Determinants of Cost Efficiency and Productivity Growth of the Indonesian Insurance Industry

Determinants of Cost Efficiency and Productivity Growth of the Indonesian Insurance Industry

Viverita, Shinta Wulandari, Emilyn Cabanda
Copyright: © 2016 |Pages: 13
DOI: 10.4018/IJKBO.2016040105
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This paper provides new empirical evidences on determinants of cost efficiency and productivity performance of life and property-casualty insurance firms in Indonesia. Data envelopment analysis (DEA) method is used to investigate the cost efficiency and Total Factor Productivity (TFP) among a balanced panel of 118 insurance firms (35 life insurance and 83 property-casualty insurance) over the period of 2006-2008. Results show that on average, insurers were operating at a low level of cost efficiency. However, by constructing the Malmquist Indices, this research finds a positive productivity change for the two types of insurance firms due to an increasing use of technological advances. Furthermore, the paper estimates the influence of some environmental variables on the cost efficiency using a multiple regression analysis. New findings indicate significant negative effects among types of insurance, size, and solvency on the firm's cost efficiency. Meanwhile, market share and ownership structure have positive but insignificant effects on the firms' efficiency. These findings are additional empirical evidences for the efficiency analysis of life and property-casualty insurance in a developing country.
Article Preview
Top

1. Introduction

Studies on the efficiency of insurance industry have been done for more than a decade: see for example, Cummins et al. (1996); Rai, (1996); Fukuyama (1997). A current study by Eling and Luhnen (2010) used the frontier approaches, such as data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to investigate the cost and technical efficiency of 6462 insurance firms across 36 countries. Their study shows that Denmark and Japan insurance industries have the highest average cost and technical efficiency scores in Europe and Asia, while the Philippines is the least efficient among all sample. In addition, the previous study revealed no evidence to support expense preference hypothesis. Rai (1996) applied the Stochastic Frontier Analysis (SFA) and Distribution-free Model (DFM) to investigate the cost efficiency of international firms from 11 countries, including insurance firms from 1988-1992. Rai’s study also found that X-inefficiencies are varying by country as well as size and specialization. Interestingly, the same study found that specialized firms are more cost efficient than combination of life and property-casualty firms at the international level.

In the United States, Park et al. (2009) examined the insurance distribution systems toward its cost and revenues efficiency of the U.S. property-casualty insurance industry and revealed that an independent agent is the most cost inefficient but earned higher revenue efficiency than exclusive agents. In Europe, Fenn et al. (2008) also estimated the cost efficiency of European insurance firms and found that firms’ size and domestic market share are significantly affecting its efficiency: larger firms and those with a high market share tend to be more cost inefficient.

In Asia, Md. Saad et al. (2007) investigated the efficiency of life insurance industry between conventional insurance and Islamic insurance (takaful) firms in Malaysia, and found that the technical change is the primary factor that contributes to productivity. Another study by Yao et al. (2007) analyzed China’s insurance firms, which found that insurance efficiency is positively affected by firm size, human capital, and direct sales. In Africa, Ansah-Adu et al. (2011) found that market share, firm size, and leverage are key factors of the insurance efficiency.

Most studies on the efficiency analysis of the insurance industry were largely focused on the US and European countries and some Asian markets. To date, only a few studies that include Indonesia in their samples. For example, two studies by Eling and few Luhnen (2010), and Abidin and Cabanda (2011) focused more on the efficiency of non-life insurance firms. A recent study by Cabanda and Viverita (2012) found that Indonesian life insurance industry experienced managerial efficiency decline over time, which was due to a decline in scale efficiency during the financial crisis years.

It is apparent that the existing insurance efficiency literature has lacked an Indonesian evidence for the key determinants of cost efficiency and productivity growth. This present research will fill this empirical gap by extending the sample to include both life and property-casualty insurance firms and following the empirical researches of Yao et al. (2007), Eling and Luhnen (2010), and Ansah-Adu et al. (2011).

Complete Article List

Search this Journal:
Reset
Volume 14: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 13: 1 Issue (2023)
Volume 12: 4 Issues (2022): 3 Released, 1 Forthcoming
Volume 11: 4 Issues (2021)
Volume 10: 4 Issues (2020)
Volume 9: 4 Issues (2019)
Volume 8: 4 Issues (2018)
Volume 7: 4 Issues (2017)
Volume 6: 4 Issues (2016)
Volume 5: 4 Issues (2015)
Volume 4: 4 Issues (2014)
Volume 3: 4 Issues (2013)
Volume 2: 4 Issues (2012)
Volume 1: 4 Issues (2011)
View Complete Journal Contents Listing