Macro investigation on China's engineering insurance industry: based on industrial organization theories

PurposeIn China, engineering insurance has been questioned as not being beneficial as expected. This paper seeks to further understand how China's engineering insurance industry functions and to provide a macro perspective explanation for engineering insurance's underdevelopment.Design/methodology/approachThree industrial organization hypotheses were extended to the engineering insurance context: structure conduct performance (SCP), relative market power (RMP) and efficiency structure (ES) hypotheses. This paper employed the Generalized Method of Moments (GMM) and Data Envelopment Analysis (DEA) bootstrap to test the hypotheses using panel data from 2008 to 2017.FindingsThe results suggest that the SCP paradigm is validated in China's engineering insurance market, indicating a concentrated market where the welfare of consumers (e.g. owners, contractors and designers) may be eroded. Several factors are identified to have significant impacts on engineering insurers' performance, such as the investment return, percentage of engineering business, the ratio of outstanding claims, the number of large contractors, market rivalry and entry barriers.Originality/valueDespite the sheer size of China's construction industry and the urgent need to improve risk management, the insurance industry that serves construction firms engineering insurance is underdeveloped. Engineering insurance is yet to be understood from a macro perspective, which may reveal the underlying reasons for engineering insurance's underdevelopment. The industrial organization theories provided a theoretical framework to test the functioning of this specific industry. The disaggregated data (engineering line specific) is employed to ensure effective regulation and policymaking.

[1]  Joe Zhu,et al.  A survey of data envelopment analysis applications in the insurance industry 1993-2018 , 2020, Eur. J. Oper. Res..

[2]  Yingbin Feng,et al.  Understanding why Chinese contractors are not willing to purchase construction insurance , 2018 .

[3]  Martin Eling,et al.  Under pressure: how the business environment affects productivity and efficiency of European life insurance companies , 2017, Eur. J. Oper. Res..

[4]  Peter Wanke,et al.  Efficiency drivers in Brazilian insurance: A two-stage DEA meta frontier-data mining approach , 2016 .

[5]  A. Alhassan,et al.  Market structure, efficiency and profitability of insurance companies in Ghana , 2015 .

[6]  Martin Eling,et al.  The Determinants of Efficiency and Productivity in the Swiss Insurance Industry , 2015, Eur. J. Oper. Res..

[7]  Issaka E. Ndekugri,et al.  The project insurance option in infrastructure procurement , 2013 .

[8]  Wei Huang,et al.  An efficiency comparison of the non-life insurance industry in the BRIC countries , 2012, Eur. J. Oper. Res..

[9]  V. Njegomir,et al.  Liberalisation and Market Concentration Impact on Performance of the Non-Life Insurance Industry: The Evidence from Eastern Europe , 2011 .

[10]  Sy-Jye Guo,et al.  Owner-Controlled Insurance Program and Construction Project Management for Taiwan High Speed Rail Project , 2010 .

[11]  Carlos Pestana Barros,et al.  Efficiency in the Greek insurance industry , 2010, Eur. J. Oper. Res..

[12]  M. Eling,et al.  Efficiency in the international insurance industry: A cross-country comparison , 2010 .

[13]  Nat Pope,et al.  The Market Structure Performance Relationship in the International Insurance Sector , 2008 .

[14]  Nat Pope,et al.  An Investigation into the Diversification-Performance Relationship in the U.S. Property-Liability Insurance Industry , 2008 .

[15]  D. Kamerschen,et al.  STRUCTURE, CONDUCT AND PERFORMANCE ANALYSIS OF THE SOUTH AFRICAN AUTO INSURANCE MARKET: 1980-2000 , 2008 .

[16]  Jian Liu,et al.  Study on the professional liability insurance system of the supervision engineer in China , 2007 .

[17]  Binshan Lin,et al.  Key issues and challenges of risk management and insurance in China's construction industry: An empirical study , 2007, Ind. Manag. Data Syst..

[18]  B. Choi,et al.  An Empirical Investigation of Market Structure, Efficiency, and Performance in Property-Liability Insurance , 2005 .

[19]  C. Daraio,et al.  How Deregulation Shapes Market Structure and Industry Efficiency: The Case of the Italian Motor Insurance Industry , 2004 .

[20]  V. Bajtelsmit,et al.  Market Structure and Performance in Private Passenger Automobile Insurance , 1998 .

[21]  A. Saunders,et al.  An Investigation of the Performance of the U.S. Property-Casualty Insurance Industry , 1997 .

[22]  Anne Carroll,et al.  An Empirical Investigation of the Structure and Performance of the Private Workers' Compensation Market , 1993 .

[23]  S. Rhoades.  Market share as a source of market power: Implications and some evidence , 1985 .

[24]  Sam Peltzman,et al.  The Gains and Losses from Industrial Concentration , 1977, The Journal of Law and Economics.

[25]  H. Demsetz.  Industry Structure, Market Rivalry, and Public Policy , 1973, The Journal of Law and Economics.

[26]  G. Stigler.  A Theory of Oligopoly , 1964, Journal of Political Economy.

[27]  Joe S. Bain,et al.  Relation of Profit Rate to Industry Concentration: American Manufacturing, 1936–1940 , 1951 .

[28]  Amr Kandil,et al.  Construction Risks: Single versus Portfolio Insurance , 2010 .

[29]  B. Choi,et al.  State regulation and the structure, conduct, efficiency and performance of US auto insurers , 2008 .

[30]  Shujie Yao,et al.  On technical efficiency of China's insurance industry after WTO accession , 2007 .

[31]  P. W. Wilson,et al.  Estimation and inference in two-stage, semi-parametric models of production processes , 2007 .

[32]  P. W. Wilson,et al.  Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models , 1998 .