Vol. 1, No. 4, December 2017

Editors: Ali Emrouznejad and Francisco Vargas
Editor-in-chief: Prof. Johannes Platje

Data Envelopment Analysis for Performance Measurement in Developing Countries

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Vol. 1, No. 4, December 2017

EDITORIAL – Data Envelopment Analysis for performance measurement in developing countries

Aston University, UK
Francisco VARGAS
University of Sonora, Hermosillo, Mexico

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Vol. 1, No. 4, December 2017

Pricing Inputs and Outputs in Banking: An Application to CEE Countries

Authors: Maryam HASANNASAB
University of Auckland Business School, New Zealand; Kharazmi University, Iran
University of Auckland Business School, New Zealand

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Aim: A problem in efficiency and productivity studies in banking is that some of the input and output prices used in the estimation of cost, revenue and profit functions are proxies of questionable quality with obvious impact on the reliability of performance measures. We address this issue focussing on the banking systems of Central and Eastern Europe where arguable this problem may even be more acute.

Design / Research methods: We employ parametric forms of directional distance functions to obtain shadow prices of bank inputs and outputs, and compare them with price proxies typically employed in empirical studies. The key idea here is to exploit cost, revenue and profit maximisation as the optimisation criteria to derive pricing rules, which allow us to find shadow prices for both inputs and outputs. We show how knowledge of one input price can be used to price outputs and how knowledge of one output price can be used to price inputs along with information on input and output quantities. We also use total cost to shadow price inputs and total revenue to shadow price outputs.

Conclusions / findings: We find differences between shadow prices and actual prices suggesting that input and/or output mix may not be consistent with cost minimisation or revenue and profit maximisation. We also find that bank efficiency is highest on average in Estonia, which also boasts the highest bank capitalisation rate in the CEE region.

Originality / value of the article: The study departs from the traditional literature on efficiency and productivity by focussing on pricing and their implications thereof for input-output mix.

Implications of the research: Prices for problem loans are not observable, hence our approach provides an avenue for computing shadow prices for bad outputs in banking. This is important since it gives us an indication of the loss of good output needed to lower the bad output by one unit.

Keywords: directional distance function, bank efficiency, shadow prices, CEE banking

JEL: D24, G21, C61

Doi: http://dx.doi.org/10.29015/cerem.556

Vol. 1, No. 4, December 2017

The Sources of Productivity Change and Efficiency in Islamic Banking: Application of Malmquist Productivity Index

Authors: Janet GANOUATI
Université de Tunis, Tunisia; Université de Lille1, France
Université de Tunis, Tunisia

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Aim: This paper aims to explore performance of Islamic banks in 13 countries from the period 2005 to 2014 and investigates sources of productivity change over the time.

Design / Research methods: The present study gather data on the 31 Islamic banks. The productivity is examined using the Data Envelopment Analysis-based Malmquist productivity index. That we decompose into scale efficiency, technological change and technical efficiency. Source of productivity change in Islamic banks is then identified. We use intermediation approach and production approach to select inputs and outputs of banks.

Conclusions / findings: Although the two approaches are different, our empirical implementation shows that they yield very similar results regarding productivity, efficiency and source of productivity change. Islamic banks are productive and efficient over the study period, but they did not show to be scale efficient and they suffer from technological change evolutions. Moreover, we are able to show that Subprime crisis had a slightly negative effect on productivity in Islamic banking industry.

Originality / value of the article:Empirical studies are still rare and findings are controversial on productivity and efficiency of Islamic banks. This study intends to fill the gaps with a specific focus on measuring productivity index using two different intermediation approach and production approach to select input and output variables.

Implications of the research (if applicable) – Islamic banks are scale inefficient and must improve size of their activities, one possible suggestion is meagering small banks.

Limitations of the research (if applicable) – Further research can use bootstrapping techniques to correct total factor productivity estimates for bias and to assess the uncertainty surrounding such estimates.

