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This chapter begins with a brief discussion of variations in productive efficiency using airlines as an example. It then presents the main purpose of the book, which is to study inefficiency in production and its impact on economic and financial performance. The chapter then provides background material and focuses on hypotheses that have been prop...
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This paper examines the relationship between productivity, markup, scale economies, and the business cycle. The paper contributes to the literature by presenting a simple econometric framework that permits simultaneous estimation of the changes in productivity, markup, and scale economies from a panel of firm-level data. The framework is then appli...
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... Nonparametric in nature, DEA aligns with the error term assumptions of the SFA, making it an effective benchmarking tool for evaluating production efficiency. Unlike other methods, DEA does not require a functional or distributional form specification and allows for the relaxation of the assumption of 'constant returns to scale' production [3,[40][41][42]. ...
This study focuses on evaluating the technical and scale efficiencies of smallholder pineapple farmers in Ghana’s Central Region. We surveyed 320 participants selected using random sampling and applied an input‐oriented Data Envelopment Analysis (DEA) method to gauge their technical, pure, and scale efficiencies. Our findings indicate that the mean technical efficiency among these farmers is 0.505, with individual scores ranging from 0.079 to 1.000. Notably, 90.82% of the farmers are operating below maximum efficiency levels, suggesting a potential input reduction of up to 49.5% while maintaining current production levels. Relaxing the assumption of constant returns under Variable Returns to Scale (VRS) conditions reveals a notable improvement in technical efficiency, with 10.82% more farmers achieving optimal efficiency levels. Furthermore, our analysis highlights scale inefficiencies, with 67.26% of farmers operating below optimal scale levels. By increasing production by 22.8%, these scale‐inefficient farmers could enhance their efficiency and productivity within existing technological frameworks. These findings underscore the importance of collaborative efforts among policymakers, practitioners, and stakeholders within the agricultural value chain to implement interventions such as improving access to technology and innovation for smallholder farmers and making necessary investments in farmer education and training programs to enhance both technical and scale efficiencies in Ghana’s pineapple sector. Such initiatives can drive sustainable growth, improve farmers’ livelihoods, and bolster the sector’s overall competitiveness.
Keywords: data envelopment analysis; technical efficiency; scale efficiency; farming production
... Nonparametric in nature, DEA aligns with the error term assumptions of the SFA, making it an effective benchmarking tool for evaluating production efficiency. Unlike other methods, DEA does not require a functional or distributional form specification and allows for the relaxation of the assumption of 'constant returns to scale' production [3,[40][41][42]. ...
This study focuses on evaluating the technical and scale efficiencies of smallholder pineapple farmers in Ghana's Central Region. We surveyed 320 participants selected using random sampling and applied an input-oriented Data Envelopment Analysis (DEA) method to gauge their technical , pure, and scale efficiencies. Our findings indicate that the mean technical efficiency among these farmers is 0.505, with individual scores ranging from 0.079 to 1.000. Notably, 90.82% of the farmers are operating below maximum efficiency levels, suggesting a potential input reduction of up to 49.5% while maintaining current production levels. Relaxing the assumption of constant returns under Variable Returns to Scale (VRS) conditions reveals a notable improvement in technical efficiency, with 10.82% more farmers achieving optimal efficiency levels. Furthermore, our analysis highlights scale inefficiencies, with 67.26% of farmers operating below optimal scale levels. By increasing production by 22.8%, these scale-inefficient farmers could enhance their efficiency and productivity within existing technological frameworks. These findings underscore the importance of collaborative efforts among policymakers, practitioners, and stakeholders within the agricultural value chain to implement interventions such as improving access to technology and innovation for smallholder farmers and making necessary investments in farmer education and training programs to enhance both technical and scale efficiencies in Ghana's pineapple sector. Such initiatives can drive sustainable growth, improve farmers' livelihoods, and bolster the sector's overall competitiveness .
