2007 Annual Meeting of the American Risk and Insurance Association Quebec City, Canada

1. Regulator Performance, Regulatory Environment and OutcomesAn Examination of Insurance Regulator Career Incentives on State Insurance Markets by 2007 Annual Meeting of the American Risk and Insurance Association Quebec City, Canada

2. Revolving Door The door can swing in two directions Industry  Government Government  Industry DAVID LAURISKI, chosen as the Labor Department’s Assistant Secretary of Mine Safety and Health, previously spent 30 years in the mining industry, during which time he advocated loosening of coal dust standards. Once in office, he issued controversial rules (later blocked by the Senate) that would have reduced coal-dust testing in mines. Lauriski resigned from his position in late 2004 and took a job with a mine-industry consulting company. The Charleston Gazette later reported that Lauriski had been negotiating for private-sector jobs as early as six months before leaving office. Source: A Matter of Trust (Revolving Door Working Group: Washington D.C., 2005)

3. Revolving Door • Debate exists whether revolving doors between a regulatory agency and the industry it oversees should be open or closed • Traditional concern is about capture by regulated industry • Stigler (Bell Journal 1971) • However, agency can be captured by other than industry interests • Peltzman (J. of Law and Economics 1976) • More recent literature suggests • Regulators may pursue own private incentives • Laffont (various papers with various authors) • Revolving doors may provide incentives that actually increase overall efficiency of the regulated market place • Che (RAND 1995) • Salant (RAND 1995)

4. Research Objectives of this Paper • Who are the regulators of the insurance industry? • Where do they come from? • What professional backgrounds do they have? • How do they become insurance commissioner? • Where do they go when they are no longer the insurance commissioner? • Can we find evidence that the decisions of insurance regulators, in states that provide them a means, are influenced by their • Pre-agency employment • Post-agency career ambitions, or by • The manner through which they attained the office? • Can we explain the rather surprising result that rate regulation, on average, appears to have little effect on insurance prices yet in some states and at some times the effect appears large?

5. Prior Literature • Regulatory Incentives • Peltzman (JLE 1976) • Laffont and Martimort (RAND 1999) • Che (RAND 1995) • Salant (RAND 1995) • Selection Mechanism • Besley and Coate (J. of the European Econ. Assoc. 2003) • Rate Regulation and Automobile Insurance • Harrington (Brookings-AEI 2002) • Cummins, Phillips, and Tennyson (JIR 2001) • And a number of other papers not cited here…

6. Revolving Door Sample of the Empirical Literature • Gormley (American Journal of Political Science 1979) • Revolving door between industry and government for FCC regulators • Cohen (American Journal of Political Science 1986) • Revolving door between government and industry for FCC regulators • Gely and Zardkoohi (American Law & Economic Review 2001) • Revolving door between U.S. cabinet positions and lobbying firms • Boylan (American Law & Economic Review 2005) • Revolving door between U.S. attorneys and judgeships and big-firm partnerships

7. Industrial Focus of Our Research • Personal auto insurance is an ideal setting • Some states provide authority for regulator to approve rates prior to their use (Prior Approval States) • Some states provide limited or no authority to approve rates (Competitive States) • Some states have elected commissioners – others are appointed • One insurance commissioner per state • Proxy for the price of automobile insurance is well established in the literature

8. Database of State Insurance Commissioners: 1985 - 2002 • Biographical information on all state insurance commissioners • Information collected included • Gender • Educational background • Prior agency professional background • Post agency career choice • Data Sources • NCOIL’s The Insurance Legislative Fact Book and Almanac (various years) • Trade press and national and local newspapers in Lexis-Nexis and Factiva • Google/Internet Searches • Total number of insurance comm’s 254 • - Number of interim comm’s 10 • - Number of comm’s w/missing data 23 • Number of comm’s in study 221 • Comm’s from regulated states 111 • Comm’s from competitive states 110

9. Anecdotal Comments about the Commissioners • One state had three insurance commissioners, in a row, convicted of either • Lying to a federal agent • Accepting illegal campaign contributions, and/or • Bribery Most recent two seem to be clean! • Six commissioners in our sample resigned for ethical reasons or were serving jail time. Since our sample two more have been forced from office over ethical issues.

