ejefas_19_06

European Journal of Economics, Finance and Administrative Sciences ISSN 1450-2275 Issue 19 (2010) © EuroJournals, Inc. 2010 http://www.eurojournals.com

Theoretical Framework of Profitability as Applied to

Commercial Banks in Malaysia

Devinaga Rasiah

Multimedia University, Faculty of Business and Law, Melaka, Malaysia

E-mail: [email protected] Tel: +00116 06 2523346

Abstract

This paper is represents a theoretical review of the profitability of Commercial banks. The determinants of profitability and theories thereof used in this study are those frequently described in conventional banking studies and literature. The profitability determinants were basically divided into two main categories, namely the internal determinants and the external determinants.

In order to incorporate the internal and external determinants into a single profitability model, it was necessary to pool cross-section and time-series data. As a result, it was necessary to include dummy variables to take account of inter-firm and inter temporal differences in the intercept. Thus, pooled regression analysis was applied to a linear model to analyse the profitability determinants of commercial banks. Keywords: Banking Profitability; Internal and External determinants on Profitability,

Financial ratios.

Introduction The main purpose of this theoretical review is to establish a theoretical framework of commercial bank profitability to determine the variables which should be included in profitability models. In this context, variations in environmental factors and financial reporting procedures is taken into account.

To begin with profitability is simply the difference between total revenue and total cost. Thus, the factors which affect commercial bank profitability would be those which affect banks’ revenue and costs. Hence, the impact of the internal and external determinants of commercial bank profitability will be analysed with a view to their impact on bank revenue and costs.

This theoretical study focuses on the dependent variable namely bank profitability. This will be followed by the internal determinants of commercial bank profitability. On the other hand, the external determinants of commercial bank profitability will be dealt before the description of the specification of external variables.

Dependent Variables Profitability will be measured in terms of ratios. The advantage of using profitability ratios is that they are inflation invariant that is they are not affected by changes in price levels. This is useful in a time series analysis such as this, where the real value of profits may be distorted by the time varying inflation rates.

75 European Journal of Economics, Finance and Administrative Sciences - Issue 19 (2010)

In analysing how well any given bank is performing, it is often useful to contemplate on the return on assets (ROA) and the return on equity (ROE) as used by Bourke (1989) and Molyneux and Thornton (1992). The choice of the profitability ratio will depend on the objective of the profitability measure. The ROA is primarily an indicator of managerial efficiency. It indicates how capable the management of the bank has been in converting the institution’s assets into net earnings. The ROA is a valuable measure when comparing the profitability of one bank with another or with the commercial banking system as a whole. A low rate might be the result of conservative lending and investment policies or excessive operating expenses. If time and savings accounts are a large proportion of the total deposits, interest expenses may be higher than average. Banks can then tailor-make lending and investment policies to generate more income and to increase their profits.

Unlike the ROE, the ROA cannot be subject to an increase of higher borrowings, as debt will increase the level of assets as well. The higher the ratio the better the profits. The ROE, on the other hand, is a measure of the rate of return flowing to the bank’s shareholders. The ROE ratio is calculated by dividing a bank’s net income by its average total equity, that is common and preferred stock, surplus, undivided profits, and capital reserves. This measure of profitability is the most important for a bank’s stockholders, since it reflects what the bank is earning on their investment. The higher the ratio the better, as it reflects a more effective utilisation of shareholders’ funds. However, it is possible for this ratio to be increased as a result of an increase in liability (such as bank borrowings) to generate net income while shareholders’ funds remain unchanged. In the context of ROE, consistent with Bourke (1989), and Molyneux and Thornton (1992), total equity is assumed to include both shareholders’ capital and reserves.

An additional uncertainty that needs to be cleared is that total assets and equity capital may not remain constant throughout the year. To this extent, in line with Frame and Holder (1994), average values of consecutive year-end balance sheet figures will be used in this study.

An additional argument with regard to net incomes is the choice between pre-tax and after tax profits. In a study which is restricted to commercial banks, the choice between pre and post tax profits may seem important since all banks in different countries would be subject to dissimilar corporation tax. However ,if taxation is precisely thought about as a cost to the firms ,then after tax profits would positively personify more appropriate measure of performance. Thus, in line with Bourke (1989),and Molyneux and Thornthon (1992), both pre and post tax profits will be used as the dependent variable in this study.

Bourke (1989), had indicated in his study, the use of value added measures of profitability when testing the validity of the risk aversion hypothesis and the expense preference hypothesis. He added that in the value added measure of profitability, net income is aggregated with expense items such as provision for losses and staff cost. Subsequently as these costs are tax deductible, it should not be applied in determining the value added measure of profitability.

In line with the above argument, the following measures of profitability considered by Bourke (1989) will also be considered as the dependent variable in this study.

BTTA Net income before Tax as a percentage of total assets. ATTA Net income after tax as a percentage of total assets. BTCR Net income before tax as a percentage of capital and reserves. ATCR Net income after tax as a percentage of capital and reserves.

The table indicates the variables BTTA and ATTA represent before and after tax return on

assets (ROA) measure of profitability respectively. Similarly, BTCR and ATCR represent before and after tax return on equity (ROE) measure of profitability respectively

Internal Determinants of Bank Profitability In this section, the management controllable factors that affect bank revenue and costs will be analysed. To this extent, the internal factors which tend to have a direct impact on bank revenue and


costs are the banks’ assets and liability portfolio management and overhead expense management. On the other hand, liquidity ratio and capital ratios tend to have an indirect effect on bank profitability.

Asset Portfolio Mix A bank’s revenue is basically generated from its assets. However, it is worth nothing that not all assets generate revenue. Thus, the assets of a bank can basically be classified as income or revenue generating and non-income generating. To this extent, it is worth noting that banks’ income can be classified as:

i. interest income ii. Non-interest income

The interest income is basically derived from interest charged on loans, and overdrafts and trade finance. On the other hand, the non-interest income includes fees, commissions, brokerage charges and returns from investments in subsidiaries and securities. To this extent, Vong (1996), had asserted that a major source of income (about 80%)for commercial banks is interest income. The next important source of revenue is derived from dividends and gains from dealing in the securities market. Other minor sources of income include earnings from trust activities and service charges on deposit accounts.

