Perspiration versus inspiration: sources of national and provincial output growth in Indonesia [1990–2015] using province-level non-parametric frontier analysis

Author(s):  
Mitsuhiko Kataoka
Author(s):  
Konstantinos E. Kounetas ◽  
Michael L. Polemis ◽  
Nickolaos G. Tzeremes

2021 ◽  
Vol 9 (1) ◽  
pp. 7
Author(s):  
Mirpouya Mirmozaffari ◽  
Reza Yazdani ◽  
Elham Shadkam ◽  
Seyed Mohammad Khalili ◽  
Leyla Sadat Tavassoli ◽  
...  

The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.


Author(s):  
Aikaterini Kokkinou

This paper investigates technical efficiency estimation in financial markets, using both parametric and non-parametric techniques: parametric Stochastic Frontier Analysis (SFA) approach or non-parametric Data Envelopment Analysis (DEA). This chapter focuses on reviewing the stochastic frontier analysis literature regarding estimating inefficiency in financial markets level, as well as explaining producer heterogeneity along with the relationships with productive efficiency level. This chapter investigates technical efficiency estimation in financial markets, using both parametric and non-parametric techniques: parametric Stochastic Frontier Analysis (SFA) approach or non-parametric Data Envelopment Analysis (DEA). More specifically, this chapter focuses on reviewing the stochastic frontier analysis literature regarding estimating inefficiency, its industrial level, as well as explaining producer heterogeneity along with the relationships with productive efficiency level.


2019 ◽  
Vol 64 (04) ◽  
pp. 921-938
Author(s):  
YIXIAO ZHOU ◽  
RUNYANG ZHANG ◽  
LIGANG SONG

This study explores the efficiencies of firm’s R&D investment depending on the degree of reliance on government funding relative to firms’ private funding. Stochastic frontier analysis is applied on a sample of 30 provinces with data on R&D inputs and innovation outputs by all large- and medium-sized industrial firms in these provinces from 2000 to 2013. It is found that R&D investment financed by firms’ private funding is more efficient than that by government funding in generating new products, whereas R&D investment financed by government funding is more efficient than that by firms’ private funding in producing new patents.


1999 ◽  
Vol 61 (4) ◽  
pp. 455-487 ◽  
Author(s):  
Gary Koop ◽  
Jacek Osiewalski ◽  
Mark F. J. Steel

2021 ◽  
Vol 12 (1) ◽  
pp. 1-14
Author(s):  
Marketa Matulova ◽  
Jana Rejentova

This paper presents a performance evaluation of European airports, based on the application of both parametric and non-parametric approaches. We have evaluated the 115 busiest airports in Europe according to the number of passengers checked-in in 2018. The four inputs we used were the number of Terminals, Runways, Boarding gates, and Aircraft stands. Three variables were used to describe the outputs, namely, Passengers, Movements, and Cargo. The parametric method we chose to apply was the Stochastic Frontier Analysis (SFA) with the Cobb-Douglas production function, the Half-Normal distribution of inefficiency component, and the Normal distribution of an error term. As a basic SFA model only allows for a single output, we employed different methods to get a single efficiency score for each and every airport. Next, we evaluated the airport performance non-parametrically using several Data Envelope Analysis (DEA) models including the super-efficiency model. We compared the results obtained by individual approaches and discussed their pros and cons. Finally, we applied the program evaluation procedure to explore the effect of the different forms of airports ownership on their performance.


2021 ◽  
Vol 25 (110) ◽  
pp. 14-22
Author(s):  
Martha Bucaram Levarone ◽  
Francisco Quinde Rosales ◽  
Joy Mayorga Ramos ◽  
Martha Bueno Quinonez

