Prod Anal Research Articles

Does corporate governance really matter for bank efficiency? Evidence from ASEAN countries

This paper examines the impacts of corporate governance on the efficiency of ASEAN banks from 2007 to 2014. The bank efficiency levels are estimated using the SFA model of Kumbhakar et al. (J Prod Anal 41:321–37, https://doi.org/10.1007/s11123-012-0303-1 , 2014). The impacts of various corporate governance aspects on bank efficiency are assessed using the Dynamic system GMM model. The results indicate that government-owned banks are more cost-efficient, but not more profit efficient than both foreign and private banks. Banks with larger boards are more cost-efficient in both the long term and short term, but only more profit efficient in the short term. In addition, foreign ownership, board independence, and CEO duality show no significant impact on bank efficiency levels.

A meta-stochastic frontier analysis for energy efficiency of regions in Japan

This paper measures the metafrontier total-factor energy efficiency (TFEE) of 47 regions in Japan for the period 1996–2008, using the stochastic frontier analysis (SFA). The two-step output-oriented SFA approach by Huang et al. (J Prod Anal 42:241–254, 2014) is followed but converted into a two-step input-oriented SFA approach. The metafrontier TFEE is defined as a product of the group TFEE and the technological gap ratio (TGR). The mean group TFEE is smaller than the mean TGR for both the groups, which shows that the energy inefficiency in Japanese regions with respect to the metafrontier comes from primarily operating inefficiency, rather technology gap. The mean metafrontier TFEE of the metropolitan areas is smaller than that of rural areas, implying that the former is energy inefficient than the latter. The mean TGR of the metropolitan areas is also smaller than that of rural areas, implying that many Japanese regions with major cities are far below the metafrontier and still have much room for energy savings.

Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation

The treatment of the contextual variables (Z) has been one of the most controversial topics in the literature on efficiency measurement. Over the last three decades of research, different methods have been developed to incorporate the effect of such variables in the estimation of efficiency measures. However, it is unclear which alternative provides more accurate estimations. The aim of this work is to assess the performance of two recently developed estimators, namely the nonparametric conditional DEA method (Daraio and Simar in J Prod Anal 24(1):93–121, 2005; J Prod Anal 28:13–32, 2007a) and the StoNEZD (Stochastic Non-Smooth Envelopment of Z-variables Data) approach (Johnson and Kuosmanen in J Prod Anal 36(2):219–230, 2011). To do this, we conduct a Monte Carlo experiment using three different data generation processes to test how each model performs under different circumstances. Our results show that the StoNEZD approach outperforms conditional DEA in all the evaluated scenarios.

A sequential global Malmquist productivity index: Productivity growth index for unbalanced panel data considering the progressive nature of technology

This study proposes an alternative Malmquist productivity index for measuring productivity growth that can be applied to an unbalanced panel data set by considering the progressive nature of technology. The proposed methodology overcomes the weakness of the conventional Malmquist productivity index, which bears spurious technical change and cannot be applied to unbalanced panel data. To develop the methodology, we integrated the concepts of the sequential production possibility set of Tulkens and Vanden Eeckaut (Eur J Oper Res 80:474–499, 1995) and of the global frontier of Asmild and Tam (J Prod Anal 27:137–148, 2007). The suggested index is applied to analyze unbalanced panel data on electric utilities of Korea and the USA between 2001 and 2010. Using the empirical investigation, we show how the suggested index overcomes the fictitious technical regress phenomenon and can be employed for unbalanced panel data.

Efficiency in the Consolidation of the Italian Water Sector

Despite since the mid-90s the regulation has encouraged horizontal and vertical bundling, the Italian water and sewerage industry is still largely fragmented. This work investigates the potential benefits of the process of consolidation, relying on realistic ex-ante merger hypotheses. A parametric methodology is used to implement the Bogetoft and Wang 2005’s decomposition of potential gains from mergers (J Prod Anal 23:145–171). When looking at strictly technological aspects, results do not provide univocal evidence in favor or against merger strategies, recommending a case-by-case approach in evaluating real merger projects. Moreover, the largest potential gains are due to managerial rather than technological inefficiency, thus their effective ex-post attainment ultimately depend on the ability to tackle the change and on political will.

