scholarly journals Structural efficiency in Lithuanian family farms

2015 ◽  
Vol 37 (4) ◽  
pp. 462-479
Author(s):  
Tomas Baležentis
Keyword(s):  
Returns To Scale ◽  
Scale Efficiency ◽  
Family Farms ◽  
Technical Inefficiency ◽  
Structural Efficiency ◽  
Scale Size ◽  
Level Data ◽  
Farm Accountancy Data Network ◽  
Most Productive Scale Size ◽  
Research Period

Along with firm-specific technical inefficiency, sector-specific structural inefficiency might induce losses in productivity. This paper therefore aims to identify the trends in structural efficiency in Lithuanian family farms. Specifically, the four farming types are considered, namely cereal farming, field cropping, dairying, and mixed farming. Farm-level data from Farm Accountancy Data Network are used for the analysis. The research period spans over the years 2004–2011. The trends in technical and scale efficiency are presented. Furthermore, the prevailing returns to scale are discussed thus offering insights into the most productive scale size and deviations from it in Lithuanian family farms. Finally, the dynamics in structural efficiency are discussed. The results indicate that the aggregate output of certain farming types could be augmented by some 20–25% due to reallocation of inputs among farms. Anyway, technical inefficiency remains the major driver of structural inefficiency.

scholarly journals Dynamic efficiency in Lithuanian cereal farms

2016 ◽  
Vol 38 (2) ◽  
pp. 114-127 ◽  
Author(s):  
Tomas Baležentis
Keyword(s):  
Technical Efficiency ◽  
Structural Changes ◽  
Returns To Scale ◽  
Adjustment Cost ◽  
Scale Efficiency ◽  
Dynamic Efficiency ◽  
Family Farms ◽  
Technical Inefficiency ◽  
Efficiency Measures ◽  
Multi Temporal

Lithuanian family farms are subject to both production and investment support under the Common Agricultural Policy. As a result, there have been structural changes in the sector. Therefore, it is important to analyse farm performance from an adjustment cost perspective. The dynamic efficiency measures encompass multi-temporal cost minimisation. This paper addresses the following problem: what are the key trends in dynamic efficiency and what are the implications thereof on further development of cereal farming in Lithuania? The present paper aims to identify the prospective paths for development of Lithuanian cereal farms by analysing their dynamic efficiency. Data Envelopment Analysis is applied to calculate technical efficiency scores under different assumptions regarding returns to scale. The results indicate pure technical inefficiency remained as the main source of the overall technical inefficiency with scale inefficiency increasing throughout 2004–2014. A more detailed analysis showed that it was smaller farms that suffered from losses in the pure technical efficiency to the highest extent. The exit of the smaller cereal and oilseed farms, therefore, has likely contributed to the decreasing technical inefficiency, yet it has dampened scale efficiency.

scholarly journals Productivity change in Lithuanian family farms with the sequential technology

2014 ◽  
Vol 36 (2) ◽  
pp. 207-222
Author(s):  
Tomas Baležentis
Keyword(s):  
Returns To Scale ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Family Farms ◽  
Efficiency Change ◽  
Tfp Growth ◽  
Farm Accountancy Data Network ◽  
Variable Returns To Scale ◽  
Decision Making Units

The sequential Malmquist-Luenberger productivity index was employed to assess the sources of changes in the total factor productivity in Lithuanian family farms. The research sample encompasses 200 family farms reporting to the Farm Accountancy data Network. The sequential Malmquist-Luenberger index was decomposed by taking into account scale efficiency change and variable returns to scale technology. The obtained efficiency scores suggest that years 2006 and 2009 were those of the most inefficient farming activity. Analysis of the scale efficiency scores suggested that the mixed farming should expand its operation scale in order to maintain the economic viability and competitiveness. The sequential Malmquist-Luenberger productivity index suggested that the TFP had decreased by some 2.9% throughout 2004–2009. The technical change component stagnated in 2009, yet remained the most important factor of TFP growth accounting for increase of some 14% during 2004–2009. The decreasing pure technical efficiency, however, reduced the TFP by 16%. The scale efficiency change did not play an important role. Innovative decision making units – family farms – were identified in terms of distance function and productivity index values.

scholarly journals DEA Window Analysis Efficiency Measurement of Selected Nigerian Bank

2021 ◽  
Vol 4 (1) ◽  
pp. 176-184
Author(s):  
IJ DIKE
Keyword(s):  
Returns To Scale ◽  
Balance Sheet ◽  
Scale Model ◽  
Scale Efficiency ◽  
Average Efficiency ◽  
Window Analysis ◽  
Scale Size ◽  
Constant Returns To Scale ◽  
Dea Window Analysis ◽  
Variable Returns To Scale

