scholarly journals Hungarian dairy and beef production sector technical efficiency comparsion using DEA

2017 ◽  
Vol 11 (3-4) ◽  
pp. 131-138 ◽  
Author(s):  
Krisztián Kovács ◽  
Ratnesh Pandey
Keyword(s):  
Technical Efficiency ◽  
Production Efficiency ◽  
Dairy Farms ◽  
Farm Size ◽  
Medium Size ◽  
Small Farms ◽  
Beef Production ◽  
Dea Model ◽  
The World ◽  
Beef Sector

To examine and compare the technical efficiency of dairy sector and the beef sector, this research introduced the main indicators of milk and beef production in the world, EU and Hungarian aggregates. Based on the data it can be said that the milk and beef production of Hungary does not occupy any significant position in the world as well as in the European Union neither today nor even in the past. If Hungry must compete in the European counties and international market, their dairy sector must focus to increase of their production efficiency as the key breakthrough point. This paper we compared technical efficiency of both dairy and beef sectors in total, for the year 2014 and 2015 separately and based on the farm size. The specific objectives of the research are: comparing dairy and beef farms efficiency in Hungary. Based on the results, we can determine which sector in Hungary is more effective. The second objective is to compare the efficiencies of both the sectors in 2014 and 2015 separately and from the results we can determine which year was more effective in terms of production efficiency and the third objective of the research is technical efficiency comparison of certain economic sizes for both sectors. In the research, we used (KOVACS, 2009) deterministic (DEA) model adapted to the Hungarian dairy farms and beef farms. For the dairy farms milk and dairy products as well as meat (other income). The input factors originated from the domestic AKI - FADN database. Summarizing the results of the research it can be conclude that the dairy sector is more effective than the beef sector in Hungary. In terms of years compared 2014 was more effective for both sector as compared with 2015. In regards to the farm size almost the same result in evaluating the scale of efficiency, which means that large economies can in most cases, manage resources more efficiently than small farms. In the examined years, based on the results of the DEA model, the VRS technical efficiency of the test for these two years was 72.90% for the dairy farms and 63.60% for the beef farms, which means that the dairy sector is more efficient than the beef sector in Hungary. The VRS technical efficiency of the research was 82.10% in 2014 and 75.10% in 2015 for the dairy farms and 77.50% in 2014 and 68.90% in 2015 for the beef farms, which means that both the dairy sector and the beef sectors followed the same trend and were more efficient in 2014 compared to the efficiency in 2015. The large size dairy farms were most effective in Hungary in the examined period (90.90%). VRS technical efficiency for small farms is 88% and the total number of small, the technical efficiency medium farms was 72.80% For the beef sector VRS technical efficiency for small farms is 71.30% and the technical efficiency medium farms was 74.40% and 70% of the beef meat producing farms in Hungary are medium sized. So, the conclusion is the small size dairy farms have a higher VRS efficiency than the small size beef farms whereas medium sized beef farms had higher VRS efficiency than the medium size dairy farms. As a conclusion, both dairy and beef sectors in Hungary have the potential to overcome technology and knowledge constraints and attain the upmost attainable productivity level through improvements in; farmer volume of production i.e. output, beef cattle technologies, and advertising, and the efficiency of the technology transfer process. JEL Code: Q13

scholarly journals Economics of Horticulture Crops in Jammu and Kashmir: A Case Study of apple fruit

2019 ◽  
Vol 15 (1) ◽  
pp. 3-11
Author(s):  
Vishakha Shreesh Kutumbale ◽  
Jawad Ul Haque Eytoo
Keyword(s):  
Technical Efficiency ◽  
Production Function ◽  
Production Efficiency ◽  
Cost Benefit Analysis ◽  
Increasing Returns ◽  
Farm Size ◽  
Medium Size ◽  
Apple Orchards ◽  
Jammu And Kashmir ◽  
Operational Conditions

