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 (Rinker School of Business, Palm Beach Atlantic University, West Palm Beach, FL, USA) and Emilyn Cabanda (School of Business and Leadership, Regent University, Virginia Beach, VA, USA)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJISSS.2018010101


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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