EVALUATING BANKING
PRODUCTIVITY AND INFORMATION
TECHNOLOGY USING THE TRANSLOG
PRODUCTION FUNCTION
MADUEME IFEOMA STELLADEPARTMENT OF ECONOMICS, UNIVERSITY OF NIGERIA, NSUKKA.
ENUGU STATE NIGERIA
ABSTRACT
This empirical study tried to assess the impact of Information Communication Technology (ICT) on the productivity of the Nigerian banking sector. Impact on Productivity was conceptualized as ability to make positive contributions to output after deductions for depreciation and labour expenses has been made. The Trancendental Logarithimic Production function and the CAMEL rating were used for the study. Results showed that bank output such as loans and other assets increased significantly to changes in expenditure on information communication technology. Information communication technology labour expenses impacted more on bank output more than capital expenditure on ICT gadgets. The recommendation centered on the need to increase investments in information technology in order to increase productivity of banks. This is based on the purview that increased productivity in many instances leads to improved operational efficiency and profitability which are the laudable goals of any banking establishment.
KEYWORDS: IMPACT , INFORMATION TECHNOLOGY, BANKING, PRODUCTIVITY INTRODUCTION
Productivity as a concept involves the transformation of resources into final goods and services. The relationship between inputs and output is a technological relationship which economists summarize in a production function. Production is the creation of wealth which adds to welfare. It is a vital link in the process of satisfying unlimited wants subject to available resources. It is measured by comparing the amount produced with the time taken or resources used to produce it. Production functions involve and can provide measurements of marginal productivity of factors of production, marginal rate of substitution and elasticity of substitution, factor intensity, efficiency, efficiency of production and returns to scale. The basic theory of productivity usually concentrates on the range of output over which the marginal product of factors although positive, decrease or over the range of diminishing (but non negative) productivity of the factors of production. Alternatively, productivity theory concentrates on levels of employment of the factors over which their marginal products are positive but decreasing. According to Koutsoyiannis (1979), its laws describe the technically possible ways of increasing the level of output. The adoption of information communication technology (ICT) in banks is aimed at improving the productivity of banks which will in turn impact on profitability positively. After many years of adopting information technology in Nigeria, it becomes pertinent to assess the impact on banking productivity in the banks. Hence this singular null hypothesis was formulated to guide the study. HO1: There is no significant difference in the productivity of Nigerian banks before and after the adoption of information communication technology. (P<.05)
THEORETICAL FRAMEWORK
Other researchers such as Inkster (1991), Baucchi (1990), have all noted that technology is an instrument for socio- economic development. The utilization of present day technology is the distinguishing factor between human species in today’s contemporary society.
Of all the technologies of our time, information technology has the greatest influence at the international arena. According to Hanna, Boyson and Gunaratne (1996), ‘as some economic historians would assert, the pervasiveness of information technology on society amounts to a second industrial revolution’. It is an enabling technology for quality enhancement. Various models have been propounded on how to measure the impact of information technology on economic sectors. A synthesis of the works of Chief Information Officer (1992) and Strassman (1990) show that the impact of IT on sectors could be assessed through the following models:
(a) Balanced Score Card Model – Under this method, four inter related operational and financial measures are used. These measures center on customer’s view of organizational performance, line manager’s view of internal processes, strategic manager’s view of innovation effects and the shareholders view of financial rewards.
(b) Information Economics Model – Relative weights are assigned to tangible and intangible corporate objectives. IT systems are scored based on their impacts on each of the objectives. The final step is a peer review process to evaluate the scoring for errors and oversights.
(c) Impact Focus Strategy Model – This approach relies on the listing of benefits anticipated by an organization at onset of system’s implementation. It also involves the creation of benchmarks, which the system must meet to have an impact.
(d) The Value Framework Model – This method uses a grid to define multiple impacts of an information system based on two dimensions namely impact and value. The value dimension includes additional service/product quality cost by technology. The impact dimension included time compression of processes, overcoming geographic restrictions and restructuring business relationships.
(e) Alternative Payoff Scenarios Model – The value of information technology investment is calculated by determining how the value of generated information leads to a payoff. This payoff is compared with the payoff without information technology by quantifying impacts in non monetary terms; quantifying monetary benefits from associated improvements. These net profit effects are compared with expected net profits from changed decisions and processes without information technology.
(f) The Return on Management Model (ROM) - Information technology here is regarded as a tool primarily to improve managerial performance. Management outputs and inputs are compared at a ratio to arrive at management value added; the lower the ratio, the lower the ROM and vice versa.