A new approach to estimating the metafrontier production function based on a stochastic frontier framework

This paper proposes a new two-step stochastic frontier approach to estimate technical efficiency (TE) scores for firms in different groups adopting distinct technologies. Analogous to Battese et al. (J Prod Anal 21:91–103, 2004), the metafrontier production function allows for calculating comparable TE measures, which can be decomposed into group specific TE measures and technology gap ratios. The proposed approach differs from Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) mainly in the second step, where a stochastic frontier analysis model is formulated and applied to obtain the estimates of the metafrontier, instead of relying on programming techniques. The so-derived estimators have the desirable statistical properties and enable the statistical inferences to be drawn. While the within-group variation in firms’ technical efficiencies is frequently assumed to be associated with firm-specific exogenous variables, the between-group variation in technology gaps can be specified as a function of some exogenous variables to take account of group-specific environmental differences. Two empirical applications are illustrated and the results appear to support the use of our model.

A comparison of the technical efficiency of accounting firms among the US, China, and Taiwan under the framework of a stochastic metafrontier production function

This study employs the newly developed stochastic metafrontier production function by Huang et al. (A new approach to estimating the metafrontier production function based on a stochastic frontier framework. Working paper, Vanderbilt University, National Cheng-chi University, Taiwan, 2012) to compare the technical efficiencies of accounting firms (AFs) among the US, China, and Taiwan, operating under different technologies. Although AFs play an important role in a nation’s capital market, the accounting industry has not attracted much attention to academic researchers. The main difference between the stochastic metafrontier function and the one proposed by Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) lies in the second step, where the stochastic frontier approach (SFA) is recommended instead of programming techniques. Taiwan’s AFs are found to have the highest average metafrontier technical efficiency (MTE) and AFs in the US have the highest technology gap ratio (TGR). Nonetheless, the average TGR and MTE values of American AFs are closer to those of Taiwan. The low performance of Chinese AFs may be attributed to government regulations and the lack of market competition. However, the programming technique suggests reverse results for AFs in Taiwan and the US and larger variances for TGR and MTE. Then these three countries’ AFs show decreasing returns to scale, indicating that mergers and acquisitions may not be advantageous for expanding their production scale.

Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency

This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi: 10.1007/s11123-012-0303-1 , 2012) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the log-likelihood function of the model using results from the closed-skew normal distribution. Our Monte Carlo analysis shows that MLE is more efficient and less biased than the multi-step KLH estimator. Moreover, we obtain closed-form expressions for the posterior expected values of the random effects, used to estimate short-run and long-run (in)efficiency as well as random-firm effects. The model is general enough to nest most of the currently used panel SF models; hence, its appropriateness can be tested. This is exemplified by analyzing empirical results from three different applications.

Distance optimization approach to ratio-form efficiency measures in data envelopment analysis

The standard data envelopment analysis measures of the Charnes–Cooper–Rhodes (CCR) and slacks-based measure (SBM) are ratio-form efficiency measures, which do not yield the closest projections. However, because of difficulties implementing projections based on standard measures, the closest projections identified by means of least-distance measures may be preferable. Taking into account the practical significance of closest projection points, Aparicio et al. (J Prod Anal 28:209–218, 2007) proposed a least-distance approach based not only on the 1-norm (Manhattan), 2-norm (Euclidean), and ∞-norm (Chebyshev), but also on the procedure presented by Cherchye and Van Puyenbroeck (Eur J Oper Res 132(2):287–295, 2001). Recently, Tone (Eur J Oper Res 200(2):901–907, 2010) presented a least-distance version of SBM (or equivalently, the enhanced Russell graph measure). However, these authors examined neither the occurrence of multiple optimal projections nor the strong/weak monotonicity of the ratio-form least-distance efficiency measures over the efficient frontier of the production technology. Furthermore, it is not well known that the standard measures of CCR and SBM suffer from the occurrence of multiple optimal solutions or efficient targets. Therefore, the present paper also investigates the possibility of multiple optimal targets and axiomatic properties of ratio-form efficiency measures within a unified p-norm efficiency measurement framework.

