Non-parametric Efficiency Measurement Research Articles

Nonparametric efficiency measurement of undergraduate teaching by university size

Conventional data envelopment analysis (DEA) models assume that all decision-making units (DMUs) are homogenous. While higher education institutions (HEIs) of very different sizes challenge the homogeneity of DMUs, DEA studies have paid relatively little attention to university size when assessing the performance of HEIs. This article proposes novel, effective methods for evaluating university performance and identifying useful benchmarks for improving the operations of inefficient performers. Specifically, DEA and cluster analysis (CA) are applied for the evaluation of the performance of traditional Spanish public universities. DEA is utilized to examine the relative performance of these universities in terms of undergraduate teaching output. CA is applied to find similar-in-scale universities prior to the DEA to facilitate peer-groupings. The advantage of this method is that when DMUs are clustered based on their size, one can obtain homogenous groups of units with comparable operating environments. Furthermore, using the meta-frontier framework, this research finds significant evidence that there is an efficiency advantage for medium- and large-sized universities over small ones in providing undergraduate teaching. A bootstrapped, non-parametric meta-frontier approach also verifies this latter result. Some of the factors that contribute to the differences in the relative efficiencies are identified as well.

Measuring technical efficiency and total factor productivity change with undesirable outputs in Stata

In this article, we introduce two community-contributed data envelopment analysis commands for measuring technical efficiency and productivity change in Stata. Over the last decades, an important theoretical progression of data envelopment analysis, a nonparametric method widely used to assess the performance of decision-making units, is the incorporation of undesirable outputs. Models able to deal with undesirable outputs have been developed and applied in empirical studies for assessing the sustainability of decision-making units. These models are getting more and more attention from researchers and managers. The teddf command discussed in the present article allows users to measure technical efficiency, both radial and nonradial, when some outputs are undesirable. Technical efficiency measures are obtained by solving linear programming problems. The gtfpch command we also describe here provides tools for measuring productivity change, for example, the Malmquist–Luenberger index and the Luenberger indicator. We provide a brief overview of the nonparametric efficiency and productivity change measurement accounting for undesirable outputs, and we describe the syntax and options of the new commands. We also illustrate with examples how to perform the technical efficiency and productivity analysis with the newly introduced commands.

Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Order picking is a crucial but labor- and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations.

Statistical inference for the Russell measure of technical efficiency

Data envelopment analysis (DEA) has become a popular approach to nonparametric efficiency measurement. The statistical inference using bootstrap methods is readily available for the radial DEA estimator; however it is missing for the Russell measure, the nonradial DEA estimator. We propose a bootstrap based procedure for making statistical inference about the individual Russell measures of technical efficiency. We perform simulations to examine finite sample properties of the proposed estimator. Finally, we present an empirical study using proposed bootstrap procedure.

