scholarly journals Analyzing the Efficiency Differences among Basic Health Units in Sargodha District

2011 ◽  
Vol 3 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Touqeer Abbas ◽  
Muhammad Amir Aslam . ◽  
Muhammad Waqas .

Pakistan has adequate infrastructure for health services delivery at primary level. The study aims to calculate the technical efficiency of Basic Health Units (BHUs) in Sargodha by using the Data Envelopment Analysis (DEA) with the choice of inputs and outputs being specific to BHUs operation. DEA model results reveals that the mean technical efficiency under, Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) was 0.719 and 0.807 while the mean scale efficiency was 0.88. Study exposed that 77 % BHUs were technically inefficient under CRS while 66 % BHUs were technically inefficient under VRS modal. Overall 76% BHUs were inefficient and destructing the infrastructure. Moreover, findings evidently point to adverse inefficiency of BHUs in health services delivery. Study concluded that existing high level of inefficiency in BHUs needs institutional fascination for scaling up BHUs to meet both regional as well international targets such as Millennium Development Goals (MDGs) and recommended such measures that may curb the waste.

2016 ◽  
Vol 13 (4) ◽  
pp. 470-482 ◽  
Author(s):  
Majed Alharthi

This study empirically estimates efficiency and its determinants in 190 Islamic (IBs), conventional (CBs), and socially responsible banks (SRBs) in 22 countries during the period 2005-2012. The study first uses non-parametric approaches to estimate the efficiency measures (scale efficiency (SE), technical efficiency-constant returns to scale (CRS), and technical efficiency-variable returns to scale (VRS)) and second employs ordinary least squares, fixed effects, random effects, and TOBIT models to get the efficiency determinants. The findings indicate that the average efficiency is 0.966, 0.952, and 0.983 for the SE, CRS, and VRS, respectively. However, efficiency measures show that the SRBs are most efficient banks whereas, the least efficiency scores archived by Islamic banks. Islamic bank efficiency is positively correlated with size, loan intensity, ROA, inflation rates, market capitalization and financial crisis. However, conventional banks’ TE and CRS efficiency are positively and significantly correlated with size, ROA, and market capitalization, while their VRS efficiency is negatively and significantly related to capital ratio, age and GDP. In addition, SRBs’ efficiency is increased by size, capital ratio, loan intensity, ROA, foreign ownership, domestic ownership, inflation and financial crisis. Furthermore, the financial crisis affects the SE and CRS efficiency measures in Islamic banks while socially responsible banks SE efficiency measure is positively affected by the financial crisis, which means that socially responsible banks were stabled and resisted during the crisis period. Finally, there is no significant correlation between financial crisis and efficiency indictors in conventional banks during the period


Author(s):  
Abebe Birhanu Ayele

This study measures the technical and scale efficiency of Micro and Small Enterprises (MSEs) and input slacks using Data Envelop Analysis (DEA) model and identifies the determinants of efficiencies of MSEs by employing ordinary least square (OLS) econometrics model. A sample of 375 randomly selected MESs are included in the study. The study found that the average technical and scale efficiency of MSEs are relatively low; technical efficiency averaged at 30 percent and 38.4 percent under constant returns to scale (CRS) and variable returns to scale (VRS) assumptions, respectively. Besides, the overall average scale efficiency score of MSEs was estimated at 77.8 percent. The highest mean technical and scale efficiencies were registered in the construction (71.8 percent) and manufacturing (85.7 percent) sectors, respectively. Whereas, the lowest technical and scale efficiency goes to urban agriculture sector and service sector, with 38.9 percent and 67.2 percent, respectively. The level of inputs, enterprise age and sector, human capital, labor productivity variables significantly affect relative technical efficiency level of MSEs with different directions while variables such as start-up capital, gender of the enterprise manager and availability of support from the government identified statistically not significant in determining the MSEs’ technical efficiency.


2002 ◽  
Vol 31 (2) ◽  
pp. 211-220 ◽  
Author(s):  
Kalyan Chakraborty ◽  
Sukant Misra ◽  
Phillip Johnson

Technical efficiency for cotton growers is examined using both stochastic (SFA) and nonstochastic (DEA) production function approaches. The empirical application uses farm-level data from four counties in west Texas. While efficiency scores for the individual farms differed between SFA and DEA, the mean efficiency scores are invariant of the method of estimation under the assumption of constant returns to scale. On average, irrigated farms are 80% and nonirrigated farms are 70% efficient. Findings show that in Texas, the irrigated farms, on average, could reduce their expenditures on other inputs by 10%, and the nonirrigated farms could reduce their expenditures on machinery and labor by 12% and 13%, respectively, while producing the same level of output.


