Relative Technical Efficiency Research Articles

Assessment of care provision integration in a community-based mental health system: balanced care model implementation in Andalusia (Spain)

BackgroundAndalusia is the second largest region in Spain, and it has developed a comprehensive mental health (MH) plan that encourages the consolidation of the balanced care model. However, its geographical and socioeconomic disparity is a great challenge for a community-based MH system. Both the assessment of the implementation of the MH plan and the development of new tools to support decision-making can be considered critical.ObjectivesThe present study aims (i) to assess how the integration of different types of MH care may influence system performance and (ii) to check the performance evolution of the integration process geographically regarding the small MH areas of Andalusia.MethodsThe performance of the Andalusian MH system was assessed by combining Monte Carlo simulation, fuzzy inference and data envelopment analysis. The relative technical efficiency was the main performance indicator.ResultsA correct integration of appropriate types of MH care, according to population needs, increases the performance of the Andalusian MH system both from global and regional perspectives. The spatial representation (based on small MH areas) of the results highlights how the performance depends on specific geographical characteristics. By analyzing the identified spatial clusters, defined by different management patterns depending on user and socioeconomic characteristics, benchmark areas and areas for improvement can be studied to design evidence-informed policies and interventions.ConclusionsA global analysis of MH system performance was carried out, including both the successive integration of different types of care and its spatial evolution. Although an appropriate integration of different types of MH care has a positive effect on the Andalusian MH system, this process has different profiles depending on specific geographically based user and socioeconomic characteristics. The balanced care model can be considered the paradigm for assessing the performance of a large and populated territory such as Andalusia, which has a community-based MH system. This methodological approach (performance assessment and spatial analysis) may be used as a guide for developing future evidence-informed policies and managerial interventions.

Frontier model of the environmental inefficiency effects on livestock bioeconomy.

This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

A double bootstrap data envelopment analysis model with stochastic reducible outputs and expandable inputs: An application to power plants

Clean production of electricity is not only cost-effective but also effective in reducing pollutants. Toward this end, the use of clean fuels is strongly recommended by environmentalists. Benchmarking techniques, especially data envelopment analysis, are an appropriate tool for measuring the relative efficiency of firms with environmental pollutants. In classic data envelopment analysis models, decision-makers are faced with production processes in which reducible inputs are used to produce expandable outputs. In this contribution, we consider production processes when the input and output data are given in stochastic form and some throughputs are reducible and some others are expandable. A stochastic directional distance function model is proposed to calculate the relative technical efficiency of firms. In order to evaluate firm-specific technical efficiency, we apply bootstrap DEA. We first calculate the technical efficiency scores of firms by classic DEA model. Then, the double bootstrap DEA model is applied to determine the impact of explanatory variables on firm efficiency. To demonstrate the applicability of the procedure, we present an empirical application wherein we employ power plants.

Budget monitoring, accountability practices and their influence on the efficiency of county health systems in Kenya.

Public Finance Management (PFM) practices influence the attainment of health system goals. PFM processes are implemented within the budget cycle which entails the formulation, execution, and monitoring of government budgets. Budget monitoring and accountability actors, structures, and processes are important in improving the efficiency of health systems. This study examined how the budget monitoring and accountability processes influence the efficiency of county health systems in KenyaWe conducted a qualitative case study of four counties in Kenya selected based on their relative technical efficiency. We collected data using in-depth interviews with health and finance stakeholders (n = 70), and document reviews. We analyzed data using a thematic approach, informed by our study conceptual framework. We found that weak budget monitoring and accountability mechanisms compromised county health system efficiency by a) weakening the effective implementation of the budget formulation and execution steps of the budget cycle, b) enabling the misappropriation of public resources, and c) limiting evidence-informed decision-making by weakening feedback that would be provided by effective monitoring and accountability. Devolution meant that accountability actors were closer to implementation actors which promoted timely problem solving and the relevance of solutions. Internal audit practices were supportive and provided useful feedback to health system managers that facilitated improvements in budget formulation and execution. The efficiency of county health systems can be improved by strengthening the budget monitoring and accountability processes. This can be achieved by increasing the population's budget literacy, supporting participatory budgeting, synchronizing performance and financial accountability, implementing the existent budget monitoring and accountability mechanisms, rewarding efficiency, and sanctioning inefficiency.