(g) Embedded Network Productivity Measurement Model - This approach predefines measurement parameters, which are built into network management software, and real time indices of compliance with performance targets are generated.
The framework adopted for this study is the impact focus strategy model propounded by the Systems Research Center, Boston University. This model relies on the listing of benefits anticipated by an organization at onset of systems implementation. Benchmarks, which the system must meet in order to have an impact, are also created. The benefit anticipated in this instance are improved productivity of the banking sector. Hence as this study proposes to determine the extent to which the use of information communication technology have impacted on this afore- mentioned benefit, the impact focus strategy model is deemed best suited above other models for such a kind of study.
In order to empirically determine the returns from investments in information communication technology by sectors, the most widely used methodology is the production theoretical framework (Loveman; 1994, Lichtenberg; 1995 and Baba and Harker; 1997). According to Parsons, Gotlieb and Denny (1993), in the absence of measures of actual benefits associated with information communication technology (ICT), it is not possible to perform cost benefit analysis of ICT investments and thus production functions which relate to ICT spending to overall productivity or output measures are seen as the best alternative. In his work on the practice of econometrics, Berdnt (1994) recommended Production function techniques as a reliable measure to access the impacts of information technology. Loveman (1994) and Lichtenberg (1995) noted that many studies on impacts of ICT on productivity use Cobb Douglas production function for their empirical analysis. According to Prasad and Harker (1997), the choice of the form of production function is constrained by economic theory which requires that conditions such as monotonicity and quasi concavity be satisfied. However Berndt(1991) noted that one of the simplest most proven production functions for decades which fulfills such conditions is the Cobb Douglas production function theory. The formula is as follows:-
Where Q is the output rate; L is the quantity of labor; K is the quantity of capital; M is the quantity of raw materials and A, α1, α2 , α3 are the associated output elasticity parameters that vary from case to case. It is of course true that in the estimation of the Cobb Douglas production function, a relatively high correlation may be expected between the independent variables. Nevertheless Kennedy (1985) noted that the existence of multicollinearity in a data set does not necessarily mean that the coefficient estimates in which the researcher is interested in have unacceptably high variances. Most studies on assessment of the impact of information communication technology on productivity have used this model and obtained reliable estimates . Some of such works are those of Loveman (1994), Lichtenberg (1995), Brynjolfsson and Hitt (1996) and others.
Another commonly estimated production function which forms the theoretical framework of this work is the transcendental logarithmic function – the translog (Christensen, Jorgenson and Lau 1973). The attraction of the translog is its flexibility for it can approximate virtually any functional form (Intriligator 1978). The translog is estimated by including squares and cross-products of the explanatory variables. Thus the traditional Cobb Douglas Production function of Y = f( L , K ) would be estimated as:
2
21 2 3 4
5 6
1
1
(
)
(
)
(
)
2
2
(
)
( )
...(4)
t t t t t
t t t t
In BY
InL
InK
InL
InK
InL InK
D
where,
and
= the associated output elasticitiesD = 1, if bank output pre-adoption of ICT
= 0, otherwise (i.e. if bank output post-adoption of ICT)
If the parameters
3,
4and
5are not significantly different from zero, the function reduces to Cobb-Douglas. In the translog model, there are likely to be a large number of parameters to be estimated; hence for every additional variable added to the model, it is necessary to include a squared term and cross-products with the existing variables. If
represents the sum of variables, the number of parameters amounts to approximately
(
+1)/2, with a consequent reduction in the degrees of freedom available (Newhouse 1994).According to Baba and Harker (1997), while production functions have been used by various studies in the past, it is imperative to mention that production function approaches, addresses both impacts on productivity and profitability. With respect to productivity, an impact analysis of ICT investments makes positive contributions to output after deductions for depreciation and labor expenses have made. On the other hand profitability studies are concerned with whether ICT investments contribute to profits of the firm or its stock market value.
The major problem of productivity studies with respect to the banking sector is on the issue of what constitutes the output of a bank since ICT investments must make positive contribution to output for it to have an acceptable impact. According to Berger and Humphrey (1992) there are various approaches for evaluating the output of banks which may be classified into three namely; the user cost approach, the value added approach and the asset approach.
