Bias-corrected Efficiency Scores Research Articles

Corporate governance mechanisms and efficiency of insurance firms: evidence from an emerging market

The paper assessed linkage amongst governance mechanisms and efficiency of insurers in Kenya over 8 year period from 2013 to 2020. The study estimated the efficiency of insurers using DEA approach in light of previous literature during the first stage. During the second stage, the bias-corrected efficiency scores were regressed against corporate governance (CG) proxies and control variables using SW (2007) approach on a sample of 53 insurers. Using this two-stage, bootstrapping SW approach, the study documents that the Kenyan insurers are technically inefficient. Overall, the paper presents evidence showing that CG variables influence technical efficiency of insurers in Kenya. Precisely, board independence, gender diversity and audit quality positively and significantly impact Kenyan insurers’ technical efficiency. Further, the paper finds that size of the board negatively affect Kenyan insurers’ technical efficiency. However, the study established insignificant relationship between CEO duality, intensity of board activities and technical efficiency. The paper makes contribution to the bourgeoning reservoir of empirical works on the insurers’ CG-efficiency nexus from an emerging market perspective. Particularly, the article offers empirical insights on some of the least studied CG proxies such as gender diversity, quality of audit and intensity of board activities. The research outcomes also have practical implications for regulators, academia, insurers, government policy makers, practitioners, shareholders and consumers of insurance products by raising their awareness on the influence of CG proxies on the efficiency of the insurers. This is especially beneficial in countries that are pursuing CG and efficiency policy reforms.

Operational efficiency of major cargo seaports in some developing regions: results from a bootstrap DEA

This paper's aim is to investigate the efficiency of main ports located in five different developing regions. The consideration of multiple developing regions constitutes a unique geographic setting that has been neglected in the research literature. A sample of 40 ports was studied and the ports' bias corrected efficiency scores were estimated by means of a bootstrap DEA approach. The study is based on data covering the period 2013-2018. The results showed that most of the ports were not operating at their optimal scale and reported an increasing and decreasing trend in their CRS and VRS efficiency scores respectively. Most of the ports have experienced an increase in their operations without attaining the corresponding increase in their technical capabilities. The ports exhibited a dynamic behaviour, which was due to their operational dynamism rather than their infrastructure dynamism. The overall and regional top port performers were identified for benchmarking purposes.

Measuring Efficiency in the Movie Theater Industry: A Bootstrap Data Envelopment Analysis Approach

ABSTRACT This paper aims to propose a method to measure the operational efficiency of the movie theater businesses. The method is based on a bootstrap data envelopment approach to test the statistical significance of the performance difference between companies in the movie theater industry. The proposed method is utilized to investigate the operational efficiency of the three major U.S. movie theater chains. This article utilizes data from each company’s individual financial filings to estimate their bias-corrected efficiency scores. An aggregate report of the efficiency scores shows that the movie theater industry is experiencing a significant decline in both scale and technical efficiencies. The efficiency assessment of the three movie theater chains reports statistically significant differences. Based on the constant returns to scale assumption, the efficiency scores are different among the three movie theater chains. Closely, two significant differences are identified when considering the variable returns to scale assumption. The kernel density of the efficiency scores is estimated as well. Results suggest that the movie theater chains are in imperative need of developing an innovative strategic plan to tackle poor attendance and weak managerial practices. Other contributions and managerial issues are also discussed.

Technical efficiency evaluation of colorectal cancer care for older patients in Dutch hospitals.

