Performance analysis of non-banking finance companies using two-stage data envelopment analysis
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Performance analysis of non‑banking finance companies using two‑stage data envelopment analysis Pankaj Dutta1 · Aayush Jain1 · Asish Gupta1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This paper analyses the performance of non-banking finance companies (NBFC) in the Indian context using data envelopment analysis (DEA). The underlying objective of this study is to fill the void in the domain of NBFC, although a lot of research has been done on the banking industry in the context of the application of DEA, but none on NBFCs. The paper takes the panel data of the last 5 years (2014–2018) to calculate super-efficiencies in the first stage and then regresses the same on exogenous factors in stage-2. Descriptive statistics are used to estimate the efficiency by carrying out the calculations using both the traditional models (OTE, PTE and SE) and super-efficiency model. A comparison is made by categorizing NBFC’s based on the size of total assets and using non-parametric statistic tests to find whether the efficiency scores are significantly different across different categories. The second stage DEA analysis uses Tobit regression to find the exogenous factors which affect the model significantly. Based on traditional models, the total number of efficient DMUs are 8 out of 43 while there are 15 after considering the super-efficiency algorithm. Malmquist Indices are used to study the productivity indices of NBFCs over the last 5 years, and it gives us a maximum productivity growth of 8.53%. It was noticed that there is a significant difference in the mean efficiency values of different sized NBFC’s which can be explained by the lack of standardization in the NBFC domain and the few companies which are listed on the stock market. The managers should not consider ROE as a significant indicator of efficiency and should instead focus on aspects such as ROA and income diversity. Through the Malmquist analysis, the managers can break down the productivity change into technical and efficiency shifts for further investigation. Keywords Data envelopment analysis · NBFC · Super-efficiency · Tobit regression · Malmquist indices · India
* Pankaj Dutta [email protected] Aayush Jain [email protected] Asish Gupta [email protected] 1
Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
13
Vol.:(0123456789)
Annals of Operations Research
1 Introduction NBFC’s or non-banking financial companies are the financial institutions which provide banking services but do not hold a banking license and are not allowed to take deposits. They are increasingly important in the financial landscape of India, wherein they can increase the flow of credit from the savers to the investors in the economy. NBFC’s have been around since 1956 and became more prevalent around the 1970s. Their importance has increased in recent times with the increasing credit needs in the economy, which can’t be sufficiently be fulfilled by the banks. Safania (2010) con
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