Loans and Interest Income It is needless to emphasize that one of the principal activities of commercial banks in is to grant loans to borrowers. Loans are among the highest yielding assets a bank can add to its balance sheet, and they provide the largest portion of operating revenue. In this respect, the banks are faced with liquidity risk since loans are advanced from funds deposited by customers. However, the higher the volume of loans extended the higher the interest income and hence the profit potentials for the commercial banks. At this point, it is also worth noting that banks with a high volume of loans will also be faced with higher liquidity risk. Thus, the commercial banks need to strike a balance between liquidity and profitability.

The recent financial crisis in East Asian countries like South Korea, Indonesia, Thailand and Malaysia presents clear evidence of the importance of loan quality. A high volume of loans alone is not a guarantee for high interest income. If the borrowers default then the interest income will not be earned and this will certainly affect the profitability of the bank adversely. Thus, the quality of the loans would also contribute towards higher profitability. To this extent, it is worth nothing that

the non-performing loans can be used as an indicator of the loans quality. Hence, the non-performing loans must also be taken into account as a factor which may affect a bank’s interest income and hence profitability. Furthermore, it must also be noted that higher interest income are not merely a function of higher volume of loans but are in fact also dependent on the lending rates and the interest rate elasticity of loans as well. The interest rate elasticity of loans will depend on the national affluence or national income. The following variable will be used to capture the inter firm difference of the commercial bank asset composition.

LOTA Loans and advances as a percentage of total assets.

Investments Haslem (1985) indicated that commercial banks allocate funds to investments once funds has been allocated for revenues, given the loan portfolio, the residual funds are allocated to investments in either in their subsidiaries or investment in securities. Haslem (1985) highlights that while bank loans are for short periods say, a few months or at the most a year or two, investments are generally longer and also in the form of government securities. Commercial banks prefer investments for two reasons firstly, to


acquire assets, which can be easily shifitable to other banks, and secondly, they should have good income-yielding capacity. Investments involve a risk element in selling them in times of need, if their market price is lower than the price at which the bank had originally purchased them. If however, a commercial bank has a certain amount of funds, which can be left undisturbed. Hence, investments variable is divided into two categories as follows:

INVS Investments in securities of each commercial bank as a percentage of total assets INVSUB Investments in subsidiaries of each commercial bank as a percentage of total assets

Non-Interest Income Earning Assets Sources of income other than earnings from loans are called non-interest income. Non- interest income includes fees earned from offering unit trust services, service charge on deposit account, standard fees and charges for other bank services. With increasing globalisation and financial liberalisation the banking business has been undergoing a gradual transformation away from the traditional business of financial intermediation and towards provision of other financial services including mutual fund, insurance etc. Thus, non-interest income would represent a key source of bank revenue in the future. By more aggressively selling services other than loans such as brokerage, insurance and trust services, bankers have found a promising channel for boosting the income statement by diversifying their income sources, and for insulating their banks more adequately from fluctuations in interest rates and loan default risk.

Total Expenses The expenditure items that fall within the control of bank management can be broadly divided into 3 categories: staff expenses, provision for loan losses, and other general expenses. Expenses, such as payment for income tax, are considered statutory expenses and hence beyond the control of management. In the case of making provisions for loan losses, for example, the amount set aside for these expenses is reflected in the quality of their credit policies undertaken by the bank.

To this extent, one of the major expense incurred in generating revenue include interest paid out to depositors which is termed as interest expenses. Other expenses are non-interest expenses such as overhead expenses, operating expenses, salaries and wages paid to employees and miscellaneous expenses, the more expenses incurred by the bank, the less profit the bank will make. Operating Expenses

Operating expenses are defined in the OECD Bank Bulletin (1987), as including all expenses relating to the ordinary and regular banking business other than interest expenses, fee and commission expenses, provisions, income taxes and computer programming and equipment maintenance costs. Thus, operating costs comprises all expenses related to the use of physical and labour factors. Since these expenditures are management controllable expenses, and if controlled properly, can contribute positively to the generation of operating revenue. Personnel Expenses

In view of the size of the wages and salaries components in the operating expenses of commercial bank, inter-firm differences in labour productivity (the amount of product per worker per unit of time) may also affect operating expenses and hence profitability. The cost of labour, property, rents and technology would be the most significant cost items in the commercial banks operating expenses. The proportion of staff cost to total operating cost in most Asian counties is reaching an unprecedented level of between of 60% to 65%.


To this extent, Rhoades and White (1984), analysed productivity trends for U.S. banks over the period from 1972 to 1979. Their results indicated a slight decline in labour productivity. This coupled with inflationary pressures, annual increase in staff compensation and new staff recruitment had pushed up staff cost, thus adversely affecting operating expenses and hence profitability.

However, studies carried out by Miller and Noulas (1994), reported that higher salaries and benefits per employee was consistently associated with higher net charge offs to total assets. They suggested that banks with higher salaries and benefits would require higher net interest margins to maintain profitability.

Consequently in order to assess a firm‘s efficiency at expenses management, we would have to repel the expenditure to reflect variations in activity level. To this extent, the usual practise in most bank research reviewed in chapter four was to deflate total expenditure by total assets which would indicate the cost incurred per monetary unit of asset. Thus, in line with Stienherr and Huveneers (1994), applied total overhead expenditure in their study. Based on the availability of data, this study also uses total overhead expenditure instead of staff expenses as a proxy for expenditure. The variable used in the model is given below:

OVHTA Total overhead expenditure as percentage of total assets

Liability Composition

Liability portfolio Management especially deposit composition may also influence the profitability of commercial banks. Heggestard (1977) and Clark (1992) had considered the ratio of time and saving deposits to total deposits to capture variations in banks profits rates resulting from time and saving deposits to total deposit to capture variations in banks profits rates resulting from inter bank differences in deposit composition. Since time and savings deposits represent a relatively higher cost source of funds, the more a commercial bank is committed to time and saving deposit, the higher would be the funding cost and hence the lower the profits. Deposit Composition

The number one expense item for a bank is interest paid. Commercial banks mainly depend on the funds deposited with them by the public to lend it out to others inorder to earn interest income.

