scholarly journals An Analysis of Technical Efficiency of Rice Production in Indonesia

2014 ◽  
Vol 11 (3) ◽  
Author(s):  
Unggul Heriqbaldi ◽  
Rudi Purwono ◽  
Tri Haryanto ◽  
Martha Ranggi Primanthi
2018 ◽  
Vol 67 (9) ◽  
pp. 1792-1815 ◽  
Author(s):  
Joko Mariyono

PurposeThe purpose of this paper is to investigate the productivity of rice production by decomposing the growth of total factor productivity (TFP) into four components: technological change, scale effects, technical and allocative efficiencies.Design/methodology/approachThis study employed an econometric approach to decompose TFP growth into four components: technological change, technical efficiency, allocative efficiency and scale effect. Unbalanced panel data used in this study were surveyed in 1994, 2004 and 2014 from 360 rice farming operations. The model used the stochastic frontier transcendental logarithm production technology to estimate the technology parameters.FindingsThe results indicate that the primary sources of TFP growth were technological change and allocative efficiency effects. The contribution of technical efficiency was low because it grew sluggishly.Research limitations/implicationsThis study has several shortcomings, such as very lowR2and the insignificant elasticity of labour presented in the findings. Another limitation is the limited time period panel covering long interval, which resulted in unbalanced data.Practical implicationsThe government should improve productivity growth by allocating more areas for rice production, which enhances the scale and efficiency effects and adjusting the use of capital and material inputs. Extension services should be strengthened to provide farmers with training on improved agronomic technologies. This action will enhance technical efficiency performance and lead to technological progress.Social implicationsAs Indonesian population is still growing at a significant rate and the fact that rice is the primary staple food for Indonesian people, the productivity of rice production should increase continually to ensure social security at a national level.Originality/valueThe productivity growth is decomposed into four components using the transcendental logarithm production technology based on farm-level data. The measure has not been conducted previously in Indonesia, even in rice-producing countries.


2019 ◽  
Vol 11 (24) ◽  
pp. 6974
Author(s):  
Nalun Panpluem ◽  
Adnan Mustafa ◽  
Xianlei Huang ◽  
Shu Wang ◽  
Changbin Yin

Rice production holds a significant position in the Thai economy. Although it is the world’s largest rice exporter, Thailand’s increase in rice production is the result of an expansion in the cultivation area rather than an increase in yield per unit area. The present study was designed to estimate the technical efficiency and its governing factors for certified organic rice-growing farms in Yasothon Province, Thailand. A data envelopment model was employed to assess the technical efficiency of 328 farmer groups. The data revealed that the average technical efficiency was 23% and 28% under constant returns to scale (CRS) and variable returns to scale (VRS) specifications, respectively. Farmers can reduce the use of machinery, fertilizer, seed, and labor as input factors by about 80.1%, 25.62%, 24.72%, and 19.15%, respectively, while still achieving the same level of output. Multiple regression analysis was applied to estimate factors that affect the pure technical efficiency score (PTES) in the test regions. Results show that household size, farm size, water source, market accessibility, health symptoms, income, and labor were highly related to the TES and the amount of organic rice production. The regression coefficients of the predictors show that the income was the best predictor of the PTES at a significance level of p < 0.05. It is concluded that the farmers can potentially increase their yields by up to 72%–77% under current management practices.


2019 ◽  
Vol 48 (3) ◽  
pp. 237-245 ◽  
Author(s):  
Thi Huyen Trang Dam ◽  
TS Amjath-Babu ◽  
Peter Zander ◽  
Klaus Müller