Incorporating Risk into Technical Efficiency: The Case of ASEAN Banks

The objective of this paper is to incorporate risk in technical efficiency of listed ASEAN banks in a panel data framework for the period 2000 to 2015. Many researchers apply frontier estimation techniques such as data envelopment analysis (DEA) or stochastic frontier analysis (SFA) for their efficiency analysis. However, the banks’ complex production process requires more sophisticated techniques to account for internal structures within the black box so relying only traditional DEA or SFA is not adequate to deal with a multiple-input and multiple-output production technology. To incorporate undesirable outputs such as risk into inefficiency, we rely on the directional distance function (DDF). We employ the DDF under both parametric (SFA) and semi-parametric (SEMSFA) framework to make a comparison efficiency scores with risk adjusted in two scenarios. Our results suggest that risk is an important factor that bank managers should pay more focus to achieve long-term efficiency in ASEAN banks
 Keywords
 Bank efficiency; risk; directional distance function (DDF); semiparametric estimation of stochastic frontier models (SEMSFA)
 References
 ADB. (2013). The road to ASEAN financial integration: A combined study on assessing the financial landscape and formulating milestones for monetary and financial integration in ASEAN. Andor, M., & Hesse, F. (2014). The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the ‘‘oldies’’ (SFA and DEA). J Prod Anal 41, 85-109. doi: 10.1007/s11123-013-0354-yBerger, A. N., & DeYoung, R. (1997). Problem loans and cost efficiency in commercial banks. Journal of Banking & Finance, 21(6), 849-870. Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: international survey and directions for future research. European Journal of Operational Research, 98, 175-212. Chan, S.-G., Koh, E. H. Y., Zainir, F., & Yong, C.-C. (2015). Market structure, institutional framework and bank efficiency in ASEAN 5. Journal of Economics and Business, 82, 84-112. Chang, C.-C. (1999). The Nonparametric Risk-Adjusted Efficiency Measurement: An Application to Taiwan’s Major Rural Financial Intermediaries. American Journal of Agricultural Economics, 81(4), 902-913. Chang, T.-C., & Chiu, Y. H. (2006). Affecting factors on risk-adjusted effciency in Taiwan’s banking industry. Contemporary Economic Policy 24(4), 634-648. Gardener, E., Molyneux, P., & Nguyen-Linh, H. (2011). Determinants of efficiency in South East Asian banking. The Service Industries Journal, 31(16), 2693-2719. Huang, T.-H., Chiang, D.-L., & Tsai, C.-M. (2015). Applying the New Metafrontier Directional Distance Function to Compare Banking Efficiencies in Central and Eastern European Countries. Economic Modelling, 44, 188-199. Karim, M. Z. A. (2001). Comparative Bank Efficiency across Select ASEAN Countries. ASEAN Economic Bulletin, 18(3), 289-304. Karim, M. Z. A., Sok-Gee, C., & Sallahudin, H. (2010). Bank efficiency and non-performing loans: Evidence from Malaysia and Singapore. Prague Economic Papers, 2, 118-132. doi: 10.18267/j.pep.367Khan, S. J. M. (2014). Bank Efficiency in Southeast Asian Countries: The Impact of Environmental Variables. In Handbook on the Emerging Trends in Scientific Research. Malaysia: PAK Publishing Group. Laeven, L. (1999). Risk and Efficiency in East Asian Banks (Vol. 2255). Washington, D.C. : World Bank, Financial Sector Strategy and Policy Department.Manlagnit, M. C. V. (2011). Cost efficiency, determinants, and risk preferences in banking: A case of stochastic frontier analysis in the Philippines. Journal of Asian Economics, 22, 23-35.
 Sarifuddin, S., Ismail, M. K., & Kumaran, V. V. (2015). Comparison of Banking Efficiency in the selected ASEAN Countries during the Global Financial Crisis. PROSIDING PERKEM, 10, 286-293. Sarmientoa, M., & Galán, J. E. (2015). The Influence of Risk-Taking on Bank Efficiency: Evidence from Colombia. CentER Discussion Paper, 2015-036. Vidoli, F., & Ferrara, G. (2015). Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models. Empir Econ, 45, 641-658. Williams, J., & Nguyen, N. (2005). Financial Liberalisation, Crisis, and Restructuring: A Comparative Study of Bank Performance and Bank Governance in South East Asia. Journal of Banking and Finance, 29(8-9), 2119-2154. Wong, W. P., & Deng, Q. (1999). Efficiency analysis of banks in ASEAN countries. Benchmarking: An International Journal, 23(7), 1798-1817. Yueh-Cheng Wu, I. W. K. T., Wen-Min Lu, Mohammad Nourani, Qian Long Kweh. (2016). The impact of earnings management on the performance of ASEAN banks. Economic Modelling, 53, 156-165. Zhu, N., Wang, B., Yu, Z., & Wu, Y. (2016). Technical Efficiency Measurement Incorporating Risk Preferences: An Empirical Analysis of Chinese Commercial Banks. Emerging Markets Finance and Trade, 52, 610-624.

Veri Zarflama Analizi ile Türk Sigorta Sektörünün Elementer Branşlarda Değerlendirilmesi - Evaluation of Turkish Insurance Sector in Non-Life Insurance With Data Envelopment Analysis

This study is aimed to determine the efficiency levels of the insurance companies in elementary branches in the last three years period in the Turkish Insurance Sector with Data Envelopment Analysis (DEA). DEA is a nonparametric efficiency measurement method. Data Envelopment Analysis is defined as a linear programming based method used to evaluate the relative activities of decision units that produce outputs with similar inputs. Financial and non-financial variables determined by literature review were used in the study. The established model which is based on a variable return-based assumption, Banker-Charnes-Cooper (BCC) model was solved by the DEA-SOLVER program.