Deposits are of three kinds, namely: 1. Current or demand deposits 2. Fixed or Time deposits / Term deposits. 3. Savings deposits

On current or demand deposits, the bank pays practically no interest in Malaysia. They can be withdrawn in part or in full at any time by issuing cheques. Fixed / Time / Term deposits are so called because they are left with the bank for a certain fixed period before the expiry of which they cannot be withdrawn except after giving due notice. On such deposits, the bank pays higher interest. Savings deposits can be withdrawn anytime subject to certain limitations regarding the amount withdrawn or the frequency of withdrawals. In actual fact, only a small percentage of savings are withdrawn at any particular time. Since withdrawals can and do take place, the commercial bank has to keep a certain proportion of its assets in liquid form. Commercial banks, accepts cash and hold on to as much of it as possible because the more it has and can retain the more funds it can lend to the public. That is, the more cash a commercial bank has the greater is its capacity to make profits. And because the commercial bank always utilises its funds to the full in lending funds, the greater is the commercial banks’ profitability. Hence, the competition for deposits is really a competition for profits. Commercial banks compete for deposits in order to become larger and thus to be able to supply more funds to the public. However such financial growth is profitable only if the commercial bank does not incur additional expenses to obtain and retain cash.


The liability component is not the same due to the difference in the reporting of data by the commercial banks in their annual reports. For this study the variables will be maintained as structured in the annual reports. The addition of the savings, fixed deposits and current accounts ratios would lead to the sum of the total deposits and this would lead to a multicollinearity problem. The saving deposit would be dropped since it had the lowest correlation and only fixed deposit and current account deposits ratios will be maintained.

In view of the above discussion the liability composition would be represented by the following variable:

CAD Current account deposit as a percentage of total deposits TSAVD Time and Savings deposit as a percentage of total deposit

Liquidity Ratios

In addition to the maintenance of cash reserve with the Central Bank, the commercial banks are also required to maintain a minimum level of liquid assets. While the primary reason behind the imposition of minimum liquidity ratio is to ensure that the commercial banks have, at all times, a reservoir of liquidity which can be tapped to meet unusual deposit withdrawals, the ratio can also be used as a means of influencing the monetary situation in theses countries.

Furthermore, it must be noted that liquidity is the quality of an asset that makes it easily convertible into cash with little or no risk of loss. A bank is considered to be liquid when it has sufficient cash and other liquid assets, together with the ability to raise funds quickly from other sources, to enable it to meet its payment obligation and financial commitments in a timely manner. When total demand for liquidity exceeds its total supply, the commercial banks will be faced with liquidity deficit. In such a situation these institutions will be forced to raise additional liquid funds by borrowings or disposing some of their liquid assets. Usually, short-term borrowings are costly and the loss of income from the sale of liquid assets will tend to have an adverse effect on profitability. On the other hand, idle funds and the lower returns on liquid assets may also adversely affect the profitability of those institutions with surplus liquidity. Thus, liquidity management represents yet another important determinant of commercial bank profitability. Since data on loans to deposits of commercial banks are disclosed in their annual reports, the loans to deposit ratio can be easily calculated. Consequently, the loans to deposit ratio will be used in this study as a proxy for liquidity and will be denoted as follows:

LIQ Loans to deposit ratio of each bank.

The loans to deposit ratio is inversely related to liquidity and consequently the higher the loans

to deposit ratio the lower the liquidity and vice versa. Subsequently liquidity is inversely related to profitability, and hence the coefficient of the loans to deposit ratio expected to be positive.


Capital Structure

Capital structure in commercial banks are made up of shareholders’ funds, reserves and retained profits. In addition, capital also represents a source of funds along with deposits and borrowings which is regulated by the capital adequacy requirements.

The capital structure is assumed to affect the profitability of commercial banks via its effect on leverage and hence on risk. To this extent, the assets of the commercial banks can either be capital or debt financed. However, debt financing can be more risky compared to capital financing in view of the credit risk and liquidity risk faced by the commercial banks.

A commercial bank with higher capital asset ratio would be able to assume higher risk. This may induce the commercial banks to absorb greater risk in their asset portfolios in the hope of maximising expected returns. In line with the above discussion the capital assets ratio is also included in this study and is defined as follows:

CTRA Capital and reserve as a percentage of total assets.

A summary of specification of internal variables is indicated above. In relation to the expected

results, the impacts of the variables on profitability are described positive, negative or uncertain.

External Determinants Apart from revenue and costs, a plethora of factors have an overbearing influence on the banks’ profit and loss statement. Unlike the internal determinants, these factors operate outside the control of the banking firm. These external determinants are indirect factors, which may be uncontrollable, but nevertheless influence the bank’s profitability. The commercial banks cannot control these indirect factors but can build flexibility into their operating plans to react to changes in these factors.

Specification of Variables of commercial Banks

Summary of Internal Variables and The Expected Results

Determinants Variables Description Expected

Relationship

LIQUIDITY Loan to deposit ratio of each bank LIQ Positive CAPITAL Capital and reserves as a percentage of total assets CTRA Negative LIABILITY

(DEPOSIT)

COMPOSITION

Time and saving deposit of each commercial bank as a percentage of total deposit Current account deposit of each commercial bank as a percentage of total deposit.

TSTD CATD Negative Positive

ASSETS

COMPOSITION

(LOANS)

Loans and advance of each commercial bank as percentage of total assets.

LOTA Positive

INVESTMENTS

(SECURITIES)

(SUBSIDIARIES)

Investments in securities of each commercial bank as a percentage of total assets. Investments in securities of each commercial bank as a percentage of total assets

INV SEC INV

SUB

Positive

Positive

The following indirect factors that affect the profitability of commercial banks will be

considered in this study: i. Regulation

ii. Inflation iii. Interest Rate iv. Market Share v. Market Growth

vi. Firm size


Regulations

Commercial banks are stringently regulated by the Central bank to prevent failures because of fraud, mismanagement etc. Commercial banks must comply with all applicable laws, such as statutory reserve requirements, liquidity requirements, laws relating to taxation and accounting procedures, opening of new branches, mergers, etc.

