An empirical investigation of efficiency and productivity in the Indian non-life insurance market

Abstract

Purpose The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of efficiency, productivity and returns-to-scale economies. In addition to this, it identifies the determinants of efficiency. Design/methodology/approach This study employs a two-stage data envelopment analysis (DEA) bootstrap approach to estimate the level and determinants of efficiency. In the first stage, the DEA bootstrap approach is employed to estimate bias-corrected efficiency scores. In the second stage, the truncated bootstrapped regression is used to identify the effect of firm-level characteristics on the efficiency of insurers. Moreover, the bootstrapped Malmquist index is used to examine the productivity growth over the observation period 2005–2016. Findings The bootstrapped DEA results show that the Indian non-life insurance sector is moderately technical, scale, cost and allocative efficient, and there is a large opportunity for improvement. Moreover, the results reveal that the public insurers are more cost efficient than the private insurers. It is also evident that all the insurers irrespective of size and ownership type are operating under increasing returns to scale. Malmquist index results divulge an improvement in productivity of insurers, which is attributable to the employment of the best available technology. Bootstrapped DEA and bootstrapped Malmquist index results also show that the global financial crisis of 2008 has not severely affected the efficiency and productivity of the Indian non-life insurance sector. The truncated regression results spell that size and reinsurance have a statistically significant negative relationship with efficiency. It also shows a statistically significant positive age–efficiency relationship. Practical implications The results hold practical implications for the regulators, policy makers, practitioners and decision makers of the Indian non-life insurance companies. Originality/value This study is the first of its kind that comprehensively investigates different types of robust efficiency measures, determinants of efficiency, productivity growth and returns-to-scale economies in the Indian non-life insurance market for an extended time period.

Efficiency drivers of insurers in GCC: an analysis incorporating company-specific and external environmental variables

“…The company's age does not impact the company's productivity. Whether it is old or new, it is immaterial for efficiency; this contradicts the findings of Ilyas and Rajasekaran (2019) on "age of the company" significantly positive with technical efficiency.…”

“…However, in the study done by M. M. Jaloudi (2019), it was concluded that reinsurance is insignificant to insurers' efficiency. We expect a negative relationship for reinsurance like Cummins et al (2010) and (Ilyas & Rajasekaran, 2019)…”

“…They have applied BCC and CCR models of DEA and revealed that a good number of insurance companies operating in KSA were found to be efficient on managerial efficiency scale. Ilyas and Rajasekaran (2019) examined the Indian general insurance sector in terms of efficiency, productivity and returns to scale economies. They had employed DEA bootstrapped regression to estimated bias-corrected efficiency scores and also applied truncated bootstrapped regression to identify the effect of firm-level characteristics on the efficiency of insurers.…”

Measuring the Managerial Efficiency of Insurance Companies in Saudi Arabia: A Data Envelopment Analysis Approach

“…Studies reviewed in the said paper applied DEA to calculate the efficiency of firms from various backgrounds, with multiple inputs and outputs. There are other studies in literature (Borges et al, 2008;Cummins & Weiss, 2013;Ilyas Ashiq, 2019;Mandal, 2014), which calculated the efficiency of insurance companies by adopting DEA as tool for efficiency measurement.…”

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“…Of the two main kinds of insurance, Life insurance, where the insurer invests the insured’s savings undertaking to pay a capital or an income in case of a life event, such as death; and P&C—Property and Casualty insurance, that protects the insured against possible losses deriving from damages to persons or objects (Marchionni, 2006 ), we concentrate on insurance companies solely in the P&C insurance business. The P&C segment is particularly detrimental for the market as it deals with almost any kind of risk (Ilyas & Rajasekaran, 2019 ) affecting daily and business continuity. Indeed, process digitalization (such as for sales and distribution) and achievement of higher efficiency are among the top trends in the P&C market according to practitioners (EY, 2019 ), with the promise of promoting efficiency in processes that are particularly relevant for this kind of insurance (e.g.…”