Center for Data Analysis Report- Both the Economic Freedom Project Reports and the Center for Data Analysis generate reports, giving researchers the raw data that drives Heritage's policy positions.
July 25, 2006
By Michael J. New, Ph.D.
The U.S. Census Bureau estimates that 45.8 million
Americans (15.7 percent of the total population) lack health
insurance. Even though many are uninsured for only
part of the time in a given year, the persistently high number of
Americans without health insurance continues to inspire an intense
debate in policy circles, with both Democrats and Republicans
offering ideas about how to provide affordable health care coverage
for more Americans.
Many health policy analysts who cite Census Bureau statistics
argue for greater government intervention in health care as a way
to cover a larger percentage of Americans. One commonly proposed
solution is "single payer" plans, in which the government
would directly pay for or subsidize various health services.
Another proposal that continues to receive some attention is "pay
or play" plans, in which employers are required either to provide a
specified level of health insurance for their employees or to pay a
tax that is earmarked for providing coverage for the uninsured.
Often overlooked, however, is the fact that government
policy, particularly excessive regulatory intervention, may price
many Americans out of coverage and thus contribute to the high
numbers of uninsured.
The Current System
Health insurance is heavily regulated at the state level. Some
states require insurance plans to cover certain types of health
care providers or to provide certain types of health benefits.
Other state regulations affect the rating rules for insurance
or the ability of insurance plans to exclude people from coverage.
Still others limit the ability of insurance companies to select
health care providers.
Many of these regulatory initiatives, particularly in the area
of health insurance underwriting, are designed to achieve specific
policy goals, such as controlling escalating health care costs or
expanding the availability of health coverage, particularly
for high-risk individuals. Achieving these goals invariably
requires trade-offs, but policymakers rarely make these trade-offs
explicit. For example, rating rules that enable high-risk, older,
or sicker employees to get low-cost health insurance without
exclusions for medical conditions can make health insurance
affordable for these employees but at the price of making younger
and healthier employees pay higher premiums than they would
otherwise obtain in the market. When younger persons do not or
cannot participate in the health insurance market, their
conspicuous absence increases the pressure on the premiums for
those who remain in it.
Of course, the impact varies from state to state depending on
the specific regulations. In some states, regulations make it
impossible for individuals to purchase a low-cost plan that
would provide only catastrophic coverage. In other cases, the
benefit mandates and insurance rules might raise premiums
to the point that insurance is prohibitively expensive for many
The economic impact of state-level health insurance
regulations has generally received little analytic attention
from both the academy and the broader health policy community.
However, a more detailed analysis of this topic might provide
insights into how to lower insurance costs and provide better
health care coverage for more Americans.
It should be noted that the scope of this study is limited to
individualhealth insurance plans. This constitutes only a small
subset of the overall health insurance market. In 2000 and 2001,
67.2 percent of the U.S. non-elderly population was enrolled in
employer group coverage. Conversely, only 3.6 percent was enrolled
in non-group or individual coverage.
However, even though only a relatively small number of
individuals obtain insurance in the non-group market, it should be
noted that insurance costs in the individual market can have a
large impact on the number of uninsured individuals. The individual
market is effectively a residual market, consisting largely of
those without access to employer-sponsored insurance. Workers who
buy individual health insurance policies, in sharp contrast to
workers enrolled in employer-based group insurance, do not enjoy
the generous tax breaks that accompany the purchase of employer
group plans. Because non-group markets are a market of last resort
for so many individuals, the cost of premiums in these markets
likely affects whether or not many of these Americans can afford to
purchase health insurance for themselves and their families.
Furthermore, emerging economic trends will likely increase the
share of the working population without access to
employer-sponsored insurance. Beyond those who work in businesses
in which the employer does not offer health insurance,
increasing numbers of individuals are employed as sole
proprietors or independent contractors and need to purchase
insurance in non-group markets. Ensuring access to affordable
non-group health insurance should therefore be a priority for
Other Regulatory Studies
Relatively little academic and policy literature examines the
impact of state-level health insurance regulations on health
insurance premiums. Historically, part of the reason has been
the lack of publicly available state data on individual health
insurance costs. This is starting to change, and three studies
issued in 2005 have examined the issue.
