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Item type:Publication, An introduction to data envelopment analysis(Springer Science+Business Media, 2021-12-11)Following the seminal work of Farrell (1957), Charnes et al. (1978) introduced DEA as a deterministic and nonparametric efficiency evaluation tool. DEA is a linear programming-based technique that has been widely accepted as a competing methodology to evaluate the relative efficiency of entities or decision-making units, DMUs (Charles et al., 2016, 2018; Tsolas et al., 2020). DEA is a data-oriented technique (Zhu, 2020) that is used to construct an empirical production frontier to measure efficiency. Note that the original DEA program of Charnes et al. (1978) is based on the CRS specification of technology and is used to measure the technical and scale efficiency of DMUs. However, Banker et al. (1984) extended this program to the case of VRS to estimate purely technical efficiency. Over the past three decades, DEA has been widely used to evaluate the relative efficiency of production firms, the nature of the returns-to-scale, and the productivity changes. The DEA literature has seen a wide variety of applications across a plethora of domains, having become a powerful management science tool (Charles et al., 2018). In this chapter, we briefly review the fundamental concepts in DEA, along with the basic technologies and programs. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Risk, competition, efficiency and its interrelationships: evidence from the Chinese banking industry(Emerald, 2021-10-20)This study investigates the interrelationships between efficiency, competition and risk in the Chinese banking industry. Design/methodology/approach: Parametric stochastic frontier analysis is used to estimate bank efficiency; the Lerner index is used as the competition indicator; accounting ratios and a translog function are used to measure different types of risk and finally, the three-stage least square estimator is used to investigate the interrelationships. Findings: The results of this study show that the impact of competition on different types of risk is significant and positive, while there is a significant and positive impact of credit risk, liquidity risk and capital risk on bank competition. In addition, the findings demonstrate that the interrelationships between efficiency and competition are significant and negative. The authors do not find any robust interrelationships between different types of risk and different types of efficiency; the authors find that diversification and higher levels of profitability reduce bank credit risk. The results suggest that a higher developed banking sector reduces the level of bank competition in China. Originality/value: This is the first piece of research that comprehensively investigates the interrelationships between different types of risk, competition and different efficiencies in China. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The performance of regional governments under the results-based budgeting framework: A two-stage sectoral analysis(EDP Sciences, 2022-03-01)The results-based budgeting (RBB) framework is a public management strategy in which economic resources are allocated to certain budget programs, oriented towards delivering specific products and results to the population. The present paper analyzes the regional governmentsa' efficiency in using their economic resources, under the RBB framework, with an application to the Peruvian context. To this end, we employ a data envelopment analysis (DEA) model with bootstrapping. In the first stage, different sectors of the regional governments are considered individually: education, security, health, sanitation, transportation, and recreation. In the second stage, the overall efficiency index is calculated using the sectoral indices obtained in the first stage. Finally, the factors or determinants influencing the level of efficiency are analyzed. The results show improvements in efficiency levels in the areas of health and sanitation, to the detriment of the rest of the sectors. The average overall efficiency level over the period 2013-2016 remains in the range of 0.25-0.30, which indicates an inefficiency level of 70%. Finally, the variables fiscal autonomy, capital stock, and population density show a positive relationship with respect to the overall efficiency index.