Investment fund selection techniques from the perspective of Brazilian pension funds

ABSTRACT The aim of this article was to evaluate the effectiveness of investment fund selection techniques from the perspective of Brazilian pension funds. Asset liability management (ALM) and liability driven investment (LDI) strategies are usually adopted to guide pension fund managers in relation to strategic allocation in asset classes that should compose their investment portfolios and to the liquidity needed in each period, but not specifying in which assets to allocate resources from among the infinity of assets available in the financial market. This article contributes to tactical management in the fixed income and stock segments outsourced via funds and demonstrates that adopting simple indicators can increase investment performance. The article broadens the knowledge on pension fund investment decisions and creates confidence in the adoption of the Sharpe ratio as a technique for choosing investment funds. We analyzed the returns obtained by hypothetical portfolios built using the following techniques: (i) the Sharpe ratio; (ii) the alpha of a multifactor model; (iii) data envelopment analysis (DEA) efficiency; and (iv) the different combinations of these techniques. We considered information on 369 funds from 2013 to 2018, adopting 12 temporal windows for choosing and re-evaluating the portfolios. The returns obtained were compared with the mean actuarial goal of the benefits plans administered by the pension funds, by means of the unplanned divergence (UD). When outsourcing pension fund investments in fixed income and stock investment funds it was verified that the Sharpe ratio contributes significantly to pension fund performance, compared with other indicators and techniques or a combination of them.

The Productive Efficiency of Science and Technology Worldwide: A Frontier Analysis

We are interested in how codified knowledge is produced around the globe (which inputs are used to produce scientific articles and patented inventions) and the efficiency of the process (how do the best performers produce more with the same inputs or produce the same with less inputs). Using a Data Envelopment Analysis (DEA) efficiency frontier approach, we aim to determine which countries are more efficient at producing codified knowledge. We proxy knowledge production by publications and patents, obtained through human (researchers) and non-human (R&D expenditure) resources. We built a 15-year database with more than 800 observations of these and other variables. Our findings enable us to distinguish efficiency by country, geographical region, and income area. We run four different specifications and correlate the results with partial productivity indexes seeking consistency. Under constant returns to scale, the most traditional producers of knowledge are not fully efficient. Instead, small countries with limited resources appear to be efficient. When we add environmental conditions, both sets of countries are efficient producers of knowledge outputs. High-income regions, on the one hand, and East Asia, North America, and Europe and Central Asia, on the other, are the most efficient regions at producing knowledge.

Analysing drivers of efficiency in the leather industry: a two-stage double bootstrap DEA approach

PurposeThe Indian leather industry contributes to economic growth at a significant environmental cost. Due to the rising global demand for sustainable leather products, promoting efficient input utilisation has become vital. This study measures input efficiency and its determinants for leather industry in order for it to improve its future performance.Design/methodology/approachIn the first stage, bootstrap data envelopment analysis (DEA) approach is used for measuring efficiency and analysing firms' differences based on their geographical location, organisational structures, urban-rural location and sub-industrial groups. A second stage regression examines efficiency determinants using size, age, skill and capital-labour intensity as the explanatory variables.FindingsEfficiency result shows a significant potential of minimising inputs by 47% provided the firms adopt best practices. West Bengal firms, urban located firms, individual and proprietorship owned firms and leather consumer goods firms are found to be relatively efficient to their counterparts. Size, skilled managerial staff and labour-intensive firms positively affect efficiency.Practical implicationsConstruction of well-connected roads for accessing urban retail markets and provision of reliable electricity would improve efficiency of rural firms. Small-scale enterprises have a larger share in Indian leather industry; therefore, policy should focus on enhancing the firms' scale and investing in training facilities to skill employed labour for ensuring optimal use of inputs.Originality/valuePrevious studies on the leather industry have used the conventional DEA efficiency measurement approach. This study uses DEA bootstrapping model for robust efficiency estimates and provides consistent inferences about the determinants.

Value-added intellectual capital and productive efficiencies: evidence from Taiwan listed electronics companies

PurposeThis study examines the effect of value-added (VA) intellectual capital on business performance from the perspective of productive efficiency, which is derived from its main contributors, namely, profitability and marketability efficiencies in two stages.Design/methodology/approachFirst, this study applies a dynamic network slacks-based measure in a data envelopment analysis (DEA) approach to estimate productive efficiency and its components of 766 Taiwan listed electronics companies over the period of 2010–2018. Second, this study performs regression analyses of the association between intellectual capital (IC), which is proxied by VA intellectual coefficient (VAICTM) and estimated DEA efficiency scores through various regression techniques.FindingsEmpirical evidence shows a significantly positive association between VAICTM and productive efficiency. This study finds the same result from the IC components after splitting VAICTM into (1) IC efficiency, which comprises human capital efficiency (HCE) and structural capital efficiency and (2) capital employed efficiency. Further examination reveals that HCE is the sole main contributor of the productive efficiency, and profitability and marketability efficiencies of a company.Practical implicationsThe findings of this study highlight the need to discuss the values of intellectual coefficient (IC) from the perspective of productive efficiency for better comprehensiveness.Originality/valueAlthough previous studies have shown that IC is a contributor of business performance, this study further zooms in VAIC and examines its effect on the efficiency of a company in transforming its inputs into outputs.