Economic-financial performance and value creation in the Brazilian construction industry

PurposeThis paper aims to analyze the economic-financial performance (EFP) and value creation (VC) in the Brazilian construction industry.Design/methodology/approachBased on the theories of strategy and finance, a quantitative-qualitative, descriptive and explanatory and applied study was carried out, contrasting the performance of the Direcional company and the civil construction industry – both listed on the Brazilian Stock Exchange and the Over-the-Counter Market (B3)FindingsThe analysis of the EFP in the Brazilian construction industry shows that EZTEC, Helbor, Trisul and Direcional were the companies with the best EFP in the period. The analysis of the Economic Value Added (EVA®, henceforth EVA), as a VC metric and basis for assessing the relative technical efficiency score by Data Envelopment Analysis (DEA®, henceforth DEA), revealed that the companies Direcional, EZTEC, MRV and CR2 were considered efficient throughout the period covered. The multicriteria methodology for empirical testing of the EFP and VC allowed not only contrasts Direcional's results with the other companies of the construction industry but also offered a complementary tool for comparative analysis of enterprises of different sizes, structures and realities.Research limitations/implicationsRegardless of any contextual limitations, from a theoretical point of view, the research not only helps fill the research gap aforementioned but also expands knowledge on the topic and demonstrates how this multi-criteria methodology (integrating DEA and EVA) can be used to assess EFP and VC in addition to traditional tools. However, this new approach evaluates, at the same time, corporate and sectorial effectiveness by contrasting the efficiency and efficacy (simultaneously) in the generation of performance and value of a company in relation to the industry.Practical implicationsSignificant implications for managerial practice could be noted by offering a tool to improve company performance and creating a competitive benchmarking process for analysts, investors, managers, financing agencies, shareholders, policymakers and business owners, as well as organizations and sectors in similar situations – who need to assess the EFP and VC holistically and improve their decision-making processes.Originality/valueThe uniqueness and innovation of this research come from the original multi-criteria methodology developed, applied and validated for analysis of EFP and VC. This methodology was operationalized through DEA applied to the companies' EVA, making it possible to compare corporate results and those of the whole industry in a balanced way – an unexplored issue in the literature, especially in emerging economies, opening several avenues for future research.

Impact of the workforce allocation on the technical performance of mental health services: the collective case of Helsinki-Uusimaa (Finland)

BackgroundLong-term mental health (MH) policies in Finland aimed at investing in community care and promoting reforms have led to a reduction in the number of psychiatric hospital beds. However, most resources are still allocated to hospital and community residential services due to various social, economic and political factors. Despite previous research focussing on the number and cost of these services, no study has evaluated the emerging patterns of use, their technical performance and the relationship with the workforce structure.ObjectiveThe purpose of this study was to observe the patterns of use and their technical performance (efficiency) of the main types of care of MH services in the Helsinki-Uusimaa region (Finland), and to analyse the potential relationship between technical performance and the corresponding workforce structure.MethodsThe sample included acute hospital residential care, non-hospital residential care and outpatient care services. The analysis was conducted using regression analysis, Monte Carlo simulation, fuzzy inference and data envelopment analysis.ResultsThe analysis showed a statistically significant linear relationship between the number of service users and the length of stay, number of beds in non-hospital residential care and number of contacts in outpatient care services. The three service types displayed a similar pattern of technical performance, with high relative technical efficiency on average and a low probability of being efficient. The most efficient acute hospital and outpatient care services integrated multidisciplinary teams, while psychiatrists and nurses characterized non-hospital residential care.ConclusionsThe results indicated that the number of resources and utilization variables were linearly related to the number of users and that the relative technical efficiency of the services was similar across all types. This suggests homogenous MH management with small variations based on workforce allocation. Therefore, the distribution of workforce capacity should be considered in the development of effective policies and interventions in the southern Finnish MH system.

An alternative measure of profit shifting and corporate income tax losses

The aim of this paper is to assess an alternative method of estimating the amount of profit shifting and corporate income tax revenue losses. We propose a nonstandard methodology to refine the measurement of profit shifting beyond the traditional semi-elasticity procedure. A four-stage Data Envelopment Analysis (DEA) is used to estimate the relative technical efficiency of profits before taxation reported by foreign-owned companies in Czechia. The efficiency gap resulting from the difference between the first-stage and third-stage technical efficiency scores represents the level of profit shifting. Using the statutory and average effective corporate income tax rates, we calculate the amount of corporate income tax revenue losses attributable to profit shifting. The estimated mean level of profit shifting by foreign subsidiaries involved in the manufacturing and service sectors between 2009 and 2016 is over 570 million EUR, and the mean amount of tax losses exceeds 100 million EUR. In relative terms, profit shifting leads to a decrease in total corporate income tax revenues of 2% in Czechia. Foreign-owned companies involved in the manufacturing sector are less efficient than foreign-owned companies from services industries in terms of relative technical efficiency scores, while companies involved in the service sector have a considerably high efficiency gap with respect to companies involved in the manufacturing sector.

