scholarly journals Does Agricultural Mechanization Improve Agriculture Environment Efficiency?-Evidence from China’s Planting Industry

2021 ◽  
Author(s):  
Yingyu Zhu ◽  
Yan Zhang ◽  
Huilan Piao
Keyword(s):  
Stochastic Frontier Analysis ◽  
Carbon Sink ◽  
Cumulative Effect ◽  
Practical Significance ◽  
Empirical Literature ◽  
Frontier Analysis ◽  
Spatial Spillover ◽  
Agricultural Mechanization ◽  
Spatial Autoregressive ◽  
The Impact

Abstract It has important theoretical value and practical significance to study the impact of agricultural mechanization (AM) on agriculture environment efficiency (AEE), as AM is an important way to improve the level of rural modernization and accelerate the high-quality development of agriculture, while the increase of energy consumption of AM has brought greenhouse gas emissions. Using the panel data of 30 provinces in China from 2001 to 2019, this article adopts stochastic frontier analysis method with output oriented distance function to measure AEE based on net carbon sink, and empirically analyzes the impact of AM on AEE. The empirical analysis finds that the AEE of the whole country and all provinces shows an upward trend with time, and has significant spatial positive autocorrelation characteristics. There is a Kuznets inverted "U" relationship between AM and AEE. Meanwhile, AM has spatial spillover effect and time cumulative effect on AEE, and this basic conclusion is still robust after using instrumental variables, spatial autoregressive model, sub sample regression, changing spatial weight matrix and independent. Further research shows that the effect of AM on AEE depends on the input effect and output effect caused by AM, and the mechanism is mainly reflected in agricultural technology progress, expansion of the scale of agricultural operation, optimization of resource allocation and spatial spillover. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

scholarly journals Does Agricultural Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

2021 ◽  
Author(s):  
Yingyu Zhu ◽  
Yan Zhang ◽  
Huilan Piao
Keyword(s):  
Total Factor Productivity ◽  
Stochastic Frontier Analysis ◽  
Carbon Sink ◽  
Stochastic Frontier ◽  
Empirical Literature ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Frontier Analysis ◽  
Agricultural Mechanization ◽  
The Impact

Agricultural mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sink, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

scholarly journals Does Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

2021 ◽  
Author(s):  
Yingyu Zhu ◽  
Yan Zhang ◽  
Huilan Piao
Keyword(s):  
Total Factor Productivity ◽  
Stochastic Frontier Analysis ◽  
Carbon Sink ◽  
Stochastic Frontier ◽  
Empirical Literature ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Frontier Analysis ◽  
Oriented Distance ◽  
The Impact

Mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Using the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of planting industry based on net carbon sink, and empirically studies the impact of mechanization on the planting green total factor productivity. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

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 Farm Structure And Efficiency In The Hungarian Agriculture

2015 ◽  
Vol 4 (2) ◽  
pp. 51-56
Author(s):  
Orsolya Tóth ◽  
István Takács
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Farm Size ◽  
Empirical Literature ◽  
Data Envelopment ◽  
Frontier Analysis ◽  
Parametric Data ◽  
Legal Forms ◽  
On Farm

Abstract It has long been the subject of empirical researches to examine the technical efficiency on farm (micro) level. Two main methods are most often used in the empirical literature: the non-parametric Data Envelopment Analysis (DEA) based on linear programming, and the Stochastic Frontier Analysis (SFA) introduced by Aigner, Lovell and Schmidt (1977). The present study aimed to investigate the technical efficiency of farms involved in agricultural activities in Hungary using the DEA-method and the data from the Hungarian FADN database. The technical efficiency was examined based on legal forms, farm size categories and the type of farming between 2001 and 2013.

scholarly journals The Impact of Corporate Social Responsibility as a Marketing Investment on Firms’ Performance: A Risk-Oriented Approach

2021 ◽  
Vol 14 (11) ◽  
pp. 515
Author(s):  
Mohamed Ibrahim ◽  
Mohamed El Frargy ◽  
Khaled Hussainey
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Banking Sector ◽  
Stochastic Frontier Analysis ◽  
Positive Impact ◽  
Frontier Analysis ◽  
Strategic Commitment ◽  
Corporate Social ◽  
The Impact

In light of the growing interest in corporate social responsibility (CSR), there is still controversy regarding its impact on firms’ performance. In this paper, we examine the impact of CSR initiatives, as a marketing investment, on firms’ performance. We treat CSR initiatives as investment and, consequently, the returns appear over the long term. We use the stochastic frontier analysis (SFA) approach which is a forward-looking financial market-based metric that captures the firm’s long-term performance. We focus on the banking industry as it confronts a variety compound of risk. We find that CSR implementation is positively reflected in profit efficiency, regardless of the strategic commitment to implementing CSR and bank size, as these variables do not influence the CSR–performance relationship. However, we find that bank age and competitive positioning have a significant impact on the CSR–performance relationship. Our study provides valuable insights to CSR practitioners and researchers, especially in the banking sector. We provide empirical evidence on the importance of CSR and its positive impact on bank performance in Egypt as one of the emerging markets.

scholarly journals The Spatial Spillover Effects of Environmental Regulation on China’s Industrial Green Growth Performance

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 267 ◽  
Author(s):  
Xiping Wang ◽  
Moyang Li
Keyword(s):  
Growth Performance ◽  
Environmental Regulation ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Green Growth ◽  
Frontier Analysis ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

This study investigated the spatial spillover effects of environmental regulation (ER) on industrial green growth performance (IGGP) in China. Firstly, a parametric stochastic frontier analysis (SFA) was estimated to measure IGGP using the data of China’s 30 provincial industry sectors during 2000–2014. Then, considering the space–time characteristics in IGGP, the spatial spillover effects of three types of ER, namely, administrative environmental regulation (AER), market-based environmental regulation (MER), and voluntary environmental regulation (VER), on IGGP was examined by employing spatial Durbin model (SDM). The main findings are: (1) the IGGP is low but shows a trend of continuous improvement and there is a significant disparity and spatial autocorrelations amongst regions; (2) the spillover effects of the three types of ER are different, specifically, the spillover effects of AER are significant negative, while the effects of MER and VER are both significant positive. The difference between the latter two is that the positive spillover effect of MER on IGGP is so large to outperform the negative direct effect, while the effect of VER is very minor. Based on these findings, relevant policy suggestions are presented to balance industrial economic and environmental protection in order to promote IGGP.

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