The Impact of Rate Regulation on Claims: Evidence from Massachusetts Automobile Insurance Sharon Tennyson Department of Policy Analysis and Management Cornell University st96@cornell.edu Richard A. Derrig Opal Consulting, LLC Richard@derrig.com CAS Spring Meeting Quebec City, Canada June 16-18, 2008 Impact of Rate Regulation AGENDA Regulation and Competition – The Rationale and the Reality A Little Theory and Practice Auto Insurance: Brookings/AEI Case Studies The Case of Massachusetts Implications for California Why (now) Do States Regulate P-C Insurance Rates? Automobile insurance Homeowners insurance Workers compensation insurance Medical malpractice insurance Mandatory or socially desirable insurance Uninsured parties shift financial risk to others in society Some consumers face high prices Some markets experience price shocks Rate Regulation as Redistribution Not equally practiced in all regulated states or lines Some regulated states lightly regulate voluntary market rates Residual market rates are regulated in all states and lines Implications of redistribution Price subsidies for some consumers To high risk consumers From low risk consumers To high risk consumers From insurance company capital To all consumers From insurance company capital Efficient Redistribution? Not Likely: Not Sustainable The Problem: Competitive Market Forces Attempts to move prices a significant distance from competitively-determined prices will distort market functioning Company responses to regulation Consumer responses to regulation Regulator responses to the responses Efficiency Consequences: Supply Rate suppression distorts insurance supply Decreased writing of voluntary coverage Reduced innovation and quality of service Reduced entry of firms Increased exit of firms Rate uncertainty distorts insurance supply All of the above effects Price stickiness and market volatility Efficiency Consequences: Demand Rate subsidies distort consumer behavior: Insurance demand Increased demand from high risk consumers Decreased demand from low risk consumers May cause low risk consumers to forego insurance Safety incentives Prices are less responsive to changes in losses/risk Claiming incentives Prices are less responsive to changes in losses/risk Implications Stringent regulation of insurance rates produces unintended effects: Reduced competition Higher cost inflation Lower insurance availability Greater market volatility Regulated outcomes may even be contrary to the regulatory objectives pursued What is the Empirical Record? On average and over the long run, rate regulation has little effect on average loss ratios (Harrington, 2002) Not necessary for market functioning Creates uncertainty and costly compliance In states and markets where rate regulation is stringently applied, empirical studies find effects supportive of theory In states and markets where stringent rate regulation is dismantled, empirical studies find effects supportive of theory Evidence from Massachusetts State regulation of private passenger auto insurance rates has created widely-recognized market problems Exit of insurance providers, especially national firms Small number of suppliers Larger than normal residual market at times Cost inefficiencies Politicized ratemaking environment Less recognized problem: In the aggregate, regulation drives overall claims costs higher Table 1 Major Regulatory Changes, 1970-2000 Massachusetts Private Passenger Automobile Insurance Year Regulation 1971 Nofault auto insurance effective 1975 State rate-setting extended to all auto coverages 1977 Competitive rate-setting allowed 1978 State rate-setting reinstituted 1989 Automobile Insurance Reform Law effective 1991 Insurance Fraud Bureau began operation 1996 Competitive Discounts and Deviations begin at -7.4% 2006 Competitive Discounts and Deviations stabilize at -1.7% 2007 Competitive rate-setting allowed 4/1/08 Table 2 Direction of Subsidies by Driver Class and Territory Compulsory Insurance Coverage 2004 Experienced Classes Non-Boston Territories Boston Territories Inexperienced Classes Business Classes Average Premium $527.15 $1,220.54 $500.67 Average Subsidy -$26.00 $138.29 -$46.43 Cells Subsidized (%) 12.50% 42.71% 6.25% Average Premium $813.33 $1,434.04 $751.98 Average Subsidy $253.77 $520.09 $32.30 Cells Subsidized (%) 64.65% 72.73% 36.36% Table 3 Massachusetts Private Passenger Automobile Historical Summary of Industry Discounts/Deviations Annual Change in Discount Year Average Discount 1996 -7.4% 1997 -9.2% -1.8% 1998 -9.2% +0.0% 1999 -6.5% +2.7% 2000 -5.5% +1.0% 2001 -3.0% +2.5% 2002 -2.2% +0.8% 2003 -1.9% +0.3% 2004 -1.7% +0.2% 2005 -1.8% -0.1% 2006 -1.7% +0.1% 2007 -1.7% est'd +0.0% Source: Automobile Insurers Bureau of Massachusetts Impact of Rate Regulation on Claims: First Cut: State-level data on average loss costs 50 states 1972-1998 (before and after Massachusetts effective subsidies) Hypothesis: Massachusetts’ loss costs will be higher than otherwise predicted during period of stringent regulation Impact of Rate Regulation on Claims Second cut: Massachusetts town-level data on loss cost levels for 5 coverages 360 towns Biennial data 1999-2007 Hypothesis: Loss cost growth higher in subsidized towns than in other towns State Data Figure 1: Average Annual Loss Costs per Insured Car Massachusetts vs National Average 600 (Losses Incurred/Written Car Years) 500 400 National Average 300 Massachusetts 200 100 0 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 Year Impact of Rate Regulation State by State Estimation DATA: 1972- 1998 NAIC Coverage Variations Demographics Regulation METHOD: Panel Data Regression Models Ln(Liab. Loss / W Car Years) State Regression Estimates Lst = ß0 + ß1CSYearst + ß2MAsCSYearst + γ’Xst + ß4StateRegsst + ß5StateRegsstCSYearst + as + Tt + εst CSYears = 1978-1998 or 1978-1995 Test ß2 > 0 Control variables = traffic density, cost of hospital stay, per capita income, rate regulation, nofault, PIP limits, compulsory insurance minimums as and Tt are state and year fixed-effects Adjust S.E. for arbitrary heteroskedasticity and for arbitrary correlation within state State Estimation Results Explanatory Variable MA x CS Years CS Years Dummy Reg x CS Years Nofault x CS Years R-squared N CSYears 78-98 CSYears 78-95 0.3781 *** 0.3663 *** 0.1543 0.1101 -0.0807 *** 0.0523 *** 0.0291 0.0181 0.1097 *** 0.0418 0.0338 0.0260 0.0114 0.0046 0.0316 0.0245 0.8742 0.8769 1334 1334 State Regression Estimates Lst = ß0 + ß1CSYearst + γ’Xst + ß4StateRegsst + ß5StateRegsstCSYearst + as + Tt + εst Estimate identical model specification without MA data or MA interaction term Apply estimated coefficient vector to Massachusetts variable values, 1972-1998 Obtain predicted value of Massachusetts loss costs for each year Compare Actual – Predicted value Actual – Predicted Losses Actual Losses Incurred vs Predicted Losses from Regression Model: Massachusetts 1972-1998 150 Prediction difference 100 50 0 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 -50 -100 -150 Year Actual Loss - Predicted Loss Impact of Rate Regulation on Claims: Second Cut Panel of Massachusetts town-level data on loss cost indices for 5 coverages from AIB 360 towns Biennial data 1999-2007 Pure premium index Average class rating factor Hypothesis: Indices will grow faster in subsidized towns than in other towns Town Data - BIL Figure 2: BIL Pure Premium Index Growth Subsidized vs Unsubsidized Towns (1999=1) 1.06 1.04 1.02 Index 1 0.98 0.96 Unsubsidized Towns Subsidized Towns 0.94 0.92 0.9 0.88 1999 2001 2003 2005 Rating Year Source: Automobile Insurers Bureau Filings on Territories and Actuarial Notices on Subsidies 2007 Impact of Rate Regulation Town Level Estimation DATA: 5 coverage Town Data AIB Territory Filings Rate Subsidies All Years Town Index – Bayesian Estimate/ Class Normalized (ACRF) METHOD: Regression Models on Town Relativity Growth Town Regression Estimates %ΔPPit = ß0 + ß1Subsidyit-τ + ß2PPit + ß3%ΔACRFit + ß4%ΔExposuresit + ß5%ΔDensityit + ß6Bostoni + Tt + εit Use subsidy from year in which losses were generated Test ß1 > 0 Adjust S.E. for arbitrary heteroskedasticity and for arbitrary correlation within state Pure Premium Growth Estimates BIL Lag subsidy indicator 0.0717 PIP *** 0.0220 Lag pure premium R-squared 0.0566 PDL *** 0.0112 COL ** 0.0277 COM *** 0.0206 0.0184 0.0061 0.0088 -0.0105 -0.0035 -0.0284 0.0192 0.0076 0.0083 0.0101 0.0114 0.0396 0.0794 0.0625 0.0701 0.0841 -0.0598 F-statistic 2.95 N 1439 *** *** 19.22 1439 *** 7.54 1439 *** 7.51 1439 *** 0.0134 *** *** -0.0616 8.90 *** *** 1439 Standard errors appear below the coefficient estimates, and are adjusted to allow for arbitrary heteroskedasticity and for arbitrary correlation in errors across years within Impact of Rate Regulation California Auto Territories PROP 103 (1989) Driving History Emphasized for Relative Pricing; Mandatory and Optional Classes April 2006 Change: Territory must be less “important” than Mandatory Prop 103 Factors: Annual Mileage, Driving Safety Record, Years Licensed Implementation gradual; full for 7-1-08 Effect yet to be seen but moves away from cost-based must introduce Mass-like subsides varying by insurer Rural to Urban, High Income to Lower Income, High Cost to Low Cost Impact of Rate Regulation California Auto Territories April 2006 Change: Optional Territory Frequency and Territory Severity (and 14 others) must each be forced to be less “important” (less relativity weight) than Mandatory Prop 103 Factors: Annual Mileage, Driving Record, Years Licensed DOI Study Showed 3 Scenarios that implied: Increases for 53 of 58 Counties (High +37%,Low 1.3%) Decreases for 5 of 58 Counties (High -0.5%,Low -12%) LA Zips (High – 6%, Low -11%), Beverly Hills Zips (High -10%, Low -23%) Corr Prem to LossPP, (Current 0.75, New 0.725 to 0.62) Papers R.A. 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