Portfolio selection in a multi-moment setting: A simple Monte-Carlo-FDH algorithm

This paper proposes a non-parametric efficiency measurement approach for the static portfolio selection problem in a general inputs–outputs space, where inputs can include variance and kurtosis and outputs can include mean and skewness. Our work is in the vein of Briec, Kerstens, and Jokung (2007) and Jurzenko, Maillet, and Merlin (2006) who develop a directional distance (shortage function) approach to evaluate the performance of portfolios in Mean–Variance–Skewness and in Mean–Variance–Skewness–Kurtosis spaces. Our approach use the Free Disposal Hull (FDH) estimator to derive an algorithm avoiding the heavy and non-robust numerical optimization approaches suggested so far. This new approach is much faster, more robust to reach the optimum and more flexible since it can be extended to more general situations. We illustrate the algorithm with a data set on the French CAC 40 already used in the literature, to compare our method with the numerical optimization approaches. It appears that our approach is much more performant than the numerical optimization techniques, both in terms of computing time, but also in terms of robustness, avoiding the pitfall of local numerical optima.

Nonparametric Frontier Analysis Using Stata

In this article, we describe five new Stata commands that fit and provide statistical inference in nonparametric frontier models. The tenonradial and teradial commands fit data envelopment models where nonradial and radial technical efficiency measures are computed (Färe, 1998, Fundamentals of Production Theory; Färe and Lovell, 1978, Journal of Economic Theory 19: 150–162; Färe, Grosskopf, and Lovell, 1994a, Production Frontiers). Technical efficiency measures are obtained by solving linear programming problems. The teradialbc, nptestind, and nptestrts commands provide tools for making statistical inference regarding radial technical efficiency measures (Simar and Wilson, 1998, Management Science 44: 49–61; 2000, Journal of Applied Statistics 27: 779–802; 2002, European Journal of Operational Research 139: 115–132). We provide a brief overview of the nonparametric efficiency measurement, and we describe the syntax and options of the new commands. Additionally, we provide an example showing the capabilities of the new commands. Finally, we perform a small empirical study of productivity growth.

연구개발 사업화 성과 평가 : DEA 기반 3단계 R&BD 성과 모형

This study proposes a three-stage model of R&BD performance which captures commercialization outcomes as well as conventional R&D performance. The model is composed of three factors ：inputs (R&D budgets and researchers), outputs (patents and papers), and outcomes (technical fees, products sales, and cost savings). Three stages are defined for each transformation process between the three factors ：efficiency stage from input to output (stage 1), effectiveness stage from output to outcome (stage 2), and productivity stage from input to outcome (stage 3). The performance of each stage is measured by data envelopment analysis (DEA). DEA is a non-parametric efficiency measurement technique that has widely been used in R&D performance measurement. We measure the performance of 171 projects of 6 public R&BD programs managed by Seoul Business Agency using the proposed three-stage model. In order to provide a balanced and holistic view of R&BD performance, the R&BD performance map is also constructed based on performance of efficiency and productivity stages.

Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis

SummaryWe use an appropriate nonparametric two‐step approach on conditional efficiencies to investigate how foreign direct investment (FDI) and time affect the process of catching up. By using a dataset of 44 countries over 1970–2007, we explore the channels under which FDI fosters productivity by disentangling the impact of this factor on the production process and its components: impact on the attainable production set (input–output space) and the impact on the distribution of efficiencies. We extend existing methodological tools—conditional nonparametric efficiency measures—to examine these interrelationships. We emphasize the usefulness of smoothing over time to better analyze the potential dynamic influence of FDI on efficiency. We find that both FDI and time play an important role as influencing efficiency distribution and affecting, to a smaller extend, the production set. This effect of FDI does not seem to vary much over time. By the second‐stage nonparametric regression of the conditional efficiencies over FDI and time we identify clearly the effect of time and FDI on conditional efficiency and we determine idiosyncratic efficiency, which represents the‘Solow residual’, measured by looking to the unexplained part of the conditional efficiencies. Copyright © 2014 John Wiley & Sons, Ltd.

