Factors Influencing Productivity and Technical Efficiency of Rice Farmers in Isabela, Philippines

2017 ◽  
Vol 4 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Diosdado C. Cañete ◽  
◽  
Biley E. Temanel
Keyword(s):  
Technical Efficiency ◽  
Rice Farmers ◽  
Factors Influencing

Effects of Irrigation Modes on Technical Efficiency of Rice Farmers in Mali

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Diakalidia Kouyate ◽  
Kimseyinga Savadogo ◽  
Franck Cachia
Keyword(s):  
Technical Efficiency ◽  
Rice Farmers

scholarly journals Investigation of Factors Influencing the Technical Efficiency of Agricultural Producers Participating in Farm Credit Programs: The Case of Greece

2003 ◽  
Vol 35 (3) ◽  
pp. 529-541 ◽  
Author(s):  
Anthony N. Rezitis ◽  
Kostas Tsiboukas ◽  
Stauros Tsoukalas
Keyword(s):  
Technical Efficiency ◽  
Family Income ◽  
Stochastic Frontier ◽  
Agricultural Producers ◽  
Credit Program ◽  
Factors Influencing ◽  
Efficiency Measures ◽  
Farm Credit ◽  
Negative Effect ◽  
Hired Labor

This study investigates a number of factors influencing technical efficiency of Greek farms participating in the 1994 European Union (EU) farm credit program. Technical efficiency measures are obtained within the framework of a parametric stochastic frontier. Factors showing a positive effect on technical efficiency are value of liabilities, number of hours of mechanical operation, large land size, and rental land, whereas those showing a negative effect are value of EU product subsidies, value of off-farm family income, and hired labor. The value of investments incurred by farms because of their participation in the 1994 farm credit program does not show any significant effect on technical efficiency. The predicted levels of technical efficiency indicate that the average technical efficiency of farms 3 years after participating in the 1994 farm credit program is lower than the average technical efficiency of the same farms the year before participating in the program. Thus, the program has failed to increase the efficiency of farms.

scholarly journals DETERMINANTS OF AGRICULTURAL LOAN DECISION MAKING PROCESS FOR RICE (ORYZA SATIVA) FARMERS IN ABUJA, NIGERIA. APPLICATIONS OF HECKMAN TWO-STAGE MODEL AND FACTOR ANALYSIS

2021 ◽  
Vol 59 (1) ◽  
Author(s):  
Olugbenga Omotayo Alabi ◽  
Ayoola Olugbenga Oladele ◽  
Mohammed Bello Usman
Keyword(s):  
Rice Production ◽  
Farm Size ◽  
Farm Income ◽  
Decision Making Process ◽  
Stage Model ◽  
Gross Margin ◽  
Two Stage ◽  
Rice Farmers ◽  
Factors Influencing ◽  
Socio Economic Factors

This study focuses on determinants of the agricultural loan decision-making process of rice (Oryza sativa) farmers in Abuja, Nigeria, using the Heckman two-stage model and factor analysis. This study was designed specifically to achieve the following objectives: determine the socio-economic profiles or characteristics of rice farmers, analyze the costs and returns of rice production, evaluate factors influencing rice farmers’ decision to obtain an agricultural loan, evaluate socio-economic factors influencing the amount of the agricultural loan, and determine the constraints or problems facing rice farmers. A multi-stage sampling design was employed. A total sample of one hundred (100) rice farmers was included, and primary data were utilized. Data were obtained through the use of a well-structured and well-designed questionnaire. Statistical and econometric tools used in analyzing data included descriptive statistics, gross margin analysis, financial analysis, the Heckman two-stage model, and principal component analysis. The results show that 63% of rice farmers were between the age of 31–50 years. The mean age was 41.90 years. About 65% of rice farmers were male, and 54% of them were married. Also, 93% of rice farmers had formal education and were literate. The household sizes were large, with an average of six persons per household. An average of 71,550 nairas was the loan amount granted to rice farmers by financial institutions. The average farm size amounted to 1.49 hectares. Factors influencing the decision of rice farmers to obtain agricultural loan included age (P < 0.01), marital status (P < 0.05), household size (P < 0.10), educational level (P < 0.05), farm size (P < 0.05), farm and non-farm income (P < 0.10), farm experience (P < 0.05), collateral property (P < 0.05), extension services (P < 0.10), and awareness of loan or credit facilities (P < 0.05). Rice production was profitable with a net farm income of 744,300 nairas. The gross margin ratio of 0.95 means that 95 kobos covered profits, taxes, expenses, interest, and depreciation for every naira invested in rice production activities. Socio-economic factors statistically and significantly influencing the amount of agricultural loan obtained by rice farmers included (P < 0.05) sex (P < 0.01), household size (P < 0.05) and educational level (P < 0.01). The constraints facing rice farmers in obtaining the agricultural loan and production activities included lack of collateral property, lack of fertilizer input, poor-quality feeder roads, lack of credit facilities, inadequate labor input, and complicated and costly administrative procedures to obtain a loan. It is recommended that agricultural loans be made available to rice farmers in sufficient amounts and at low-interest rates. Also, farm inputs, fertilizer inputs, improved seeds, and chemicals should be made available to rice farmers

