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Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model
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Author(s): 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
Volume: 10
Issue: 1
Pages: 15
Source title:
International Journal of Information Systems in the Service Sector (IJISSS)
Editor(s)-in-Chief: John Wang (Montclair State University, USA)
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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