scholarly journals Technical efficiency of rice farming in Aceh Province, Indonesia

2022 ◽  
Vol 951 (1) ◽  
pp. 012075
Author(s):  
H Gunawan ◽  
M S A Majid ◽  
R Masbar

Abstract This study measures the technical efficiency of rice farming in Aceh Province, Indonesia. A sample of 5,351 households from the 2017 Household Farming Cost Structure Survey conducted by the Central Bureau of Statistics of Aceh Province, Indonesia were gathered and analysed using the Data Envelopment Analysis (DEA). Three inputs (i.e., number of labour working days, fertilizer, and seeds) and one output (i.e., number of rice harvest) were used to measure the technical efficiency of rice farming in the province. The study recorded a very low average level of technical efficiency either using a Constant Return to Scale (CRS) or a Variable Return to Scale (VRS) approaches. Two inputs were found not optimal for rice farming activities, namely the number of labour working days and the use of fertilizers, while the use of seeds was found optimal. The study suggests that the farmers should use fertilizers proportionately to the land area. The use of agricultural technology should be intensified to minimize the use of excess labour to reduce wage spending.

2019 ◽  
Vol 2 (1) ◽  
pp. 17
Author(s):  
Mutia Fhazira ◽  
Devi Andriyani

This study aims to analyze the technical efficiency of rice farming in Desa Meunasah Panton Labu, Tanah Jambo Aye Sub-district, North Aceh Regency. This study uses primary data obtained from the distribution of questionnaires to 50 respondents who are landowners and farmers in Desa Meunasah Panton Labu, Tanah Jambo Aye Sub-district, North Aceh Regency. This study used is the Purposive sampling method. Data Envelopment Analysis (DEA) is used to analysis the data. The results showed that the landowners were more technically efficient than sharecroppers where the number of farmers who had reached the level of efficiency as many as 19 respondents.


2016 ◽  
Vol 78 (12-3) ◽  
Author(s):  
Na’imah Ali ◽  
Noor Asiah Ramli ◽  
Faridah Zulkipli

RISDA has targeted for the income of each smallholder to be at least RM2500 per month by the end of 2015. However, approximately almost 90% of the smallholders’ monthly income is still below the target. Hence, in order to observe if this target is achievable, a study was conducted to evaluate the efficiency level of producing rubber among 95 rubber smallholders in Pahang. In addition, the study also investigated if there was any opportunity for increment of production among the rubber smallholders. Therefore, the Data Envelopment Analysis (DEA) model, under the assumption of Variable Return to Scale (VRS) and Constant Return to Scale (CRS), was used to analyse the scale and the technical efficiency of the smallholders. Scale Efficiency was measured in order to estimate the return to scale of the smallholders. As a result, the study found that the average Overall Technical Efficiency (OTE) and Pure Technical Efficiency (PTE) scores of the smallholders were 43.47% and 43.78%, respectively. Thus, the majority of the smallholders were not technically efficient in producing rubber. Furthermore, based on the return to scale estimated, 41% of the smallholders were operating under the Increase Return to Scale (IRS), which implied that the smallholders had a sub-optimal scale size. The results obtained had been useful as the optimal input-output for the efficient rubber yield can be determined and may help RISDA, as well as agricultural planners, to devise a strategy in order to increase the productivity of rubber smallholders in Malaysia.   


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rachman Hakim ◽  
Tri Haryanto ◽  
Dyah Wulan Sari

AbstractRice is a staple food in East Java, and the average consumption is 100 kg/capita/year. However, rice productivity has declined dramatically in recent years. Food security can be reached by improving the technical efficiency of rice farming, especially in rice farming centers such as East Java Province. This study aims to measure technical efficiency and its determinants using two limit tobit. And it also aims to examine the effect of the technical efficiency of rice farming on food security using logit regression. Technical efficiency will be measured by using data envelopment analysis (DEA). The results show that the technical efficiency of rice farming is very low in East Java. Government assistance, irrigation, and extension have a significant effect on technical efficiency. Meanwhile, membership of farmer organization has no effect on technical efficiency. Around 69% of farmers can be categorized as food secure households. The estimation of logit regression shows that household size, income, land size, education, age, and gender significantly influence food security in East Java. Meanwhile, credit and technical efficiency did not have any significant effect.


2015 ◽  
Vol 65 (s2) ◽  
pp. 101-113 ◽  
Author(s):  
Ling Jiang ◽  
Yunyu Jiang ◽  
Zhijun Wu ◽  
Dongsheng Liao ◽  
Runfa Xu

In the era of knowledge economy, a country’s economic competitiveness depends largely on the development level of high-tech industry. This paper evaluates the efficiency of China’s high-tech industry in 31 provinces in 2012 with data envelopment analysis. The empirical results are summarized as following. Firstly, when the effects of exogenous environmental variables are not controlled, the comprehensive technical efficiency of 31 provinces will be overestimated, the pure technical efficiency will be underestimated, and the scale efficiency value will be overestimated. Secondly, after eliminating the environmental impact, the comprehensive technical efficiency of 31 provinces with the average of 0.395 is rather low, due to the low scale efficiency.


2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier

In this article, we used bootstrap data envelopment analysis techniques to examine technical and scale efficiency scores for a balanced panel of 564 farms in Kansas for the period 1993–2007. The production technology is estimated under three different assumptions of returns to scale and the results are compared. Technical and scale efficiency is disaggregated by farm size and specialization. Our results suggest that farms are both scale and technically inefficient. On average, technical efficiency has deteriorated over the sample period. Technical efficiency varies directly by farm size and the differences are significant. Differences across farm specializations are not significant.


2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.


2018 ◽  
Vol 286 (1-2) ◽  
pp. 703-717
Author(s):  
Murilo Wohlgemuth ◽  
Carlos Ernani Fries ◽  
Ângelo Márcio Oliveira Sant’Anna ◽  
Ricardo Giglio ◽  
Diego Castro Fettermann

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