This study analyzes the performance efficiency of six selected banks in Nigeria for the period 2010 – 2016. DEA window analysis was employed to establish the performance efficiency of the selected banks. The analysis is based on panel data for the period under review. The result of the DEA window analysis for the reviewed period showed that the average efficiency scores under constant returns to scale ranged from 84% to 91%. Under the variable returns to scale, the average efficiency scores ranged from 91% to 95%. The average inefficiency of the selected Nigeria commercial banks under the constant returns to scale model was in the range 9 – 16%. This inefficiency could be attributed to the excess of customers deposits on the balance sheet of the selected banks. The average scale efficiency for the banks was 93%. Guaranty Trust Bank was the most efficient bank on all measures. United Bank for Africa was the most inefficient bank under constant returns to scale and variable returns to scale. It was however, more scale efficient than three other banks, an indication that its inefficiency cannot be attributed to inappropriate scale size.

scholarly journals DECOMPOSITION OF SBM TECHNICAL EFFICIENCY OF THE SECONDARY EDUCATION SYSTEM INTO RADIAL EFFICIENCY AND MIX EFFICIENCY: A STATE-WISE ANALYSIS IN INDIA

2015 ◽  
Vol 7 (2) ◽  
pp. 1304-1315
Author(s):  
Rangalal Mohapatra
Keyword(s):  
Technical Efficiency ◽  
Education System ◽  
Important Implication ◽  
Scale Efficiency ◽  
Male And Female ◽  
Female Teachers ◽  
Scale Size ◽  
The Mean ◽  
Most Productive Scale Size ◽  
Girl Students

This paper is an attempt to decompose the non-radial technical efficiency in terms of a scalar called SBM of efficiency (input Oriented) of the performances of 23 states of India in the 10th class examination. Applying CCR, BCC and SBM models for five inputs and two outputs obtained from the Statistics of school education, 2010-11 (MHRD, Govt. of India), the efficiency scores were computed and the SBM efficiency scores were decomposed into technical efficiency, pure technical efficiency, scale efficiency and mix efficiency. The mean TE scores are 0.86 with a SD of 0.17 and mean PTE score of 0.92 with SD of 0.09. Out of 23 states 10 states achieved MPSS status and 13 states were in efficient. As per the SBM score, out of 23 states 10 states  fully SBM efficient with score equals to 1 and hence they are TE, PTE and Scale efficient implying most productive scale size. But more than half of the states (13) are inefficient with Assam being the lowest performer (0.18) followed by Kerala (0.22), Rajasthan (0.25) and Chhattisgarh (0.31). The states with low SBM score due to PTE and MIX are Assam, Karnataka, Maharastra, Odisha, Rajasthan and UP. The states having low score due to low PTE and low SE are Assam and Karnataka. The states with low SBM score due to low PTE, MIX and SE are Assam and Karnataka. The study emphasizes, merger of small private schools, increase in the appointment of both trained male and female teachers, Creation of more class rooms. One important implication of the result is that the state should focus more on the giving special coaching to the SC/ST students and the girl students especially in English, math and science. 

scholarly journals The use of the farm accountancy data network for estimation of the optimal family farm size according to the microeconomic theory

2014 ◽  
pp. 101-112
Author(s):  
Tomas Baležentis ◽  
Romualdas Valkauskas
Keyword(s):  
Agricultural Policy ◽  
Agricultural Sector ◽  
Public Support ◽  
Farm Size ◽  
Scale Efficiency ◽  
Microeconomic Theory ◽  
Family Farms ◽  
Farm Accountancy Data Network ◽  
Current Maximum ◽  
Factor Markets

Benchmarking of the economic subjects—viz. enterprises, organizations, regions—usually involves assessment of the efficiency. Suchlike analyses are not only important in the private sector, but also in the public one for public agencies are usually funded by public funds and thus need to be effective. Indeed, the private (business) subjects are sometimes also operating under the environment requiring appropriate regulation based on benchmarking. This is the case for the agricultural sector which receives voluminous public support as direct payments and rural development measures. On the other hand, the efficiency of agricultural sector impacts the prices of agricultural products as well as factor markets. Therefore, it is important to measure the efficiency of agricultural sector as an outcome of the effectiveness of the agricultural policy. The scale efficiency constitutes one of the components of the gross technical efficiency. The latter measure is related to the farm size and farm structure in general. Furthermore, the optimal farm size is a key issue for the agricultural policy and thus is often influenced by the legal regulations. This paper aims at identifying the optimal scale size for Lithuanian family farms. The paper discusses the neoclassical methodology for analysis of the scale efficiency. The results indicate that the optimal farm size depends on the farming type. Nevertheless, the current maximum limit of land area (i. e. 500 ha) has not been exceeded by any farming type.

