Municipal Efficiency and Economies of Scale in Bosnia and Herzegovina

2018 ◽  
Vol 16 (4) ◽  
pp. 715-734 ◽  
Author(s):  
Aida Soko ◽  
Jelena Zorič

This study estimates municipal efficiency and economies of scale of municipalities in Bosnia and Herzegovina by employing data envelopment analysis (DEA) with variable (VRS) and constant (CRS) returns to scale. The results indicate low overall municipal efficiency, with economies of scale reached in very few municipalities. The average municipal efficiency score is 0.7115 under DEA VRS assumption, where only 16% of municipalities are found efficient. The average scale efficiency is 0.7458 with full scale efficiency reached by only 11% of municipalities in Bosnia and Herzegovina. Furthermore, the analysis shows strong positive impact of number of inhabitants on overall municipal efficiency. Politically motivated fragmentation of municipalities, aiming to bring peace and stability to the country, did not go hand in hand with improved economic efficiency.

Author(s):  
Ezekiel O. Haruna ◽  
Elizabeth E. Samuel ◽  
Blessing Amechima

This study examined the economic and scale efficiency in processing cassava into gari in Ankpa Local Government, Kogi State. Data were collected from 120 cassava processors through a multistage sampling technique in 2019 using questionnaire as the instrument for data collection. Data collected were analyzed through the use of Data Envelopment Analysis (DEA), ordinary Least squares regression analysis and simple descriptive statistics. The result of the study revealed that about 8.33% and 63.33% achieved full technical efficiency (TE = 1) under the CRS and VRS respectively while 12.50% achieved both full allocative and economic efficiency. About 8.33% achieved full scale efficiency. These efficiency scores revealed the presence of considerable level of inefficiency and room for improvement in order to become fully efficient. The returns to scale analysis revealed that majority of cassava processors (about 90%) are operating under increasing returns scale implying that most of the firms in the sample are too small and therefore would benefit from an increase in scale. The OLS result showed that household size, experience and education are the most important and significant factors affecting both technical and economic efficiency of the processors in the study area. We recommend that processors should be encouraged to form and join viable cooperatives where they can access credit, information, training and processing facilities in order to improve their efficiency.


2011 ◽  
Vol 43 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Amin W. Mugera ◽  
Michael R. Langemeier

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.


Author(s):  
Fadzlan Sufian

This paper investigates the performance of Malaysian non-bank financial institutions during the period of 2000-2004. Several efficiency estimates of individual NBFIs are evaluated using the non-parametric Data Envelopment Analysis (DEA) method. The findings suggest that during the period of study, scale inefficiency outweighs pure technical inefficiency in the Malaysian NBFI sector. We find that the merchant banks have exhibited a higher, technical efficiency compared to their peers. The empirical findings suggest that scale efficiency tends to be more sensitive to the exclusion of risk factors, implying that potential economies of scale may be overestimated when risk factors are excluded.  


2017 ◽  
Vol 1 (2) ◽  
pp. 067
Author(s):  
Abi Pratiwa Siregar ◽  
Jamhari Jamhari ◽  
Lestari Rahayu Waluyati

This study assessed the performance of 32 village unit co-operatives (KUD) in Yogyakarta Special Region during 2011 to 2012. The efficiency level of the KUD were evaluated by employing the data envelopment analysis and multiple regression analysis using panel data to determine the factors affecting efficiency level. Efficiency analysis was decomposed into three dimensions to explore possible sources of inefficiency. According to Marwa and Aziakpono (2016), the first dimension was technical efficiency, which explored the overall effectiveness of transforming the productive inputs into desired outputs compared to the data-driven frontier of best practice. The second dimension was pure technical efficiency, which captured managerial efficiency in the intermediation process. The third dimension was scale efficiency, which explored whether KUD were operating in an optimal scale of operation or not. The results found that the average scores are 64%, 92%, and 68% for technical, pure technical, and scale efficiency respectively in 2011, while in 2012 the average scores are 57%, 94%, and 60% for technical, pure technical, and scale efficiency. Factors having significantly positive impact on several measures of efficiency are incentive and dummy variables (agriculture inputs and hand tractor). Accounts receivable only has positive relationship to pure technical efficiency. On the other hand, rice milling unit and electricity services have negative impact with several measures of efficiency.


Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4902
Author(s):  
Biswaranjita Mahapatra ◽  
Chandan Bhar ◽  
Sandeep Mondal

Coal is the primary source of energy in India. Despite being the second-largest coal-producingcountry, there exists a significant difference in demand and production in India. In this study, the relativeefficiency of twenty-eight selected opencast mines from a large public sector undertaking coal companyin India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This studyused input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency,and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiencyand pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient witha decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employedto measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019).The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPIefficiency and productivity assessment throughout the years, changes in innovation and technology areincreasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluationof each variable with mines performance. The author formulated the strategies, which in turn help coalprofessionals to improve the efficiency of the mine.


