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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 |Volume: 10 |Issue: 1 |Pages: 15
ISSN: 1935-5688|EISSN: 1935-5696|EISBN13: 9781522543169|DOI: 10.4018/IJISSS.2018010101
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MLA

Copeland, Mary Kay, and Emilyn Cabanda. "Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model." IJISSS vol.10, no.1 2018: pp.1-15. http://doi.org/10.4018/IJISSS.2018010101

APA

Copeland, M. K. & Cabanda, E. (2018). Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model. International Journal of Information Systems in the Service Sector (IJISSS), 10(1), 1-15. http://doi.org/10.4018/IJISSS.2018010101

Chicago

Copeland, Mary Kay, and Emilyn Cabanda. "Efficiency Analysis of the U.S. Publicly Held Insurance Industry: A Two-Stage Efficiency Model," International Journal of Information Systems in the Service Sector (IJISSS) 10, no.1: 1-15. http://doi.org/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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