Keywords: Islamic banks, Productivity, efficiency, Data Envelopment Analysis, Malmquist index decomposition

JEL: D24, G21

Doi: http://dx.doi.org/10.29015/cerem.555

Vol. 1, No. 4, December 2017

Bank efficiency in Saudi Arabia: examining the impact of the global financial crisis

Authors: Golam SOLAIMAN, Abdul KADAR
International Islamic University Chittagong, Bangladesh
Federal University of Rio de Janeiro, Brazil
Abdul Kalam AZAD
Bangladesh Army International University of Science and Technology, Bangladesh

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Aim: The global financial crisis in 2008 has obstructed almost every bank around the world. This study examines the impact of global financial crisis on bank efficiency in Saudi Arabia.

Design / Research methods: This study examines the impact of global financial crisis in bank efficiency applying the data envelopment analysis (DEA) during 2006-2014. Eleven commercial banks were examined from Saudi banking sector which covers almost half of total banks of Saudi Arabia. Scale efficiency, technical efficiency and productivity of banks have been examined for assessing the impact of financial crisis overtime.

Conclusions / findings: Results reveal that banks in Saudi Arabia are inefficient in terms of technical and scale efficiency. The results also reveal these banks are not immune to the global financial crisis. Though only one bank has kept their unit efficient positions during the study period, the impact of global crisis on bank efficiency is found visible among other banks. The robustness of this study is also tested.

Originality / value of the article: The importance of this study is twofold. First, examining bank efficiency with special attention to financial crisis. Second, Saudi Arabia needs sustainable growth to be ensured. Hence, examination of impact of financial crisis on bank efficiency of Saudi Arabia will surely help the policy makers for future planning.

Implications of the research: The findings of this study will assist the policy makers in Saudi Arabia for taking corrective measure in advance in case of such future financial crisis. Moreover, the results will be used by the managers of the respective banks for decision making and problem solving.

Keywords: slack based model, data envelopment analysis, efficiency, Saudi Arabia

JEL: C23; G21; L2

Doi: http://dx.doi.org/10.29015/cerem.580

Vol. 1, No. 4, December 2017

Efficiency Determinants of Microfinance Institutions in India: Two Stage DEA Analysis

Authors: Santa Kar, Joyeeta Deb
Assam University, Silchar, India

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Aim: In India, Microfinance Institutions (MFIs) emerged as major player in providing microfinance services and therefore such institutions need to be financially sustainable in order to achieve their double bottom-line objective. Besides, Indian MFIs cannot protect themselves from the curse of loan non-repayment. Therefore, this study aims to measure performance of the Indian MFIs and examine whether sustainability has any significant impact on the efficiency of the MFIs.

Design / Research methods: In order to gauge the performance of the Indian MFIs, non parametric Data Envelopment Analysis (DEA) is adopted. Two models of DEA (BCC Model-input oriented and Undesirable Measure Model-output oriented) are applied used for better analysis. Further, to examine the factors influencing efficiency of the MFIs and particularly to answer whether Sustainability has any significant impact on efficiency, Tobit regression is applied in the study. Data of thirty-one Indian MFIs for seven years (2009-2015) are collected from MiX Market for the study.

Conclusions / findings: Result of the study shows that average technical efficiency of the MFIs is estimated to be 79 percent under BCC model and 98 percent under Undesirable Measure Model. Indian MFIs can attain production frontier if they can trim their bad output (proxied by Portfolio at Risk 30) to an extent of around 14 percent. Further, the study validates that sustainability (proxied by Operational Self Sufficiency) has positive impact on efficiency.

Originality / value of the article: Studies made so far on Indian MFIs have not addressed how the MFIs could become efficient by reducing their undesirable/bad output. Besides, no study so far has analysed the impact of sustainability on efficiency of the Indian MFIs. Therefore, this research tries to fill the existing research gap.

Implications of the research: The result of the study can be useful to the Indian Microfinance Industry in improving their performance. The result can further be used by Reserve Bank of India (RBI) to frame yardstick for the clients of the MFIs in connection with borrowing loans from MFIs.