Preoperative colorectal cancer care pathways for older patients show considerable practice variation between Dutch hospitals due to differences in interpretation and implementation of guideline-based recommendations. This study aims to report this practice variation in preoperative care between Dutch hospitals in terms of technical efficiency and identifying associated factors. Data on preoperative involvement of geriatricians, physical therapists and dieticians and the clinicians' judgement on prehabilitation implementation were collected using quality indicators and questionnaires among colorectal cancer surgeons and specialized nurses. These data were combined with registry-based data on postoperative outcomes obtained from the Dutch Surgical Colorectal Audit for patients aged ≥75 years. A two-stage data envelopment analysis (DEA) approach was used to calculate bias-corrected DEA technical efficiency scores, reflecting the extent to which a hospital invests in multidisciplinary preoperative care (input) in relation to postoperative outcomes (output). In the second stage, hospital care characteristics were used in a bootstrap truncated regression to explain variations in measured efficiency scores. Data of 25 Dutch hospitals were analyzed. There was relevant practice variation in bias-corrected technical efficiency scores (ranging from 0.416 to 0.968) regarding preoperative colorectal cancer surgery. The average efficiency score of hospitals was significantly different from the efficient frontier (p = <0.001). After case-mix correction, higher technical efficiency was associated with larger practice size (p = <0.001), surgery performed in a general hospital versus a university hospital (p = <0.001) and implementation of prehabilitation (p = <0.001). This study showed considerable variation in technical efficiency of preoperative colorectal cancer care for older patients as provided by Dutch hospitals. In addition to higher technical efficiency in high-volume hospitals and general hospitals, offering a care pathway that includes prehabilitation was positively related to technical efficiency of hospitals offering colorectal cancer care.

Efficiency of South African water utilities: a double bootstrap DEA analysis

ABSTRACT Although the efficiency of the water sector has been studied extensively utilizing data envelopment analysis (DEA), most of the literature tends to use the conventional DEA model to compute efficiency scores. In addition, there are many studies that undertake a second stage regression of the efficiency scores against a set of covariates. However, such second-stage analyses are problematic due to potential serial correlation inherent in the estimated efficiency scores. To determine the bias-corrected efficiency scores of rural and urban water utilities in South Africa, this study uses a robust, non-parametric DEA bootstrapping model to generate them. Moreover, little is known about relative performance of the conventional DEA versus bias-corrected DEA. In addition, the truncated double-bootstrap regression results provide insights into the drivers of efficiency, including how water policies and the political and institutional contexts of water utilities can impact relative efficiencies. We found that there are significant differences between the rankings and efficiency scores generated by the conventional DEA model compared to the double-bootstrap DEA model, for both urban and rural samples. The regression model found the location and the ratio of metered to unmetered connections to be significant determinants of efficiency for both urban and rural water utilities.

Ownership and performance of microfinance institutions: Empirical evidences from India

The study examines the efficiency differences across the ownership structure of Indian microfinance institutions (MFIs) operating during the year 2005/06 to 2017/18 in response to regulatory reforms initiated by the Reserve Bank of India (RBI) in the year 2011. We remove the outliers from the dataset first. Thereafter, we employ the bootstrap data envelopment analysis (DEA) to assess the bias-corrected efficiency scores. To identify the performance determinants, we use bootstrap truncated regression. The empirical results suggest that the performance difference between NBFCs and Non-NBFC MFIs is not statistically significant in the sample period. Further, the study finds that the size and ownership structure of MFI has a positive and statistically significant impact on the efficiency level. Although the coefficient of PAR30 (Portfolio at risk, 30 days) is statistically insignificant, however, the results conclude that the deteriorating credit quality has hindered the efficiency level. The Indian MFI industry needs to focus on the adoption of more innovative technology and partnership with FinTech (financial technology) firms to reduce the transaction costs and service time. The RBI essentially endorses the regulatory-sandbox practices to offer micro-financial services to the poor.

Oncology services efficiency in the age of pandemic: A jackknife and bootstrap sensitivity analysis for robustness check of DEA scores

BackgroundDeveloping countries face great challenges in health care because of changing disease dynamics and the increasing burden of chronic diseases such as cancers. Thus, effective operational design of health services is critical to better manage scarce health care resources. This study aimed to examine the spatial distribution of the efficiency of Turkey’s oncology services. MethodsData was collected from the 2017 Public Hospitals Statistical Yearbook, and a total of 55 provinces with advanced centers for cancer were analyzed. This study applied Charnes, Cooper, and Rhodes’s input-oriented data envelopment analysis (DEA) and performed jackknifing for robustness check of DEA scores. ResultsThe iteration procedure generated four models. The final model included 38 decision-making units (DMUs), and 50 % of provinces were found to have efficient oncology services. The final model’s average conventional efficiency score was 0.79. Next, bootstrapped DEA procedure was incorporated into the final model to gather bias-corrected efficiency scores. After applying the bootstrapping approach, efficiency scores are significantly improved and the difference between conventional and bias-corrected efficiency scores are statistically significant (U = 475; p < 0.05). ConclusionsGeographic planning of cancer care services is a relevant principle in health operations design that requires specific health service configurations for preparedness of health crisis such as pandemic. The results highlighted that health policymakers must be aware of regional imbalances and eliminate them to provide advanced oncology care services for population groups in poor areas of the country. Policy summaryHealth policy makers should prioritize a balanced geographical distribution of professional oncology services to provide vulnerable groups better access to critical care.

