Valuing environmental factors in cost-benefit analysis using data envelopment analysis

Environmental cost-benefit analysis (ECBA) is used for the social evaluation of investment projects and policies that involve significant environmental impacts. Economic valuation of environmental impacts forms one of the critical steps of ECBA. We develop a new method for this purpose, which does not require price estimation for environmental impacts using stated or revealed preference methods. Our approach is based on data envelopment analysis (DEA), which is modified to ECBA by using absolute shadow prices instead of relative prices. We also discuss how the method can be used for sensitive analysis in ECBA. We illustrate the method by means of a hypothetical numerical example.     

Measuring the efficiency of health systems of OECD countries by data envelopment analysis

This study aims to assess the efficiency of health sectors of 34 OECD countries by employing input-oriented data envelopment analysis (DEA) method both under constant and variable returns to scale assumptions. In the analysis, the number of doctors, number of patient beds and health expenditure per capita were used as input variables and life expectancy at birth and infant mortality rate were used as outputs. At the first stage, DEA analysis was performed for 34 countries, and at the second stage outlier 8 countries were eliminated to form a more homogeneous group and to achieve more accurate results. 11 of the 26 countries were found to have efficient health systems, and there is room for efficiency improvements in health sector in the remaining 15 countries.     

The use of data envelopment analysis for the detection of price above the competitive level

Economic theory can predict the impact of exogenous influences on the equilibrium prices in a market. However, it is difficult to measure the magnitude of such effects because the appropriate data are usually not available. In this paper a new approach to comparing prices is explored using individual firm data which are typically available. If the firms in different markets can be assumed to use the same technology, price differentials can be inferred from the estimates can be assumed to use the same technology, price differentials can be inferred from the estimates of best practice frontiers. The new approach is applied to data on the Swiss construction industry in different cantons. In some cantons the market can be said to be competitive, in others non-competitive procurement rules are expected to raise equilibrium prices. The data envelopment analysis estimates the price differential to be approximately equal to 7.5%.Helpful criticism from participants of a seminar at the Business Institute of the University of Vienna are gratefully acknowledged.     

Economies of scale in the US computer industry: An empirical investigation using data envelopment analysis

Up to recently, economists have had no good tools to measure the returns to scale of individual corporations in an industry. Data envelopment analysis (DEA) is a linear programming technique for determining the efficiency frontier (the envelope) to the inputs and outputs of a collection of individual corporations or other productive units. While DEA offers an avenue for calculating the returns to scale of individual corporations, the approach has been riddled by mathematical complications arising from the possibility of alternate optima. The present paper develops theory for calculating the entire range of these alternate optima. Furthermore, in a quite ambitions empirical application, DEA is employed to determine the time path of returns to scale of all publicly held U.S. computer companies over the time period 1980–1991. For the great majority of companies, a unique time path is obtained; only in less than 4 percent of the linear programming calculations is an entire range of alternate optima obtained. The results indicate that the computer industry was polarized into two camps: large aging corporations with decreasing returns to scale, and swarms of small upstart companies with advanced technology exhibiting increasing returns to scale.     

Impact of input substitution and output transformation on data envelopment analysis decisions

Data envelopment analysis (DEA) can aid managerial decision-making because it offers an opportunity to measure organizational performance in a holistic manner, aggregating data from partial indicators into a single comprehensive measure. However, there are some methodological hazards associated with the use of DEA that are especially relevant to managerial decisions, but which have been largely ignored in the literature. Herein, we identify and show the impact of a ubiquitous methodological hazard in DEA modelling – the economic assumptions regarding input substitutions and output transformations.     