2011 ◽  
Vol 1 (2) ◽  
pp. 225
Author(s):  
Izah Mohd Tahir ◽  
Mehran Ali Memon

The efficiency of manufacturing companies is one of the critical elements for its competitiveness in the domestic as well as international markets. Previous research on efficiency measurement usually adopts Data Envelopment Analysis (DEA) approach. Therefore this paper is aimed to analyse the efficiency of 14 top manufacturing companies in Pakistan for a five year period from 2006 to 2010. Data of top 14 manufacturing companies are gathered from OSIRIS database. DEA method is applied using both the Constant Returns to Scale (CCR) and Variable Returns to Scale (BCC) models to find the overall efficiency, technical efficiency and scale efficiency. In this paper we use two input variables (total expenses and total assets) and two output variables (sales and profit before tax). The results under CCR method show that only one company is considered technically efficient while the average overall technical efficiency varies from 0.64 to 0.99. Company number 5 (NRL) demonstrates the best performance for all years under study.


2021 ◽  
Vol 34 (1) ◽  
Author(s):  
MOHAMMED AL-SIYABI ◽  
SHEKAR BOSE ◽  
HUSSEIN AL-MASROORI

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.


2015 ◽  
Vol 01 (01) ◽  
pp. 1450005
Author(s):  
Betul Sayin ◽  
Ibrahim Yilmaz

This study was conducted to measure the efficiency level of irrigation unions in the Antalya Province of Turkey. An input-oriented data envelopment model, a linear programming procedure, was used to measure the relative efficiency scores of irrigation unions. Research results showed that technical efficiency (TE) scores varied between 0.39 and 1.00 and the mean TE score was 0.85. Based on the results of decomposition, the pure TE and scale efficiency were 0.81 and 0.95, respectively and the main source of inefficiency in the research area was pure TE. 47% of the examined unions had constant returns to scale, while that of decreasing returns to scale was 53%. The study also revealed that the irrigation area sustainability ratio and the ratio of energy cost in total expenses of technically efficient unions were lower than that of inefficient ones. The study suggested that restoration and modernization efforts should be initiated in order to enhance the efficiency level in the long term. Designing training for the managers and workers of the irrigation unions, adjusting the unions based on the fluctuation in energy market and declining the leakage of the irrigation system may be beneficial to increase the TE.


BMJ Open ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. e035703
Author(s):  
Qian Li ◽  
Liqi Tian ◽  
Xiaolin Jing ◽  
Xianghua Chen ◽  
Jiangfeng Li ◽  
...  

ObjectiveTo evaluate the efficiency of county public hospitals in Shandong Province following China’s new medical reform and compare the efficiency of hospitals with different bed sizes for improving efficiency.Design and settingThis was a cross-sectional study on the efficiency and size of 68 county public hospitals in China in 2017.Outcome measuresData envelopment analysis was used to calculate the efficiency scores of hospitals and to analyse the slack values of inefficient hospitals. The actual number of open beds, doctors, nurses and total expenditure were selected as inputs, and the total number of annual visits, discharges and total income were selected as outputs. The Kruskal-Wallis H test was employed to compare the efficiency of hospitals with different bed sizes. The χ2 test was used to compare the returns to scale (RTS) of hospitals with different bed sizes.ResultsTwenty (29.41%) hospitals were efficient. There were 27 hospitals with increasing returns to scale, 23 hospitals with constant returns to scale and 18 hospitals with decreasing returns to scale (DRS). The differences in technical efficiency (p=0.248, p>0.05) and pure technical efficiency (p=0.073, p>0.05) were not statistically significant. However, the differences in scale efficiency (p=0.047, p<0.05) and RTS (p<0.001) were statistically significant. Hospitals with DRS began to appear at 885 beds. All sample hospitals with more than 1100 beds were already saturated and some hospitals even had a negative scale effect.ConclusionsThe government and hospital managers should strictly control the bed size in hospitals and make hospitals resume operating in the interests of public welfare. Interventions that rationally allocate health resources and improve the efficiency of medical workers are conducive to solving redundant inputs and insufficient outputs.