The purpose of our study is to evaluate the impact of saltwater intrusion on the productivity and technical efficiency (TE) of rice farms in Central Vietnam using the stochastic frontier (SF) production function. In contrast to existing studies, this research quantitatively analyses rice variety and season-differentiated impact of soil salinity (as measured by electrical conductivity (EC)) on the TE of rice production. The empirical results indicate that salinity induces significantly varying negative impacts on yield and technical inefficiency of rice farms depending on the salinity class, variety planted and the season. TE begins to sharply decline after reaching salinity class 3 (EC = 4–8 dS/m) and drops to zero under salinity class 4 (EC = 8–16 dS/m) unless salt-tolerant (ST) varieties are planted. A 1% increase in the EC level decreases rice yields by 0.24% in various SF models, while TE shows a cubic relationship with EC, with negative coefficients for linear and quadratic terms. A combination of farm plots consolidation, irrigation, integrated pest management, input optimisation and shifts in varietal selection can potentially offset the yield decline caused by saline intrusion for salinity classes 1 to 4, while adoption of ST varieties seems to be the best option for higher salinity classes over 4. These adaptation measures could also help farmers to avoid maladaptive options such as increased use of pesticide sprays to offset the yield losses due to soil salinity resulting from saline water intrusion. The insights offered by the study is applicable to coastal delta regions cultivating rice in whole of Asia and in other continents.


2017 ◽  
Vol 67 (2) ◽  
pp. 233-241 ◽  
Author(s):  
Joseph Mkanthama ◽  
Godswill Makombe ◽  
John Kihoro ◽  
Elija M. Ateka ◽  
Matshidiso Kanjere

Author(s):  
Sokvibol Kea ◽  
Hua Li ◽  
Linvolak Pich

The aims of this study are to measure the technical efficiency (TE) of Cambodian household&rsquo;s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of the production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015, TE of household&rsquo;s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household&rsquo;s rice production, while disaster, education of household head, family size and other crops&rsquo; cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.


Author(s):  
Sokvibol Kea ◽  
Hua Li ◽  
Linvolak Pich

Rice is the most important food crop in Cambodia and its production is the most organized food production system in the country. The main objective of this study is to measure technical efficiency (TE) of Cambodian rice production and also trying to identify core influencing factors of rice TE at both national and household level, for explaining the possibilities of increasing productivity and profitability of rice, by using translog production function through Stochastic Frontier Analysis (SFA) model. Four-years dataset (2012-2015) generated from the government documents was utilized for the national analysis, while at household-level, the primary three-years data (2013-2015) collected from 301 rice farmers in three selected districts of Battambang province by structured questionnaires was applied. The results indicate that level of rice output varied according to the different level of capital investment in agricultural machineries, total actual harvested area, and technically fertilizers application within provinces, while level of household rice output varied according to the differences in efficiency of production processes, techniques, total annual harvested land, and technically application of fertilizers and pesticides of farmers. The overall mean TE was estimated at 78.4% (national-level) and 34% (household-level), indicates that rice output has the potential of being increased further by 21.6% (national production) and 66% (household) at the same level of inputs and technology if farmers had been technically efficient. The TE also recorded -7% decreasing rate at the national-level and -14.3% at household-level due to highly affected of natural disasters and various environmental and social factors during the study periods.


Agriculture ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1240
Author(s):  
Chukwujekwu A. Obianefo ◽  
John N. Ng’ombe ◽  
Agness Mzyece ◽  
Blessing Masasi ◽  
Ngozi J. Obiekwe ◽  
...  

The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic frontier model in such cases, a stochastic meta-frontier (SMF) analysis is recommended to account for environmental factors between regions. It follows that differences in environmental factors between the upland and lowland regions in Anambra State, Nigeria, may result in farmers producing rice under different production and environmental conditions. Using the SMF model, this study, for the first time, determines technical efficiency (TE) and technological gap ratios (TGRs) of rice production from the upland and lowland regions in the Awka North Local Government Area of Anambra State, Nigeria. Our data are from a cross-section sample of randomly selected rice farmers. Results reveal that lowland regional rice producers are on average, significantly more technically efficient (91.7%) than their upland counterparts (84.2%). Additionally, mean TGRs associated with lowland rice farmers are higher (92.1%) than their corresponding upland producers (84.7%). While the upland rice producers are less technically efficient and further away from their full potential, results indicate that both sets of farmers do not use advanced technologies to match the industry’s potential. We suggest that agricultural policy should focus on providing regionally specific technologies, such as improved rice varieties that fit the working environment of the lagging area, to help rice farmers improve their resource efficiency and minimize technological gaps.


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