Keywords: Microfinance Institutions, Sustainability, Data Envelopment Analysis

JEL: G21, C67, C33

Doi: http://dx.doi.org/10.29015/cerem.580

Vol. 1, No. 4, December 2017

Technical efficiency decomposed – The case of Ugandan referral hospitals

Authors: Zungu Mathias MULUMBA, Lindah NALUBANGA, Christine L NANKANJA, Kwihangana MANASSEH
Office of the Audit General, Uganda
Linnaeus University and The Swedish National Audit Office, Sweden
The Swedish National Audit Office, Sweden

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Aim: In an audit report provided to the Ugandan Parliament by the Office of the Audit General, Uganda, technical efficiency in Ugandan referral hospitals was measured and analysed. The audit report pointed out that there was a relatively low level of technical inefficiency, at least in comparison with other African countries. The purpose of this study is to look further into the issue of why there is inefficiency.

Design / Research methods: We use a Data Envelopment Analysis framework and decompose long-run technical efficiency into short-term technical efficiency, scale efficiency and congestion.

Conclusions / findings: Our results reveal that the source of the long-run inefficiency varies over the years. For 2012, more than 50% of the observed inefficiency relates to scale factors. However, in 2013 and 2014 the major contributor to the long-run inefficiency was input congestion.

Originality / value of the article: Even though there are a substantial amount of research on efficiency in African hospitals, no other study have investigated existence of congestion. In that respect our research contributes to the existing research.

Implications of the research: We recommend that inefficient hospitals should use efficient hospitals as benchmarks for improving their own efficiency. Further, since a large part of the technical inefficiency relates to congestion we recommend further investigation to identify factors in the production, or organisation that could be related to congestion.

Key words: technical efficiency, scale efficiency, congestion, Uganda, hospitals

JEL: D2, H4, I2.

Doi: http://dx.doi.org/10.29015/cerem.513

Vol. 1, No. 4, December 2017

Efficiency analysis of public health spending in Brazilian capitals using network Data Envelopment Analysis

Authors: Maria Stella de CASTRO LOBO
Rio de Janeiro Federal University UFRJ, Brazil
World Bank, USA

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Aim: In 1988, Brazil implemented profound changes in the organization and financing of its public health system, with the creation of the Unified Health System (Sistema Unico de Saúde – SUS), establishing universal health coverage. The gradual expansion of the health system and entitlements to services has been accompanied by the debate about the appropriate level of government spending and health system efficiency.

Design / Research methods: The study uses Variable Returns to Scale output-oriented, Dynamic Network Slacks-Based-Measure Data Envelopment Analysis (DEA) model, period 2008-2013, to depict the relationships that take place between diverse levels of care (primary health care/PHC and secondary-tertiary health care/STC). Decision Making Units are Brazilian state capitals, which implement key health policies and assist patients from smaller surrounding municipalities, especially for STC. Inputs are PHC and STC budgets; outputs are their respective services provided and avoidable deaths. The link variable is PHC medical consultation, entrance door to the system and gatekeeper for more complex levels of care. Dynamic model evaluates efficiency across time.

Conclusions / findings: Overall performance was 0.86; for PHC, 0.90; for STC, 0.85 (SD=0.15). 8 out of 27 capitals were fully efficient. Capitals increased average scores in both levels of care, but only STC had a positive technological change (frontier shift >1). Link variable behavior denotes a bottleneck between levels of care. Projections onto the frontier enable establish own management diagnosis and goals for financing and development.

Originality / value of the article: Network models mimic hierarchically organized health systems. The appliance of results aids health policy.

Keywords: network DEA, efficiency measurement, health and economic development, public health

JEL: H21, H51, O10, O54

Doi: http://dx.doi.org/10.29015/cerem.538

Vol. 1, No. 4, December 2017

An evaluation of the determinants of total factor productivity growth in Indian information technology industry: an application of DEA-based Malmquist Index

Author: Prosenjit DAS
University of Kalyani, India

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Aim: This study aims at assessing the Total Factor Productivity Growth (TFPG) and its determinants in the Indian Information Technology (IT) industry.

Design / Research methods: To realize the objectives of the study, firm level data has been collected from the Centre for Monitoring Indian Economy (CMIE) PROWESS database. For empirical analysis, we have applied a two-stage method. In the first-stage, we have used Data Envelopment Analysis (DEA) based Malmquist Productivity Index (MPI) to evaluate the TFPG in the Indian IT industry during the period from 2004-05 to 2014-15. For this purpose, a balanced panel dataset consisting 70 IT firms has been considered. Further, the TFPG has been decomposed into three components, viz. catch-up, frontier-shift, and scale efficiency change (SEC). Consequently, in the second-stage, three random-effects panel regression models are considered to investigate the determinants of TFPG, catch-up, and frontier-shift separately.