Drivers of financial and operational efficiency of MFIs: empirical evidences from Eastern Europe and Central Asia

PurposeThe study attempts to examine the bias-adjusted financial and operational efficiency estimates of microfinance institutions (MFIs) operating in the Eastern Europe and Central Asia (ECA) region during the financial year 2017–2018. In addition, the study also identifies the responsible factors determining the financial and operational performances of MFIs operating in the ECA region.Design/methodology/approachThe study employs two-stage bootstrap data envelopment analysis (DEA). In the first stage, the authors incorporate the bootstrap procedure in the DEA framework as suggested by Simar and Wilson (2000) to estimate the bias-corrected efficiency scores of 67 sample MFIs. In order to identify the drivers of efficiency level, the study deploys the bootstrap truncated regression model following the Simar and Wilson (2007) guidelines in the second stage of analysis.FindingsThe authors note from the empirical results that MFIs operating in the ECA region are relatively more financially efficient (0.588) than socially efficient (0.496). However, none of the MFIs were found to be operating at best-practice frontier while considering the bias-adjusted efficiency estimates. Further, the results of second stage of analysis confirm that corporate governance, that is, board size has positive and statistically significant impact on MFIs’ performances. In addition, the bad credit quality deteriorates both financial revenue and operational efficiency. Moreover, the MFIs’ size, profit status and debt-to-equity ratio were also found to be statistically significant to determine the operational and financial efficiency of MFIs in the ECA region.Practical implicationsThe study provides the robust efficiency estimates and factors responsible to determine the financial and operational efficiency of MFIs operating in the ECA region. Further, the empirical results of the study provide the inputs and further direction to the policymakers, regulators, practitioners and managers in framing the policy and optimal operating strategies for ECA MFIs industry.Originality/valueThe study extends the DEA analysis by incorporating the bootstrap procedure in DEA model to estimate the bias-adjusted efficiency scores which are more reliable and robust. In addition, bootstrap truncated regression has been applied to identify the drivers of efficiency. Moreover, in the literature there is no single study which has deployed the double bootstrap DEA framework to examine the financial and operational efficiency estimates and its drivers.

The Efficiency of New Zealand District Health Boards in Administrating Public Funds: An Application of Bootstrap DEA and Beta Regression

ABSTRACT This study uses quarterly data from 2011 to 2018 to evaluate the technical efficiency of New Zealand District Health Boards (DHBs) in providing hospital services. It examines how efficiency is affected by various patient structures and contextual factors. An intertemporal data envelopment analysis and bootstrap approach are used to compute the bias-corrected technical efficiency scores, followed by highly flexible beta regression to assess the relationship between technical efficiency and related factors. The results indicate that the technical efficiency levels of New Zealand DHBs have not improved since 2011, and on average DHBs could increase their provision of hospital services by approximately 12%. Furthermore, most of the poor performing DHBs operate in the area of high socio-economic deprivation. The results from beta regression show that DHBs providing hospital services in highly deprived areas are associated with a decreasing level of technical efficiency as the proportion of surgical, acute, Māori and Pacific inpatient increases. However, an increase in capital to labour ratio improves the technical efficiency of these DHBs. Therefore, policymakers need to formulate comprehensive strategies involving a longer time horizon that facilitates capital investments in critical technology and capacity development to improve the long-run efficiency performance of DHBs operating in the area of high deprivation.

