1. 1 Nonspecialized Strategy versus Specialized Strategy ： Evidence from the Property-Liability Insurance Industry Lih-Ru Chen National Chengchi University Gene C. Lai Washington State University Jennifer L. Wang National Chengchi University ARIA Meeting, August, 2007

2. 2  Why do we observe the long-lived coexistence of joint producers and specialist in the U.S. property- liability insurance industry?  Whether joint producers or specialist is more efficient ? 1.whether nonspecialized strategy or specialized strategy is more efficient for property-liability insurers. 2.what types of insurers are likely to realize economies of scope. Research Question and Research Purpose

3. 3 Conglomeration hypothesis  Teece(1980)  Argued that Multiproduct enterprise is an efficient way of organizing economic activity.  Panzar and Willing (1981)  First to introduce the concept of economies of scope. Strategic focus hypothesis  Comment and Jarrell (1995)  The greater corporate focus is consistent with shareholder wealth maximization.  Kanatas and Qi (2003)  Integrated financial services market is less innovative than one with specialized intermediaries.  Chen (JFQA,2006)  focused firms exhibit significantly better post-investment operating performance than diversified firms. The Literature I

4. 4 The Literature II Insurance Related  Kellner and Mathewson (1983); Meador, Ryan, and Shellhorm (1998), Cummins, Weiss, and Zi (2003), and Hirao and Inoue (2004) found results consistent with diversification strategy.  Grace and Timme (1992) and Yuengert (1993)  Berger et al. (2000) found mixed results.  Jeng and Lai (2005) find that Keiretsu firms seem to be more cost-efficient than nonspecialized independent firms.

5. 5 The main contribution of this study 1.This paper examines diversification/focus strategy from the perspective of a property- liability insurer rather than two sectors of insurance industry. 2.We examines whether the technology of nonspecialists is the same as that of the specialists using the cross-frontier approach. 3.Focusing on a more recent time period enables us to determine whether the most recent wave of financial consolidation will change the focus strategy.

6. 6 Data and Methodology Sample & Data  Period: 1997-2004  Insurer’s Annual Statement from NAIC  Herfindahl index of net premium is used to identify the specialists and nonspecialists. Methodology  Data Envelopment Analysis (DEA)  Stochastic Frontier Approach (SFA)

7. 7 Hypotheses Development  H1: The Nonspecialized Hypothesis  H2: The Specialized Hypothesis  H3: The technology of nonspecialists is the same as that of the specialists.  H4: It is infeasible to replicate nonspecialists input-output bundle using the specialists technology.  H5: There are no scope economies for either nonspecialists or specialists.

8. 8 Inputs/Outputs using in value-added approach  Cummins and Weiss (1993), Cummins, Weiss, and Zi (1999), and Cummins et al. (2004) Output Y1= Losses incurred in short-tailed personal lines Y2= Losses incurred in long-tailed personal lines Y3= Losses incurred in short-tailed commercial lines Y4= Losses incurred in long-tailed commercial lines Y5= Total Invested Assets Input Input Price X1=Labor cost P1=Price of Labor X2=Business Service P2= Price of Business Service X3=Equity P3= Price of Equity X4=Debt P4= Price of Debt

9. 9 Table 1 Summary Statistics for non-specialists and specialists Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

10. 10 Table 5 Cost efficiency results: 1997–2004

11. 11 Table 5 Cost efficiency results: 1997–2004 (continuous) Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

12. 12  Cummins et al., (1999) F-scores measure the dominance with respect to the frontiers.

13. 13 Table 7 Dominance Statistics by Size Quartile Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

14. 14 Table 8 Summary Statistics for regression Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

15. 15 Table 9 Dominance Regression for nonspecialists and specialists Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

16. 16 SFA variables VariablesDefinitions y1 losses incurred for personal line y2losses incurred for nonpersonal lines y3invested assets p1price of labor=average weekly wages for insurance agent (standard industrial classification [SIC] Class 6411) by using U.S. Department of Labor data. p2business services price index =average weekly earnings of workers in SIC 7300. Coststotal expense paid of other underwriting expense Revenuestotals of net premiums written + net investment income-losses incurred current year – total expenses incurred Profitrevenue-cost

17. 17 NonspecialistsSpecialists VariablesMean Standard deviation Test stat. Mean Standard deviation y134,397,47973,221,866***135,658918,295 y262,233,108144,033,832***10,595,82325,071,999 y3428,584,725989,856,777***77,766,932192,140,149 p14351343513 p22812128121 Cost ($ thousand) $47,819$102,550***$5,063$9,790 Revenue ($ thousand) $62,983$146,969***$10,908$35,355 Profit ($ thousand) $15,164$64,700***$5,845$27,689 Table 10 Summary Statistics for stochastic frontier approach Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

18. 18 Q1MedianQ3Q4 Cost Scope Economy 25.35%***–9.93%***–28.30%***–58.07%*** T stat(18.85)(–7.39)(–19.67)(–48.18) Revenue Scope Economy–8.07%***19.93%***34.24%***60.99%*** T stat(-5.17)(13.61)(22.88)(49.29) Profit Scope Economy –39.14%***–5.63%***14.98%***43.84%*** T stat(–34.60)(–4.28)(12.46)(38.7)1 Table 11 Scope Economy by Quartile Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level.

19. 19 Independent variablesRandom EffectFixed Effect CoefficientT statCoefficientT stat Intercept–2.3521–9.34***–1.8529–3.37*** Log Asset0.11728.75***0.09233.09*** Commercial Output %–0.2046–6.41***–0.4028–4.65*** Cost Efficiency0.29136.99***0.38547.93*** ROE Standard Deviation0.05551.96**0.04821.57 Capital to Asset Ratio0.19442.82***0.14691.43 WCONC16.58401.0330.50460.97 Stock–9.38E–02–3.04***–9.77E–02–0.86 Vertical Integration Dummy2.70E–030.05 Average value of dependent variable –12.43% R2R2 9.74%59.79% Note:*** Statistically significant difference at 1% level or better; ** Statistically significant difference at 5% level; * Statistically significant difference at 10% level. Table 12 Profit Scope Economy Regression for simulated non-specialists

20. 20 Concluding remarks 1.Supports for Hypothesis1,2,4 are found. 2.The nonspecialists and specialists operate on different efficient frontiers in P/L insurance industry. 3.Nonspecialists (specialists) dominate specialists (nonspecialists) in producing nonspecialists (specialists) input–output vectors. 4.The regression results generally support the coexistence of the nonspecialized strategy and specialized strategy.