A comparative analysis of the technical efficiency in the production of national cocoa among the main producing cantons of the province of Guayas was carried out. For this, the study was based on an analysis with inductive reasoning and empirical-analytical paradigm, through the elaboration of surveys to 361 UPA's in the cantons of: Milagro, San Jacinto de Yaguachi, El Empalme, Alfredo Baquerizo Moreno, Naranjal and Simón Bolívar; these data served as the basis for the elaboration of the Data Envelopment Analysis (DEA) model. The results show that on average, the Simón Bolívar canton is the canton with the highest technical efficiency, with 50% of the total UPAs surveyed in the range of 70% and 99% effectiveness. Finally, regarding the observed averages of allocative efficiency, it can be concluded that Jujan has the highest average with 75%. Keywords: Technical and Allocative Efficiency, National Cocoa, Enveloped Data Analysis, Non Parametric Method. References [1]M. Naranjo., «Un Puerto en busca de una Nación, Guayaquil y la idea fundacional del Ecuador como país,» de Seminario Internacional Poder, Política y Repertorios de la Movilización Social en el Ecuador Bicentenario, Quito, 2009. [2]S. C. Mogro, V. Andrade-Díaz y D. P.-. Villacís, «Posicionamiento y eficiencia del banano, cacao y flores del Ecuador en el mercado mundial,» Revista Ciencia UNEMI, vol. 9, nº 19, pp. 48-53, 2016. [3]M. Vassallo, Diferenciación y agregado de valor en la cadena ecuatoriana del cacao, Quito: Editorial IAEN, 2015. [4]M. Pigache y S. Bainville, Cacao tipo ‘Nacional’ vs. Cacao CCN51: ¿Quién ganará el partido?, Quito: Ird Editions, 2007. [5]M. Chiriboga, Jornaleros, grandes propietarios y exportación cacaotera, Quito: Universidad Andina Simón Bolívar, 2013. [6]A. Acosta., Breve Historia Económica del Ecuador, Quito: Editora Nacional, 2006. [7]M. Espinoza y Y. Arteaga., «Diagnóstico de los Procesos de Asociatividad y la Producción de Cacao en Milagro y sus sectores aledaños,» Revista Ciencia UNEMI, vol. 8, nº 14, pp. 105-112, 2015. [8]E. Romero, M. Fernández, J. Macías y K. Zúñiga, «Producción y comercialización del cacao y su incidencia en el desarrollo socioeconómico del cantón Milagro,» Revista Ciencia UNEMI, vol. 9, nº 17, pp. 56-64, 2016. [9]e. I. I. d. C. A. Ministerio de Agricultura y Ganadería, La Agroindustria en el Ecuador. Un diagnóstico integral, Quito: IICA, 2006. [10]R. Rodríguez, M. Brugiafreddo y E. Raña., «Eficiencia técnica en la agricultura familiar: Análisis envolvente de datos (DEA) versus aproximación de fronteras estocásticas (SFA),» Nova Scientia, vol. 9, nº 18, pp. 342-370, 2017. [11]A. Resti., «Evaluating the cost-efficiency of the Italian banking system: what can be learned from the joint application of parametric and non-parametric techniques,» Journal of Banking & Finance, vol. 21, nº 2, pp. 221-250, 1997. [12]T. Coelli y S. Perelman, «A Comparison Of Parametric And Non-Parametric Distance Functions: With Application To European Railways,» European Journal Of Operational Research, vol. 117, nº 2, pp. 326-339, 1999. [13]B. Iráizoz, M. Rapún y I. Zabaleta., «Assessing the technicalb efficiency of horticultural production in Navarra, Spain,» Agricultural Systems, vol. 78, nº 3, pp. 387-403, 2003. [14]K. Sharma, S. Ping y H. Zaleski., «Productive efficiency of the swine industry in Hawaii,» Research Series, vol. 77, pp. 1-24, 1996. [15]D. Tingley, S. Pascoe y L. Coglan, «Factors affecting technical efficiency in fisheries: Stochastic Production Frontier versus Data Envelopment Analysis approaches,» Fisheries Research, vol. 73, nº 3, pp. 363-376, 2005. [16]H. Johansson, «Technical, allocative and economic efficiency in Swedish dairy farms: the Data Envelopment Analysis versus the Stochastic Frontier Approach,» de Poster background paper prepared for presentation at the XIth International Congress of the European Association of Agricultural Economists (EAAE), Copenhagen, 2005. [17]F. Madau, «Technical and scale efficiency in the Italian Citrus Farming: A comparison between Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) Models,» Munich Personal RePEc Archive (MPRA), vol. 41403, nº 18, pp. 1-25, 2012. [18]E. A. S. d. Pedro, Nivel de competitividad y eficiencia de la producción ganadera, Córdoba: Tesis doctoral. Departamento de Producción Animal, 2013. [19]F. Bacon, Novum Organum, Londres, 1620. [20]Seminario Metodología de la Investigación, Bogota: Facultad de Ciencias Económicas, Universidad Nacional de Colombia, 2015.  


2014 ◽  
Vol 8 (1) ◽  
pp. 67-72 ◽  
Author(s):  
Henry de-Graft Acquah

This paper highlights the sensitivity of technical efficiency estimates to estimation approaches using empirical data. Firm specific technical efficiency and mean technical efficiency are estimated using the non parametric Data Envelope Analysis (DEA) and the parametric Corrected Ordinary Least Squares (COLS) and Stochastic Frontier Analysis (SFA) approaches. Mean technical efficiency is found to be sensitive to the choice of estimation technique. Analysis of variance and Tukey’s test suggests significant differences in means between efficiency scores from different methods. In general the DEA and SFA frontiers resulted in higher mean technical efficiency estimates than the COLS production frontier. The efficiency estimates of the DEA have the smallest variability when compared with the SFA and COLS. There exists a strong positive correlation between the efficiency estimates based on the three methods.  


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