Assessing the efficiency of integrated public transit stations based on the concept of transit-oriented development

Encouraging a modal shift from cars to transit by employing Transit-Oriented Development (TOD) strategies have gained attention owing to the rising concerns about sustainability. Despite its benefits, the assessment of public transit station efficiency with regards to TOD planning concepts is limited. By employing TOD and network centrality measures as inputs, this study explores the efficiency of transit stations using a robust bootstrap Data Envelopment Analysis (DEA). In the first stage, bias-corrected efficiency scores are estimated and used in truncated regression analysis in the second stage to identify instrumental determinants of station efficiency. Results indicate that an increase in population, land-use diversity and the number of bus stops around subway stations improve efficiency, whereas transfer distance was negatively correlated with station performance. The findings provide useful insights into how transport planners can modify existing station conditions to derive the benefits of TOD and to improve the quality of citizens’ lives.

Impact of environmental variables on the efficiency of water companies in England and Wales: a double-bootstrap approach.

An important aspect of the regulatory process is the performance comparison of regulated firms. This exists in regulated industries where tariffs are determined through a benchmarking process such as the English and Welsh water industry. A double-bootstrap data envelopment analysis (DEA) approach was applied to overcome the uncertainty in efficiency scores and to reveal the influence of environmental variables on 18 water companies in England and Wales during the 2001-2016 period. The results showed that bias and bias-corrected efficiency scores lead to changes in the water companies' rankings. This reveals the importance of using reliable methodologies to support the decision-making process. Higher levels of average pumping head, leakage, and abstraction of water from reservoirs lead to lower efficiency. In contrast, increased population density leads to larger efficiency. We also link the results from the efficiency of water companies with the regulatory cycle. Our findings can be useful to policy makers for them to better understand water utilities' performance and to aid them in reshaping their current policies and practices to improve efficiency and provide better service to customers.

An empirical investigation of efficiency and productivity in the Indian non-life insurance market

PurposeThe purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of efficiency, productivity and returns-to-scale economies. In addition to this, it identifies the determinants of efficiency.Design/methodology/approachThis study employs a two-stage data envelopment analysis (DEA) bootstrap approach to estimate the level and determinants of efficiency. In the first stage, the DEA bootstrap approach is employed to estimate bias-corrected efficiency scores. In the second stage, the truncated bootstrapped regression is used to identify the effect of firm-level characteristics on the efficiency of insurers. Moreover, the bootstrapped Malmquist index is used to examine the productivity growth over the observation period 2005–2016.FindingsThe bootstrapped DEA results show that the Indian non-life insurance sector is moderately technical, scale, cost and allocative efficient, and there is a large opportunity for improvement. Moreover, the results reveal that the public insurers are more cost efficient than the private insurers. It is also evident that all the insurers irrespective of size and ownership type are operating under increasing returns to scale. Malmquist index results divulge an improvement in productivity of insurers, which is attributable to the employment of the best available technology. Bootstrapped DEA and bootstrapped Malmquist index results also show that the global financial crisis of 2008 has not severely affected the efficiency and productivity of the Indian non-life insurance sector. The truncated regression results spell that size and reinsurance have a statistically significant negative relationship with efficiency. It also shows a statistically significant positive age–efficiency relationship.Practical implicationsThe results hold practical implications for the regulators, policy makers, practitioners and decision makers of the Indian non-life insurance companies.Originality/valueThis study is the first of its kind that comprehensively investigates different types of robust efficiency measures, determinants of efficiency, productivity growth and returns-to-scale economies in the Indian non-life insurance market for an extended time period.

Benchmarking on Water Resource Utilization Efficiency of Prefecture-Level Cities in Jiangxi, China: A Bootstrap-DEA Approach with Three-Stage DEA Models

China has long been adopted traditional data envelopment analysis (DEA) models to measure water resources utilization efficiency of different provinces and cities without bias correction of efficiency scores. In this study, the Bootstrap-DEA approach embedded 3-stage DEA models was introduced to analyze the comprehensive efficiency of water resources utilization in the different prefecture-level cities Jiangxi and tried to improve the application of this method for benchmarking and inter-regional research. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional DEA model, which implies that Chinese researchers need to update their DEA models for more scientific calculation of water resources utilization efficiency scores. This research has helped narrow the inter-regional gap in the comprehensive efficiency measurement and improvement of water resources utilization. It is suggested that Bootstrap-DEA embedded 3-stage DEA models be widely applied into afterward research to measure comprehensive efficiency of water resources utilization in regional inter-city so as to better serve for efficiency improvement and related decision making.