According to Baba and Harker (1997), the user cost approach on the other hand focuses on the net contribution of each of the financial products to the banks revenue. It assumes that if assets financial returns are more than its opportunity cost, it becomes an output as does a liability whose financial costs are less than its opportunity cost. The assets and liabilities which fail to satisfy these conditions become inputs. Hancock(1991) utilized this approach where regarded loans as banks output with demand deposits and time deposits as inputs. This approach however is not free from problems. According to Berger and Humphrey (1992) it is difficult, if not virtually impossible to measure and unambiguously apportion financial returns and opportunity costs among the various financial products of a bank.
exclusively. Benston, Hanweck and Humphrey (1982) posited that output should be measured in terms of what banks do that cause operating expenses to be incurred. In line with this Berger and Humphrey (1992) argued that the value added for each financial measure of the bank should be determined on the basis of operating costs and those that have significant value added should be considered as the outputs of the bank.
Another measure that is often considered representative of a bank’s output is based on the works of Lichtenberg (1995) and Bryjolfolsson and Hitt (1996). Revenue is regarded as output of the few banks they studied. Unfortunately econometric studies of the banking industry do not use revenues as an output measure. This is because revenues are often both inputs and output for example in the case of interest and fees derived from loans can be considered as output, but often borrowers are required to hold idle deposits as a condition for loans and such deposits give rise to implicit revenues. Hence this makes revenues an unreliable guide for determining outputs (Berger and Humphrey; 1992).
The theoretical framework for the assessment of what constitutes the output of a bank is based on the asset approach by Baba and Parker (1972). This approach regards banks as financial intermediaries between borrowers and depositors. In this approach, loans and other assets are regarded as bank output while depositors and other liabilities which provide the finance and equip banks with the capacity to ‘sell’ finance are regarded as bank inputs. Mester (1987) noted that under this approach inputs refer to labor, capital and deposits while bank outputs are the dollar value of the earning assets of the firm. Hence bank output is conceptualized as loans and other assets.
EMPIRICAL LITERATURE
Various empirical studies on information technology and its impact on sectors in various countries have been conducted over the years. Various scholars such as Wilson (1993), Freund, Konig and Roth (1997), Radeck, Wenninger and Orlow(1997), O’Sullivan (1998, 2000) and others have been engaged in unending discourse on the positive payoffs emanating from the utilization of information technology in various enterprises. Such academic debates have resulted in the origin of the term ‘information technology productivity paradox’ which is concerned with appraising the impact of information technology on operational efficiency and the productivity of organizations. A cursory look at the industry level studies of the nineties such as the works of Wilson (1993), Jordan, John and Katz(1999), Furst, Lang and Nolle (1998) portray that in many instances a positive correlation is posited between increased investment in information technology and productivity. On the contrary, other works such as those of Strassman (1990), Morrison and Berndt (1990), Dos-Santos and others (1993) show that additional investments in information technology does not necessarily contribute positively to productivity. Such works argue that the estimated marginal benefits are less that the estimated marginal costs; that for each additional dollar spent in information technology equipment, the marginal increase in measured output was only eighty cents. Brynjolfsson and Hitt (1996) noted that most of such results from researches account for what he referred to as the ‘economic theory of equilibrium’. This means that increased profitability is not necessarily a by product of increased spending in information technology.
Some other researchers such as Loveman (1994), Lichtenberg (1995) and others have worked on ICT impact at the level of firms. Loveman in his work complied data from the Management Productivity and Information database (MPIT). He discovered that the utilization of information technology made no significant impact to the output of manufacturing firms. Lichtenberg in his work obtained his data from yearly surveys conducted from the eighties to the nineties by Computer world magazines. Using the Cobb Douglas production function as his theoretical framework, he estimated a positive correlation between increased investment in information technology and the productivity of firms. In addition, the International data Group (IDG) usually compiles on a yearly basis, details of expenditures made by firms on information technology while the Standard and Poor’s Compustat II database provides various measures of output and non information communication technology expenses. These two sets of data were analyzed by Brynjolfsson and Hitt (1996). His findings revealed that information communication technology staff were twice more productive than their non information communication technology counterparts. In addition, computer capital contributes over eighty percent marginal increase in output whereas the contribution of non information communication technology capital is as low as six percent.