scholarly journals Adoption of Improved Soybean Varieties and Differences in Technical Efficiency Between Improved and Local Soybean Varieties in Southern Shan State, Myanmar

2020 ◽  
Vol 12 (8) ◽  
pp. 55
Author(s):  
Ei Thazin Soe ◽  
Yoshifumi Takahashi ◽  
Mitsuyasu Yabe
Keyword(s):  
Technical Efficiency ◽  
Production Efficiency ◽  
Market Access ◽  
Study Data ◽  
Stochastic Production Frontier ◽  
Soybean Production ◽  
Government Organizations ◽  
Factors Influencing ◽  
Multi Stage ◽  
And Training

This study determined the factors influencing the adoption of improved soybean varieties and examined the technical efficiencies of improved and local soybean varieties production in Southern Shan State, Myanmar. For this study, data from a sample of 337 respondents were collected by employing a multi-stage random sampling method. Logit model was adopted to determine the factors influencing the adoption of improved soybean varieties. Additionally, a stochastic production frontier was used to examine technical efficiencies of improved and local soybean varieties. Results show that factors that positively and significantly influence the adoption of improved soybean varieties are education, market access, extension access and training access. Examination of technical efficiency reveals that labor, fertilizer, machinery, and use of pesticide and harvester are inputs that significantly contribute to improving production efficiency among the improved variety farmers while seeds, labor, and fertilizer are significant inputs of local soybean production. On average, the estimated yield of the improved soybean varieties is 1.51 t/ha, which is higher than the yield of local soybean varieties grown at 0.88 t/ha. It was also revealed that improved soybean varieties had a relatively higher level of mean technical efficiency (85.04%) than local varieties (70.13%) and significantly different at 1% level. The results show that improved soybean production is more efficient than local soybean production. Therefore, government and non-government organizations should improve and provide market access, efficient and effective extension services and training to encourage farmers to adopt improved soybean varieties.

scholarly journals Agricultural basic industry subjects productivity development examination in the region Trnava (SR) by adopting the Malmquist indexes

2010 ◽  
Vol 56 (No. 3) ◽  
pp. 108-115
Author(s):  
P. Bielik ◽  
D. Hupková ◽  
M. Vadovič ◽  
V. Benda
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Future Trend ◽  
Factor Productivity ◽  
Technological Changes ◽  
Efficiency Change ◽  
Basic Industry ◽  
Factors Influencing ◽  
Two Factors ◽  
Malmquist Indexes

Analysis of the productivity and efficiency development could be used to asses the trend and factors influencing this process. The main goal of this paper is estimation of the Total Factor Productivity (TFP) development of agricultural farms in the Trnava region in the period 2002–2006. Results of this analysis could be used to detect the trend in the TFP development. The results of the analysis confirmed there is no evident trend in the average TFP indicators. This could be explained by the variation of technical efficiency change and technological changes during this period. These two factors represent the components of the TFP indicator. According to the present development of the TFP indicator, it is not possible to unambiguously forecast the future trend.