Statutory liquidity requirements have a very visible impact on assets and liability management in commercial banks. The commercial banks are required to keep a percentage of all deposits in certain specified liquid assets. These liquid assets (often including a percentage in minimum cash balances to be placed at zero interest with the external bank) have to be managed so that the punitive cost of keeping these liquid assets will not increase the commercial bank’s cost of funds to an uncompetitive level. Inflation

Inflation had been one of the least researched issues in earlier bank profitability studies. Revell (1979) had suggested that inflation may be a factor in the causation of variations in bank profitability although it is worth noting that researchers had paid very little attention on the impact of inflation on commercial bank profitability.

The classical belief is that, because bank assets and liabilities are expressed in monetary terms and because these assets will normally grow in line with growth in money supply, banks are relatively immune from the effects of inflation. The best remedy for fighting inflation is to reduce the aggregate spending. Monetary policy can help in reducing the pressure of aggregate demand. In brief, monetary policy works by controlling the cost and availability of credit. During inflation, the Central bank can raise the cost of borrowing and reduce the credit creating capacity of commercial banks. This will make borrowing more costly than before and thereby the demand for funds will be reduced. Similarly with a reduction in their credit creating capacity, the banks will be more cautious in their lending policies. The result will be a fall in the volume of spending.

In a time series analysis of profitability such as this, it would certainly be important to consider whether the profitability gains are real. To this extent, if the rate of increase in profits were less than the rate of inflation then the commercial bank profitability would stand to lose in real terms. Hence, it is certainly important to account for inflation in model for determining commercial bank profitability.

Furthermore, inflation may also affect commercial bank profitability by diminishing the real value of banks’ assets and liabilities. Since banks are net monetary creditors, their nominal assets would be greater than their nominal liabilities. Hence, inflation would decrease the value of their nominal assets to a greater extent rather than increase the value of their nominal liabilities.

To this extent, Perry (1992), working on banks’ gains and losses from inflation asserted that the effect of inflation on bank performance depends on whether the inflation is anticipated. If inflation is fully anticipated, then all interest rates will rise to include an inflation premium. Hence, the real value of all assets and liabilities except the bank’s demand deposits and reserves will remain unchanged. Demand deposits net of reserves will however decrease in value as prices rise. Thus, the liabilities of the bank will fall in real terms and the bank becomes more profitable.

Studies carried out by Bourke (1989), and Molyneux and Thornton (1992), are some of the few researchers who have categorically examined the effect of inflation on bank profitability. They had used the annual percentage increase in the consumer price index as a measure of the rate of inflation. Their studies revealed a significant positive relationship between the rate of inflation and bank profitability. This may be so, if the inflation is anticipated and interest rates adjust correspondingly resulting in revenue which increases faster than costs. However, the above positive relationship between inflation and bank profitability may not be expected to bear out in conditions of unanticipated or excessive inflation.

Consequently, the profits of commercial banks would depend to a large extent on the effect of inflation on their revenues and costs. However, since economy are blessed with low inflation and


sustained economic growth as a whole, we can expect a positive relationship between inflation and bank profitability consistent with Bourke (1989), and Molyneux and Thornton (1992). Consequently, inflation will be included in this model and is defined as follows :

INF Annual percentage increases in the Consumer price Index.

Interest Rate

Interest expenses and interest income, affect net interest income and hence bank profitability. In view of this, interest rates have also been considered as determinants of bank profitability in most bank research. Furthermore, since local monetary policies and supply and demand conditions affect interest rates, it has been included as an external profitability determinant in these studies. Short and Long Term Effects of Interest Rate on Assets.

The effects of interest rate changes on financial institutions’ portfolios depend on the extent and speed with which rate change on short -and long -period securities. They also depend on the proportion of an institution’s assets and liabilities that are long period rather than short period and the speed and flexibility with which the institution can alter its revenue streams and cost of funds.

a) Short term Asset gains

When interest rates fluctuate as result of changes in monetary policy or general economic conditions, commercial banks usually encounter a comparative change in the rate of return they earn on their assets. This occurs because banks hold many assets of relatively short maturity, and the rates booked on short-period loans fluctuate quickly when interest rates fluctuate.

b) Long-term Asset gains

The only components of a banks’ investment portfolio that will not encounter rapidly falling yields when interest rates decrease are specifically: consumer loans, fixed-rate, mortgage loans, rates on bank credit card loans, business term loans, long period investment securities, real assets, such as rental offices in the bank building. Consequently, even the longer -period components of a bank’s assets portfolio are susceptible to yield declines when market interest rates fall, although their yields fall more gradually than short-period yields. In the short run, however, as general market interest rates descend, the market value of longer assets with fixed contractual terms will rise. Thus, the bank could, if it wishes, sell some of its longer -period assets at an appreciated price after market interest rates fell. In the short run, such sales would increase a bank’s profitability.

In view of the above-suggested problems, the base-lending rate (BLR) appears to be the ideal candidate to proxy for market interest rate. Since 1991 the commercial banks were allowed too freely quote their own BLR based on a standardised formula, which takes the funding cost into account. The standardised formula is matched to ensure that the BLR will move in synchronisation with market conditions. A further benefit of the BLR is that it would be reflective of both movements in cost of funds and lending rates. The only problem with the BLR is that the commercial banks are required to calculate their BLR on a monthly basis and hence may be subject to variations on a month to month basis.

In this context, the Monetary Authority of Singapore, (1996) reported that in Singapore, prior to July 1975, interest rates were determined by a cartel system under which all banks quoted the same prime lending and deposit rates. Since July 1975, banks have been free to quote their own prime lending and deposit rates. The prime (minimum) lending and deposit rates are the average rates quoted by 10 leading banks in terms of loans and deposits respectively. Thus, in this study market interest rate will be represented by annual average BLR on commercial banks and will be described as follows:


BLR Average annual BLR of commercial Bank

As for inflation and lending rates being correlated, interest rates will increase as inflation rate

increases and therefore only lending rates will be maintained. Market Share

Market share has been attended to in this study as an external determinant of commercial bank profitability for two reasons:

• Market share expansion could create potentials for increase income.