Empirical reports on impact analysis of information technology in developing countries especially Nigeria are quite few. It is upon this premise that this study is designed to fill this gap in the body of knowledge. MATERIALS AND METHOD
The transcendental Logarithmic function or translog by Christensen, Jorgenson and Lau (1973) was used for the study in addition to the CAMEL rating by the Central Bank of Nigeria. The Translog methodology offers more parameters than the Cobb-Douglas. Therefore, to estimate variables for productivity in Nigerian banks the Translog Production Function was employed. However, it has a specific advantage in the modeling of human capital. Overtime, several researchers have argued that the Cobb-Douglas is inappropriate for modeling the productive contribution of education in particular and human capital in general. The point is that human capital is typically embodied in other factors of production; its effect therefore arises in large part through its interaction with these other factors, especially as factors are renewed. It is argued that it would be better to analyze these effects with a more flexible functional form than Cobb-Douglas, and that is the reason for the utilization of the translog approach in this study to estimate ICT impacts on bank productivity.
Production function summarizes a technical relationship among the maximum outputs attainable for different combinations of all possible factors of production. Then the production function would be written as:
BY
f L K
,
...(1)
where,BY = Commercial bank Output per unit of Labour; L = ICT Human Capital per unit of Labour; K = ICT Physical Capital per unit of Labour;
and where
f
.
describes the functional relationship between bank output and different mixes of ICT labour expenses and ICT capital of the commercial banks.One of the most widely used production functions is the Cobb-Douglas, which takes a logarithmic form and can be written as:
1 2
...(2)
BY
L K
and estimated as:
InBY
t
1InL
t
2InK
t
t...(3)
where,
is the regression disturbance.Also,
1and
2are parameters describing the combinations to commercial bank output made by labour (staff) and capital (ICT) respectively. The logarithmic form allows these parameters to be interpreted as elasticities: a 1 per cent increase in the amount of labour employed is predicted to lead to a percentage increase in output to the value of
1.
2
2
1
2
3
4
5
6
1
1
(
)
(
)
(
)
2
2
(
)
( )
...(4)
t
t
t
t
t
t
t
t
t
In BY
InL
InK
InL
InK
InL InK
D
where,
and
= the associated output elasticities D = 1, if bank output pre-adoption of ICT= 0, otherwise (i.e. if bank output post-adoption of ICT)
If the parameters
3,
4and
5are not significantly different from zero, the function reduces to Cobb-Douglas.One of the drawbacks of the translog is that there are likely to be a large number of parameters to be estimated hence for every additional variable added to the model, it is necessary to include a squared term and cross-products with the existing variables. If
represents the sum of variables, the number of parameters amounts to approximately
(
+1)/2, with a consequent reduction in the degrees of freedom available (Newhouse 1994).RESULTS AND DISCUSSION
IMPACT OF ICT ON COMMERCIAL BANK PRODUCTIVITY PRE- AND POST- ICT ADOPTION IN NIGERIA.
The results with respect to the impact of ICT on productivity are presented as follows:
Table 1: Impact of ICT on Commercial Bank Output Pre- and Post- ICT adoption in Nigeria
Dependent Variable: In(BY) Method: Least Squares Date: 01/22/08 Time: 13:54 Sample(adjusted): 1996 2007
Included observations: 12 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C -26.02760 90.43318 -2.878103 0.0347
In(L) -19.74.250 68.51800 -2.881360 0.0345
In(K) 26.84504 8.994546 2.984591 0.0306
In(L)2 10.22513 35.32500 2.894587 0.0340
In(K)2 -1.301088 0.443337 -2.934761 0.0325
In(LK) -0.022582 0.014373 -1.571117 0.0177
D 19058.93 6645.627 2.867890 0.0351
R-squared 0.990471 Mean dependent var 14.64999
Adjusted R-squared 0.979036 S.D. dependent var 1.235628
S.E. of regression 0.178905 Akaike info criterion -0.312730
Sum squared resid 0.160034 Schwarz criterion -0.029868
Log likelihood 8.876383 F-statistic 86.61948
Durbin-Watson stat 2.210841 Prob(F-statistic) 0.000069
Log-Linear Model
amount of ICT facilities acquired at post adoption era by banks is predicted to a percentage increase in commercial bank productivity to the value of 26.8. The elasticity of BPY with respect to the squared term L is about 10.22, suggesting that if ICT labour expenses go up by 1 per cent, on the average, the bank productivity goes up by about 10.22 percent. Thus, bank productivity is very responsive to changes in ICT labour expenses. This is one reason why banks keep a keen eye on productivity and staff employment decisions.