Factors Influencing the Adoption of Climate-Smart Agricultural Technologies Among Rice Farmers in Northern Ghana

2020 ◽  
Vol 4 (1) ◽  
pp. 257-271 ◽  
Author(s):  
Abraham Zakaria ◽  
Suhiyini I. Alhassan ◽  
John K. M. Kuwornu ◽  
Shaibu B. Azumah ◽  
Mercy A. A. Derkyi
Keyword(s):  
Northern Ghana ◽  
Agricultural Technologies ◽  
Rice Farmers ◽  
Factors Influencing

scholarly journals Efisiensi Teknis Usaha Tani Padi di Provinsi Kepulauan Bangka Belitung

2019 ◽  
Vol 17 (2) ◽  
pp. 139
Author(s):  
Fitri Kartiasih ◽  
Adi Setiawan
Keyword(s):  
Technical Efficiency ◽  
Rice Seed ◽  
Rice Farming ◽  
Stochastic Production Frontier ◽  
Production Frontier ◽  
Land Preparation ◽  
Rice Productivity ◽  
Rice Farmers ◽  
Stochastic Production ◽  
Preparation Equipment

<p>Rice productivity in Indonesia varied greatly between provinces. Rice productivity in the Bangka Belitung Islands was the lowest figure compared to other provinces in Indonesia from 2013 to 2015. The purpose of this study was to provide an overview of rice farming, analyze the technical efficiency and its influencing factors of rice farming, and analyze the income level of rice farming in the Province of Bangka Belitung Islands. The data used in this study were raw data of the 2014 Household Survey of Rice Crop Farming (SPD 2014) conducted by Statistics Indonesia. The analytical method used was the Stochastic Production Frontier. The results showed that the factors influencing rice production were seeds, fertilizers, pesticides and the use of hired labours. The average level of technical efficiency of rice farmers was 20% of maximum production. This shows that rice farming was not yet efficient. Factors that negatively affect the technical efficiency of rice farming were those among other age of the farmer, land preparation equipment, ownership status of land preparation equipment and the planting system. The results of the study also showed that the more efficient the rice farming, the greater the farmers' income. To increase productivity through increasing technical efficiency, it is recommended that rice farmers are facilitated or supported to use a better quality of rice seed.</p><p> </p><p>Abstrak</p><p>Produktivitas padi di Indonesia sangat bervariasi antar provinsi, di mana produktivitas padi di Kepulauan Bangka Belitung menunjukkan angka terendah dibandingkan provinsi lain di Indonesia selama tahun 2013 hingga 2015. Tujuan penelitian ini antara lain untuk memberikan gambaran usaha tani padi di Provinsi Kepulauan Bangka Belitung, menganalisis efisiensi teknis usaha tani padi serta faktor-faktor yang memengaruhinya, dan menganalisis tingkat pendapatan usaha tani padi. Data yang digunakan dalam penelitian ini adalah <em>raw </em>data hasil Survei Rumah Tangga Usaha Tanaman Padi 2014 (SPD 2014). Metode analisis yang digunakan adalah <em>Stochastic Production Frontier. </em>Berdasarkan hasil penelitian menunjukkan bahwa faktor-faktor yang memengaruhi produksi padi di Kepulauan Bangka Belitung adalah penggunaan benih, pupuk, pestisida dan penggunaan pekerja dibayar. Rata-rata tingkat efisiensi teknis petani padi di Kepulauan Bangka Belitung adalah 20% dari produksi maksimum. Hal ini menunjukkan bahwa usaha tani padi belum efisien. Faktor-faktor yang berpengaruh negatif terhadap infesiensi teknis usaha tani padi adalah faktor umur petani, alat pengolahan lahan, status alat pengolahan lahan dan sistem tanam. Hasil penelitian juga menunjukkan bahwa semakin efisien usaha tani padi maka pendapatan petani juga semakin besar. Untuk meningkatkan produktivitas dengan cara meningkatkan efisiensi teknis, disarankan petani padi difasilitasi atau didorong untuk menggunakan benih yang berkualitas.</p>

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