An Analysis of Banks Performance in Pakistan Using Two-step Double Bootstrap Dea Approach

AuthorHAFIZ KHALIL AHMAD, HAFIZ GHULAM MUJADDAD and MUHAMMAD NADEEM

Abstract

This study analyzes the technical efficiency and sources of technical efficiency of conventional banking sector of Pakistan by applying the DEA double bootstrap technique. In the first stage, we applied the bootstrapped DEA variable returns to scale model for measuring the efficiency scores by utilizing the two inputs and three outputs. In the second stage, we employed the bootstrapped truncated maximum likelihood regression model to determine the sources of technical efficiency. As per our results, size of banks does not matter for technical efficiency of banks as the coefficient was insignificant. The liabilities of banks negatively and significantly affect efficiency of banks. Privately owned banks significantly perform better than public sector banks in terms of efficiency scores. Thus, our results shed support in favour of privatization hypothesis.

Keywords: Technical efficiency, Banks, DEA double bootstrap, Truncated regression, Pakistan

  1. INTRODUCTION

    Banks play a significant role in growth and development of any economy where they hold the savings of the public and finance the expansion of business, investment and trade. So, it is not possible to work effectively in the fast developing world without a strong banking system. Empirical evidence shows a positive relationship between financial sector growth and economic growth (Zaidi, 2005). Since commercial banks are the leading financial institutions, therefore, developing countries have focused their attention on the performance of banking sector. This is because efficiency of banking sector affects economic growth positively while their inefficiency retards economic growth by creating financial crisis. Evaluation of efficiency is significant for the investors, expected depositors and policy makers as banks play a vital role in the formation and implementation of monetary policy.

    It is important for companies, organizations or banks to touch the optimal level in order to compete with their business rivals all over the world. It is a pre-requisite for every country to observe that its institutional performance is adorable with high efficiency and maximum output in order to attain its targets. Fundamentally, performance measurement examines the achievement of different organizations, companies or banks by comparing the facts and figures about what really occurred to what was preliminarily decided or intended (Wholey and Hatry, 1992). Maximization of the output or profit and minimization of the cost are the basic criteria for measuring the efficiency. Under certain conditions, the technical efficiency (TE) is measured as the ability of a bank or unit to produce.

    An organization or a bank is known as technically efficient if it is producing a certain quantity of output by utilizing the minimum quantity of inputs or producing maximum output from a certain given quantity of inputs. According to Koopmans (1957), "A possible point in the commodity space is called efficient whenever an increase in one of its coordinates (the net output of one good) can be achieved only at the cost of a decrease in some other coordinate (the net output of another good)."

    Farrell (1957) was the first to introduce the measuring of the efficiency of producing units. A lot of work has been done on Farrell's (1957) classic TE. There are two basic techniques for the measurement of efficiency: parametric and non-parametric. Meeusen and Broeck (1977) and Aigner et al. (1977) have initiated the parametric technique which is known as stochastic frontier analysis (SFA). Linear programming models of Charnes et al. (1978) and Fare et al. (1985) provided the basis for the production efficiency analysis. Charnes et al. (1978) developed the DEA. Banker et al. (1984) further modified it on the basis of frontier efficiency concept first defined by Farrell (1957).

    Simar and Wilson (2007) have identified several limitations of the two- stage DEA technique, i.e. the data generating process (DGP) is not described in these models and the efficiency scores, which are estimated in DEA, are serially correlated. As such, the general two-stage DEA techniques are statistically invalid due to these limitations. Simar and Wilson (2000) also explain that DEA efficiency scores are exaggerated because of the underestimation of the frontier by this technique. In view of these severe drawbacks of DEA, Simar and Wilson (2007) proposed an alternative estimation and statistical inference procedure based on a double-bootstrap approach. In this study, the DEA double bootstrap is employed for analysis.

    The remaining of the study is designed as follows: Section II contains review of related literature in the context of this study. Section III provides methodological framework and describes sources of data. Empirical results of conventional banking sector are discussed in section IV. Section V concludes this study and provides some recommendations.

  2. REVIEW OF LITERATURE

    Several studies are found in literature on measuring the performance of banking sector. But almost in every study, two approaches (DEA and SFA) are widely used to analyze the efficiency of different sectors including banking sector. But empirical analysis with respect to the appropriate technique is limited in Pakistan. Very rare, if any, study is found in Pakistan which has analyzed the efficiency of banking sector by applying DEA double bootstrap technique.

    Percin and Ayan (2006) measured the efficiency of 31 commercial banks of Turkey over the 2003 to 2004 period by applying the DEA and Malmquist Productivity Index (MPI). They used two outputs and four inputs for measuring output oriented efficiency scores. They found that eleven banks were efficient under the assumption of constant returns to scale while sixteen banks remained efficient under the assumption of variable returns to scale in DEA. Meanwhile, they found that there was a significant increase in the efficiency of banking sector for the 2003 to 2004 period as MPI analysis showed.

    Akmal and Saleem (2008) measured the efficiency of thirty commercial banks of Pakistan for the 1996 to 2005 period. They applied general two- stage DEA approach to measure the efficiency in the first stage and in the second step they used Tobit regression to find the impact of macroeconomic and internal bank factors on efficiency. They found that efficiency of foreign banks was greater than local national and privatized banks and overall efficiency level of banking sector started to increase after 2000.

    Chansarn (2008) applied the DEA to examine the relative efficiency of 13 Thai commercial banks for the 2003 to 2006 period. He used DEA under two different approaches: operational approach where three inputs and two outputs were utilized and intermediation approach where two inputs and two outputs were used to measure the relative efficiency. It was found that efficiency of Thai commercial banks was very high and stable under operational approach and the efficiency was moderately high and little volatile under the intermediation approach.

    Nazir and Alam (2010) applied the traditional method and DEA approach to calculate efficiency scores of twenty-eight commercial banks of Pakistan over the 2003 to 2007 period. They also tested whether privatization really improved the efficiency of banks? Their results suggested that privatization could not help banks in improving their operating income. It was also noted that public banks were better able to cover their interest and non-interest expenses from their corresponding revenues.

    Akhtar et al. (2011) analyzed the determinants of profitability for conventional banks of Pakistan over the 2006 to 2009 period. They employed the OLS method for analyzing the multivariate regression. They formulated two different regression models with different dependent variables (return on equity and return on assets as proxies of profitability) and the same independent variables for both models. Gearing ratio, assets management and non-performing loans showed a significant impact in both models while size of banks was insignificant indicator where return on equity was used as the proxy for profitability.

    Assaf et al. (2011) measured the efficiency of nine Saudi banks for the 1999 to 2007 period. They applied DEA double bootstrap technique for measuring the TE in the first stage and found out determinants of efficiency by applying the truncated regression in the second stage. They used three inputs and three outputs based on the intermediation approach to evaluate the efficiency scores. They found that Saudi banks were operating in a highly efficient environment.

    Haque and Tariq (2012) evaluated the efficiency of banking sector of Pakistan including sixteen conventional and six Islamic banks for the 2006 to 2010 period. They applied non-parametric frontier technique of DEA analysis for measuring efficiency by utilizing three inputs and three outputs based on intermediation approach. They found that efficiency of overall banking sector...

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