The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)

Based on the seminal paper of Farrell (J R Stat Soc Ser A (General) 120(3):253–290, 1957), researchers have developed several methods for measuring efficiency. Nowadays, the most prominent representatives are nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA), both introduced in the late 1970s. Researchers have been attempting to develop a method which combines the virtues—both nonparametric and stochastic—of these “oldies”. The recently introduced Stochastic non-smooth envelopment of data (StoNED) by Kuosmanen and Kortelainen (J Prod Anal 38(1):11–28, 2012) is such a promising method. This paper compares the StoNED method with the two “oldies” DEA and SFA and extends the initial Monte Carlo simulation of Kuosmanen and Kortelainen (J Prod Anal 38(1):11–28, 2012) in several directions. We show, among others, that, in scenarios without noise, the rivalry is still between the “oldies”, while in noisy scenarios, the nonparametric StoNED PL now constitutes a promising alternative to the SFA ML.

An examination of the cost efficiency of banks in Taiwan and China using the metafrontier cost function

Using the stochastic metafrontier framework of Battese et al. (J Prod Anal 21:91–103, 2004), this study proposes to compare and measure the cost efficiency and cost frontier gap between the banking industry in Taiwan and China. It further identifies environmental variables that determine bank’s cost frontier gap between two countries. Data on 69 sample banks for years 2005–2009 are used in the empirical analysis and inference. The empirical results show that Taiwanese banks have in general the superior cost frontier of production, but inferior cost efficiency of operation than Chinese banks. Private banks in Taiwan have the best cost frontier, whereas foreign banks in China are most cost efficient among all banks in Taiwan and China. The empirical results also reveal that the majority of Taiwanese banks are undersized and that most banks in China are oversized. Finally, the regression results show that the financial market structure, institutional environment, and political development are significant determinants of the cost gap between the cost frontiers of banks in Taiwan and China. Therefore, programs related to changes directed toward a better bank production environment can be initiated to improve the cost technologies of banks in both Taiwan and China.

Measuring the effect of Kyoto protocol agreement on countries’ environmental efficiency in CO2 emissions: an application of conditional full frontiers

This paper applies the probabilistic approach developed by Daraio and Simar (J Prod Anal 24:93–121, 2005, Advanced robust and nonparametric methods in efficiency analysis. Springer Science, New York, 2007a, J Prod Anal 28:13–32, 2007b) in order to develop conditional and unconditional data envelopment analysis (DEA) models for the measurement of countries’ environmental efficiency levels for a sample of 110 countries in 2007. In order to capture the effect of countries compliance with the Kyoto protocol agreement (KPA) policies, we condition first the years since a country has signed the KPA until 2007 and secondly the obliged percentage level of countries’ emission reductions. Particularly, various DEA models have been applied alongside with bootstrap techniques in order to determine the effect of KPA on countries’ environmental efficiencies. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating environmental performance issues. The results indicate a nonlinear relationship between countries’ obliged percentage levels of emission reductions and their environmental efficiency levels. Finally, a similar nonlinear relationship is also recorded between the duration which a country has signed the KPA and its environmental efficiency levels.

Two-stage DEA: caveat emptor

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a second-stage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (J Prod Anal 13:49–78, 2007), truncated regression provides consistent estimation in the second stage, where as in the model proposed by Banker and Natarajan (Oper Res 56: 48–58, 2008a), ordinary least squares (OLS) provides consistent estimation. This paper examines, compares, and contrasts the very different assumptions underlying these two models, and makes clear that second-stage OLS estimation is consistent only under very peculiar and unusual assumptions on the data-generating process that limit its applicability. In addition, we show that in either case, bootstrap methods provide the only feasible means for inference in the second stage. We also comment on ad hoc specifications of second-stage regression equations that ignore the part of the data-generating process that yields data used to obtain the initial DEA estimates.

Efficiency and Risk-Taking in Pre-Crisis Investment Banks

Investment banks’ core functions expose them to a wide array of risks. This paper analyses cost and profit efficiency for a sample of investment banks for the G7 countries (Canada, France, Germany, Italy, Japan, UK and US) and Switzerland prior to the recent financial crisis. We follow Coelli et al. (J Prod Anal 11:251–273, 1999)’s methodology to adjust the estimated cost and profit efficiency scores for environmental influences including key banks’ risks, bank- and industry- specific factors and macroeconomic conditions. Our evidence suggests that failing to account for environmental factors can considerably bias the efficiency scores for investment banks. Specifically, bank risk-taking factors (including liquidity and capital risk exposures) are found particularly important to accurately assess profit efficiency: i.e. profit efficiency estimates are consistently underestimated without accounting for bank risk-taking. Interestingly, our evidence suggests that size matters for both cost and profit efficiency, however this does not imply that more concentrated markets are more efficient.