... Productivity = output/input. Productivity is an important driver for economic growth and prosperity (Fried et al., 2008) for companies. The most frequently used indicators for measuring productivity are labour productivity and capital productivity. ...
Efficient use of production resources in enterprises is necessary for increasing their competitiveness and the potential for their future development. In today's global world, companies are forced to invest in new technologies that are both more energy-efficient and more environmentally friendly, including in the food industry. The paper focusses on the efficiency of production factors in relation to their economic success. The aim is to find possible variants of the development of the links between capital labour ratio and labour productivity in relation to the development of profitability of returns. Empirical analysis coved 2,526 enterprises in food industry in four examined European countries (Visegrad group -V4) - Czech Republic, Hungary, Poland, Slovak Republic. The contribution of the paper is the generalization of the links between the indicators of the efficiency of production factors in the form of recommended inequalities that can be used by enterprises for economically successful development.
... In microeconomics theory, the concept of productivity and efficiency is seen from two different but related concepts. The productivity of a firm can be briefly defined as the ratio of output(s) to its input(s) (Coelli et al., 2005;Fried et al., 2008;Rasmussen, 2011). The productivity of a firm could be measured using partial productivity, such as yield per hectare, output per labor, or total factor productivity (TFP) (ratio of aggregate output to aggregate input). ...
This study examined the effects of research-based recommended cereal production practices on the technical efficiency of farm households based on household-level data generated from questionnaire surveys, focus group discussions, and key informant interviews. The technical efficiency scores were estimated using the stochastic meta-frontier approach because it allows addressing the expected differences in production technologies. Tobit regression framework was applied to identify factors related to farm inefficiency. Results showed mean technical efficiency of 58%, implying that the farm households can improve cereal output by about 36% with the current level of input mix and technologies. The t-test results revealed farm households who adopted high-yielding varieties with research-based recommended production practices were technically more efficient than their counterparts. Our econometric model results also indicated that the use of high-yielding varieties and research-based recommended seed rate affects the technical efficiency of farm households positively and significantly. In addition, we find gender, age, mobile telephone ownership, cooperative membership, access to input market, and crop damage as significant factors affecting the efficiency of farm households. Our findings highlight the importance of addressing technology adoption gaps and gender-based disparities, expanding access to information and modern inputs, strengthening social capital, and adopting climate change adaptation practices to improve the efficiency of farm households.
... Efficiency focusses on the quantity of resources used in relation to the result. "It is measured by comparing observed and optimum cost, revenue, profit, or whatever goal the producer is assumed to pursue, subject, of course, to any appropriate constraints on quantities and prices" (Fried et al., 2008). The concept of efficiency is too narrow for the purpose of this research, as it takes into account only one aspect (the cost/benefit ratio), without considering neither the process nor the outcome of a policy. ...
The socioeconomic impacts of COVID-19 have been felt worldwide, but especially in low-income countries. In these contexts, the effects of the global crisis have exacerbated the need for humanitarian assistance. While humanitarian programmes have become more critical, ensuring their effectiveness remains a challenge. The thesis investigates the factors that may affect humanitarian aid programmes’ effectiveness by looking at the European Union (EU), one of the top donors worldwide. Therefore, the two research questions are, firstly: why does the effectiveness of EU humanitarian aid programmes vary?; and secondly: What are the factors causing this variation? The research is meaningful because it addresses a critical, current challenge and because it also attempts to fill a gap in EU foreign policy literature by empirically assessing the external effectiveness of the EU ‘on the ground’ in contexts of wars and natural crises. It also assesses the relationship that it has with United Nations (UN) agencies and Non-Government Organizations (NGOs) in the field, in a sector, humanitarian aid, that has been overlooked as part of development aid. Following a precise definition of effectiveness and based on empirical data gathered through official reports, documents and interviews with UN, NGO, and EU officials, the thesis seeks to answer to the research questions by formulating three hypotheses on the factors that could influence the effectiveness and by empirically assessing them in the context of Myanmar, Lebanon and Mozambique, between 2015 and 2017. The hypotheses include: the EU Member States internal cohesiveness and coordination with Directorate-General for European Civil Protection and Humanitarian Aid Operations (DG ECHO) on the ground; delegation and coordination in the field between DG ECHO and UN agencies/NGOs; the national authorities’ attitude vis-à-vis EU humanitarian aid programmes. The research finds that the last two factors can be particularly decisive in the effectiveness of the programmes and proposes a formula for effectiveness. It suggests that EU humanitarian aid programmes should focus on resilience and preparedness, that the agents involved should closely coordinate, and the use of new technologies to speed up processes should be increased. Finally, the thesis suggests pathways to generalise these findings to non-EU humanitarian and to development actors, such as the World Bank.