Frontier model of the environmental inefficiency effects on livestock bioeconomy

Background: This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. Methods: The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. Results: The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. Conclusions: It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

Measuring the economic performance of transition economies: DEA-bootstrapping approach

PurposeThe paper analyzes the relative technical efficiency of the transition economies of the Western Balkans in the period 2007–2021, in comparison with the former countries with a socialist state system, today members of the European Union (EU), based on selected macroeconomic indicators and panel data.Design/methodology/approachData envelopment analysis (DEA), i.e. its extension, DEA Window analysis, is applied. Total technical efficiency, as a prerequisite of economic efficiency, is decomposed into pure technical efficiency (PTE) and scale efficiency (SE). Bootstrapping method and Mann–Whitney U test were used to check the robustness of the obtained results, i.e. efficiency values.FindingsThe results show that in 2020, all observed countries recorded a significant drop in economic efficiency as a result of a general, disproportionate drop in the value of selected macroeconomic variables, which occurred due to the global economic crisis and the slowdown in economic activity caused by the COVID-19 pandemic. This drop in efficiency was significantly greater in the former socialist states, now members of the European Union, which showed their greater sensitivity to global crises. None of the observed economies in the observed period was relatively efficient, that is, at the level of best practice, which occurred primarily as a consequence of the inefficiency of business conditions expressed in the economies of scale.Research limitations/implicationsThe main limitation of this study stems from the very nature of the concept of DEA efficiency, which is relative in nature. Also, the results and their interpretation are also significantly influenced by the choice of model variables, as shown by Lábaj et al. (2013), as well as a small number of decision-making units (DMUs). The mentioned limitations prevent unambiguous interpretation and generalization of the obtained results.Practical implicationsThe study may be of importance to economic policy makers in macroeconomic decision-making. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage on the international market.Originality/valueSince research of this type is very limited, the results of this study make a theoretical and empirical contribution to the literature, creating a basis for future research and reexamination. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage in the international market.

Dynamic comparison on the technical efficiency between China's EPEs and PEs: Two-dimensional measurement based on SFA

It is of equal importance to improve the efficiency of environmental protection enterprises (EPEs) and polluting enterprises (PEs) for Environmental Protection and Green Development, which is a micro-foundation for China's economic transformation and high-quality development. This paper redefines the efficient frontier of enterprises, distinguishing between “absolute technical efficiency” (ATE) and “relative technical efficiency” (RTE), and conducts two-dimensional measurements and dynamic comparison to examine the technical efficiency characteristics of China's EPEs and PEs listed on the A-share market, based on the stochastic frontier analysis (SFA) method. The results demonstrate that, first, the ATE of EPEs exhibits a reverse upward trend, while the ATE of PEs and A-share enterprises as a whole is declining simultaneously. Second, in contrast to the shrinkage of the ATE and RTE of PEs, the efficient frontier of EPEs has experienced rapid expansion. Third, capital utilization efficiency, rather than economies of scale effects, appears to be the main obstacle impeding the technical efficiency performance of EPEs. Therefore, improving the capital utilization efficiency and the extent of coupling and coordination between capital and labor is the key to promoting the technical efficiency of EPEs. Fourth, targeted government subsidies and tax refunds for EPEs need to be improved and an external evaluation mechanism focusing on Environment, Social and Governance (ESG) rating needs to be strengthened. Consequently, it is essential to promote the combination of top-down targeted policy support and multi-dimensional external evaluation to guide capital flows and achieve their efficient utilization, which is also the basis of the environmental protection industry's high-quality development.

The effects of provider contract types and fiscal decentralization on the efficiency of the Polish hospital sector: A data envelopment analysis across 16 health regions

BackgroundExpenditures on hospitals constitute a large proportion of total health expenditures. In Poland the share of hospital spending is higher than the European Union average. The efficiency of the Polish hospital sector merits investigation. Research goalThe goal of this study is to estimate the relative technical efficiencies of Polish hospital regions, and to measure the impacts of provider contract types, fiscal decentralization, and the 2017 reform on the relative efficiencies. MethodsUsing data from 16 hospital regions in Poland for the years 2007 to 2019, we estimate relative technical efficiencies and their determinants using a two-stage approach. In the first stage, we apply Data Envelopment Analysis, in which we assume variable returns to scale and an output orientation. In the second stage we use a truncated regression with double bootstrapping. ResultsOur findings are threefold. First, fiscal decentralization may reduce technical efficiency, but the results was not statistically significant. Second, efficiency tended to be higher in regions where a greater proportion of nurses and midwives were offered employment as opposed to consulting contracts. Contract types offered to physicians were not statistically significant. Third, the 2017 reforms seem to have had a positive impact on efficiency to date. ConclusionPolicy makers may wish to consider offering less fiscal autonomy and control to regions and encouraging employment contracts with nurses and midwives.

