) argues, that the acclaimed synergy from banks' mergers is not automatic, and that the returns from the bank merger are more likely to be negative than positive. e results con rm the works of Staikouras and Wood (2004) and Ani et al. (2012) that growing banks may face diminishing marginal returns which will cause average pro ts to decline with size. e expenses management variable has a negative and signi cant e ect on banks' pro tability as expected. is nding implies that e cient management of banks' expenses, by reducing the cost of operations, improves the performance of the banks. e most important policy lesson to the banks is that reducing the cost of operations reduces the incidence of failure of the banks and hence strengthens the con dence of the shareholders and the public through improved nancial performance of the banks. us, as stated by E ciency Structure (ES) hypothesis, an e ciently managed bank will earn higher pro ts than the less e cient ones.
In line with the researcher's expectation, the variable of interest rate was positive and statistically signi cant. is implies that the pro ts of banks tend to increase with increasing rate of interest. is is understandable in Nigeria because, o entimes, most banks charge high rate of interest on loans and advances because of their perceived risk of doing business in the country. Since the borrowers have no readily available alternative sources of borrowing to nance their investments, the availability doctrine, rather than the cost doctrine, has been the only option. is means that they are ready, at whatever cost, to obtain loans from the banks as far the loans are available. e higher interest rates bene t the banks in terms of higher pro ts, but at the expense of the overall economic development of the country.
Expectedly, the dummy of GDP variable has positive and statistically signi cant relationship with pro tability. e positive e ect is an indication that higher GDP represents improved business opportunities, which ultimately leads to higher pro tability. e result is consistent with theory as documented in the studies by Dietrich andWanzenrid (2009), andFlamini et al. (2009).

Conclusions
e paper investigates the e ects of capital, size, expenses management, interest rate and economic condition on banks' pro tability in Nigeria. ese factors a ecting banks' pro tability were categorized as bank-speci c variables (bank capital, size and expense management) and macroeconomic variables (interest rate and GDP, proxy for business cycle).
Several sources of theoretical and empirical reviews were used to support the relationship between pro tability and each of its determinants. e theories include the signaling theory, expected bankruptcy cost hypothesis, risk-return hypothesis, market power and e ciency structures hypotheses. e econometric model of xed e ects regression was employed for the study, using a panel data (comprising crosssectional and time-series data) of 20 banks in Nigeria between 2006 and 2012. e results con rm some previous ndings that the bank capital, expenses management, interest rate and the economic situation of the country have statistically signi cant e ects on banks' pro tability in Nigeria. e results indicate that improved bank capital and interest income, as well as e cient management of banks' expenses and favourable economic condition contribute to higher banks' performance and growth in Nigeria. Accordingly, the impact of GDP growth rate on pro tability indicates that banks can achieve higher (lower) pro tability under favourable (unfavourable) conditions. Government policies in Nigerian banking sector must encourage banks to regularly raise their capital and provide the enabling environment that will accelerate economic growth in the country. ese results have important implications for banks' survival and growth. It is hoped that the study will guide the policy makers and bank regulators in the formulation and implementation of macroeconomic policies which may a ect the stability of the banking system in Nigeria.