Hospital efficiency under prospective reimbursement schemes: an empirical assessment for the case of Germany

The introduction of prospective hospital reimbursement based on diagnosis-related groups (DRG) has been a conspicuous attempt to decelerate the steady increase of hospital expenditures in the German health sector. In this work, the effect of the financial reform on hospital efficiency is subjected to empirical testing by means of two complementary testing approaches. On the one hand, we apply a two-stage procedure based on non-parametric efficiency measurement. On the other hand, a stochastic frontier model is employed that allows a one-step estimation of both production frontier parameters and inefficiency effects. To identify efficiency gains as a consequence of changes in the hospital incentive structure, we account for technological progress, spatial dependence and hospital heterogeneity. The results of both approaches do not reveal any increase in overall efficiency after the DRG reform. In contrast, a significant decline in overall hospital efficiency over time is observed.

Product quality, product price, and share dynamics in the German compact car market

The present paper examines one of the central elements of evolutionary thinking – the replicator dynamics mechanism. Using data on product characteristics of automobiles sold on the German domestic market over the period 2001-2006, we construct a fitness variable for each car model applying non-parametric efficiency measurement techniques, better known as data envelopment analysis (DEA). The basic question we intend to answer is whether cars providing a higher quality-price ratio for consumers tend to increase their market share compared to variants with lower quality-price ratio for consumers. The relationship between a car models’ fitness and its market performance is empirically tested in a regression framework. The results show that the principle of ‘growth of the fitter’ is working as suggested by evolutionary theory. In particular, we find that car models with considerably lower fitness than the market average lose whereas models with above-average fitness gain additional market shares.

Productivity changes and risk management in Indonesian banking: a Malmquist analysis

In this study, we utilize a nonparametric efficiency measurement approach which combines the Semi-Oriented Radial Measure–Data Envelopment Analysis (SORM–DEA) approach for dealing with negative data (Emrouznejad et al., 2010) with the Slacks-Based Efficiency Measures (SBM) of Tone (2001, 2002) to analyse productivity changes for Indonesian banks over the period Q1 2003 to Q2 2007. The first part of the analysis showed that average productivity changes for the Indonesian banking industry tended to be driven by technological progress rather than by frontier shift, although a relatively stable pattern was exhibited for most of the period. With respect to the risk management analysis, most of the balance sheet variables were shown to have had the expected impact on Risk Management Efficiency (RME), with the state-owned grouping exhibiting the highest degree of RME and the listed and Islamic banks outperforming their nonlisted and conventional bank counterparts, respectively. A strategy based on the gradual ad...

Is a little sunshine all we need? On the impact of sunshine regulation on profits, productivity and prices in the Dutch drinking water sector

This paper analyzes the performance of Dutch drinking water utilities before and after the introduction of sunshine regulation, which involves publication of the performance of utilities but no formal price regulation. By decomposing profit change into its economic drivers, our results suggest that, in the Dutch political and institutional context, sunshine regulation was effective in improving the productivity of publicly organised services. Nevertheless, while sunshine regulation did bring about a moderate reduction in water prices, sustained and substantial economic profits suggest that it may not have the potential to fully align output prices with economic costs in the long run. In methodological terms, the DEA based profit decomposition is extended to robust and conditional non-parametric efficiency measures, so as to account better for both uncertainty and differences in operating environment between utilities.

Portfolio selection in multidimensional general and partial moment space

This paper develops a general approach for the single period portfolio optimization problem in a multidimensional general and partial moment space. A shortage function is defined that looks for possible increases in odd moments and decreases in even moments. A main result is that this shortage function ensures sufficient conditions for global optimality. It also forms a natural basis for developing tests on the influence of additional moments. Furthermore, a link is made with an approximation of an arbitrary order of a general indirect utility function. This non-parametric efficiency measurement framework permits to differentiate mainly between portfolio efficiency and allocative efficiency. Finally, information can, in principle, be inferred about the revealed risk aversion, prudence, temperance and other higher-order risk characteristics of investors.

