We investigate and compare the efficiency estimates of selected non-life insurers in India using two methodologies, the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). The primary purpose is to check if two different methods provide differing results. The secondary purpose is to identify the determinants of efficiency if these statistically significant determinants from the second stage results differ across relative and absolute measures of performance. The study uses a panel data set consisting of 19 Indian non-life insurers observed over 11 years. Results emphasize the significance of employing multiple methods to estimate efficiency, as the accuracy of these estimates varies across models. Contrary to previous findings, we show that few private insurers outperform public insurers. As SFA is pro-theoretic, most studies have adopted DEA models. The results emphasize the significance of employing multiple methods to estimate efficiency, as the accuracy of these estimates can vary across models. Additionally, the second stage analysis shows that solvency, size, age and expenses of the insurers explain the efficiency of the selected insurers.
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