Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model

Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model

Mary Kay Copeland, Emilyn Cabanda
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJISSS.2018010101
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Abstract

This paper aims to measure and analyze the efficiency of the US publicly-held insurance industry from 2011 to 2013. The paper uses a two-stage efficiency model: (1) data envelopment analysis (DEA), a non-parametric model for measuring the efficiency of 141 panel data of US publicly-held insurance firms, and (2) stochastic Tobit regression model for determining associations between insurers' financial performance and efficiency. Three significant findings are obtained: (1) There is no evidence that US insurance firms consistently improve in efficiency over time using the input-output mix. (2) There is an overall positive significant association between insurers' financial performance and technical efficiency at a very high confidence level. (3) Type of insurance is found to have a negative and significant effect on efficiency. These new findings add empirical evidence to the efficiency analysis of the US insurance industry.
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Literature Review

Hsiao and Su (2006) outlined that DEA has been widely used to measure performance in the financial services industry. In this sector, some examples include: (a) banking (Asmild, Paradi, Aggarwall & Schaffnit, 2004; Berger & Humphrey, 1997), (b) insurance (Biener & Eling, 2012; Cummins, Rubio-Misas & Zi, 2004; Cummins & Xie, 2008; Diacon, Starkey, & O’Brien, 2002; Donni & Fecher, 1997; Eling & Luhnen, 2010; Rai, 1996; Weiss, 1991), (c) investment companies (Chen & Zhu, 2004), and microfinance (Cabanda & Domingo, 2010).

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