Ownership structure and bank performance in EU-15 countries

2018 ◽  
Vol 18 (3) ◽  
pp. 509-530 ◽  
Author(s):  
Carlo Migliardo ◽  
Antonio Fabio Forgione
Keyword(s):  
Technical Efficiency ◽  
Ownership Structure ◽  
Stochastic Frontier Analysis ◽  
Random Effect ◽  
Stochastic Frontier ◽  
Bank Performance ◽  
Continuous Variables ◽  
Content Type ◽  
Frontier Analysis ◽  
The Impact

PurposeThe purpose of this paper is to investigate the impact of ownership structure on bank performance in EU-15 countries. Specifically, it examines to what extent shareholder type and the degree of shareholder concentration affect the banks’ profitability, risk and technical efficiency.Design/methodology/approachThis study uses a sample of 1,459 banks operating in EU-15 countries from 2011 to 2015. It constructs a set of continuous variables capturing the ownership nature, the concentration and their interactions, and estimates an instrumental variable random effect (IV-RE) model. In addition, a panel data stochastic frontier analysis is conducted to estimate the time-varying technical efficiency for profitability and costs.FindingsThe empirical analysis shows that bank performance is affected by shareholder type. When regressed against the entrenchment behavior of the controlling owner hypothesis, banks with large-block shareholders are more profitable, less risky and more profit efficient. Further, ownership concentration reverts the negative effect related to the institutional, bank and industry ownership.Research limitations/implicationsThe results support the hypothesis that concentrated ownership helps to overcome agency problems. They also confirm that managerial involvement in banks’ capital enhances a bank’s profit and its volatility.Originality/valueTo the best of the authors’ knowledge, this is the first study to consider the ownership nature, the concentration and their interaction using continuous variables, which allows for more precise inferences. The results provide new evidence that bank profitability, cost efficiency and risk are affected by the type of direct shareholders.

Intellectual capital: a determinant of firms' operational efficiency

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kanishka Gupta ◽  
T.V. Raman
Keyword(s):  
Intellectual Capital ◽  
Stochastic Frontier Analysis ◽  
Stock Exchange ◽  
Stochastic Frontier ◽  
Value Added ◽  
Financial Sector ◽  
Operational Efficiency ◽  
Content Type ◽  
Frontier Analysis ◽  
The Impact

PurposeIntellectual capital (IC) has been recognized in improving the efficiency of businesses and gaining competitive edge in the developed world. The present study offers perspectives into the effect of IC on the efficiency of the Indian financial sector companies.Design/methodology/approachFor the purpose of evaluating efficiency, the research has used stochastic frontier analysis (SFA). All Indian financial sector companies listed in National Stock Exchange (NSE-500) for the timeframe of ten years (2008–2018) have been considered. The paper has employed modified Pulic's Value Added Intellectual Coefficient (VAICTM) as a proxy to measure IC. Correlation and panel data regression have been used in order to examine the relationship.FindingsThe results of the study indicate positive and significant relationship between IC and efficiency of the firm. The results also show that all the components of IC, that is, human capital, relational capital, process capital and capital employed have a significant impact on firms' efficiency. Additionally, it has been seen that sample companies do not invest in research and development leading to no innovation capital.Practical implicationsThe research will assist managers in managing and controlling the IC, investors in matters related to investment and financial experts in improving the company's IC and value creation.Originality/valueThe current research is one of the pioneering studies in the context of Indian financial sector that examines the impact of modified VAIC on operational efficiency calculated using SFA.

scholarly journals Estimation of technical efficiency of Czech farms operating in less favoured areas

2019 ◽  
Vol 65 (No. 10) ◽  
pp. 445-453
Author(s):  
Tamara Rudinskaya ◽  
Tomas Hlavsa ◽  
Martin Hruska
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Positive Impact ◽  
Stochastic Frontier ◽  
Agricultural Area ◽  
Farm Size ◽  
Identification System ◽  
Accounting Data ◽  
Frontier Analysis ◽  
The Impact

This paper deals with the technical efficiency analysis of farms in the Czech Republic. The empirical analysis provides an evaluation of technical efficiency with regard to the farm size, farm specialisation, and farm location. Accounting data of Czech farms from the Albertina database for the years 2011–2015 were used for the analysis. The data were classified by the utilised agricultural area and location of the farm expressed as a less favoured area type from the Land Parcel Identification System (LPIS) database. Research was conducted using the translogarithmic production function and Stochastic Frontier Analysis. The results indicate positive impact of farm size, expressed by utilised agricultural area, on technical efficiency. The analysis of the impact of farm specialisation on technical efficiency verified that farms specialised on animal production are more efficient. The lowest technical efficiency is shown by farms situated in mountainous Less Favoured Areas (LFAs), the highest technical efficiency by farms located in non-LFA regions.