2019 ◽  
Vol 11 (2) ◽  
pp. 434 ◽  
Author(s):  
Jun Yin ◽  
Qingmei Tan

Urban efficiency can effectively measure the management and allocation level of urban factor inputs. Based on the data of 30 prefecture-level cities in Northwest China from 2006 to 2015, urban efficiency is measured by data envelopment analysis (DEA). Then the spatiotemporal evolution rule is identified by Malmquist model. The results illustrate that the overall average urban efficiency of cities in Northwest China each year from 2006 to 2015 was at the low level. Only Jiayuguan, Yulin, Yan’an, and Karamay reached the high average urban efficiency, while Dingxi, Pingliang, Guyuan, Shangluo, Tianshui, Longnan, and Baiyin were at the inefficient level. Most cities in Northwest China were still in the “growing” stage of increasing returns to scale. The scale of urban investment was relatively insufficient, and economies of scale had not yet formed. Cities with decreasing returns to scale were mainly distributed in the capital cities and the central and sub-central cities of Guanzhong-Tianshui Economic Zone with relatively abundant urban resources and capital. Cities with constant returns to scale were mainly distributed in four cities including Yan’an, Yulin, Jiayuguan, and Karamay with high efficiency. The overall comprehensive efficiency, technical efficiency, and scale efficiency of cities in Northwest China were not only low, but also showing a downward trend. The overall progress of urban technology had failed to make up for the shortfall caused by low efficiency, resulting in total factor productivity (TFP) decreasing by 0.5%. Therefore, the cities in Northwest China should continuously improve their technical efficiency and scale efficiency, and ultimately enhance the comprehensive efficiency.


2008 ◽  
Vol 38 (10) ◽  
pp. 2553-2565 ◽  
Author(s):  
Ted L. Helvoigt ◽  
Darius M. Adams

This paper uses data envelopment analysis (DEA) to characterize the changing production frontier (technical efficiency, productivity growth, technical and efficiency change, and returns to scale) of the sawmilling industry in the Pacific Northwest (PNW) US using geographical panel data for the period 1968–2002. Unlike past DEA studies, we develop confidence intervals for all estimates using an improved bootstrapping method. The results indicate that the gap between the least and most efficient regions in PNW has grown and the least efficient regions are falling further behind the most efficient regions. For the Oregon regions, the null hypothesis of constant returns to scale (CRS) could not be rejected for any year. For the Washington regions, returns to scale varied year by year, although only two of the five regions showed strong tendencies away from CRS. For PNW as a whole, mean productivity growth was 0.5% per year between 1968 and 1992. Between 1992 and 2002, the regional mean was 1.3%, although with wide variation across regions. DEA results indicate that the vast majority of productivity growth in the PNW sawmilling industry between 1968 and 2002 was due to technical change. Improvements in scale efficiency played a very small role, and efficiency change was zero or negative.


2016 ◽  
Vol 26 (1) ◽  
pp. 118-136 ◽  
Author(s):  
Peter A Aghimien ◽  
Fakarudin Kamarudin ◽  
Mohamad Hamid ◽  
Bany Noordin

Purpose – This paper aims to investigate the efficiency level of Gulf Cooperation Council (GCC) banks on technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE). Both PTE and SE represent the potential factors that influence the efficiency of the GCC banks. In total, 43 GCC banks were observed in this study over the period from 2007 until 2011. Design/methodology/approach – The Data Envelopment Analysis, a non-parametric method using variable returns to scale under Banker, Charnes and Cooper model, was used with assets and deposit (as input) and loan and income (as output). Findings – On average, the results show that many GCC banks are operating within an optimal scale of efficiency. Nevertheless, the results also show managerial inefficiency in the use of resources. Furthermore, the results indicate that, while the larger banks (the 22 largest) tend to operate at constant returns to scale (CRS) or decreasing returns to scale, the smaller banks (the 21 smallest) are susceptible to operate at either CRS or increasing returns to scale. Research limitations/implications – Because of the chosen research method, the results may lack generalisation. Therefore, researchers are encouraged to test the propositions further. An additional implication of the results is that it was able to identify some banks that may become potential targets for outside acquisition. Practical implications – The findings should be useful to banks in the GCC in increasing their efficiencies and recognizing those with a potential for outside acquisition. Originality/value – The findings are valuable because they will facilitate the maintenance of efficient banks in the GCC. This is necessary to enable the countries to maintain a healthy and sustainable economy.


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