... Performance (third in the ranking and often 2.97%) is a term quite used in this type of literature to refer to the results of local government actions or interventions from a more generic perspective and not necessarily in terms of efficiency. In this regard, performance can also be assessed in terms of effectiveness or productivity (Fried et al., 2008), for example, and not only in terms of efficiency in the area of public resource allocation (Rueda-López et al., 2020). Precisely, in the work of Balaguer-Coll et al. (2007), one of the most cited works (Table 1) in this field is focused on the determinants of local government performance in a region of Spain. ...
This paper has reviewed the international literature on the explaining factors of efficiency of local governments from 1990 to June 2019. The main objective of this work is to explore the dynamics of the development of this line of research, not only to find out the terminology preferences that have dominated the pre‐ and post‐crisis period in this field but also to identify the latest worldwide research trends. For this purpose, a bibliometric and cluster analysis by fractional accounting has been carried out. The principal result of this article is twofold. First, during the whole period 1990–2019, the ranking of the most used terms is dominated by the keywords of the publications in the second subperiod 2008–2019. Second, the analysis of the latest trends, which has been extended until June 2021, shows that in recent years, the study of the determinants of local government efficiency has revolved around concepts related to environmental issues and new forms of local management.
... Ancak performans ölçümü, son yıllarda yeni bir önem ve olağanüstü gelişme kazanmıştır. Performans ölçümü, işletme stratejisini uygulamak ve organizasyonu kontrol etmek adına önemli bir yönetim aracı ve kontrol mekanizması olarak görülmektedir (Fried, Lovell, & Schmidt, 2008;Khurram Khan, 2011). ...
İşletme yönetiminin işletme üzerinde kontrolü sağlamak için kullanacağı en önemli araçlardan biri performans ölçümüdür. Performans ölçümü, işletmelerin faaliyetlerine ilişkin geri bildirim sağlayarak kendinden beklenen sorumluluğu yerine getirmektedir. Performans ölçüm süreci boyunca işletmenin her kademesinde muhtelif göstergeler kullanılmaktadır. Etkinlik, etkililik, verimlilik, kârlılık ve performans bu süreçte en çok kullanılan göstergelerdir. Ancak bu kavramlar sıklıkla birbirleri yerine kullanılmakta ve karıştırılmaktadırlar. Bu çalışmada, ilgili kavramlara ilişkin farklılıklara, ilişkilere ve karşılaştırmalara dair açıklamalar yapılarak konuya ilişkin bir kavramsal çerçeve oluşturulması amaçlanmaktadır. Yapılan karşılaştırmalar neticesinde etkinliğin girdiler ile ilgili işlerin doğru; etkililiğin çıktılar ile ilgili doğru işlerin; verimliliğin ise etkinlik ve etkililik birleşimi olarak doğru işlerin doğru yapılmasını ifade ettiği görülmektedir. Bunların sonucunda kalite ve yenilik gibi unsurlar ile birlikte işletmelerin kârlılık sağlayabileceği belirtilmektedir. Son aşamada ise büyüme ve pazar payı benzeri faktörler neticesinde işletme performansı belirlenmektedir. Özetle, etkinlik ve etkililik gibi içsel göstergeler ile dar bir alanda başlayan performans ölçüm süreci, dışsal göstergeleri de içine alan kârlılık ve performans göstergeleri ile geniş bir alanda sonlanmaktadır. -----Performance measurement is one of the most important tools that business management will use to maintain control over the business. Performance measurement fulfills the expected responsibility by providing feedback on operating activities. Various indicators are used at all levels of the business throughout the performance measurement process. Efficiency, effectiveness, productivity, profitability, and performance are the most used