• Efficient structure hypothesis postulates those firms with exceptional efficiency and hence low cost structures earn supernormal profits and these firms are then presumed to expand and gain large market shares.

In this context, the efficient structure hypothesis postulates that firms with superior efficiency and hence low cost structures acquire supernormal profits (Smirlock, 1985). These firms are then assumed to develop and secure large market shares, thus ensuing in high market concentration. Consequently, efficient firms are assumed to be driving both profits and market structure. Therefore evidence in favour of the efficient structure hypothesis can be found if firm’s profitability is positively correlated with the market share variable.

However, in this study market share instead of market concentration is used to analyse the validity of the expense preference hypothesis and the risk aversion hypothesis. The justification for this is that sub-market bank concentration data are not readily available. Nevertheless, since market concentration is homogeneous with the market shares of the firms participating in the market, it is felt that market share can be used as an appropriate proxy for market concentration.

In view of the forgoing controversy, market share is also included as an external determinant of commercial bank profitability. However, since both deposit and loans can be carefully thought about as bank output, there is the choice between a deposit or asset measure of market share. In view of the fact that the asset components may include investment in securities and subsidiaries, which in actuality would be homogenous across firms, the deposit measure of market share is considered to be more impartial measure of market share for commercial banks in this. Hence, the Market Share variable is defined as follows:

MSD Total deposit of each bank as a percentage of all banks assets

Market Growth

Previous studies by Bourke (1989) indicated that development in the total market could be associated with entry barriers and this may lead to banks earning higher profits. However, Molyneux and Thornthon (1992), had applied money supply as an independent variable to proxy for market growth . Molyneux and Thornthon (1992), highlighted in his study that in the proximity of other deposit taking institutions such as the merchant banks and discount houses, the annual growth in the total deposit of just commercial banks would not in full measure represent the actual market growth. Thus, the annual growth in money supply will also be carefully thought about as a proxy for growth in this study.

Earlier studies showed that Market growth has been represented by growth in total deposit. Researchers such as Smirlock (1985), Clark (1987) and Rhoades (1987). Bourke (1989), and Molyneux and Thornton (1992) had used annual growth in money supply as an independent variable to proxy for market growth.

In view of the presence of other deposit taking institutions such as the merchant banks and discount houses, the annual growth in the total deposit of just commercial banks would not sufficiently represent the actual market growth. Thus, the annual growth in money supply will also be considered as a proxy for market growth in this study.


In this extend, the M2 measure of money supply in Malaysia is defined as currency in circulation plus the commercial banks demand deposits, savings deposits, fixed deposits, net issues of NCD and repo transactions at commercial banks. The M3 measure of money supply is in turn defined as M2 plus the savings deposits, fixed deposits, net issues of NCD and repo transactions of finance companies, discount houses and the Islamic bank. Whereas, in Singapore, the M1 measure of money supply is defined by MAS (1986), as currency in circulation plus the commercial banks demand deposits. The M2 measure of money supply is in turn defined as Quasi-money, fixed deposit, savings and other deposits issues of S$NCDS. Finally, the M3 measure of money supply is in defined as net deposit with non-bank financial institutions.

MON Annual growth in the M3 measure of money supplies.

Firm Size

As far as banks are concerned, like other organisations, the management is quite distinct from the owners of the business. So the management is not directly responsible for making size-related decisions. T this extent the size factor would be considered as an external variable. This is particularly worthy of noting that the determinants of bank profitability were divided into internal determinants or management controllable factors and external determinants or factors beyond the control of management. In this context since size-related decisions are beyond the control of management, they are considered as external determinant of bank profitability in this study.

Early studies carried out by researchers such as Short (1979), had considered bank size as an independent variable to account for size related economies and diseconomies of scale. Heggestad (1977), and Smirlock (1985), had also included bank size in their profitability models to take account of the possibility of greater loan and product diversification and accessibility of larger banks to excess markets which are not available to smaller banks. If indeed this is true, then it should imply higher profits for larger banks.

However it is also important to note that Kwast and Rose (1982), Hunter, et al (1990), and Berger, A N and Humphrey D. B (1991), had indicated that banks’ encounter increasing returns to scale only up to a indisputable bank size, after which there is either constant or decreasing return to scale. To this extent, Rose (1993) concluded that medium size banks are the most profitable in terms of ROA and ROE. If these assertions are bona fide in commercial banks context, then the relationship between commercial banks profitability and size variable must have a global maximum. Logarithm of total assets of individual banks could have an impact on bank profitability on the commercial bank. Thus, the size variable will be defined as follows:

The relationship between size and profitability was not obviously straightforward from the literature survey. In some earlier studies on the relationship between size and profitability, the literature survey indicated a negative relationship as indicated by Vernon (1971), Heggested (1977), and Smirlock (1985), and in the recent studies by Emery (1971), Mullineaux (1978), Rhoades and Savage (1991) found that it was positive.

The findings of this study about the expected relationship between size and profitability indicate positive. Table A shows the relationship as ‘Positive’ per study.

As far as the study on efficiency in the banking industry is concerned there have been findings indicating the U-shaped average cost curves implying that the optimum size is reached at some medium sized bank, thus implying increasing returns to scale from small to medium sized firms and then decreasing returns to scale as the size increases from medium to large sized firms. However, the size of the optimum or medium sized firms varied according to the various studies.

In view of the above the finest means to appraise the validity of this assertion would be by considering quadratic dependence between profitability and the size variable of LOGTA. As such the square of LOGTA will be attended to in the commercial banks’ profitability models which was developed.


A summary of the specification of external variables and the anticipated results are briefly presented.

Table A: Specification of External Variables For Commercial Banks

Determinants Variables Description Expected Relationship

Market Share Total deposit of each bank as percentage of all banks total deposit

MSD Positive

Market growth Annual growth in the M3 measure of money supply. MON Positive Interest Rate Average annual BLR of all commercial bank Average

annual PLR of all commercial Banks INT Positive

Inflation Annual percentage change in the consumer price index INF Positive Firm Size Logarithm of total asset of individual Commercial banks. LOGTA Positive

List of Variables used in this study

Dependent Variables ATTA Net income after tax as a percentage of total assets ATCR Net income after tax as a percentage of capital and reserves. BTTA Net income before tax as a percentage of total assets BTCR Net income before tax as a percentage of capital and reserves.