Benchmarking the economic and environmental performance of water utilities: a comparison of frontier techniques

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Molinos-Senante ◽  
Alexandros Maziotis ◽  
Ramon Sala-Garrido
Keyword(s):  
Stochastic Frontier Analysis ◽  
Methodological Approach ◽  
Stochastic Frontier ◽  
Assessment Method ◽  
Water Utilities ◽  
Content Type ◽  
Frontier Analysis ◽  
Efficiency Assessment ◽  
Lower Variability ◽  
The Impact

PurposeThe purpose of this paper is to estimate and compare the efficiency of several water utilities using three frontier techniques. Moreover, this study estimates the impact of several qualities of service variables on water utilities’ performance.Design/methodology/approachThe paper utilizes three frontier techniques such as data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) to estimate efficiency scores.FindingsEfficiency scores for each methodological approach were different being on average, 0.745, 0.857 and 0.933 for SFA, DEA and StoNED methods, respectively. Moreover, it was evidenced that water leakage had a statistically significant impact on water utilities’ costs.Research limitations/implicationsThe choice of an adequate and robust method for benchmarking the efficiency of water utilities is very relevant for water regulators because it affects decision making process such as water tariffs and design incentives to improve the performance and quality of service of water utilities.Originality/valueThis paper evaluates and compares the performance of a sample of water utilities using three different frontier methods. It has been revealed that the choice of the efficiency assessment method matters. Unlike SFA and DEA, a lower variability was shown in the efficiency scores obtained from the StoNED method.

scholarly journals EFISIENSI TEKNIS, PERTUMBUHAN TEKNOLOGI DAN TOTAL FAKTOR PRODUKTIVITAS PADA INDUSTRI MENENGAH DAN BESAR DI INDONESIA

2018 ◽  
Vol 6 (1) ◽  
pp. 1-20
Author(s):  
Muhammad Fazri ◽  
Hermanto Siregar ◽  
Nunung Nuryartono
Keyword(s):  
Technical Efficiency ◽  
Manufacturing Industry ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Reform Era ◽  
Frontier Analysis ◽  
Tfp Growth ◽  
Technological Growth ◽  
Before And After ◽  
The Impact

Indonesia's economic growth this decade has good development. Not only growing but also more stable than before the reform era which is visible from the persistence of Indonesia at the level of positive growth during the economic crisis of 2008. Growth was good was followed by a change in the proportion of manufacturing industry in Indonesia which, if seen followed by a decrease in the production of some subsector indices industry. Total factor productivity (TFP) is one measure to look at other factors apart from the impact on production inputs such as technical efficiency and technological growth. In this study, in addition to trying to calculate TFP in some manufacturing industries subsector, in this study also wants to see the value of technical efficiency and the growth of the technology is a component of TFP calculations by the method of Stochastic Frontier Analysis (SFA). The results show that there is growing value of technical efficiency in some industries and most industries experienced relatively low growth of the technology. In the era before and after the crisis most of the industry has increased TFP growth but some industry decreased TFP growth. Keywords: SFA, Technical efficiency, Technological growth, TFP

The Effects of Improved Cassava Variety Adoption on Farmers’ Technical Efficiency in Indonesia

2021 ◽  
Vol 11 (4) ◽  
pp. 269-278
Author(s):  
Syafrial ◽  
Hery Toiba ◽  
Moh Shadiqur Rahman ◽  
Dwi Retnoningsih
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Probit Regression ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Frontier Analysis ◽  
Access To Credit ◽  
Farm Work ◽  
The Impact

The adoption of technological innovations, such as an improved variety, has been widely promoted worldwide to improve agricultural productivity. This study aimed to examine factors affecting farmers’ decision to adopt a new improved cassava varieties (NICV), and to estimate the effects of NICV adoption on farmers’ technical efficiency. This research used cross-sectional data from 300 cassava farmers in East Java, Indonesia. Furthermore, the data were analyzed by probit regression to examine factors affecting farmers’ decision to adopt NICV. Propensity score matching (PSM) procedures and stochastic frontier analysis were applied to evaluate the impact of NICV adoption on farmers’ technical efficiency. The results indicated that adoption was highly influenced by cooperative membership, access to credit, internet access, certified land, and off-farm work. The stochastic frontier analysis, by controlling the matched sample using PSM procedures, demonstrated that NICV adoption positively and significantly impacted farmers’ technical efficiency. Those who adopted NICV showed a higher technical efficiency level than those who did not. This finding implies that improved varieties could be further promoted to increase productivity. The research suggests that there is a need to improve NICV adoption to increase the levels of technical efficiency and productivity.

Efficiency levels of sub-national governments: a comparison of SFA and DEA estimations

2014 ◽  
Vol 26 (3) ◽  
pp. 275-283 ◽  
Author(s):  
Primož Pevcin
Keyword(s):  
Technical Efficiency ◽  
Best Practice ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Empirical Literature ◽  
Fiscal Year ◽  
Content Type ◽  
Frontier Analysis ◽  
Traditional Approaches ◽  
National Governments

