Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes

2012 ◽  
Vol 39 (2) ◽  
pp. 101-110 ◽  
Author(s):  
Ryan L. Mutter ◽  
William H. Greene ◽  
William Spector ◽  
Michael D. Rosko ◽  
Dana B. Mukamel
Keyword(s):  
Nursing Homes ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Frontier Analysis ◽  
The Impact

scholarly journals International R&D Spillovers and Innovation Efficiency

2018 ◽  
Vol 10 (11) ◽  
pp. 3974 ◽  
Author(s):  
Jianping Liu ◽  
Kai Lu ◽  
Shixiong Cheng
Keyword(s):  
Capital Stock ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Sensitivity Analyses ◽  
Frontier Analysis ◽  
Country Level ◽  
Scientific Papers ◽  
Catch Up ◽  
The Right ◽  
The Impact

The objective of this study is to examine the impact of international research and development (R&D) spillovers on innovation efficiency of specific R&D outcomes, employing the country-level panel data for 44 countries in the 1996–2013 period. Fully considering the heterogeneity of different R&D outputs, scientific papers, PCT (Patent Cooperation Treaty) patents, US patents, and domestic patents are observed separately, which enriches the angles of measuring international R&D spillovers. By applying a stochastic frontier analysis to knowledge production function, we find that foreign R&D capital stock positively contributes to the innovation efficiency of scientific papers, but suppresses the productivity of domestic patents, whereas it does not really matter for PCT or US patents. These results are robust to control for a set of institutional factors and also in sensitivity analyses. Hence, dependence on international R&D spillovers seems neither to be the right way for emerging economies to catch up, nor to be a sustainable model for developing countries to fill the technical gap. Local R&D capital stock, instead, keeps an essential contributor to all four R&D outputs, so raising internal R&D expenditure is actually the key to improving innovation level and sustainable development ability.

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 The Impact of Urbanization on Farmland Productivity: Implications for China’s Requisition–Compensation Balance of Farmland Policy

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 311 ◽  
Author(s):  
Zhongqi Deng ◽  
Qianyu Zhao ◽  
Helen X. H. Bao
Keyword(s):  
Labor Force ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Agricultural Labor ◽  
Frontier Analysis ◽  
Conservation Policies ◽  
Use Efficiency ◽  
Urbanization Rate ◽  
Impact Of Urbanization ◽  
The Impact

The rapid growth of China’s economy since the reform in 1978 should be largely attributed to urbanization. Nonetheless, in terms of farmland productivity, urbanization may lead to perverse incentives and thus threaten food security. On the one hand, the requisition–compensation balance of farmland (RCBF) policy could reduce farmland productivity because of a “superior occupation and inferior compensation”; on the other hand, urbanization promotes the transfer of the younger labor force and thus reduces the productivity of the agricultural labor force. To investigate the undesirable effects, based on some stylized facts, this study selects 29,415 county-level samples in a Chinese county from 2000–2014 to construct an empirical model. With a new stochastic frontier analysis method that eliminates the classical econometric issues of endogeneity and heterogeneity, the empirical results show that there is a U-shaped relationship between the farmland use efficiency (productivity) and urbanization rate, indicating that only when the urbanization rate is relatively low would urbanization decrease the farmland use efficiency; in contrast, when the urbanization rate is relatively high, technical progress would obviously be accompanied by urbanization, and thus, the undesirable effects are fully offset. Furthermore, the U-shaped relationship is robust after considering the endogeneity of the urbanization rate and total-factor farmland use efficiency. With these findings, recommendations to implement sustainable management and conservation policies regarding farmland resources are made.

scholarly journals The Impact of Foreign Ownership in Czech Football

2021 ◽  
Vol 15 (1) ◽  
pp. 63-70
Author(s):  
Selçuk Özaydın
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Foreign Ownership ◽  
Competitive Balance ◽  
Main Interest ◽  
Foreign Investors ◽  
Frontier Analysis ◽  
Football Team ◽  
European Football ◽  
The Impact

Foreign ownership in European football has been rapidly increasing especially in the last two decades. Although the main interest for the foreign investors are the teams of Big 5 leagues, there are some occasional surprises. One of the surprises is the oldest football team in Czech football, SK Slavia Prague. This study investigates the impact of Slavia’s takeover on Czech First Division. First a stochastic frontier analysis is conducted and efficiency scores are estimated. The results indicate that Slavia’s athletic efficiency has improved significantly after the takeover. The transfer activity in the league increased greatly thanks to Slavia’s additional funds allocated to transfers and also it should be noted that Slavia’s domestic transfers have created an opportunity for the other teams to improve their finances. Finally, the overall competitive balance in the league improved after the takeover despite Slavia’s dominance in the league after the takeover.

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

scholarly journals Using Environmental, Social, Governance (ESG) and Financial Indicators to Measure Bank Cost Efficiency in Asia

2021 ◽  
Vol 13 (20) ◽  
pp. 11139
Author(s):  
Hai-Yen Chang ◽  
Lien-Wen Liang ◽  
Yu-Luan Liu
Keyword(s):  
Cost Efficiency ◽  
Banking Sector ◽  
Stochastic Frontier Analysis ◽  
Developing Economies ◽  
Stochastic Frontier ◽  
Financial Indicators ◽  
Frontier Analysis ◽  
Asian Economies ◽  
Cost Efficient ◽  
The Impact

Environmental, social, and governance (ESG) practices have been used as non-financial indicators to measure bank performance worldwide in the last decade. The United Nations (UN) has specified 17 Sustainable Development Goals (SDGs) for the implementation of these ESG concepts. However, it remains unclear whether the costs of ESG have exceeded the benefits. The purpose of this study is to examine the impact of ESG on the cost efficiency of developed and developing Asian banks using a two-step approach comprising stochastic frontier analysis (SFA) and stochastic metafrontier analysis (SMF). The data sample from 2015 to 2018 is separated into two groups: 60 Asian developed economies and 85 developing economies. The results show that banks in the developed Asian economies become more cost-efficient through environmentally friendly activities. The banks in the developing Asian economies increase their cost efficiency by socially responsible activities and improved governance. Moreover, banks in the developed Asian economies outperformed those in the developing Asian economies in terms of technology gap ratio (TGR) and metafrontier cost efficiency (MCE). The results of this study benefit not only investors and bank managers but also the entire banking sector and the world economy.

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