Independent Variables Internal Variables

FD Fixed deposit as a percentage of total deposit LIQ Loans to deposit ratio of each commercial bank CRTA Capital and reserves as a ratio of total assets. CAD Current account deposit as a percentage of total deposit LOANS Loans and advances as a percentage of total assets NPL Non–performing loans as a percentage of total loans INV SUB Investment in Subsidiaries as a percentage of total assets INV SEC Investment in Securities as a percentage of total assets OVH Total overhead expenditure as percentage of total assets

External Variables

RGDP Annual growth in M3 measure of money supply BLR Annual average base lending rate (BLR) of all commercial banks INF Annual average increase in the Malaysian consumer price index LOGTA Logarithm of the individual bank’s total assets

Dummy Variables

di Dummy variable accounting for cross-sectional differences with a value of one for commercial bank-I and zero otherwise for I = 2 to 16

yt Dummy variable accounting for temporal difference with a value one for year-t and zero otherwise for t = 2 to 9.

Functional Form and Model Formulation Short (1979), had considered several functional forms and concluded that linear functions produced results as good as any other functional form. Consequently, a linear model will also be used in this study and pooled regression of cross-section time series data will be used to analyse the profitability determinants of commercial banks. However, some commercial banks may enjoy the firms’ specific competitive advantages due to corporate image or customer relationships which may not be easily quantifiable and hence may not be accounted for by the variables included in this study. Furthermore, economic booms and recessionary periods may also affect the profitability of commercial banks. In these regards, the varying economic conditions from one year to another can also be expected to have an impact on the profitability of these institutions. Thus, the regression parameters of the linear profitability model may also change over time and may differ between cross-sectional units. This


problem is overcome by including dummy variables in the model to capture the effects of temporal and cross-sectional differences on profitability.

To this extent, temporal and cross sectional differences are postulated to be limited to the intercept term. This is because, if the slopes were to vary as well as over time and cross-section units regression would entail a distinct model and pooling would be inappropriate. Consequently, in line with prior studies on bank profitability determinants the implicit assumption in this model is that the slopes are fixed over cross-section units and over time. The General Unrestricted Model

Consequently, the general unrestricted model for this study where the intercepts are not restricted to be equal over time and over cross-sectional units may be stated as follows:

N T K

Yit

= Σ γ i D

it + Σ λ

t W

it + Σ β

k X

kit + ∈

it

i =2 t=2 k=1 (1)

Where :

Yit = the profitability measure of firm-one in year-t Dit = the dummy variable to account for cross-sectional units Wit = the dummy variable to account for time (years in this case) N = the total number of firms (banks) T = the total number of time periods K = the total number of independent or predictor variable ε it = error term

The firm specific dummy variable, D

it assumes a value of one for the i-th firm and zero

otherwise. On the other hand, the dummy variable Wit

assumes a value of one for the t-th year and zero

otherwise. It will be noted that there are only N-1 dummy variables included to account for cross-sectional differences and T-1 dummy variables for temporal differences. The reason for this is to avoid the problem of perfect multicollinearity among the dummy variable. Test for Temporal & Cross Sectional Stability

Thus, before applying simple ordinary least squares (OLS) regression techniques it would be essential to test for temporal and cross-sectional stability. If evidence could be found for temporal stability then the dummy variables W

it for temporal differences in the intercepts would not be jointly significant and

hence could be removed to yield the following restricted model. N K Yit = Σ γ

I D

it + Σ β

k Χ

kit + ε

it

i=2 k=1 (2) Similarly, in the absence of temporal stability but presence of cross-sectional stability the

restricted model would be represented as follows: T K Y

it = Σ λ W

it + Σ β

k Χ

kit + ε

it __

i=2 k=1

(3)

However, in the presence of both temporal and cross-sectional stability the intercepts would be equal over time and cross-sectional units and the dummy variables W

it and D

it would be irrelevant and

hence could be removed to yield the following restricted model. K Y

it = Σ β

k Χ

kit + ε

it _

k=1 (4)


The decision to include the dummy variables Dit

and Wit

in the profitability models will thus be

based on statistical testing . This involves the comparison of the error or residual sum of squares (RSS) of the unrestricted and the restricted models by using the following F-test (Doran and Guise, 1984 and Pindyck and Rubenfeld, 1991).

[ RSSR-RSS

ur ] / M

F = ----------------------------

RSSur

/ (nt-k)

Note: The F distribution with M, (n-k) note that ur and R stand for unrestricted and restricted, respectively.

Where,

RSSR = Residual sum of squares of the restricted model RSSUR = Residual sum of squares of the unrestricted model. M = Number of linear constraints in the restricted model NT = Total number of observations k = Number of parameters in the unrestricted model.

The purpose of this test is basically to determine the joint significance of the omitted variables

in the restricted model. Suppose the omitted variables have no significant effect on the dependent variable then the

error sum of squares of the restricted model will not be very different from the error sum of squares of the unrestricted model. In this case, the value of (RSS

R – RSS

UR) residual sum of squares of the

restricted model minus residual sum of the unrestricted model will be small and hence a small F-value would indicate that the omitted variables are jointly and statistically insignificant. Thus, to reject the restricted or constrained model at the α level of significance. Gujarati (1995) indicates that the decision rule will be that ,if the computed F exceeds Fα (m, n – k), where Fα (m,n-k) is the critical F at the α level of significance, we reject the null hypothesis: otherwise we do not reject it.


Testing to Determine the Joint Significance of the Omitted Variables in the

Restricted Model Figure A:

In this case, the restricted model in equation (2) will be compared with the unrestricted model in equation (1) to test for temporal stability. If there is significant evidence of temporal stability then the dummy variables W

it will not be taken into account and the model for this study would be reduced

to equation (2). In which instance, the next step would be to test for cross-sectional stability by comparing the restricted model in equation (4) with the relatively unrestricted model in equation (2).

If there is positively evidence of cross-sectional stability under the circumstances the appropriate model for this study would be further reduced to equation (4). Nonetheless, if in the foremost there is no evidence of temporal stability then, the restricted model in equation (3) will be compared with the unrestricted model in equation (1).