Efficiency: Mutual vs. Stock P-L Insurers

This paper reviews evidence from the U.S. property-liability insurance industry that examines technical efficiency between mutual and stock organizational forms. I exploit a modified slacks-based measure data envelopment analysis methodology to estimate technical efficiency of a property-liability insurer relative to a reference set consisting of all such insurers with the same organizational form. Then, I distinguish relative technical efficiency between insurers’ capacity to maximize social capital (reputational efficiency) and to maximize investment returns (investment efficiency). I document statistically significant evidence that mutual insurers outperform stock insurers in terms of reputational and investment efficiencies. My findings thus reflect a newer appreciation of organizational forms in insurance and illuminate how households make key insurance decisions.

Frontier model of the environmental inefficiency effects on livestock bioeconomy

Background: This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. Methods: The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. Results: The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. Conclusions: It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

Efficiency of public spending on human capital in Africa

Government spending on human capital continues to increase over the years. However, knowledge of the efficiency of such spending is limited. Using data from World Bank’s World Development Indicator and World Governance Indicator from 2006 to 2017 and Data Envelopment Analysis and DEA Bootstrapping models, the study examined the relative technical efficiencies of public spending on human capital and their correlates in Africa. The study found public spending on health and education in Africa to be inefficient. Efficiency was much higher in health spending than in educational spending. Factors such as institutional quality, economic growth, government expenditure, foreign direct investment, and trade openness were found to influence the efficiency of public spending on human capital. Government should put in place measures to stimulate trade, ensure institutional quality and growth of urbanization to help improve efficiency in public spending.

A Two Stage Technical Efficiency of Primary Schools in Ethiopia: The Case of Harari Regional State

This study aims to estimate relative technical and scale efficiency of primary schools in Harari Region. To measure change in productivity of school for the period 2013-2019 and to determine factors that affecting the technical inefficiency of schools, quantitative approach with a two stage Data Envelopment Analysis (DEA) employed for measuring technical efficiency of schools. Malmquist Total Factor Productivity (MTFP) index was implemented to determine overall productivity growth of school within the given period. Censored Tobit regression model was used to determine factors affecting school’s inefficiency. The result of the Constant Return to Scale DEA model shows that 10(21.7%) schools were found technically efficient, while 36(78.3%) were inefficient. The VRS DEA model indicated that fourteen (30.4%) schools were technically efficient and thirty two (69.6%) schools were technically inefficient. Out of the total schools, 47.8% schools were found to be scale efficient, while 52.2% were scale inefficient. Further, non-government schools have higher efficiency scores (99.6 %) than their counterpart government schools (91.6%). The Tobit model regression result indicated that school’s ownership and location have a significant and negative sing, while coefficients of student-teacher ratio, student-class ratio and teacher’s qualification and experiences had a positive singe with inefficiency of schools. Keywords: Data envelopment analysis, technical efficiency, productivity, Tobit model. DOI: 10.7176/JEP/13-25-01 Publication date: September 30 th 2022

Efficiency analysis of primary healthcare facilities in Afghanistan

BackgroundAfghanistan’s health system is unique in that primary healthcare is delivered by non-governmental organizations funded by multilateral or bilateral donors, not the government. Given the wide range of implementers providing the basic package of health services, there may be performance differences in service delivery. This study assessed the relative technical efficiency of different levels of primary healthcare services and explored its determinants.MethodData envelopment analysis was used to assess the relative technical efficiency of three levels of primary healthcare facilities (comprehensive, basic, and sub-health centers). The inputs included personnel and capital expenditure, while the outputs were measured by the number of facility visits. Data on inputs and outputs were obtained from national health information databases for 1263 healthcare facilities in 31 provinces. Bivariate analysis was conducted to assess the correlation of various elements with efficiency scores. Regression models were used to identify potential factors associated with efficiency scores at the health facility level.ResultsThe average efficiency score of health facilities was 0.74 when pooling all 1,263 health facilities, with 102 health facilities (8.1%) having efficiency scores of 1 (100% efficient). The lowest quintile of health facilities had an average efficiency score of 0.36, while the highest quintile had a score of 0.96. On average, efficiency scores of comprehensive health centers were higher than basic and sub-health centers by 0.11 and .07, respectively. In addition, the difference between efficiency scores of facilities in the highest and lowest quintiles was highest in facilities that offer fewer services. Thus, they have the largest room for improvement.ConclusionsOur findings show that public health facilities in Afghanistan that provide more comprehensive primary health services use their resources more efficiently and that smaller facilities have more room for improvement. A more integrated delivery model would help improve the efficiency of providing primary healthcare in Afghanistan.