The elasticity of BPY with respect to the squared term K is about -1.30, suggesting that if ICT Capital expenditure goes up by 1 percent, on average, the bank output goes down by about 1.30 percent. Thus, bank productivity is from empirical results obtained is not responsive to changes in ICT capital expenditures. Hence changes in the output of banks are more responsive to increased ICT labour expenses than increased ICT capital expenditure. This findings somewhat agrees with the works of Morrison and Bernt (1991), Mendrik (1992) who worked on Indonesian banks and Frischtak (1992) who worked on impact of ICT on Brazilian banks. These all discovered that ICT impacted positively on the output of the banking industry. Hence the null hypothesis of the study which states that there is no significant difference in the productivity of Nigerian commercial banks pre and post adoption is therefore rejected from the evidence from empirical results which shows that ICT labour expenditure had significant impacts on the productivity of banks. Chart A and B are used to present a graphical summary of ICT impacts on banking productivity.
Chart A Chart B 12 14 16 18 20 22
95 96 97 98 99 00 01 02 03 04 05 06 07
BY L K
O u tp u t, IC T L abou r and C api tal ( = N =' m l) Years
Relations hip between I CT Labour Expens es , I CT Capital and Bank Productivity Pre- and Pos t Adoption of I CT
in Nigeria (1995-2007)
12 13 14 15 16 17 18 19 20 21 22
95 96 97 98 99 00 01 02 03 04 05 06 07
B Y K
IMPA C T O F IC T C A PITA L ON B A N K PR OD U C TIVITY PR E A N D POST A D O PTIO N OF IC T IN N IG ER IA ( 1 9 9 5 - 2 0 0 7 )
Y E A RS
SUMMARY AND RECOMMENDATIONS
Productivity has been conceptualized in this work as the transformation of resources into final goods and services for the creation of wealth which adds to welfare. Hence ICT investments is assumed to have significant impacts when they are able to make positive contributions to output after deductions for depreciation and labour expenses have been made. It is of course true that the determination of what constitutes the output of the service sector has been problematic over the years due to the intangibility of the sector yet Baba and Harker (1997) and Hancock (1991) in their asset approach which was the theoretical framework for this study, regards banks as financial intermediaries between borrowers and depositors. Hence anything that provides the finances and equips banks as financial intermediaries with the capacity to ‘sell’ finance is regarded as inputs.
The results of this empirical study have focused on ICT contributions to loans and other assets as representative of banks output. The results reveal that generally a one percent increase in ICT expenses impacted on the productivity of Nigerian banks to the tune of 26.8 percent. This shows that banks output are quite responsive to changes in ICT expenditure. It was also discovered that ICT labour expenses impacted more on banks output than capital expenses on information technology. This agrees with Kirkup and Keller (1992) and Oscamp and Spacapan (1990) who noted in their separate works that Information communication technology has a dominant influence on all life in the modern world. According to Hanna, Boyson and Guarantne (1996) the pervasiveness of information technology can be likened to a second industrial revolution. This is because it is an enabling technology for enhancement purposes. In fact, Wellenius (1992) and Hanna (1991) show that in their separate works that information technology accounts for more than 46 percent of Gross National Product in the United States of America. It is also expected to grow to more than 60 percent in the European Community.
The findings of this empirical study agree with industry level studies of the nineties such as the works of Wilson (1993), Jordan, John and Katz (1999), and Furst, Lang and Nolle (1998) who all posited a positive correlation between increased investment in information technology and productivity. At the level of firms, the works of Loveman (1994) and Lichenterg (1991) also in their works which spanned the periods of eighties and nineties showed also that increased investment in information technology impacted positively on productivity. It is therefore recommended that increased investments should be made in both capital and labour expenditure in information technology in order to increase the productivity of the banking sector in general.
IMPLICATIONS
This study has tried to fill a void in the body of knowledge with respect to the provision of current empirical information on the impact of information communication technology on the Nigerian banking sector which is a relatively unexplored area. It has also employed the uses of the Transcendental Lograthimic Production production framework in its methodology which has not been used in any related studies in Nigeria. On the other hand the study has great benefits since increased output or productivity at minimal cost is a major goal of enterprises because it has forward linkages to profitability, efficiency and the overall Gross National Product of any nation. Hence the positive impact of information technology on banking productivity is a much desired goal since it will impact positively on their operational efficiency and profitability. If a positive correlation has been established between banks productivity and increased investments in information technology, it then becomes imperative to increase ICT investments in order to increase productivity. This is based on the purview that the banking sector occupies a strategic position in economic transformation and development.
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