Horticultural sector has assumed ever-increasing importance in Jammu and Kashmir economy. In this regard, the present study was carried out to evaluate the cost and benefits received by the different groups of farmers in the Kulgam and Shopian district of Kashmir valley. For this purpose, data from 180 apple growers was collected through a structured questionnaire. Cost-Benefit Analysis (CBA) and Cobb-Douglas production function was run to obtain results. The finding indicated that the average profit received by the producer Rs. 350,695.48 on the apple cultivation while in case of different farmers, medium and large size farm owners were major beneficiaries.  Furthermore, the findings indicate that in case of medium size and large farm owners, law of increasing returns to scale was operating while in case of small growers law of decreasing returns was operational. The findings indicate that farm size is key factor in the production efficiency of apple orchards. The significance of the study is that it will help to understand technical efficiency and operational conditions prevalent in the apple orchards. Keywords: ever-increasing, production function, increasing returns, decreasing returns, production efficiency, technical efficiency, operational condition.

scholarly journals Technical Efficiency Assessment of Dairy Farm in the South-west Region of Bangladesh

2020 ◽  
pp. 21-28
Author(s):  
Fariha Farjana ◽  
Afia Khatun
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier ◽  
Percent Level ◽  
Dairy Farms ◽  
Farm Size ◽  
The South ◽  
Average Output ◽  
West Region ◽  
South West ◽  
South West Region

The paper concentrates on the measurement of the total factor productivity of dairy farms in the south-west region of Bangladesh. The study used stochastic frontier approach for analyzing the technical efficiency of the dairy farms. Here, seventy dairy farms are considered as a sample. The data reveals that the number of labor and the quantity of food are statistically significant at a 1 percent level of significance.The data also manifests that numerous farm-specific characteristics, i.e. farm size, farmer’s age, and amount of credit are statistically significant at 1 percent, 10 percent, and 10 percent respectively. The range of technical efficiency for the farms varies from 26 percent (minimum) to 95 percent (maximum) where the mean value is 68 percent for the dairy farms of the south-west region. This implies that an average output of milk production falls 32 percent short of maximum possible level. Hence, there is scope of improvement in this sector. Therefore, to improve the farm productivity government should provide proper training, and medical treatment facilities for the farms so that the animals become healthy. If it is possible to do so then the farm level production frontier will shift upward.

Systematic review and meta-regression analysis of technical efficiency in dairy farms

2016 ◽  
Vol 65 (3) ◽  
pp. 279-301 ◽  
Author(s):  
Taciana Mareth ◽  
Antonio Marcio Tavares Thomé ◽  
Fernando Luiz Cyrino Oliveira ◽  
Luiz Felipe Scavarda
Keyword(s):  
Systematic Review ◽  
Regression Analysis ◽  
Technical Efficiency ◽  
Geographical Location ◽  
Dairy Farms ◽  
Two Dimensions ◽  
Farm Size ◽  
Content Type ◽  
Meta Regression ◽  
Meta Regression Analysis

Purpose – The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE). Design/methodology/approach – The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed. Findings – The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers. Originality/value – This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement.

EFFICIENCY AND PRODUCTIVITY CHANGE IN FIELD CROP AND MILK FARMS IN LUBLIN PROVINCE IN 2014-2016

2018 ◽  
Vol XX (1) ◽  
pp. 137-142
Author(s):  
Alina Syp ◽  
Dariusz Osuch
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Dairy Farms ◽  
Productivity Change ◽  
Data Envelopment ◽  
Field Crop ◽  
Dea Model ◽  
Malmquist Indices ◽  
Efficiency And Productivity ◽  
Efficiency Indicators

The aim of the study was assessment of efficiency and productivity of farms in the Lublin province in the years 2014-2016. The analysis was based on the Data Envelopment Analysis (DEA) model oriented on inputs and Malmquist indices with its components. The calculations were made for medium-sized field and dairy farms that continuously collected data for the FADN system during the period under consideration. In our research all efficiency indicators for dairy farms were larger than for field crop farms. In the years 2014-2016, the average technical efficiency of dairy farms was 0.752, which means that in those farms it is possible to reduce inputs on average by 25% and the value of production will remain at the same level. In the case of field crop farms, inputs should be limited by 33%. The applied decomposition of calculated Malmquist indices allowed to define what factors influenced changes in productivity.