A two-stage translog marginal cost pricing approach for Floridian hospital outputs

Since the passage of the Affordable Care Act (ACA) of 2010, issues still remain regarding the mandated purchase of insurance to ensure more universal coverage. One such issue is the pricing of these insurance packages and whether or not the reimbursements will cover necessary services. Therefore, policy concerns exist that increasing the number of insured individuals may not curtail costs. Conversely, providers may not wish to treat patients covered by excessively frugal plans such as Medicaid; hence the trade-offs between access and cost control. In this article, we present findings from a cost function and a productivity approach to determine the marginal cost of providing inpatient hospital care for hospitals operating in Florida during 2005. Using these methodological approaches, we are able to use the marginal rate of transformation to determine the relative marginal costs while controlling for hospital technical and allocative inefficiency. Our work differs from earlier articles as we avoid the Greene problem for cross-sectional models through a two-step approach. By including both reimbursement rates under conditions of hospital efficiency, we can ascertain payment schemes that should, at least in theory, cover necessary costs for patient care without leading to excessive input usage.     

Contract farmer and poultry farm efficiency in Bangladesh: a data envelopment analysis

The objective of this article is to determine the efficiency of the poultry farm in Bangladesh and to assess the influence of contract farming system, using a data envelopment analysis. Seventy-five commercial poultry farms (25 and 50 independent and contract farms, respectively) were randomly selected. The results reveal that efficiency scores vary across sample farms. To explain some of these variations, the efficiency scores were regressed on some human capital variables and farming system using a Tobit model. The study also estimates elasticities to provide the information on the magnitude of the influence of variables on Technical Efficiency (TE), Allocative Efficiency (AE) and Economic Efficiency (EE). The results show that the contracting system is positively and significantly related to the farm's TE, AE and EE. This is expected because under contractual agreement, in order to obtain sufficient supplies of the right quality of poultry meat at the right time, the company provides technical know how assistance through company's recruited supervisor, production inputs and services, and production credit along with intensive supervision, which in turn improves farm efficiency. Thus, by receiving technical know how contract farmers have gained more knowledge on their resource and practices, which enables them to use resources more efficiently. Empirical results can provide crucial information to policy makers that improve poultry farm efficiency.     

Public and private inputs in aggregate production and growth: a cross-country efficiency approach

In a cross section of OECD countries, we replace the macroeconomic production function by a production possibility frontier, total factor productivity being the composite effect of efficiency scores and possibility frontier changes. We consider, for the periods 1970, 1980, 1990 and 2000 one output – GDP per worker – and three inputs – human capital, public physical capital per worker and private physical capital per worker. We use a semi-parametric analysis, computing Malmquist productivity indexes, and we also resort to stochastic frontier analysis. Results show that private capital is important for growth, although public and human capital also contribute positively. A governance indicator, a nondiscretionary input, explains inefficiency. Better governance helps countries to achieve a better performance. Nonparametric and parametric results coincide rather closely on the movements of the countries vis-à-vis the possibility frontier and on their relative distances to the frontier.     

Environmental cost-benefit analysis of alternative timing strategies in greenhouse gas abatement: A data envelopment analysis approach

Assessing the benefits of climate policies is complicated due to ancillary benefits: abatement of greenhouse gases also reduces local air pollution. The timing of the abatement measures influences both the economic costs and ancillary benefits. This paper conducts efficiency analysis of ten alternative timing strategies, taking into account the ancillary benefits. We apply the approach by Kuosmanen and Kortelainen [Valuing Environmental Factors in Cost-Benefit Analysis Using Data Envelopment Analysis, Ecological Economics 62 (2007), 56-65], which does not require prior valuation of the environmental impacts. The assessment is based on synthetic data from a dynamic applied general equilibrium model calibrated to The Netherlands. Our assessment shows that if one is only interested in GHG abatement at the lowest economic cost, then equal reduction of GHGs over time is preferred. If society is willing to pay a premium for higher ancillary benefits, an early mid-intensive reduction strategy is optimal.     

Pursuing efficiency: a data envelopment analysis of MFIs in Latin America

This article analyses the overall profitability efficiency (PE) of Microfinance Institutions (MFIs) in Latin America. The PE of each MFI in the study is broken down into two components: pure technical efficiency and scale efficiency. One data envelopment model is used to analyse each component. Each MFI was labelled as either a bank, cooperative and credit union, nonbanking financial institution or non-governmental organization, and then the analysis was performed on each separate group. The results suggest that, on average, banks are the most efficient MFIs; while NGOs are, on average, the least efficient MFIs. On average, all 4 groups are more pure technically efficient than scale efficient. Banks, nongovernmental organizations, nonbanking financial institutions, cooperatives and credit unions all seem to have problems with scale efficiency. Many MFIs seem to be operating on the increasing returns to scale frontier and are in a more favourable position for expansion.     