2017 ◽  
Vol 1 (2) ◽  
pp. 379 ◽  
Author(s):  
Primož Pevcin

<p>The purpose of this paper is to empirically verify if the possible existence of scale economies actually supports the argument that municipal consolidation is needed in Slovenia. The major reform of local self-government in Slovenia was implemented in 1994, when the transformation of existing 58 »communal« municipalities was envisaged. From 1995 onwards, the number of municipalities increased to the current number of 212 municipalities. Consequently, the necessity to implement structural reforms of local self-government in Slovenia has been stressed. The arguments favoring municipal amalgamations stressed that country has become too fragmented and municipal amalgamation would enable the reduction of (administrative) costs, and increase efficiency as well as quality of services provided, indicating that technical aspects of local government operation are targeted. Following, technical efficiency of Slovenian municipalities is estimated with the Data Envelopment Analysis (DEA) method, in order to determine if (and which) municipalities are experiencing increasing returns to scale (i.e., scale economies). The results indicate that there is important scale efficiency component, and predominantly very small municipalities are experiencing economies of scale, but their number is relatively low. Therefore, one of the classical arguments for municipal amalgamation, achieving economies of scale, can only be applied at a limited scale. This does not imply that more extensive amalgamation is not warranted, but it demands that other arguments justifying municipal amalgamation should be presented.  </p>


Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 536-551 ◽  
Author(s):  
Seyed Hossein Razavi Hajiagha ◽  
Shide Sadat Hashemi ◽  
Hannan Amoozad Mahdiraji

Purpose – Data envelopment analysis (DEA) is a non-parametric model that is developed for evaluating the relative efficiency of a set of homogeneous decision-making units that each unit transforms multiple inputs into multiple outputs. However, usually the decision-making units are not completely similar. The purpose of this paper is to propose an algorithm for DEA applications when considered DMUs are non-homogeneous. Design/methodology/approach – To reach this aim, an algorithm is designed to mitigate the impact of heterogeneity on efficiency evaluation. Using fuzzy C-means algorithm, a fuzzy clustering is obtained for DMUs based on their inputs and outputs. Then, the fuzzy C-means based DEA approach is used for finding the efficiency of DMUs in different clusters. Finally, the different efficiencies of each DMU are aggregated based on the membership values of DMUs in clusters. Findings – Heterogeneity causes some positive impact on some DMUs while it has negative impact on other ones. The proposed method mitigates this undesirable impact and a different distribution of efficiency score is obtained that neglects this unintended impacts. Research limitations/implications – The proposed method can be applied in DEA applications with a large number of DMUs in different situations, where some of them enjoyed the good environmental conditions, while others suffered from bad conditions. Therefore, a better assessment of real performance can be obtained. Originality/value – The paper proposed a hybrid algorithm combination of fuzzy C-means clustering method with classic DEA models for the first time.


2013 ◽  
Vol 13 (4) ◽  
pp. 99-103 ◽  
Author(s):  
Chia-Hui Ho

Abstract Operating performance could affect the survival and future development of a business that both businesses and business managers would devote to the enhancement of operating performance. Having developed for more than four decades, the consistent upstream, mid-stream and downstream system have been constructed in domestic textile industry. The output value of textiles in Taiwan has exceeded 480 billion NT dollars, which is not a sunset industry, as generally described. The impacts of high labour cost, environmental protection measures and changes of capital market as well as the competition of emerging countries, particularly Mainland China, have made textile industry in Taiwan face great market competition and pressure. Since textiles are regarded as one of the major products in Taiwan, the operating performance could affect the survival of the overall industry. In this case, operating performance survey of textile manufacturers in Taiwan during 2010–2012 is combined with Data Envelopment Analysis and Slack Variable Analysis to measure the total efficiency, pure technical efficiency and scale efficiency of top 12 textile manufacturers in Taiwan, tending to provide the reference of operating efficiency improvement for the manufacturers. The empirical results show that the overall efficiency in the 3 years appears 0.89 averagely. The relative efficiency (1) between two manufacturers, Far Eastern New Century and Ruentex Industries, achieves the optimal operating efficiency, whereas the remaining 10 are comparatively worse. Regarding the analysis of returns to scale, two textile manufacturers present constant returns to scale, with the optimal operating efficiency, whereas the remaining 10 show increasing returns to scale, revealing that expanding the scale could enhance the marginal return and further promote the efficiency.


The present study intended to determine the technical and scale efficiency of sample dairy farms for evaluating their performance. Data Envelopment Analysis (DEA) technique was used to estimate the technical and scale efficiency of 80 each of member and nonmember dairy farms in the Pune district of Maharashtra state during 2019. Technical efficiency score further partitioned into pure technical efficiency and overall technical efficiency. The technical efficiency score was more for member dairy farms as compared to the non-members under the assumption of constant return to scale (CRS) and variable return to scale (VRS). It highlighted that the non-members of dairy cooperatives had more potential to reduce the input use without affecting the output level compared to the member group. It was also observed that the technical efficiency under the CRS assumption was more than VRS for both member and non-member groups. It revealed that the farms were scaled inefficient (SE<1) and not operating at optimal scale. The study further revealed a positive relationship between technical efficiency and herd size. It also revealed that the resource-saving potential due to the scale effect. So, it supported the policy of providing technical advice on the use of feed and fodder resources, better management practices, and increasing the herd size to increase the technical and scale efficiency.


Author(s):  
Mini Kundi ◽  
Seema Sharma

Purpose The purpose of the present study is to evaluate the efficiency of glass firms in India. Design/methodology/approach Data envelopment analysis (DEA) has been employed to study the technical, scale and super efficiency measures of glass firms in India. Findings Major findings of DEA analysis show that 65 percent firms are found to be technically efficient. Returns to scale analysis indicate that five firms are operating at decreasing returns to scale and two firms are exhibiting increasing returns to scale. Further, results show that small– and medium–scale firms are more efficient than large–scale firms. Old firms are more efficient compared to the young firms and foreign-owned firms are technically more efficient compared to the domestic firms. Practical implications The results of this study would help the managers to assess their relative efficiency and take corrective measures to efficiently use their resources. Originality/value This seems to be the first study to apply DEA to analyze the efficiency of glass firms in India. No previous study on glass industry seems to have decomposed the measure of overall technical efficiency into its components, namely pure technical efficiency and scale efficiency and no study seems to have examined whether ownership, age and size of a firm are significant for its efficiency. In addition, no earlier study seems to have ranked the glass firms based on their efficiency values. Further, target values of inputs and outputs are demonstrated in this study. Stability of efficiency scores is also checked.


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