scholarly journals Decomposition of the technical efficiency of the banking system

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Sanderson Abel ◽  
Alex Bara ◽  
Pierre Le Roux
Keyword(s):  
Technical Efficiency ◽  
Commercial Banks ◽  
Returns To Scale ◽  
Banking System ◽  
Efficiency Score ◽  
Foreign Banks ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Analysis Method ◽  
Technical Inefficiency

The study investigated the technical efficiency of the commercial banks in Zimbabwe during the period 2009–2015. The study entailed the decomposition of the technical efficiency into pure technical and scale efficiency to understand the sources of the technical inefficiency in the commercial banks in Zimbabwe. To accomplish the task, the study sampled 11 commercial banks of which 6 are domestic and the other 5 are foreign banks. The study used the data envelopment analysis method. The results of the study revealed that commercial banks in Zimbabwe are technically inefficient with an efficiency score of 82.9%. The average pure technical and scale efficiency scores were 96.6% and 85.6%, respectively. The results imply that technical inefficiency of the Zimbabwean commercial banks is mainly a result of scale inefficiency emanating from decreasing returns to scale. The deduction is that commercial banks in Zimbabwe are operating at below their optimum capacity and hence have scope to increase their operations in order to improve on technical efficiency.

Returns to scale and most productive scale size in DEA with negative data

2016 ◽  
Vol 255 (2) ◽  
pp. 545-558 ◽  
Author(s):  
Biresh K Sahoo ◽  
Mohammad Khoveyni ◽  
Robabeh Eslami ◽  
Pradipta Chaudhury
Keyword(s):  
Returns To Scale ◽  
Negative Data ◽  
Scale Size ◽  
Most Productive Scale Size

scholarly journals Does Farm Size and Specialization Matter for Productive Efficiency? Results from Kansas

2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Production Technology ◽  
Returns To Scale ◽  
Productive Efficiency ◽  
Farm Size ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Sample Period ◽  
Analysis Techniques

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.

scholarly journals Efficiency of Estonian grain farms in 2000 2004

2008 ◽  
Vol 17 (1) ◽  
pp. 31 ◽  
Author(s):  
N. VASILIEV ◽  
A. ASTOVER ◽  
M. MÕTTE
Keyword(s):  
Parametric Method ◽  
Returns To Scale ◽  
Scale Efficiency ◽  
Small Scale ◽  
Data Envelopment ◽  
The European Union ◽  
New Member States ◽  
Farm Scale ◽  
Grain Farms ◽  
The Eu

The aim of this study is to analyse the efficiency of Estonian grain farms after Estonia’s transition to a market economy and during the accession period to the European Union (EU). The non-parametric method Data Envelopment Analysis (DEA) was used to estimate the total technical, pure technical and scale efficiency of Estonian grain farms in 2000–2004. Mean total technical efficiency varied from 0.70 to 0.78. Of the grain farms 62% are operating under increasing returns to scale. Solely based on the DEA model it is not possible to determine optimum farm scale and the range of Estonian farm sizes operating efficiently is extensive. The most pure technically efficient farms were the smallest and the largest but the productivity of small farms is low compared to larger farms because of their small scale. Therefore, they are the least competitive. Since pre-accession period to the EU, large input slacks of capital have replaced the former excessive use of labour and land. This raises the question about the effects on efficiency of the EU’s investment support schemes in new member states.;

scholarly journals Does Access to Modern Marketing Channels Improve Dairy Enterprises’ Efficiency? A Case Study of Punjab, Pakistan

1998 ◽  
Vol 17 (1) ◽  
pp. 63-82
Author(s):  
Sana Sadaf ◽  
Khalid Riaz
Keyword(s):  
Returns To Scale ◽  
Marketing Channels ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Land Area ◽  
Fresh Milk ◽  
The Mean ◽  
Using Data ◽  
Variable Returns To Scale

The main objective of this study is to investigate how access to modern marketing channels impacts the efficiency of dairy enterprises. Using data on dairy farms in central Punjab (Sargodha), we carry out a nonparametric data envelopment analysis to measure their technical and scale efficiencies. The results show that, for the sample dairy enterprises, the mean technical efficiency under variable returns to scale was 0.89 while scale efficiency was 0.94. The results of a follow-on regression analysis support the hypothesis that the access to modern marketing channels, where payment for fresh milk is based on measured milk quality (fat content), improved efficiency. We find that efficiency is positively affected by the size of dairy operations, and negatively by the size of operational land area. Moreover, dairy enterprises with smaller herds tend to operate at a suboptimal scale, possibly due to credit and/or land constraints.

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