indicators in this measurement process. However, these indicators are often used interchangeably and confused. In this study, it is aimed to create a conceptual framework on the subject by making explanations about the differences, relationships, and comparisons regarding the indicators. As a result of the comparisons made, the following can be expressed. Effectiveness is doing things right with inputs. Effectiveness is doing the right things about the outcomes. Productivity is doing the right things right, as a combination of efficiency and effectiveness. As a result of these and with factors such as quality and innovation, it is stated that businesses can achieve profitability. In the next stage after profitability, business performance is determined as a result of factors such as growth and market share. In summary, the performance measurement process, which starts in a narrow field with internal indicators such as efficiency and effectiveness, ends in a wide area with profitability and performance indicators that include external indicators.
... Farrell and Fieldhouse (1962) extended the 1957 model to accommodate increasing returns to scale [43]. Estimation methods of the best practice frontier have evolved significantly over the past few decades and a rich menu is now available including parametric, nonparametric, stochastic, and deterministic formulations [44]. ...
... The initial approach was in two stages, where TE was first generated parametrically or nonparametrically and then the TE scores were regressed on a set of variables. This two-stage approach has been criticized by several authors for introducing statistical bias and this led Fried, Lovell and Schmidt (2008) to write: "We hope to see no more two-stage models" (p. 39) [44]. ...
... This two-stage approach has been criticized by several authors for introducing statistical bias and this led Fried, Lovell and Schmidt (2008) to write: "We hope to see no more two-stage models" (p. 39) [44]. Several one-step SPF models have been introduced including Battese and Coelli (1992), which uses panel data where the temporal pattern of TE is the same for all units in the sample, and Battese and Coelli (1995), which allows for time-varying inefficiency effects and accommodates explanatory variables related to technical inefficiency [59,67]. ...
... Because of the flexibility of DEA, researchers in a number of fields have quickly acknowledged these techniques as an excellent methodology for modeling operational processes. The empirical orientation and absence of a priori assumptions have resulted in numerous studies involving best-practice identification in a wide array of sectors -for a comprehensive introduction and a complete list of applications see Fried, Lovell, and Schmidt (2008). Indeed, the popularity of DEA has increased exponentially in these years as recent volumes devoted to specific sectors and industries bear witness; e.g., Blackburn, Brennan, and Ruggiero (2014), Ozcan (2014), Paradi, Sherman, and Tam (2018) and Khezrimotlagh and Chen (2018). ...
The Data Envelopment Analysis Toolbox is a new package for MATLAB that includes functions to calculate the main data envelopment analysis models. The package includes code for the standard radial input, output and additive measures, allowing for constant and variable returns to scale, as well as recent developments related to the directional distance function, and including both desirable and undesirable outputs when measuring efficiency and productivity; i.e., Malmquist and Malmquist-Luenberger indices. Boot-strapping to perform statistical analysis is also included. This paper describes the methodology and implementation of the functions, and reports numerical results using a reliable productivity database on US agriculture to illustrate their use.