Assessing the performance of alternative investments using non-parametric efficiency measurement approaches: Is it convincing?

DEA-based performance assessment in the alternative investment fund industry is often motivated by the fact that DEA is capable of simultaneously handling multiple input (risk) and multiple output (return) measures, thereby still offering a single real number as a performance index without utilizing subjective weights to aggregate these inputs and outputs. This paper aims at investigating whether DEA-based performance indexes previously used to assess alternative investment fund performance are actually able to satisfy these properties, and to contrast the findings using a DEA-based performance index with those using a traditional financial performance index.

Cost allocation and convex data envelopment

Abstract This paper considers allocation rules. First, we demonstrate that costs allocated by the Aumann–Shapley and the Friedman–Moulin cost allocation rules are easy to determine in practice using convex envelopment of registered cost data and parametric programming. Second, from the linear programming problems involved it becomes clear that the allocation rules, technically speaking, allocate the non-zero value of the dual variable for a convexity constraint on to the output vector. Hence, the allocation rules can also be used to allocate inefficiencies in non-parametric efficiency measurement models such as Data Envelopment Analysis (DEA). The convexity constraint of the BCC model introduces a non-zero slack in the objective function of the multiplier problem and we show that the cost allocation rules discussed in this paper can be used as candidates to allocate this slack value on to the input (or output) variables and hence enable a full allocation of the inefficiency on to the input (or output) variables as in the CCR model.

Nonparametric conditional efficiency measures: asymptotic properties

Cazals et al. (J. Econom. 106: 1-25, 2002), Daraio and Simar (J. Prod. Anal. 24: 93-121, 2005; Advanced Robust and Nonparametric Methods in Efficiency Analysis, 2007a; J. Prod. Anal. 28: 13-32, 2007b) developed a conditional frontier model which incorporates the environmental factors into measuring the efficiency of a production process in a fully nonparametric setup. They also provided the corresponding nonparametric efficiency measures: conditional FDH estimator, conditional DEA estimator. The two estimators have been applied in the literature without any theoretical background about their statistical properties. The aim of this paper is to provide an asymptotic analysis (i.e. asymptotic consistency and limit sampling distribution) of the conditional FDH and conditional DEA estimators.

Cost Allocation and Convex Data Envelopment

This paper considers allocation rules. First, we demonstrate that costs allocated by the Aumann-Shapley and the Friedman-Moulin cost allocation rules are easy to determine in practice using convex envelopment of registered cost data and parametric programming. Second, from the linear programming problems involved it becomes clear that the allocation rules, technically speaking, allocate the non-zero value of the dual variable for a convexity constraint on to the output vector. Hence, the allocation rules can also be used to allocate inefficiencies in non-parametric efficiency measurement models such as Data Envelopment Analysis (DEA). The convexity constraint of the BCC model introduces a non-zero slack in the objective function of the multiplier problem and we show that the cost allocation rules discussed in this paper can be used as candidates to allocate this slack value on to the input (or output) variables and hence enable a full allocation of the inefficiency on to the input (or output) variables as in the CCR model.

Sensitivity analysis of efficiency and Malmquist productivity indices: An application to Spanish savings banks

Hypothesis testing and statistical precision in the context of non-parametric efficiency and productivity measurement have been investigated since the early 1990s. Recent contributions focus on this matter through the use of resampling methods—i.e., bootstrapping techniques. However, empirical evidence is still practically non-existent. This gap is more noticeable in the case of banking efficiency studies, where the literature is immense. In this work, we explore productivity growth and productive efficiency for Spanish savings banks over the (initial) post-deregulation period 1992–1998 using Data Envelopment Analysis (DEA) and bootstrapping techniques. Results show that productivity growth has occurred, mainly due to improvement in production possibilities, and that mean efficiency has remained fairly constant over time. The bootstrap analysis yields further evidence, as for many firms productivity growth, or decline, is not statistically significant. With regard to efficiency measurement, the bootstrap reveals that the disparities in the original efficiency scores of some firms are lessened to a great extent.