The efficiency of social public expenditure in European countries: a two-stage analysis

Do European countries differ in the efficiency of their welfare policies? And which factors can account for such variability? To address these questions, we perform a two-stage efficiency analysis. First, based on a composite output indicator for social protection expenditure, we measure efficiency by means of the Free Disposable Hull and Data Envelopment Analysis techniques. Second, we perform an econometric analysis to identify the factors that can be associated to cross-country differences. We find that countries scoring higher efficiency have higher education and GDP levels, a smaller population size, a lower degree of selectivity of their welfare systems and a lower corruption level.     

Risk management and dynamic network performance: an illustration using a dual banking system

This study applies dynamic network data envelopment analysis to compare a dual banking system, namely conventional and Islamic banks, with emphasis on risk measures. Non-oriented, variable return-to-scale dynamic network slacks-based measure is used to model the banking performance for the period 2008–2012. Under the consideration of risk measures, the findings highlight that Islamic banks excel in managerial efficiency while conventional banks surpass in profitability efficiency. Furthermore, the regression results find that the number of directors on the risk management committee has a positive impact on banking performance. Meanwhile, the high number of independent directors improves the profitability efficiency but worsens the managerial efficiency.     

The performance of German water utilities: a (semi)-parametric analysis

Germany's water supply industry is characterized by a multitude of utilities and widely diverging prices, possibly resulting from structural differences beyond the control of firms’ management, but also from inefficiencies. In this article, we use Data Envelopment Analysis and Stochastic Frontier Analysis to determine the utilities’ Technical Efficiency (TE) scores based on cross-sectional data from 373 public and private water utilities in 2006. We find large differences in TE scores even after accounting for significant structural variables like network density, share of groundwater usage and water losses.     

Treatment of candidemia with echinocandins: data on hospital resource use from a real world setting

Abstract

Objective:

Real-world data on patients treated with echinocandins for candidemia are limited. This study examined the effect of three echinocandin-based treatment regimens on resource utilization in patients with Candida infection.

Research design and methods:

A retrospective cohort study of patients hospitalized between 2005 and 2010 with a blood culture positive for Candida. Length of stay (LOS) following AF initiation (post-AF LOS) and total days with AF treatment were compared in patients treated with three different echinocandin regimens: patients with echinocandin only, patients who received fluconazole prior to an echinocandin (fluconazole-echinocandin), and patients who received an echinocandin prior to fluconazole (echinocandin-fluconazole). Generalized linear models were used to adjust for confounders.

Results:

A total of 647 patients met inclusion criteria. Patients treated with echinocandin only were more acutely ill, having more organ dysfunction and sepsis. Unadjusted post-AF LOS was significantly greater in the groups that received both echinocandin and fluconazole (mean, 13.1 days for echinocandin-only vs 25.5 and 21.2 days for fluconazole-echinocandin and echinocandin-fluconazole groups, respectively, p?<?0.001). These groups also had a higher total number of days with AF orders. These differences remained after multivariate adjustment and in survivor-only analyses. Compared with echinocandin-only treatment, the average marginal effect of fluconazole-echinocandin and echinocandin-fluconazole regimens were associated with significantly longer adjusted post-AF LOS (by 7.2 days and 9.3 days, respectively, p?<?0.001) and significantly more adjusted total AF days (by 5.3 days for fluconazole-echinocandin and 6.5 days for echinocandin-fluconazole patients, p?<?0.001). Limitations included lack of visibility to specific reasons for therapy changes.

Conclusions:

Fluconazole before or after echinocandin was associated with significantly greater resource utilization than echinocandin use alone.     