Assessment of the performance of assertive community treatment: the case of Bizkaia (Spain)

IntroductionA mental health (MH) assertive community treatment (ACT) is always designed expecting for a decrease in the pressure (visits and readmissions) in inpatient services and to increase care quality. An appropriate management of ACT provision can be crucial to develop a balanced community-based MH ecosystems.ObjectivesTo assess the impact of the ACT on the performance of the MH ecosystem of Bizkaia (Basque Country, Spain).MethodsThe ecosystem is structured by 19 MH areas, supported by 5 ACT teams. Here ACT provides high intensity mobile outpatient care to people suffering from severe mental disorders. The impact of these teams on the ecosystem performance was assessed by Monte-Carlo simulation, the Data Envelopment Analysis (DEA) and fuzzy inference. The input variables were the availability, number of psychiatrics, nurses and total of professionals of ACT services in each area. The outputs were: frequentation, incidence and prevalence of ACT services in each MH area. Performance indicators were: relative technical efficiency (RTE), statistical stability and entropy.ResultsThe global ecosystem performance was high (RTE on average=0.799 -input DEA orientation- and 0.825 -output orientation- up to 1, the maximum), the stability was medium-low (respectively 38,67% and 13.64% up to 100%, the maximum) and the entropy was medium-high (respectively 70,41% and 65.9% up to 100%, the maximum).ConclusionsResults highlighted a positive impact of ACT in Bizkaia. Nevertheless, stability and entropy levels showed the existence of a high structural variability in ACT services due to the necessity of adjusting them to the user’s specific needs.DisclosureNo significant relationships.

Application of a decision support system for providing better mental health care: the case of the Basque Country (Spain)

IntroductionDecision Support Systems (DSS) are appropriate tools for guiding policymaking processes in Mental Health (MH) management, especially where a balanced and integrated care provision is required.ObjectivesTo assess the performance of a MH ecosystem for identifying benchmark and target-for-improvement catchment areas according to the Balanced Care model.Methods The MH provision, distinguishing inpatient, day and outpatient main types of care, has been assessed in the Mental Health Network of Gipuzkoa (Basque Country, Spain) using a DSS, integrating Data Envelopment Analysis, Monte-Carlo Simulation and Artificial Intelligence. 13 catchment areas, defined by a reference MH centre, are the units (universe) for the analysis. The indicators for MH ecosystem performance were: relative technical efficiency, stability and entropy, for identifying both benchmarking and target-for-improvement areas. The analysis of the differences between the two groups can be used to design organizational interventions.ResultsThe Mental Health Network of Gipuzkoa showed high global efficiency scores, but it can be considered statistically unstable (small changes in variable values can have relevant impacts on its performance). For a global performance improvement, it is recommended to reduce admissions and readmissions in inpatient care, increase workforce capacity and utilization of day care services and, finally, increase the availability of outpatient care services.ConclusionsThis research offers a guide for evidence-informed policy-making to improve MH care provision in the main types of care and provide aftercare. The characteristics of the area to be improved are critical to design interventions and assess their potential impact on the MH ecosystem.DisclosureNo significant relationships.

No service is an island: towards an ecosystem approach to mental health service evaluation.

No service is an island: towards an ecosystem approach to mental health service evaluation.

Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull

In the technical efficiency evaluation area, it may happen that many observations obtain a similar relative technical efficiency status, making it difficult to discriminate between them. The determination of super-efficiency has been a way of solving this problem by providing a method to differentiate between the performance of observations. Despite the existence of some approaches dealing with the notion of super-efficiency in the literature, there have been few attempts to address this problem from the standpoint of machine learning techniques. In this paper, we fill this gap by adapting Random Forest to determine super-efficiency in the context of the Free Disposal Hull (FDH) technique. The new super-efficiency approach is robust to resampling on inputs and data. Additionally, we show how the new approach could be a possible solution for dealing with the curse of dimensionality problem; typically associated with FDH. Furthermore, exploiting the adaptation of Random Forest, a new method for assessing the importance of input variables is introduced. Finally, the advantages of the proposed approach are illustrated through a real example.