scholarly journals The Technical Efficiency of Specialised Milk Farms: A Regional View

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Jindřich Špička ◽  
Luboš Smutka
Keyword(s):  
Production Efficiency ◽  
Returns To Scale ◽  
Value Added ◽  
Dairy Farms ◽  
Herd Size ◽  
Dairy Farming ◽  
Farm Size ◽  
Scale Efficiency ◽  
Economic Determinants ◽  
Net Value Added

The aim of the article is to evaluate production efficiency and its determinants of specialised dairy farming among the EU regions. In the most of European regions, there is a relatively high significance of small specialised farms including dairy farms. The DEAVRS method (data envelopment analysis with variable returns to scale) reveals efficient and inefficient regions including the scale efficiency. In the next step, the two-samplet-test determines differences of economic and structural indicators between efficient and inefficient regions. The research reveals that substitution of labour by capital/contract work explains the variability of the farm net value added per AWU (annual work unit) income indicator by more than 30%. The significant economic determinants of production efficiency in specialised dairy farming are farm size, herd size, crop output per hectare, productivity of energy, and capital (atα=0.01). Specialised dairy farms in efficient regions have significantly higher farm net value added per AWU than inefficient regions. Agricultural enterprises in inefficient regions have a more extensive structure and produce more noncommodity output (public goods). Specialised dairy farms in efficient regions have a slightly higher milk yield, specific livestock costs of feed, bedding, and veterinary services per livestock unit.

The Effectiveness of Environmental Regulation on Manufacturing Productivity in Jiangsu Province

2012 ◽  
Vol 472-475 ◽  
pp. 3286-3291
Author(s):  
Dan Yun Shen ◽  
Hui Ming Zhang
Keyword(s):  
Technical Efficiency ◽  
Environmental Regulation ◽  
Manufacturing Industry ◽  
Production Efficiency ◽  
Positive Impact ◽  
Jiangsu Province ◽  
Efficiency Frontier ◽  
Dea Model ◽  
Manufacturing Productivity ◽  
Environment Regulation

The impacts of environment regulation on production efficiency of manufacturing industry in Jiangsu province are analyzed based on DEA model. Results indicate that environment regulation has a positive impact for the whole manufacturing industry, but complex effects among the different cities. Nanjing, Lian Yungang and Taizhou enter the efficiency frontier when regulation is implemented; while the manufacturing industry of Huai’an and Zhenjiang drop in the technical efficiency. Finally this paper offers relative suggestions.

scholarly journals Irrigation, Technical Efficiency, and Farm Size: The Case of Brazil

2021 ◽  
Vol 13 (3) ◽  
pp. 1132
Author(s):  
Gabriel A. Sampaio Morais ◽  
Felipe F. Silva ◽  
Carlos Otávio de Freitas ◽  
Marcelo José Braga
Keyword(s):  
Technical Efficiency ◽  
Rural Areas ◽  
Agricultural Sector ◽  
Farm Size ◽  
Small Farms ◽  
Stochastic Production Frontier ◽  
Farm Productivity ◽  
Agricultural Census ◽  
Large Farms ◽  
On Farm

In developing countries, irrigation can help to decrease poverty in rural areas through increased employment in the agricultural sector. Evidence shows that irrigation may increase farm productivity and technical efficiency. In this paper, we estimate the effect of irrigation on farm technical efficiency in Brazil using the 2006 Agricultural Census dataset on more than 4 million farms. We estimate a stochastic production frontier at farm level, considering potential selection bias in irrigation adoption. We find that farms using irrigation are on average 2.51% more technically efficient compared to rain-fed farms. Our findings also suggest that while small farms are more efficient than medium and large farms, the largest difference in technical efficiency between rain-fed and irrigated farms is among large farms. Our results indicate that policies that seek to support expansion of irrigation adoption has also the potential to achieve greater rural development given the estimated effects estimated in this paper among very small and small farms, which are more than 70% of the farms in Brazil.