Technological progress and scientific indicators: a panel data analysis

Total factor productivity (TFP) is generally interpreted to be a proxy for technological advancement. In this paper, we use stochastic frontier analysis to decompose the growth in TFP into three components: technological progress, scale effect and change in technical efficiency. Then, we conduct a comprehensive panel data analysis using the technological progress component of the TFP growth and several scientific and technological indicators using data from 160 countries over the period from 1960 to 2009. Our results generally show that the technological progress component of the TFP growth properly reflects certain dimensions of actual scientific and technological progress. However, we also find that this result is somewhat sensitive to different econometric specifications and assumptions.     

Dynamic environmental performance analysis: A Malmquist index approach

This article presents a general framework for dynamic environmental performance analysis by generalizing the approach proposed by Kuosmanen and Kortelainen [Kuosmanen, T., Kortelainen, M., 2005. Measuring Eco-Efficiency of Production with Data Envelopment Analysis. Journal of Industrial Ecology 9(4), 59-72.] from a static to a dynamic setting. For this purpose we construct an environmental performance index (EPI) by applying frontier efficiency techniques and a Malmquist index approach. Compared to other dynamic environmental productivity and efficiency analysis approaches based on these methods, our approach builds on the standard definition of eco-efficiency as it is presented in the ecological economics literature. Recognizing the importance to analyze the sources of environmental performance changes, we show how changes in overall environmental performance can be decomposed into changes in relative eco-efficiency and shifts in environmental technology, respectively. We apply the presented technique at the macro level to dynamic environmental performance analysis of 20 member states of the European Union in 1990-2003. According to the results, environmental technical change mostly explains the improvement in overall environmental performance, while relative eco-efficiency change has been minor for most countries during the sample period.     

Exports and growth: Granger causality analysis on OECD countries with a panel data approach

This paper investigates the possibility of Granger causality between the logarithms of real exports and real GDP in twenty-four OECD countries from 1960 to 1997. A new panel data approach is applied which is based on SUR systems and Wald tests with country specific bootstrap critical values. Two different models are used. A bivariate (GDP–exports) model and a trivariate (GDP–exports–openness) model, both without and with a linear time trend. In each case the analysis focusses on direct, one-period-ahead causality between exports and GDP. The results indicate one-way causality from exports to GDP in Belgium, Denmark, Iceland, Ireland, Italy, New Zealand, Spain and Sweden, one-way causality from GDP to exports in Austria, France, Greece, Japan, Mexico, Norway and Portugal, two-way causality between exports and growth in Canada, Finland and the Netherlands, while in the case of Australia, Korea, Luxembourg, Switzerland, the UK and the USA there is no evidence of causality in either direction.     

Short-term forecasting with mixed-frequency data: a MIDASSO approach

In this article, we extend the targeted-regressor approach suggested in Bai and Ng (2008) for variables sampled at the same frequency to mixed-frequency data. Our MIDASSO approach is a combination of the unrestricted MIxed-frequency DAta-Sampling approach (U-MIDAS) (see Foroni et al. 2015; Castle et al. 2009; Bec and Mogliani 2013), and the LASSO-type penalized regression used in Bai and Ng (2008), called the elastic net (Zou and Hastie 2005). We illustrate our approach by forecasting the quarterly real GDP growth rate in Switzerland.     

A review of machine learning for big data analytics: bibliometric approach

ABSTRACT

The amalgamation of machine learning and big data has led to a revolution in data science with several influencing applications to various domains. To gain insights on the current research trends on machine learning for big data analytics, this study follows a bibliometric analysis methodology of citation data to review and quantitatively assess the explosion and impact of literature and research performance in this vibrant research area, which has witnessed rapid changes and rising interest in business, industry and academia. Using a variety of bibliometric measures and visualisation techniques, the paper examines and identifies several related issues including research productivity and directions, major contributors, publication trends and growth rates, citation and collaboration analysis, and others. The relevant bibliographic units for the study were collected from the Core Collection of the Web of Science bibliographic database. Nearly all the relevant publications prior to February 2018 were included in the analysis. The overwhelming productivity and wide-spread applications in several multidisciplinary domains have been revealed, with one-to-two ratio of journal to conference publications. Three countries (USA, China, India) are dominating the research output with more than two-thirds of the total productivity.