Analysis on Technical Efficiency and Influencing Factors of Agricultural Production in China —— Based on the Stochastic Frontier Analysis model

Huang, Weiwei; Xu, Liwenjun; Guo, Yinru

doi:10.1051/e3sconf/202123502005

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…Examining this relationship in relation to an efficiency frontier holds significant interest for government and investment agencies, economists, and management professionals.The extent of technical inefficiency is captured by the difference between the efficiency frontier and the actual input-output relationship. Studies on TE have been conducted widely in various areas, such as the Indian manufacturing sector (Singh, Ashraf, & Ashish, 2019) carrot production (Abunyuwah, Yenibehit, & Ahiale, 2019) the Malaysian transportation industry (Hashim, Mohamed, Fahmy-Abdullah, & Sieng, 2021) and the Chinese energy industry (Wanke, Tan, Antunes, & Hadi-Vencheh, 2020) and agricultural production (Huang, Xu, & Guo, 2021). This evidence indicates that TE has been recognised as a relevant indicator for evaluating production efficiency and identifying weighted input that enhances efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

Hashim,

Fahmy-Abdullah

2024

5002

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This study measured the level of technical efficiency (TE) that exerted a significant impact on the Malaysian electric and electronic manufacturing industry, which consists of 13 sub-industries, from 2010 to 2015. Unbalanced panel data from 1880 firms was obtained from the Department of Statistics Malaysia. We used stochastic frontier (SFA) analysis with the transcendental logarithmic approach to estimate the empirical analysis parametric. The maximum likelihood estimated regression of the SFA parameters revealed a high total average TE of 0.944%. Both the manufacturing sub-industries for communications equipment (MSIC 263) and irradiation, electromedical, and electrotherapeutic equipment (MSIC 266) demonstrated the highest average TE value and consistency (0.989%). The consumer electronics manufacturing sub-industry (MSIC 264) yielded a notably lower TE level (0.846%). Changes in TE for all industries were monitored via standard deviation analysis. The low standard deviation (SD) for MSIC 263, 271, and 275 indicated continuous progress and demands for these industries, while the higher SD for MSIC 264, 266, 272, and 273 pointed out major changes that happened within the period. The findings demonstrated that studies on the TE levels indicate that the E&E manufacturing industry has highly expended and continuous efforts to update technologies and human capital innovations. Therefore, the practical implication is to achieve Sustainable Development Goal 9 for sustainable industrialization and fostering innovation by 2030.

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Section: Literature Reviewmentioning

confidence: 99%

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

Hashim,

Fahmy-Abdullah

2024

5002

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“…Observasi merupakan teknik pengumpulan yang mengharuskan peneliti turun kelapangan untuk mengamati hal-hal yang berkaitan mengenai ruang, tempat, pelaku, kegiatan, waktu, peristiwa, tujuan, dan perasaan [20]. Observasi merupakan suatu metode pengumpulan data dimana peneliti atau kolaboratornya mencatat informasi-informasi sebagaimana yang mereka saksikan selama penelitian berlangsung.…”

Section: Metode Penelitianunclassified

The Analisis Faktor-Faktor yang Mempengaruhi Produksi Gambir di Kecamatan Sutera Kabupaten Pesisir Selatan

Almizan¹,

Cahyani²,

Deri³

et al. 2023

INFEB

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Productivity and product quality are very low due to cultivation methods and post-harvest processes and gambier processing that are not optimal and the lack of technological support for gambier processing. The very low level of productivity causes the amount of production produced to also be low. The decrease in the value of gambier productivity indicates that there has been inefficiency of farmers in allocating existing production factors. This research is associative with a quantitative approach. The population in this study were 18,547 gambier farmers and the sampling technique was random sampling. So in this study using a sample of 100 respondents. This study uses Multiple Linear Regression Analysis with the help of SPSS version 25. The purpose of this study was to analyze the influence of the use of production factors in the form of land area, labor, gambier prices on gambier production. The results showed that the variables of land area and labor could increase the amount of gambier production positively and significantly. Gambier price variable has a positive and insignificant effect on the amount of gambier production.

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“…SFA takes into account the impact of such random factors on output. Therefore, it is favored by an increasing number of scholars and has been applied to the evaluation of agricultural technical efficiency in many countries and regions around the world [43][44][45][46][47] The panel stochastic frontier model was used to investigate technical efficiency. Its basic form is as follows:…”

Section: Stochastic Frontier Model-measurement Of Agricultural Techni...mentioning

confidence: 99%

Spatial Dependence Evaluation of Agricultural Technical Efficiency—Based on the Stochastic Frontier and Spatial Econometric Model

Yin

2021

Sustainability

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In recent years, through the implementation of a series of policies, such as the delimitation of major grain producing areas and the construction of advantageous and characteristic agricultural product areas, the spatial distribution of agriculture in China has changed significantly; however, research on the impact of such changes on the efficiency of agricultural technology is still lacking. Taking 11 cities in Hebei Province as the research object, this study examines the spatial dependence of regional agricultural technical efficiency using the stochastic frontier analysis and spatial econometric analysis. The results show that the improvement in agricultural technical efficiency is evident in all cities in Hebei Province from 2008 to 2017, but there is scope for further improvement. Industrial agglomeration has statistical significance in improving the efficiency of agricultural technology. Further, there is an obvious spatial correlation and difference in agricultural technical efficiency. Optimizing the spatial distribution of agricultural production, promoting the innovation, development, and application of agricultural technology, and promoting the expansion of regional elements can contribute to improving agricultural technical efficiency.

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Analysis on Technical Efficiency and Influencing Factors of Agricultural Production in China —— Based on the Stochastic Frontier Analysis model

Cited by 5 publications

References 6 publications

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

The Analisis Faktor-Faktor yang Mempengaruhi Produksi Gambir di Kecamatan Sutera Kabupaten Pesisir Selatan

Spatial Dependence Evaluation of Agricultural Technical Efficiency—Based on the Stochastic Frontier and Spatial Econometric Model

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