scholarly journals Can Industrial Integration Improve the Sustainability of Grain Security?

2021 ◽  
Vol 13 (24) ◽  
pp. 13618
Author(s):  
Chen Cao ◽  
Xueyun Chen
Keyword(s):  
Production Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Grain Production ◽  
Analysis Method ◽  
Frontier Analysis ◽  
Important Trend ◽  
Grain Security ◽  
The Impact ◽  
Panel Tobit Model

The sustainability to ensure grain security is an important issue that China’s government faces. It has become more important to ensure grain security by improving the efficiency of grain production under the constraints of limited resources. At present, industrial integration has become an important trend of economic development in China. This study explores the impact of industrial integration on the sustainability of grain security from the perspective of grain production efficiency. In this paper, the grain production efficiency was measured by stochastic frontier analysis method. The degree of industrial integration is measured by the coupling coordination method. Additionally, the effect of industrial integration on grain production efficiency is empirically studied by the panel tobit model. Empirical results show that industrial integration can promote the improvement of grain production efficiency, which reveals that accelerating industrial integration can also be conducive to grain security.

scholarly journals Efficiency Comparison and Efficiency Development of the Metallurgical Industry in the EU: Parametric and Non-parametric Approaches

2020 ◽  
Vol 68 (4) ◽  
pp. 765-774
Author(s):  
Michaela Staňková
Keyword(s):  
Czech Republic ◽  
Production Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Metallurgical Industry ◽  
Analysis Method ◽  
The Czech Republic ◽  
Frontier Analysis ◽  
Parametric Data ◽  
Non Parametric

This article deals with the development of technical (production) efficiency in the metallurgical industry in EU countries with an emphasis on the situation in the Czech Republic. The efficiency of individual countries was estimated for the period from 1995 to 2015. The parametric stochastic frontier analysis method with different settings was chosen to estimate efficiency and the results were verified using a competitive non-parametric data envelopment analysis method. It was found that during the period under review, there was an average increase in efficiency in the metallurgical industry. The largest increase in efficiency (confirmed by all types of models) was observed in the Czech Republic. A visible positive efficiency shift was also recorded in Spain and Greece. Surprisingly, there has been a decline in efficiency in Sweden and Italy.

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 Evaluation of Manufacturing Competitiveness of Hubei Province Based on Stochastic Frontier Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Weidong Gai ◽  
Lei Zhou ◽  
Chun Chen
Keyword(s):  
Manufacturing Industry ◽  
Production Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Hubei Province ◽  
Central China ◽  
Frontier Analysis ◽  
Industrial Enterprises ◽  
Promotion Policies ◽  
Manufacturing Competitiveness

The manufacturing level directly manifests the comprehensive strength of a country or region. Production efficiency provides an important metric of the competitiveness of the manufacturing industry. Based on the data of China’s industrial enterprises of 1999–2011, this paper estimates the production efficiency of manufacturing in Central China’s Hubei Province through stochastic frontier analysis (SFA) and thus characterizes the differences between prefectures of Hubei in manufacturing competitiveness. The results show that, on the prefecture level, Xianning and Wuhan saw a decline in manufacturing competitiveness, while Xiangfan and Xiaogan witnessed an increase in manufacturing competitiveness. To enhance local manufacturing competitiveness and make Hubei the forerunner and cornerstone of Central China, different prefectures should adopt different industrial promotion policies, pay attention to cultivating the technological innovation capabilities of enterprises, and strengthen the integration of production, education, and research.

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.

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