Technical efficiency drivers for the Italian water industry

Author(s):  
Tiziana Caliman ◽  
Paolo Nardi

The aim of this work is to introduce a first analysis concerning the relevance that ownership and financial structure, but also market dimension and business portfolios, have on the technical efficiency of Italian water utilities. Even though scholars have provided information on the influence of some dimensional or geographical variables, mono-utility character or ownership on efficiency, no paper, to the best of our knowledge, has ever considered the presence of all these hedonic variables as efficiency shifters or drivers. Antonioli and Filippini (2001) have not included ownership; Benvenuti and Gennari (2008) have included ownership and multi-utility strategy, but excluded the geographical dimension; Fabbri and Fraquelli (2000) have not included geographical location, business strategy or ownership; furthermore, most analyses of the Italian water sector have focused on the ATO level (investments, labour costs) and not on utility performances. We have estimated four heteroskedastic stochastic production frontiers: two different parametric models, where the hedonic dummy mono is either in the model as an additional variable or it is used to parameterize the variance of the inefficiency term; two competitive statistical formulations have also been introduced to specify the inefficiency component distribution, that is, the half normal and the exponential distributions. The most important findings of this paper can be summarized as follows. The labour, capital and other input elasticities are always highly significant, positive and quite stable in all the performed models, as expected for a well-behaved production function. The main results show that the mono-business strategy is not efficient; at the same time, operating water and sewerage together implies higher efficiency than water- only management. Theoretically, the population density can have an ambiguous effect on efficiency: on one hand, it could be more expensive to serve dispersed customers, but, on the other, it could generate congestion problems. It could be argued that the second effect prevails, therefore a higher density is accompanied by a higher inef- ficiency. The analysis points out that the variance of the idiosyncratic term is a function of the size of the firm, which is measured as the number of connected properties; the null hypothesis, that the firms use a constant returns-to-scale technology, has also been rejected. Considering the 1994 reform, it is possible to state that the integration of water and sewerage has substantially been positive; at the same time, the economies of scale and the ambiguity of density justify the division into provincial basins. The role of the private sector in the water industry, in agreement with previous literature, has neither a positive nor a negative impact on efficiency and ownership is simply not influent [obviously the quality of service should be considered, although the same indifference seems to emerge (Dore et al., 2001)]. Southern Italy suffers from a higher degree of inefficiency (also recently confirmed by Svimez, 2009), and this is probably the most important issue that has to be dealt with, because of the risks of drought and watering bans in those Regions during summer.

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.


2019 ◽  
Vol 11 (24) ◽  
pp. 6974
Author(s):  
Nalun Panpluem ◽  
Adnan Mustafa ◽  
Xianlei Huang ◽  
Shu Wang ◽  
Changbin Yin

Rice production holds a significant position in the Thai economy. Although it is the world’s largest rice exporter, Thailand’s increase in rice production is the result of an expansion in the cultivation area rather than an increase in yield per unit area. The present study was designed to estimate the technical efficiency and its governing factors for certified organic rice-growing farms in Yasothon Province, Thailand. A data envelopment model was employed to assess the technical efficiency of 328 farmer groups. The data revealed that the average technical efficiency was 23% and 28% under constant returns to scale (CRS) and variable returns to scale (VRS) specifications, respectively. Farmers can reduce the use of machinery, fertilizer, seed, and labor as input factors by about 80.1%, 25.62%, 24.72%, and 19.15%, respectively, while still achieving the same level of output. Multiple regression analysis was applied to estimate factors that affect the pure technical efficiency score (PTES) in the test regions. Results show that household size, farm size, water source, market accessibility, health symptoms, income, and labor were highly related to the TES and the amount of organic rice production. The regression coefficients of the predictors show that the income was the best predictor of the PTES at a significance level of p < 0.05. It is concluded that the farmers can potentially increase their yields by up to 72%–77% under current management practices.


2013 ◽  
Vol 59 (No. 6) ◽  
pp. 271-280 ◽  
Author(s):  
J.A. Onumah ◽  
E.E. Onumah ◽  
R.M. Al-Hassan ◽  
B. Brümmer

This study considers the meta-frontier technique to compare the efficiency level of organic and conventional cocoa production systems in Ghana using a cross sectional data of 390 farms. The results reveal that the organic systems exhibit an increasing return to scale whilst, the conventional system exhibit decreasing returns to scale. All the inputs variables positively influence the production except the age of trees. The combined effects of operational and farm specific factors are identified to influence the technical efficiency although the individual effects of some variables are not significant. The mean technical efficiency relative to the meta-frontier is estimated to be 0.59 for the organic and 0.71 for the conventional farms. The study concludes that the conventional system of cocoa production is more technically efficient than the organic system. However, the increase in the scale of production in the organic system to take advantage of the economies of scale may enhance the efficiency of production. &nbsp;


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&rsquo; technical efficiency.


2018 ◽  
Vol 9 (1) ◽  
pp. 51-58
Author(s):  
Arbia Hlali

AbstractThis paper applies a non-parametric method to provide level technical efficiency for 7 Tunisian ports during 18 years (1998-2015). These ports represent different data set. The use of the model of variable returns to scale (VRS) has led to interesting results. The results show that the most ports are characterized by low levels of technical efficiency, with the exception port of Rades. In addition, the result shows the variation of variable returns to scale and constant returns to scale of technical port’s efficiency. Furthermore, we concluded that the panel data improves the efficiency estimates.


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.


2020 ◽  
Author(s):  
Benjamin Tetteh Anang ◽  
Hamdiyah Alhassan ◽  
Gideon Danso-Abbeam

Abstract The study explored the impact of improved variety adoption on technical efficiency of smallholder maize farmers in Tolon District of northern Ghana. Smallholder maize farmers in the study area were sampled using random sampling technique. Double bootstrap data envelopment analysis was applied to estimate technical efficiency and its determinants. The results indicate that producers in the study area have a bias-corrected technical efficiency of 57% under variable returns to scale (VRS) assumption and 52% under constant returns to scale (CRS) assumption. Controlling for potential endogeneity of the adoption variable, the results indicate that adoption of improved varieties enhance technical efficiency of maize farmers in the study area. Technical efficiency of the farmers increased with herd size but decreased with years of formal education, household size, extension contact, frequency of weeding, and farm size. Ensuring that improved seeds are made available and affordable to smallholder farmers and promotion of livestock rearing are policy measures likely to enhance technical efficiency of smallholder farmers.


2020 ◽  
Author(s):  
Rogers Ayiko ◽  
Paschal N. Mujasi ◽  
Joyce Abaliwano ◽  
Dickson Turyareeba ◽  
Rogers Enyaku ◽  
...  

Abstract Background: General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17. Methods: We undertook input-oriented Data Envelopment Analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1. Results: The Average Constant Returns to Scale, Variable Returns to Scale and Scale Efficiency of general hospitals for 2016/17 were 49% (95% CI, 44% - 54%), 69% (95% CI, 65% - 74%) and 70% (95% CI, 65% - 75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance. Conclusion: The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3,439) less staff and 31% (3,539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.


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