Innovation and export activities in the German mechanical engineering sector: an application of testing restrictions in production analysis

Since Solow (Q J Econ 70:65–94, 1956) the economic literature has widely accepted innovation and technological progress as the central drivers of long-term economic growth. From the microeconomic perspective, this has led to the idea that the growth effects on the macroeconomic level should be reflected in greater competitiveness of the firms. Although innovation effort does not always translate into greater competitiveness, it is recognized that innovation is, in an appropriate sense, unique and differs from other inputs like labor or capital. Nonetheless, often this uniqueness is left unspecified. We analyze two arguments rendering innovation special, the first related to partly non-discretionary innovation input levels and the second to the induced increase in the firm’s competitiveness on the global market. Methodologically the analysis is based on restriction tests in non-parametric frontier models, where we use and extend tests proposed by Simar and Wilson (Commun Stat Simul Comput 30(1):159–184, 2001; J Prod Anal, forthcoming, 2010). The empirical data is taken from the German Community Innovation Survey 2007 (CIS 2007), where we focus on mechanical engineering firms. Our results are consistent with the explanation of the firms’ inability to freely choose the level of innovation inputs. However, we do not find significant evidence that increased innovation activities correspond to an increase in the ability to serve the global market.

Likelihood ratio tests for model selection of stochastic frontier models

An important issue when conducting stochastic frontier analysis is how to choose a proper parametric model, which includes choices of the functional form of the frontier function, distributions of the composite errors, and also the exogenous variables. In this paper, we extend the likelihood ratio test of Vuong, Econometrica 57(2):307–333, (1989) and Takeuchi’s, Suri-Kagaku (Math Sci) 153:12–18, (1976) model selection criterion to the stochastic frontier models. The most attractive feature of this test is that it can not only be used for testing a non-nested model, but also still be applicable even when the general model is misspecified. Finally, we also demonstrate how to apply this test to the Indian farm data used by Battese and Coelli, J Prod Anal 3:153–169, (1992), Empir Econ 20(2):325–332, (1995) and Alvarez et al., J Prod Anal 25:201–212, (2006).

Environmental factors and productivity on Dutch hospitals: a semi-parametric approach

This paper describes the efficiency of Dutch hospitals using the method of Data Envelopment Analysis (DEA). In particular the analysis focuses on explaining cost inefficiency measures due to each hospital’s operating environment. In previous works, the resulting DEA score is regressed on environmental factors via a Tobit approach. Previously, these approaches have been used (Simar and Wilson, J Prod Anal 7(1):63–80, 2000) but later these authors (Simar and Wilson 2007) demonstrated that bias is incurred since the efficiency score is a point estimate without a probability distribution around it that is required by the Tobit methodology. In this paper we use the Simar and Wilson bootstrapping techniques in order to obtain more efficient estimates of the environmental effects. It is shown that differences in estimated effects exist between the non-bootstrapped and bootstrapped models.

Matching in local labor markets: a stochastic frontier approach

This paper investigates the technical efficiency of labor market matching from a stochastic frontier approach. The true fixed-effects model (Greene J Prod Anal 23:7–32, 2005a; J Econom 126:269–303, 2005b) is utilised in order to separate cross-sectional heterogeneity from inefficiency, and inefficiency terms are modelled following Battese and Coelli (Empir Econ 20:325–332, 1995). The data set consists of almost 17,000 observations from Local Labor Offices (LLOs) in Finland. According to the results, there are notable differences in matching efficiency between regions, and these differences contribute significantly to the number of filled vacancies. If all regions were as efficient as the most efficient one, the number of total matches per month would increase by over 23%. The heterogeneity of the job-seeker stock is an important determinant of matching efficiency: the weight of the composition of the job-seeker stock in the inefficiency terms is on average 85%.

On the inefficiency of European socialist economies

This paper aims at comparing macroeconomic performance of three European socialist economies (Hungary, Poland, Yugoslavia) with developing and developed countries during the 1970s and the 1980s. Using panel data for 89 countries, we measure macroeconomic performance with two panel data production frontier models: the WITHIN model proposed by (Cornwell et al J Econom 46:185–200, 1990), and the firm effects model developed by (Battese and Coelli J Prod Anal 3:153–169, 1992). We conclude in favor of the underperformance of socialist countries in relation to developed countries but also to developing countries in most cases, which may be explained by the features of the socialist economic system.