scholarly journals Efficiency Analysis with non parametric method: Illustration of the Tunisian ports

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.

Author(s):  
Efayena, O. Obukohwo ◽  
Enoh H. Olele ◽  
Patricia N. Buzugbe

The study analyses, empirically, the efficiency of the Pharmaceutical sector in Nigeria. Employing a balanced panel of 20 pharmaceutical firms between 2012 and 2016, the paper uses a non-parametric technique (Data Envelopment Analysis) to analyze the firms' efficiency under the constant returns to scale (CRS) and variable returns to scale (VRS) assumptions. The results obtained shows inefficiency in the pharmaceutical sector as it operates under a decreasing return to scale. This calls for an appropriate policy mix to stimulate the efficiency of the pharmaceutical sector in Nigeria by enhancing research and development (R&D) as well as regulations within the sector.


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.


Author(s):  
Ha Park ◽  
Daecheol Kim

Non-ferrous metals are widely used as basic materials in various industrial fields, and zinc is a metal that is produced and used next to iron, aluminum, and copper. In this study, DEA (data envelopment analysis) was applied to measure the efficiency of 43 zinc smelters in three countries in East Asia: Korea, China, and Japan. The constant returns to scale (CRS) and the variable returns to scale (VRS) models, and the slack-based measure (SBM) were used for the analysis. As a result of the efficiency analysis, there were three efficient zinc smelters in the CRS model, 14 in the VRS model and 14 in the SBM. The average efficiency was 0.458 based on the SBM, which indicates that there is room for improvement in efficiency. In addition, the average scale efficiency value was 0.689, showing the scale to be inefficient. Therefore, it can be seen that the labor cost and the energy cost must be brought to an appropriate level. The Tobit regression analysis was used to analyze the causes of efficiency. The greater the capacity and the larger amount of bonus Zn of the refinery, the higher the efficiency of the refinery.


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.


2017 ◽  
Vol 33 (2) ◽  
pp. 363-347
Author(s):  
Olfa Nafti ◽  
Salem Lotfi Boumediene ◽  
Slim Khouaja ◽  
Wassim Ben Ayed

The purpose of this paper is to analyze the efficiency of Islamic banks operating in different countries, over the period 2006-2009.We applied a non-parametric approach, or a Data Envelopment Analysis (DEA), that utilizes both the constant returns to scale (CRS) and the variable returns to scale (VRS) assumptions to offer measures of the technical and scale efficiency. The outcomes reveal a considerable degree of dispersion of technical efficiency between banks within the sample of the year-to-year basis. To inspect the determinants of efficiency, we apply the panel regression analysis. In fact, we used panel regression analysis in order to explain the variation in the dependent variable (calculated efficiencies) by a set of independent variables, such as banks size, asset quality, management capability, liquidity, sensitivity to markets risks, and capitalization.We find that banks with higher liquidity and a good management capability are more likely to operate at higher levels of technical efficiency. In addition, the results show that size, seem to contribute negatively to the evolution of efficiency scores of Islamic banks operating in the world.


2017 ◽  
Vol 77 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Maria Bampasidou ◽  
Ashok K. Mishra ◽  
Charles B. Moss

Purpose The purpose of this paper is to investigate the endogeneity of asset values and how it relates to farm financial stress in US agriculture. The authors conceptualize an implied measure of farm financial stress as a function of debt position. The authors posit that there are variations in the asset values that are beyond the farmer’s control and therefore have implications on farm debt. Design/methodology/approach The framework recognizes the endogeneity of return on assets (ROA). It uses a non-parametric technique to approximate the variance of expected ROA (VEROA). The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Further, the authors use a dynamic balanced panel data set from 1960 to 2011 for 15 US agricultural states from the Agricultural Resource Management Survey, and information from traditional state-level financial statements. Findings Estimation of linear dynamic debt panel data models accounting for the endogeneity of ROA and VEROA is a challenging task. Estimated variances are unstable. Hence, the authors focus on variance specification that uses the residuals squared from the ARIMA specification and non-parametric estimators. Arellano-Bover/Blundell-Bond generalized method of moments estimation procedures, although may be biased, show that VEROA has a negative and significant effect on the total amount of debt in the agricultural sector. Research limitations/implications The instruments used in this analysis are lagged regressors which may be weakly correlated with the relevant first-order condition, hence not properly identifying the parameters of interest. Future research could include the identification of better instruments, potentially use of sequential moment conditions. Originality/value Unlike previous study, the authors use non-parametric approximation of VEROA. The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Second, the authors make use of a large dynamic balanced panel data set from 1960 to 2011 for 15 agricultural states in the USA. To the best of the authors’ knowledge, this study is one of the few that provides evidence on risk-balancing behavior at the agricultural sector level, of the USA.


Author(s):  
Marek Jetmar ◽  
Jan Kubát

The article deals with the application of data envelope analysis (DEA), in examining the efficiency of selected public services provided by municipalities and cities. The method is focused on calculating indicators for individual municipalities and groups of municipalities. When calculating the efficiency, the DEA model with variable returns to scale and superefficiency is used. The distance from the efficiency limit (data envelope) is not measured by Euclidean, as classical DEA models, but by Chebyshev distance. The analysis focuses on examining efficiency within groups of municipalities, defined according to the number of inhabitants and location in relation to development centers, but also these groups in the context of the entire data set. The created model allows to calculate the efficiency of each municipality and monitor its ranking within the given category, but also the type of municipality, administrative district or region. It then shows the practical results of the calculation of efficiency - the achieved average value on the example of schools and municipal police. The variability of the results achieved is subject to interpretation with respect to the services examined. Finally, the limits of DEA use are discussed with regard to the quality of available data and the overall appropriateness of the method for monitoring the efficiency of municipalities.


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 (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.


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