Purpose – By utilizing the two most commonly used approaches to generate “best practice frontier” to estimate efficiency of observed units, the purpose of this research paper is to estimate technical efficiency for total population of 200 Slovenian municipalities for the 2011 fiscal year. Design/methodology/approach – Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods are used to estimate technical efficiency levels. Namely, the majority of studies have utilized these two “traditional” approaches. Since the advantages of one method often represent the disadvantages of the other method, the two methods have been selected to compare the results obtained on the technical efficiency levels. Findings – The results suggest that mean technical inefficiency should be approximately 22-25 percent (SFA method), whereas DEA method suggests the inefficiency in the range 12-18 percent. The DEA approach also suggests that the paper has many more technically efficient units compared to the SFA estimates. Nevertheless, the SFA assessment has revealed that, although on average the inefficiency should be larger compared to the DEA assessment, more than one-third of municipalities should exhibit relatively low levels of inefficiency (less than 5 percent). Originality/value – This study utilizes both parametric as well as non-parametric approaches to assess the technical efficiency, which is not very common in the empirical literature. Besides, it focusses on the local government efficiency in a post-socialist country.

Does household engagement in concurrent business affect the farm size-technical efficiency relationship in grain production?

2019 ◽  
Vol 11 (1) ◽  
pp. 125-142 ◽  
Author(s):  
Min Zhong ◽  
Yuchun Zhu ◽  
Qihui Chen ◽  
Tianjun Liu ◽  
Qihua Cai
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Negative Relationship ◽  
Northern China ◽  
Farm Size ◽  
Farm Income ◽  
Content Type ◽  
Frontier Analysis ◽  
Two Factors

Purpose The purpose of this paper is to examine how households’ engagement in concurrent business (CB), which is measured by the contribution of off-farm income to household income, affects the farm size–technical efficiency (TE) relationship in Northern China. Design/methodology/approach This paper applies a stochastic frontier analysis method to analyze data on 1,006 rural households collected from four major wheat-producing provinces in Northern China, adopting a translog specification for the underlying production function. Findings The analysis yields three findings. First, the farm size–TE relationship is inverted U-shaped for all CB engagement levels higher than 5 percent, and the most technically efficient farm size increases with the level of household CB engagement. Second, how TE varies with the level of CB engagement depends on farm size: an inverted-U relationship for relatively small farms (<10μ), a positive relationship for middle-size farms (10–20μ), and a negative relationship for large farms (>20μ). Finally, the overall TE score, 0.88, suggests that wheat output can be increased by 12 percent in Northern China if technical inefficiency were eliminated. Originality/value Unlike most previous studies that examine the impacts of farm size and households’ off-farm business involvement separately, this paper examines how these two factors interact with each other.

scholarly journals The Effect of Employing Temporary Workers on Efficiency: Evidence From a Meta-Frontier Analysis

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110581
Author(s):  
Koangsung Choi ◽  
Chung Choe ◽  
Daeho Lee
Keyword(s):  
Technical Efficiency ◽  
Statistical Methods ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Efficiency Analysis ◽  
Temporary Workers ◽  
Frontier Analysis ◽  
Heterogeneous Technologies ◽  
The Impact

This study examines the impact of employing temporary workers on technical efficiency (TE) by employing stochastic frontier analysis (SFA) and meta-frontier analysis (MFA). These two statistical methods yield slightly different, yet empirically meaningful, results. SFA—the more conventional methodology for conducting efficiency analysis—confirms that firms with temporary workers show a somewhat lower level of TE; while MFA, which allows a comparison of TE across groups with heterogeneous technologies, reveals that firms hiring temporary workers are technologically less efficient and have a more pronounced relative gap in efficiency. With the application of MFA, it was observed that firms hiring only temporary workers come farther to the meta-frontier than their counterparts.

scholarly journals Dampak Program Sekolah Lapang Pengelolaan Tanaman Terpadu terhadap Efisiensi Teknis Usahatani Kedelai di Kabupaten Jember

2017 ◽  
Vol 2 (2) ◽  
pp. 141
Author(s):  
Indah Ibanah ◽  
Andriyono Kilat Adhi ◽  
Dwi Rachmina
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Government Programs ◽  
Frontier Analysis ◽  
Soybean Production ◽  
Average Value ◽  
Production Factors ◽  
The Government ◽  
The Impact

<p>This study aimed to analyze the impact of Sekolah Lapang Pengelolaan Tanaman Terpadu (SLPTT) on technical efficiency soybean participants and non-participants farmers. SLPTT is one of the government programs in an effort to enhancement production and productivity of soybean through the process of learning the application of technology to the management of the use of farm inputs and integrated climate. The method used was the Stochastic Frontier Analysis (SFA) with a model of the Cobb-Douglas production function. Location research in Jember Regency, East Java.</p>The results show the factors that influence significantly to the enhancement in soybean production among others, land, seeds, chemical fertilizers, and pesticides liquid. Production factors most responsive to the enhancement in soybean production is the amount of seed used. The average level of technical efficiency of soybean farming both farmers SLPTT or non SLPTT in Jember Regency have technically efficient. However, farmers SLPTT has an average value of technical efficiency is higher than their non SLPTT, respectively worth 0.83 and 0.75. The sources that affect farmers' socio-economic enhancement of technical efficiency of soybean farming significantly among others, age, planting techniques, the use of VUB, mechanical control, and the number of counseling or SLPTT 2013.

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