Do high levels of insurance regulations benefit consumers? This ConsumerGram provides new empirical evidence showing that increased state insurance regulation is strongly correlated with higher consumer insurance premiums. Our statistical analysis finds that the average household pays about $300 more for property and casualty insurance in heavily regulated states, compared to the least regulated states. This means that, across the U.S., high regulations push up consumer property and casualty insurance premiums by approximately $13.7 billion each year. In other words, when it comes to excessive state regulations, consumers are the biggest losers.
State Report Card
Heartland Institute and the Competitive Enterprise Institute (CEI) released a joint report called the 2008 Property & Casualty Insurance Report, which scores and ranks the 50 states based on regulatory conditions. The report attempts to address the extent to which consumers have unfettered choice among insurance products and the extent to which insurance carriers are free to offer their products to consumers. The report looked at a number of variables, many of which dealt with the degree of state regulation. The variables were developed into a composite score and used to rank states in terms of their regulatory climate. The report found California, North Carolina, Florida, Maryland and Massachusetts to have the highest level of regulation, and referred to these states as having a “hostile” regulatory climate. On the other hand, Vermont, Idaho, Utah, Illinois and Wisconsin provided the least intrusive regulatory climate and were characterized as being the “best” for consumers and insurance carriers.
Initially, we were skeptical of the Heartland/CEI study. First, developing composite indicators such as these often require the weighting of very different attributes, like adding oranges and apples – which may make the results interesting but lacking any significant analytical power. Second, state regulators would take issue with the study’s main conclusion that more regulations are bad for consumers.
However, if the study results are meaningful, we should see a statistically significant correlation between the state scores and consumer insurance premiums. After all, if state regulation is bad for consumers, than there must be consequences for high levels of regulation and these should be observed in the price that consumers pay for insurance. Therefore, if the state scores and ranks are, in fact, meaningful, we should find that consumers pay more for auto and homeowners insurance in states with more insurance regulation. This ConsumerGram will test this hypothesis.
Before analyzing the study results, it is worth noting that many consumers have serious doubts about the benefits of state regulation. In 2007, an American Consumer Institute survey of consumers in two of the most heavily regulated states, North Carolina and Massachusetts, found that 23% believe that state insurance regulations benefit consumers, while 51% believed that regulations do not benefit consumers. These results were supported by the recent 2008 Consumer Pulse Survey, which found more consumers disagreeing than agreeing with the belief that state insurance regulations benefit them. These survey results seem to agree with the Heartland/CEI study conclusion that excessive regulations are, on balance, more harmful to consumers than not. However, empirical evidence is needed to validate this conclusion
Consumer Insurance Premiums
Do excessive regulations lead to higher insurance premiums? To answer this question, we used data from the Insurance Information Institute and the National Association of Insurance Regulators to develop a simple econometric model. The model’s dependent variable is the average household costs for property and casualty insurance. To estimate consumer costs, we added the average homeowners premium and consumer automobile premium for each state and the District of Columbia. An independent variable, per capita income, was included to account for economic differences among the states. We hypothesize that insurance is a normal good and that consumers with higher income and wealth will buy more insurance.
Other variables were added to account to activities associated with increased insurance losses, including the percentage of coastal properties exposed to hurricane damage (AIR Worldwide), tornados per square mile (Department of Commerce), number of earthquakes per square mile (USGS, sized 3.5 or greater) and property crime (FBI, per 100, 000 inhabitants). We expect consumer premiums to increase as these activities increase.
Next, we account for the regulatory climate in the states by using the exact state score from the Heartland/CEI study. The study’s score is a composite of a number of important factors that can influence insurance costs, including the size of the state’s auto and homeowners residual market, loss ratio stability, rate regulation and territorial rating. If the study’s results are meaningful, we expect the results to be significantly correlated with consumer insurance premiums. Specifically, as the index decreases (meaning that regulation increases), consumer insurance premiums will increase. A simple ordinary least squares model was used to test this correlation.
Two regressions were run and both produced strong statistical results. The table below summarizes the findings:
Regression #1 Regression #2
Adjusted R Squared
T–Statistics are in parenthesis.
The two models explained 55% and 51% of the variation in consumer insurance premiums, and the F-statistic indicated that the regression was highly significant. The per capita income variable was positively related and highly significant, indicating that consumer insurance is a normal good. The tornadoes and earthquake variables were not statistically significant and were excluded from regression #2. Crime and hurricane variables were statistically significant and had the correct signs, indicating that an increase incidence in either variable would lead to increase insurance premiums. The heartland/CEI regulation score was a highly significant explanatory variable for consumer premium costs, and the negatively correlated, indicating that lower score values (higher levels of regulation) result in higher consumer insurance premiums. A second regression, excluding the insignificant terms produced stable coefficients, compared to the first regression. These results suggest that consumers are, net of benefits and costs, worse off when insurance regulations are excessive, compared to the least regulated states. In other words, consumers are not protected by higher regulations – they are, in fact, harmed. Based on these results, we accept Heartland/CEI’s contention that highly regulated state insurance markets are more costly for consumers.
Using the more conservative estimates from regression #2, the table below shows the added costs that heavy regulation imposes on consumers in the most heavily regulated states. For these states, consumers are paying hundreds of dollars (per household) more for property and casualty insurance. If these costs were summed across all states and for all insured consumers, we estimate the costs of high regulation on consumers to be $13.7 billion per year. This figure does not include the full benefits of harmonizing state regulations, nor does it include the regulation’s non-price effects. Further research is needed to refine these estimates.
In summary, we find that the Heartland/CEI regulation scores are highly correlated with consumer auto and homeowners insurance premiums, making them a meaningful surrogate for measuring the level of state regulation. Most importantly, however, our analysis finds that high state regulations (net of their benefits) adversely affect consumer prices, raising auto and homeowners premiums by hundreds per household (annually) in some states and $13.7B across the U.S. These results suggest that, when it comes to state regulations, consumers are the biggest losers, and it corroborates consumer skepticism that excessive regulations are not necessarily for their benefit.
 In defense of Massachusetts, recent regulatory reforms are likely to reduce the level of regulation, which, according to our model results, will result in cost reductions and substantially increased consumer benefits.