Technical efficiency and its determinants in smallholder rice production in northern Ghana

2016 ◽  
Vol 50 (2) ◽  
pp. 311-328 ◽  
Author(s):  
Benjamin Tetteh Anang ◽  
Stefan Bäckman ◽  
Timo Sipiläinen
Keyword(s):  
Technical Efficiency ◽  
Rice Production ◽  
Northern Ghana

Productivity growth of Indonesian rice production: sources and efforts to improve performance

2018 ◽  
Vol 67 (9) ◽  
pp. 1792-1815 ◽  
Author(s):  
Joko Mariyono
Keyword(s):  
Technological Change ◽  
Technical Efficiency ◽  
Production Technology ◽  
Productivity Growth ◽  
Scale Effects ◽  
Allocative Efficiency ◽  
Rice Production ◽  
Content Type ◽  
Tfp Growth ◽  
Efficiency Effects

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.

scholarly journals Measuring the Technical Efficiency of Certified Organic Rice Producing Farms in Yasothon Province: Northeast Thailand

2019 ◽  
Vol 11 (24) ◽  
pp. 6974
Author(s):  
Nalun Panpluem ◽  
Adnan Mustafa ◽  
Xianlei Huang ◽  
Shu Wang ◽  
Changbin Yin
Keyword(s):  
Technical Efficiency ◽  
Management Practices ◽  
Returns To Scale ◽  
Water Source ◽  
Rice Production ◽  
Farm Size ◽  
Significance Level ◽  
Organic Rice ◽  
Certified Organic ◽  
Constant Returns To Scale

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.

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
Keyword(s):  
Technical Efficiency ◽  
Rice Production

Paddy in saline water: Analysing variety-specific effects of saline water intrusion on the technical efficiency of rice production in Vietnam

2019 ◽  
Vol 48 (3) ◽  
pp. 237-245 ◽  
Author(s):  
Thi Huyen Trang Dam ◽  
TS Amjath-Babu ◽  
Peter Zander ◽  
Klaus Müller
Keyword(s):  
Technical Efficiency ◽  
Soil Salinity ◽  
Saline Water ◽  
Rice Variety ◽  
Stochastic Frontier ◽  
Rice Production ◽  
Adaptation Measures ◽  
Saline Water Intrusion ◽  
Water Intrusion ◽  
The Impact

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.

Sign in / Sign up

Export Citation Format

Share Document