10. Anecdotal Comments about the Commissioners (2) • 52% of commissioners had no industry experience prior to their appointment or election • Biographical statistics • Just over 75 % are male • 48% are lawyers • 22%went to graduate school • Some of undergraduate majors represented in our sample* • Business • Education • Psychology • Mortuary Science! • Two states have had only one commissioner during the entire time period of our study * - Note - data on majors is incomplete

11. Empirical Test where pit = unit price of personal automobile liability insurance in year t and state i Xm= is a vector of explanatory market variables in year t and state i PA = is an indicator for prior approval statute in year t and state i Xr=is a vector of indicator variables controlling for the professional background, the prior and post agency employment choices of the insurance regulators, and the manner by which the regulator attained the position in year t and state i nt = is the year specific error term ηi = is the state specific error term eit=random error term bm, br, g= estimated coefficients

12. Estimation Methodology • Two sources of potential endogeneity • Decision by the states to allow the regulator to intervene may be jointly determined with insurance prices • Prior literature mixed whether this selectivity bias exists • Cummins, Phillips and Tennyson (2001) • Harrington (2002) • Econometric technique: Heckman’s (1978) two-stage sample selection model extended to a treatment effects model • Estimate first-stage Probit regression • Calculate inverse Mills terms for regulated and unregulated state-year observations

13. Estimation Methodology (2) • Two source of potential endogeneity, continued • Commissioner’s post employment choices may be jointly determined with the decisions she makes while in office • Econometric technique: Similar to Heckman’s two-stage sample selection model except post-agency choice is modeled using multinomial logistic regression. • See Lee (1983) for details. • Test null hypothesis of exogoneity using F-test restrictions on • Regulation inverse Mills terms jointly equal zero • Post-agency career choice inverse Mills terms jointly equal zero • Regression methodology • Two-way fixed effects estimated using weighted least squares

14. Data Sources and Sample • Data Sources • State insurance markets • AIPSO • NAIC • Political Environment • Berry et al (1998) Political Ideology Index • Demographic and Economic Environment • U.S. Bureau of the Census • Include all state-year observations from 1985 – 2002 • Exclude the District of Columbia • Eliminate state-year observations where we do not have complete data on the insurance commissioner • Final sample is 708 state-year observations

15. Personal Automobile Unit Price RatioAll Coverages by Regulatory Regime: 1985 - 2002 Premium Ratio is defined as the ratio of direct premiums earned divided by direct loss and loss adjustment expenses incurred plus policyholder dividends paid. Source: NAIC

16. Summary StatisticsRegulated vs. Unregulated States: 1985-2002

17. Biographical Statistics of Insurance Comm’s Regulated vs. Unregulated States: 1985 - 2002 ***, **, * denotes statistical significance at the 1,5, or 10 percent levels, respectively

18. Pre-and-Post Agency Choices of Ins. Comm’s Regulated vs. Unregulated States: 1985-2002 ***, **, * denotes statistical significance at the 1,5, or 10 percent levels, respectively

19. State Insurance Commissioners Career Choice Transition Matrix

20. Estimated Marginal Effects from Multinomial Logistical Regression of Post-Agency Career Choice

21. Probit Regression Results of the Choice of Regulatory Regime: 1985 - 2002

22. State Unit Price of Automobile Ins.Two Way Fixed-Effects Regression Results ***, **, * denotes statistical significance at the 1,5, or 10 percent levels, respectively

23. Estimated Effect of Regulator Career Incentives on the Price of Insurance in Regulated States

24. Conclusions • The overall estimated impact of rate regulation appears small • We find significant evidence of a revolving door from government to industry • Prices appear jointly determined with the post-agency career aspirations of the insurance commissioners in regulated states • Particularly strong for commissioners with aspirations to seek higher political office • Weaker evidence for commissioners seeking post-industry employment • We find no evidence the prior employment background of insurance regulators leads to price outcomes significantly different than what one would expect from a similarly situated state with a competitive rating law • We find some evidence the selection mechanism motivates commissioners inconsistent with the results of Besley and Coate (2003) • We find some evidence avowed consumer advocates are successful reducing the price of insurance