Assessment of efficiency and ranking of microfinance institutions in India: a two-stage bootstrap DEA analysis

This paper examines the financial, social and overall bias-corrected efficiencies of 82 Indian microfinance institutions for the year 2015-2016, and obtains the potential determinants of efficiency scores using double bootstrap procedure by Simar and Wilson (2007). Bias-corrected efficiency scores are used to provide a strict ranking to sampled MFIs. An attempt is made to resolve the unsettled debate on trade-off between the dual goals of the MFIs. The results reveal that Indian MFIs are found more financially efficient than socially efficient in the sampled year. The efficiency differences across the MFIs' operating in central and northern regions and distinct sizes classes of MFIs are statistically significant. The study establishes enough evidence to advocate the absence of trade-off in achieving dual goals in the Indian MFI industry in the year 2015-2016. Finally, size of MFI and equity to assets ratio influences the efficiency levels of Indian MFIs.

DATA ENVELOPMENT ANALYSIS OF RUBBER SMALLHOLDERS: BCC AND CCR MODELS AND BOOTSTRAPPING TECHNIQUE

The present study examined the economic efficiency of rubber smallholders in Peninsular Malaysia in a disaggregated form using Banker Charnes and Cooper (BCC) and Charnes Cooper and Rhodes (CCR) models of data envelopment analysis (DEA) as well as their respective bootstrap techniques. Multistage data collection was employed on 327 smallholders among 5 districts of Negeri Sembilan state. However, only 307 observations were used in computing inferential statistics, because the young-age category has been removed. The districts include Seremban, Tampin, Rembau, Kuala Pilah and Jempol. The results revealed that, the mean technical efficiency (TE) under variable returns to scale (VRS) and constant returns to scale (CRS) were 0.95, 0.97 0.96 and 0.45, 0.61, 0.33 for the all-age, matured-age and old-age crops respectively. The findings of the result also disclosed that naïve DEA has higher mean scores than bootstrapped-DEA, thus indicating the presence of bias in the former and absence of bias in the later. Also, the efficiency determinants under VRS and CRS as well as their respective bias-corrected (BC) efficiency scores were also analyzed using Tobit regression analysis against the 15 socio-demographic factors. It was found out that critical factors, common to all the age-categories, include educational level, tapping system and marital status under VRS and BC-VRS assumptions, while under CRS and BC-CRS assumptions include race, tapping system, marital status and farm’s distance. Therefore, education of smallholders should be given more attention to increase efficiency. The study finally recommends that the traditional concept of computing efficiency or productivity of rubber and other perennial crops in an aggregated form should be complemented with the disaggregated form as this eliminates any bias and gives meaningful results. Improved methods such as bootstrapping should also be used as this only gives what is called bias-corrected efficiency scores. Regarding the determinants, factors such as education, tapping system and farm distance should be given more emphasis.

On the meaning of innovation performance: Is the synthetic indicator of the Innovation Union Scoreboard flawed?

The European Union (EU) annually publishes an Innovation Union Scoreboard (IUS) as a tool to measure the innovation performance of EU Member States by means of a composite index, called the Summary Innovation Index (SII). The SII is constituted by an average of 25 indicators. The SII is claimed to rank Member States according to their innovation performance. This means that the higher the average value of the 25 indicators, the better the innovation performance is said to be. The first purpose of this article is to assess whether the SII constitutes a meaningful measure of innovation performance. Our conclusion is that it does not. Our second purpose is to develop alternative, productivity or efficiency-based, measures of innovation system performance based on a simple index number, and complement it with advanced and robust nonparametric Data Envelopment Analysis techniques. By doing so, the article offers a critical review of the SII, and proposes to put more emphasis on the identification of and relation between input and output innovation indicators. The data provided by the 2014 and 2015 editions of the IUS are here used to analyze the innovation performance of all 28 EU national innovation systems. A theoretical background and reasons for selecting the indicators used are presented, and our new ranking of the innovation performance using bias-corrected efficiency scores of all EU countries is calculated. We find that the results differ substantially between the SII and the ranking based on our method, with significant consequences for the design of innovation policies. (Less)

The analysis of energy efficiency of the Mediterranean countries: A two-stage double bootstrap DEA approach