Figure B:

Figure C:

Test for Temporal and Cross-Sectional Stability

The test for temporal stability fundamentally involves the comparison of the models represented by equations (1) and (2) for each of the profitability measures BTTA, ATTA, BTCR and ATCR as the dependent variable.

N T K Y

it = Σ γ

i D

it + Σ λ

t W

it + Σ β

k X

kit + ε

it

i =2 t=2 k=1 (1)


N K Y

it = Σ γ

i D

it + Σ β

k X

kit + ε

it

i =2 k=1 (2) The test for temporal stability basically involves the test for the joint significance of the dummy

variables, tit

accounting for time in the fully unrestricted model represented by equation (1). The

decision to accept or reject the assumption of temporal stability depends on the comparison of the residual sum of squares (RSS) of the unrestricted model represented by equation (1) with that of the restricted model represented by equation (2) by using the F-test. Effectively this would denote the following hypothesis test.

Hi: There is no statistical evidence of temporal-sectional stability in the profitability model.(wit

≠ o for all t for all i) Ho: There is statistical evidence of temporal-sectional stability in the profitability model. (w

it =

o for all t for all i) Table C: Results of Statistical Test for Temporal Stability

Dependent variable RSSUR

RSSR F-Statistic Critical value at the 5% level Conclusion

BTTA 31.880 44.765 4.46 ≈2.00 Reject Ho

ATTA 30.656 42.771 4.43 ≈2.00 Reject Ho

BTCR 2.45E+11 2.94E+11 2.24 ≈2.00 Reject Ho

ATCR 1.29E+11 1.56E+11 2.35 ≈2.00 Reject Ho

RSSUR

, : RSS of the unrestricted model, RSSR, : RSS of the restricted model

The results in table C indicates that for all the measures of profitability, BTTA, ATTA, BTCR,

and ATCR, measure of profitability do not exhibit temporal stability and hence the dummy variables, W

it accounting for temporal differences are indeed jointly and statistically significant and hence

relevant in the models for all four measures of profitability. The test for cross-sectional stability involves the test for the joint significance of the dummy

variables, Wit

accounting for inter firm differences in the intercept. The inclusion of the intercept was

to capture the effect of any omitted variables. Thus the emphasis is on sign and significance of the included variables.

Effectively the test involves the following hypothesis test. Ho: There is statistical evidence of cross - sectional stability in the profitability model (D

it = o

for all i) H

i : There is no statistical evidence of cross-sectional stability in the profitability model. (Not

all Dit

= o)

Table D: Results of statistical test for cross-sectional stability

Dependent Variable RSSUR

RSSR F-Statistic Critical value at the 5% level Conclusion

BTTA 31.880 40.727 1.75 ≈2.06 Accept Ho

ATTA 30.656 38.642 1.64 ≈2.06 Accept Ho

BTCR 2.45E+11 2.87E+11 1.08 ≈2.06 Accept Ho

ATCR 1.29E+11 1.56E+11 1.32 ≈2.06 Accept Ho

RSSUR

, : RSSR

of the unrestricted model, RSSUR

, : RSSR

of the restricted model

The results in table D indicates that for all measures of profitability, BTTA, ATTA, BTCR and

ATCR there is statistical evidence of cross-sectional stability and thus inter firm differences do not account for variations in the intercept. The inclusion of the intercept was to capture the effect of any


omitted variables. Thus the emphasis is on the sign and significance of the included variables. Thus, the dummy variables Dit accounting for cross-sectional differences are not jointly and statistically significant and hence not in the models for all measures of profitability.

In view of the above findings the final model for the ATTA, BTTA, BTCR and ATCR measures of profitability will be defined by equation (1).

N T K Y

it = Σ γ

i D

it + Σ λ

t W

it + Σ β

k X

kit + ε

it

i =2 t=2 k=1 (1) The regression results of the final models taking both temporal and cross-sectional stability are

only provided for the BTTA, ATTA, BTCR and ATCR measures of profitability in tables E and F respectively. Table E: Summary of regression results for asset based measures of bank profitability

DEPENDENT VARIABLE

BTTA ATTA

INDEPENDENT VARIABLES Coefficient t-Value p-Value Coefficient t-Value p-Value

BLR .142 2.073 .041 .128 1.903 .060

GDP .195 2.438 .016 .158 2.025 .045

LOGTA 4.890E-02 .312 .756 6.379E-03 -.042 .967

CAD 7.693 2.719 .008 6.405 2.315 .022

CRTA -5.875 -1.767 .080 -7.401 -2.277 .025

FD 4.416E-02 .047 .963 .158 .171 .864

LOANS -1.216 -.952 .343 -1.211 -.970 .334

LIQ -.865 -.765 .446 -.551 -.498 .619

INV SEC -4.088 -2.920 .004 -4.296 -3.139 .002

INV SUB -3.972E-02 -1.080 .282 -2.612E-02 -.727 .469

NPL 5.895E-09 .117 .907 -1.052E-08 -.214 .831

OVH -33.367 -2.080 .040 -23.392 -1.492 .139

In the case of the BTTA measure of profitability, the current account deposit as a percentage to

total assets (CAD), Overhead Expenditure to total Assets (OVH) and Investment in Securities (Inv Sec) are significant at 5% level.

Capital asset ratio was significant at 10% level. The external variables such as Bank Lending Rate (BLR) and Gross Domestic Product (GDP) were significant at 5% level.

In the case of ATTA measure of Profitability, Current account deposit to total assets (CAD), Capital Asset Ratio (CAD) and Investment in Securities as a percentage to total asset (INV SEC) is significant at 5% level. In addition the external variables such as Bank Lending Rate (BLR) was significant at 10% and Gross Domestic Product (GDP) was significant at 5% level.