scholarly journals Research on corn production efficiency and influencing factors of typical farms: Based on data from 12 corn-producing countries from 2012 to 2019

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254423
Author(s):  
Jiamei Wang ◽  
Xiangdong Hu
Keyword(s):  
Technical Efficiency ◽  
Production Efficiency ◽  
Conservation Tillage ◽  
Data Envelopment ◽  
Corn Production ◽  
Influencing Mechanism ◽  
The World ◽  
Average Loss ◽  
High Production ◽  
The Impact

Globally, corn is characterised by high production and high export concentrations, yet the world is experiencing an unprecedented, huge change in this regard. Ensuring the global supply of corn, and thereby the energy and food security of nations has become particularly important. To understand the importance of corn production as an influencing mechanism of global food supplies, the present study researched the corn production of typical farms in major corn-producing and importing countries around the world. I selected the corn input and output data of 18 typical farms in 12 countries from 2012 to 2019, used the data envelopment analysis (DEA) model to calculate the technical efficiency of corn production, and built a tobit model to explore the impact of farming methods, input elements, supporting services, and other factors on efficiency. The study established that the average comprehensive technical efficiency of corn production on a typical farm was 0.863, and the average loss was 13.7%. In addition, it concluded that intensive tillage and conservation tillage have high technical efficiency. It also demonstrated that the proportion of mechanical labour and technical efficiency is in a ‘U’-shaped relationship, among others.

scholarly journals Measurement and Determinants of Technical Efficiency in Crop Production: A Review

2021 ◽  
Author(s):  
Isha Sharma ◽  
M.K. Sekhon
Keyword(s):  
Technical Efficiency ◽  
Agricultural Production ◽  
Crop Production ◽  
Efficiency Analysis ◽  
Farm Size ◽  
Agricultural Product ◽  
Agricultural Crops ◽  
Access To Credit ◽  
The World ◽  
Farmer Education

Output is determined by the efficiency with which available technologies are used i.e. with the improvement in technical efficiency. There are extensive numbers of studies focusing on efficiency as a means of fostering agriculture production. The article reviews the literature devoted to technical efficiency analysis in various countries and its applications to agricultural production. The studies reviewed focused particularly on rice and wheat making them the most studied agricultural product by researchers. The review of efficiency analysis shows that agricultural output can be increased without additional inputs with given existing technology. Technical efficiency of agricultural crops like wheat, paddy, cotton etc grown in different countries of the world like India, Pakistan, Ethopia, Srilanka were reviewed and it was found that except for farm size, the variables like farmer education and experience, contacts with extension personnel and access to credit, tend to have a positive and statistically significant impact on technical efficiency.

Assessing Production Efficiency by Farm Size in Rwanda: A Zero-inefficiency Stochastic Frontier Approach

2020 ◽  
Author(s):  
Jules Ngango ◽  
Seungjee Hong
Keyword(s):  
Technical Efficiency ◽  
Production Efficiency ◽  
Stochastic Frontier ◽  
Sub Saharan Africa ◽  
Farm Size ◽  
Farm Income ◽  
Maize Production ◽  
Positive Effects ◽  
Study Results ◽  
The Relationship

Abstract This study investigates the relationship between farm size and technical efficiency for maize production in Rwanda. Since levels of technical efficiency tend to vary considerably across farms in sub-Saharan Africa, with a mixture of both inefficient and fully efficient farms, the use of the conventional stochastic frontier method is not appropriate. In this paper, we apply a zero-inefficiency stochastic frontier method that manages both efficiency and inefficiency in the studied sample. The average technical efficiency of maize farms for the full sample is estimated at 0.64, demonstrating that maize output can be improved by approximately 36% without increasing the proportion of farm inputs used. Regarding the relationship between farm size and technical efficiency, the study results show a positive relationship between farm size and technical efficiency for maize production in Rwanda. Thus, the enforcement of land reforms such as land consolidation and enhanced aggregate productivity growth are needed. The results also indicate that education, cooperative membership, extension services, access to credit, off-farm income, land tenure, and livestock ownership have significant and positive effects on technical efficiency.

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