The main purpose of this paper is to examine the energy efficiency determinants in Mediterranean countries over 2009-2012. In order to account for both the bias and serial correlation of efficiency scores, we use the double bootstrap procedure suggested by Simar and Wilson (2007) which allows for valid inference. By using a specific bootstrap procedure in the first stage, the DEA efficiency estimator is corrected for the bias. A parametric bootstrap procedure is also applied, in the second stage analysis, to the truncated regression of DEA bias-corrected efficiency scores on environmental variables. In the first stage, empirical findings show that energy efficiency levels in the Mediterranean countries are high and declining over time. The results of the second stage analysis reveal that the gross national income per capita, the population density, and the renewable energy use impact energy efficiency. Finally, the study provides policy implications for future improvement of energy efficiency.

Operational efficiency of county level public hospitals in Hubei: a Bootstrap-data envelopment analysis

Objective To estimate the operational efficiency of 37 county level public general hospitals in Hubei province using the world popular method of Bootstrap-data envelopment analysis.The aim is to make up for the theory and methodology gaps on DEA research for hospitals in China, and to provide policy and management recommendations for their further improvement. Methods The input and output indicators of hospital efficiency evaluation were selected based on our previous research.R Software was used to describe the current input and output indicators, while FEAR package used to measure Bootstrap-DEA efficiency value of the sample hospitals with bias corrected, along with such applied analysis as efficiency benchmarking for the technical efficiency outcomes. Results There are great differences among the healthcare input and output of these hospitals.In particular, the difference in the number of actual beds was 4.67 times between the highest hospital and the lowest one.All of the bias corrected efficiency scores were lower than those before correction, and the average bias corrected score of the sample hospitals is 0.717 9.Moreover, only 20 hospitals(54.05%)have their efficiency scores above the median level. Conclusions The healthcare resources allocation of these hospitals needs to be further optimized.Hospitals still have big potential to improve their efficiency.Besides providing policy support, the government is advised to guide hospitals to innovate their management mechanisms, such as introducing and applying benchmarking, ranking, inter-hospital learning among others, so as to continuously improve their operational efficiency. Key words: Bootstrap-DEA; Hubei province; County-level public hospitals; Operational efficiency; Benchmarking management

Determinants of Technical Efficiency in Chinese Banking: A Double Bootstrap Data Envelopment Analysis Approach

The main objective of this study is to measure the technical efficiency level of the Chinese banking industry. It uses a double bootstrap data envelopment analysis approach to compute bias-corrected efficiency scores and investigate the determinants of bank efficiency in China between 2003 and 2010. We observe that Chinese commercial banks regardless of ownership have shown improved efficiency from 2003 to 2010. Our results show a significant difference in the performance between state-owned banks and joint-stock banks over the period analyzed. Moreover, the equity-to-asset ratio also significantly explains variations in inefficiency across Chinese commercial banks. Initial public offering is considered one of the effective ways to improve bank efficiency in China. Overall, the present study provides valuable empirical information that can be used to help guide deliberations regarding future reform policies.

TECHNICAL EFFICIENCY AND ITS DETERMINANTS IN THE SPANISH CONSTRUCTION SECTOR PRE- AND POST-FINANCIAL CRISIS

This paper estimates technical efficiency in the Spanish construction sector before and after the start of the current financial crisis, and examines the impact of socio-economic factors on technical efficiency. Bias-corrected efficiency measures are obtained using Data Envelopment Analysis with bootstrap for a sample of medium-sized and large construction firms over the period 2000–2010. Next, bias-corrected efficiency scores are regressed on the variables explaining efficiency using bootstrap truncated regression. The results show that technical efficiency is very low and is significantly lower after the beginning of the financial crisis than before. Firms with the highest technical efficiency scores have the lowest input-ratio for material and employee costs to output and the highest for fixed assets. The examination of the determinants of technical efficiency indicates that efficiency is higher for firms that export, are highly leveraged, are integrated in the form of joint stock company, and are located in Spanish regions with higher GDP per capita, while firms with high stock relatively to turnover have lower technical efficiency. Technical efficiency increases with size for relatively small sized construction firms, but decreases beyond a critical firm size, while technical efficiency decreases with age for young firms, but eventually increases for older firms.