Table F: Summary Of Regression Results For Capital Based Measures Of Bank Profitability

DEPENDENT VARIABLE

ATCR BTCR

Independent Variables Coefficient t-Value p-Value Coefficient t-Value p-Value

BLR 7659.937 1.891 .061 10035.25 1.805 .074

GDP 15426.018 3.265 .001 20606.4 3.178 .002

LOGTA 1795.254 1.059 .092 18417.4 1.451 .050

CAD 391841.11 2.346 .021 544099. 2.373 .019

CRTA -246886.7 -1.258 .211 -323770. -1.202 .232

FD 29148.35 .522 .603 57498.8 .751 .454

LOANS 42080.5 .558 .578 58613.5 .566 .572

LIQ 5733.5 .086 .932 16987.0 .185 .853

INV SEC 156537.6 1.894 .061 303441.5 2.675 .009

INV SUB -2332.1 -1.074 .285 -.3246.5 -1.090 .278

NPL 2.580E.03 .871 .386 6.039E-03 1.485 .140

OVH -1471025 -1.554 .123 -2440861 -1.878 .063

In the case of BTCR the current account deposit ratio (CAD) and Investment in securities are

significant at 5% level. The internal variable such as Overhead Expenditure to total assets was significant at 10% and external variables such as Bank Lending Rate (BLR) and Gross Domestic Product (GDP) were significant at 5% level and firm size (LOGTA) is significant at 10% level.

In ATCR the internal variables such as Current account deposit ratio (CAD) is significant at 5% and investment in securities (INV SEC) is significant at 10% level. The external variable such as Gross Domestic Product (GDP) is significant at 5% where else Bank Lending Rate (BLR) and Firm Size (LOGTA) is significant at 10% level.

Model Specification The principal objective of this study is to theoretically investigate the profitability determinants of commercial banks. As discussed the variables specified are not equivalently applicable for all commercial banks. Furthermore, even among the common variables the nature and extent of effect of these variables may differ between the commercial banks in different countries. Thus, separate, if there is evidence of cross-sectional stability the model for this study would be reduced to equation (2), otherwise it would be represented by the unrestricted model in equation (1).

In line with the primary objective of this study, separate profitability models will be constructed and investigated:

• The internal and external profitability determinants of commercial banks in

• The adequacy of the internal variables and the external Variables using F-Test. • To investigate assertions that size had an impact on profitability.

To Investigate the Internal and External Profitability Determinants of Commercial Banks

In this context, the model equation will be estimated with ROA and ROE as the profitability measure dependent variable. However, for purpose of general definition the dependent variable will be denoted by the term PROFIT in the following model specifications.


N T PROFIT = Σ γ

i D

it + Σ λ

t W

it + β

1 FD + β

2 NPL

i = 2 t=2 + β

3 BLR + β

4 LOANS + β

5 RGDP + β

6 LIQ

+ β7

CRTA + β8

OVH + β9

CAD + β10

LOGTA

+ β11

INVSEC + β12

INVSUB + ε it (5)

A more imperative consideration is the acceptance between pre-tax and post-tax profits in determining the profitability measure dependent variable. Subsequently, the ability to minimise tax exposure is also a significant aspect of good management, regression equations are estimated using both pre-tax and post-tax profits in all cases of profitability measures except the value added measures. This is because in the value added measures, expense items such as staff expenditure and loan loss provisions are aggregated with net income and hence it would be inappropriate to mingle tax deductible expenditure items with post-tax profits.

Thus, the impact of taxation on the profitability determinants for the ROA measure of profitability will be analysed by comparing the models defined above with BTTA and ATTA as the dependent variable. Likewise, the impact of taxation on the profitability determinants for the ROE measure of profitability can be investigated by comparing the models with BTCR and ATCR as the dependent variable.

To investigate the adequacy of the internal variables and the external variables using F-Test.

The acceptability of the internal variables and the external variables will be tested by applying the F-test (Doran and Guise,1984) and Pindyck and Rubenfeld,1991). In this context the models represented by equation (6) with the restricted version of these models represented by equations (7).

N T PROFIT = Σ γi D

it + Σ λ

t W

it + β

1 LIQ + β

2 CRTA

i =2 t=2

+ β3SAV + β

4 CAD + β

5LOANS + β

6 INV SEC

+ β7 INV SUB + β8OVH +β9NPL + ε it

(6)

In equations (6) the external variables were after mature consideration omitted. If the external variables have no material effect on the profitability dependent variable then the error sum of squares of the restricted models represented by equations (7) will not be very different from the error sum of squares of the unrestricted models represented by equations (5) respectively, thus resulting in an F-value which is smaller in magnitude compared to the critical value F

α ( m, n-k) . This would indicate that

the internal variables alone are adequate in explaining the profitability of the commercial banks in Malaysia and Singapore. On the other hand, if the calculated F-value were to exceed the critical F-value F

α ( m, n-k) then it would indicate that the external variables are also relevant and hence should be

included in the profitability models.

To investigate the impact of firm size on profitability.

Within the above framework of the models used, the assertion made by Benston, Hanweck and Humphrey (1982), Hunter (1990), Noulas (1990), Berger and Humphrey (1991) and Rose (1993) that profitability was maximised at medium sized institutions will be examined. To investigate the impact of firms LOGTA was included in the models represented by equations (5) to yield equations (7)respectively. If indeed the profitability of commercial banks are maximised then it would be reflected in the sign of the coefficient of the LOGTA.


N T PROFIT = Σ γi D

it + Σ λ

t W

it + β

1 SAV + β

2 NPL

i=2 t=2 + β

3 BLR + β

4 LOANS + β

5 RGDP + β

6 LIQ

+ β7 CRTA + β

8 OVH + β

9 CAD + β

10 LOGTA

+ β11

INV SEC + β12

INV SUB + ε it

(7)

Conclusion The study offered an insight into the internal determinants and the external determinants of profitability of commercial banks. The factors indicated in this theoretical study are consistent with the variables.

The internal determinants included in this theoretical study are items involving total revenue and total cost. The internal variables included in this study are asset portfolio mix, total expenses, liability composition, and liquidity ratio and capital structure. In addition to the above the external determinants that are taken into consideration i.e, competition, regulation, inflation, market share, market growth, firm size and interest rate. The variables specified for this study are consistent with the variables used in much of the literature on bank profitability. (Bourke 1989) and (Molyneux and Thornthon 1992).

However, some of the variables such as market concentration were omitted in this theoretical study. Finally, the dependent variable of profitability and the measurement of profitability have also been broadly discussed.

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