683Data envelopment analysis for predicting pre-diabetes for primary disease prevention

Background Identifying a population at risk of risks is imperative for primary disease prevention and allows the promotion of health maintenance in a healthy population. Previous studies on hypertension and dyslipidemia using data envelopment analysis (DEA) showed that populations at risk of risks could be identified using this method. In this study, we extended DEA to include pre-diabetes. Methods A retrospective cohort study was conducted using specific health check-up data from 2008 to 2013. DEA efficiency scores were calculated for healthy subjects with baseline glycated hemoglobin (HbA1c) <5.7%. Odds ratios (ORs) for pre-diabetes onset within 3 years were analyzed. Results Among 1,501 subjects, with 373 cases of disease onset (24.9%), the OR for the incidence of pre-diabetes (on the basis of a 0.1-point increase in the efficiency score) was 0.77 (90% confidence interval [CI] 0.68–0.86, p < 0.0002). After adjusting for age and sex, the OR was 0.66 (90% CI 0.58–0.75, p < 0.0001). Furthermore, for the subgroup with no conventional diabetes risk factors, the adjusted OR was 0.50 (90% CI 0.38–0.67, p = 0.0001). Conclusions We showed that the DEA efficiency score can help identify a pre-diabetes population at risk of risks. Further studies to validate these findings would be worthwhile for optimizing primary preventative measures. Key messages DEA was assessed for its ability to evaluate the risk of pre-diabetes. Results showed that an efficiency score could predict pre-diabetes onset and demonstrated the feasibility of applying this analysis in primary preventive healthcare.

Application of Hybrid Approach in Banking System: An Undesirable Operational Performance Modelling

Non-performing loans (NPLs) is a critical constituent that impacts the operational performance of banks. Rising level of risk leads to poor operational performance, especially when it is beyond the bank’s capabilities to control the increasing bad assets. This calls for real-time performance assessment coupled with futuristic decision making to support banking managers. This observation motivates the authors of this article to develop a two-stage performance prediction assessment model. Accordingly, a hybrid approach combining data envelopment analysis (DEA) and artificial neural network (ANN) is developed to measure and predict the operational efficiency scores of banks. DEA effectively explores the operational performance as well as improvable areas of inefficient banks. The training of ANN model is dependent on estimated operational DEA efficiency scores with the objective to estimate the efficiency scores. Domain for the validation of this study includes dataset derived from Indian banks. The validation result shows that trained ANN model has the prediction capacity with minimum error and maximum accuracy. Finally, the outcome of this study is significantly directed towards business managers who can rely on predictions based on empirical findings of this proposed hybrid modelling.

Analisis Efisiensi Pembuatan Tas Bordir Aceh(Studi Kasus di Kecamatan Muara Batu Kabupaten Aceh Utara)

This study aims to analyze and find out how much the level of efficiency in making Aceh embroidery bags (Case Study in Muara Batu District, North Aceh Regency). The data used in this study are primary data obtained from 20 Aceh embroidery bag business units. This research uses Data Envelopment Analysis (DEA) method. From the Constant Return to Scale (CRS - Output Oriented), results showed that only four business units were efficient while sixteen business units were inefficient. Through the results of Variable Return to Scale (VRS - output oriented), there were seven efficient business units, while thirteen more business units were inefficient.Keywords:Data Envelopment Analysis (DEA), Efficiency, CRS, VRS, Output Oriented

Safety Performance and Occupational Injuries of Workers (OIW): A DEA Efficiency Analysis

The rapid pace of industrialization and sectoral transformation have not only induced rapid economic progress yet also engaged policy think tanks to consider the safety performance due to the increasing rate of injuries. These increasing workplace hazards have affected occupational efficiencies as well as worker’s performance. Hence, a comprehensive analysis of occupation injuries of workers (OIW) is crucial to determine the safety performance of high and low-risk industries in Pakistan. This study aims to incorporate the OIW for the estimation of the safety performance of industries employing Data Envelopment Analysis (DEA). This non-parametric technique allows calculating relative efficiencies incorporating inputs and outputs (both desirable and undesirable). The findings of the SBM-DEA model and sensitivity analyses pointed out improvements in the farm sector and demanded more comprehensive analyses for the non-farm sectors.