... In general, efficiency scores of units are measured in terms of their distance from an estimated production frontier (Simar 1992;Simar and Wilson 2000;Rosko and Mutter 2008). However, the "true" potential/frontier is unknown and thus, approximation (i.e., often dubbed as "best-practice" frontier) is required (Fried, Lovell, and Schmidt 2008). (2005) municipalities population, enrollment per school, student better the effectiveness in resource utilization as attendance per school, students who get measured by efficiency indices promoted to the next grade per school, students in the appropriate grade per school, households with access to safe water, households with access to sewage system, households with access to garbage collection I: Current spending, number of teachers, rate of infant mortality, and hospital and health services Explanatory variables for efficiency: Spatial and localization effects, socioeconomic impacts (e.g., income level and poverty proxy), royalty revenues on oil and water, economic of scale indicators (e.g., population density and urbanization rate), political impacts (e.g., mayor's political party), management variables (e.g., proxy for a good fiscal administration such as the degree to which the real estate is up-to-date and participation in intermunicipal consortia) period 1978-2005 Education indicator -the ratio of there was a significant overall improvement in the the number of teachers and staff in expenditure efficiency of local governments. ...
... Despite the difference in methods (i.e., nonparametric and parametric approaches) used in constructing the frontier, DEA and SFA are both considered as analytically rigorous benchmarking approaches to measure efficiency relative to a frontier (Fried, Lovell, and Schmidt 2008). However, extant studies (e.g., Borger and Kerstens 1996;Daraio and Simar 2007;Simar and Wilson 2007) point out some methodological issues in the use of two-stage 7 It does not assume or predetermine the functional form of the efficient frontier (Boetti, Piacenza, and Turati 2012;Seifert and Nieswand 2014), which indicates the maximum quantity of outputs that can be produced using available inputs (i.e., production frontier) and also, the minimum quantity of inputs that should be utilized to produce a certain level of output (i.e., cost frontier) [Hollingsworth 2008;Belotti, Daidone, Ilardi, and Atella 2013]. ...
... However, extant studies (e.g., Borger and Kerstens 1996;Daraio and Simar 2007;Simar and Wilson 2007) point out some methodological issues in the use of two-stage 7 It does not assume or predetermine the functional form of the efficient frontier (Boetti, Piacenza, and Turati 2012;Seifert and Nieswand 2014), which indicates the maximum quantity of outputs that can be produced using available inputs (i.e., production frontier) and also, the minimum quantity of inputs that should be utilized to produce a certain level of output (i.e., cost frontier) [Hollingsworth 2008;Belotti, Daidone, Ilardi, and Atella 2013]. 8 Or functional form of the best-practice frontier (Boetti, Piacenza, and Turati 2012) 9 Stochastic in nature which enables econometric approach to "attempt to distinguish the effects of noise from those of inefficiency, thereby providing the basis for statistical inference" (Fried, Lovell, and Schmidt 2008) 10 Banker and Natarajan (2008) adopted a DEA-based stochastic frontier estimation framework which allowed for both one-sided inefficiency deviations and two-sided random noise. 11 Aside from the estimation of the frontier, estimation of deviations from the frontier is another interest in modern efficiency analysis. ...
The study analyzes the efficiency implications of fiscal decentralization using stochastic
frontier analysis (SFA). It uses LGU health expenditure (in per capita real terms) as input. The
output variables of interest include access to safe water and sanitation, health facility-based
delivery, and access to hospital inpatient services. It also uses LGU income and its major
components (i.e., own-source revenue and IRA, in per capita real terms) as covariates; as well
as the health expenditure decentralization ratio to account for fiscal autonomy on the
expenditure side and two measures of fiscal decentralization to account for financial/fiscal
autonomy of the local government units (LGUs) on the income side (i.e., the ratio of LGU ownsource
revenue to LGU expenditures and ratio of LGU own-source revenue to LGU income)
as factors affecting efficiency. The findings of SFA lend empirical evidences to what the
literature says about the health devolution experience in the country. Issues on mismatch
between local government fiscal capacity and devolved functions, fragmentation of health
system, existence of two-track delivery system, and unclear expenditure assignments, among
others inevitably create inefficiency. These issues should be addressed to fully reap the
potential benefits (e.g., efficiency gains) from fiscal decentralization, particularly health
devolution.