Conclusions / findings: During the study period, on an average, the TFPG and frontier-shift has been improved. On the other hand, catch up effect is found to have declined. The variables, such as export intensity, salaries and wages intensity have positive and statistically significant impact on the catch-up and frontier-shift. Export intensity and Salaries and wages have positive impact on TFPG. Age of the firms has positive impact on catch-up and TFPG. On an average, the firms which spent on research and Development (R&D) have experienced improvement in TFPG and frontier-shift. The public limited firms performed better than their private counterparts in terms of catch-up, frontier-shift, and TFPG. The non-group firms have performed better than the group firms in case of catch-up. On the other hand, on an average, the firms exhibiting decreasing Returns to Scale (DRS) are found to have registered deterioration in catch-up and TFPG with respect to the benchmark Constant Returns to Scale (CRS) firms. The firms exhibiting Increasing Returns to Scale (IRS) have shown improvement in catch-up and TFPG over the benchmark CRS firms. The impact of the US subprime crisis has been negative on catch-up, frontier-shift, and TFPG. The firms, which have spent on royalty, have experienced improvement in catch-up and TFPG.

Originality / value of the article: So far in our knowledge, we have not found so many empirical studies of this kind pertaining to the IT industry, especially in a developing country like India. Moreover, we have not found any study that covers the span of the dataset considered in this study. In addition to this, the present study has employed a random-effects model to accommodate a number of time-invariant dummy variables which would not be possible in case of a fixed-effects model incorporated by some previous studies of this genre.

Implications of the research (if applicable): The identification of the determinants of TFPG and its components would help the stakeholders and policy makers to formulate appropriate policies which could mitigate the risks faced by the Indian IT industry on one hand, and stimulate the forces that would enhance the growth of this industry on the other. For instance, to mitigate future risks, Indian IT industry should reduce its dependence on the US and UK markets. In other words, it should explore new markets in domestic as well as foreign economies such as the EU, Australia and the emerging economies where the IT markets are seem to be promising. To maintain India’s robust global position in the long run, Government of India should play a key role in providing world class infrastructure and telecommunication facilities to its IT industry. In addition to this, Indian Government needs to rationalise and simplify the existing Indian labour law to facilitate the business of IT industry. Various stakeholders along with the Government should put necessary efforts to develop the domestic IT market where ample opportunities are present.

Keywords: Information Technology industry, data envelopment analysis, Malmquist productivity index, random-effects model, total factor productivity, catch-up, frontier-shift, India.

JEL: C23, C61, L86, O47

Doi: http://dx.doi.org/10.29015/cerem.566

Vol. 1, No. 4, December 2017

Government College of Engineering and Leather Technology, India

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Aim: The objective of the paper is to construct an index of fiscal performance of Indian states using DEA. The reason behind using non-parametric methods for the purpose of construction of index is that the traditional ratio approach is incapable of handling multiple input and output indicators.

Design / Research methods: The present study uses a two stage approach. In the first stage, DEA is deployed to evaluate the performance of Indian states for five consecutive years. The input and output indicators used for DEA have been selected on the basis of a simple theoretical model. Further, in order to tackle the problem of estimation bias (due to sampling variations) bootstrapped DEA is applied. In the second stage ,impact of indebtedness on the performance of the states has been assessed using a censored regression framework.

Conclusions / findings: The major outcome of the study is the construction of a fiscal performance index based on multiple indicators. Moreover, the second stage results indicate that state performance is significantly influenced by their degree of indebtedness.

Originality / value of the article: The present study is perhaps the first attempt to assess the performance of sub-national units in terms of both convex and non-convex mathematical programming methods.

Implications of the research (if applicable): The approach (with suitable modifications) can be effectively used to benchmark state performance which can serve as a basis for resource transfer from the central government to the states.

Keywords: robust frontier, Indian states, non-parametric approach

JEL: H 17 , D 21, C 61

Doi: http://dx.doi.org/10.29015/cerem.527