In January 2005, Mark Showalter, William Congdon, and
Amanda Kowalski published a working paper entitled "State Health
Insurance Regulation and the Price of High-Deductible Policies." The authors used two separate datasets in
their analysis. Golden Rule insurance provided 2003 insurance
premium data from a series of random ZIP codes in 37 states, and
eHealthInsurance.com, a major Internet broker of health insurance,
provided premium data from insurance policies sold through its
The authors focused on four types of regulations: (1) mandated
health benefits, which require insurers to cover particular
treatments or particular services; (2) "any willing provider"
laws, which restrict insurers' ability to exclude hospitals and
doctors from their networks; (3) community rating laws, which
require insurers to limit premium differences across
individuals; and (4) guaranteed issue laws, which require insurers
to sell insurance to all potential customers regardless of health
or pre-existing conditions.
The authors found that each of these four types of regulations
results in statistically significant increases in health insurance
premiums. The findings were consistent across both the
eHealthInsurance.com and Golden Rule datasets. The authors
estimated that eliminating all of these regulations could save
individuals up to $2,000 per year in insurance premiums.
A second, unpublished study was released by Tracey LaPierre and
Chris Conover of the Center for Health Policy, Law and Management
in the Terry Sanford Institute of Public Policy at Duke
University. They obtained data on health insurance
premiums from the Community Tracking Surveys in 1996-1997,
1998-1999, and 2000-2001 and used the data to examine a wider range
of health insurance regulations.
Overall, the authors found that regulations have a mixed impact
on health insurance premiums. However, the authors argue that they
are limited by a small sample size. Furthermore, state regulatory
policies exhibit little variance across time, and this makes it
more difficult to reach definitive conclusions about the
causal impact of mandates.
Finally, the Congressional Budget Office (CBO) released a study
that examines how insurance prices affect health care coverage in
the non-group market. The CBO authors did not have direct access
to state premium data, but they were able to impute premiums by
examining the strength of various state community rating
Community rating laws limit the extent to which insurers can
charge different prices to individuals with varying medical
conditions. Community rating laws are commonly thought to
increase premiums because they require insurance companies to
charge healthy and unhealthy people relatively similar premiums.
Since low premiums will not generate enough revenue to cover
higher-risk individuals, premiums eventually increase, and the
cost of insurance goes up for both healthy and unhealthy
individuals in the non-group market.
In the CBO study, the authors found that, after holding a
variety of other factors constant, more individuals choose to forgo
coverage in states with strict community rating laws. This finding
achieves statistical significance. Overall, this analysis provides solid
evidence that community rating laws increase the cost of health
Problems with the Academic and Policy
All three studies provide some evidence that state-level health
insurance regulations increase insurance premiums. However, these
studies could also be improved in some ways.
First,it is not clear that the policies examined by these
studies are comparable across states. The Showalter and LaPierre
studies hold constant deductibles, coinsurance rates, and costs for
physician visits. However, policies that possess identical
deductibles, coinsurance, and coverage for physician visits
often have different prices because they offer different types of
coverage. The best way to examine the impact of insurance
regulation would be to compare the premiums of identical insurance
policies in different states. However, that was not done in any of
Second,the studies did not examine some potentially
relevant regulatory policies. There is a considerable amount
of anecdotal evidence about the impact of community rating and
guaranteed issue rules. However, relatively little research has
analyzed the impact of laws that allow health plan
subscribers to go directly to a specialist without a prior
referral, liability laws, or laws that interfere with a health
plan's ability to contract selectively with providers. These
kinds of regulations would likely increase the costs of providing
insurance; however, they are largely unexamined in the policy
In this paper, both of these shortcomings are addressed. This
study compares the costs of identical health insurance plans across
a number of states and analyzes a wider range of insurance
regulations. This provides more accurate insights into how
state-level regulations affect the price of insurance policies.
The data on the health insurance premiums for nine plans offered
by Celtic, six Golden Rule plans, and seven Fortis plans were
obtained from eHealthInsurance.com. The premium data come from September 2005
and September 2006 and cover 36 states. These plans exhibited significant
variance in terms of deductible, coinsurance, and coverage of
doctors visits. (For a list of the health insurance plans, see
Appendix A; for a list of states in which the three insurance
providers sell insurance, see Appendix B.)
Health insurance markets are regulated in a number of ways.
This study focuses on four sets of regulations that affect health insurance
This analysis compares the average health insurance
premiums in states that have these types of regulations to the
average premiums in states without such regulations. Since the
average state has 26 mandated benefits, it also compares
health premiums in states with more than 26 mandated benefits to
insurance premiums in states with 26 or fewer mandated
benefits. The results are shown in Table 1.
The results show that premiums tend to be higher in states that
regulate more heavily. On average, states with health plan
liability laws, direct-access-to-specialists laws, and provider due
process mandates have higher health insurance premiums than states
without these regulations. Furthermore, states with more than
26 mandated benefits have higher premiums than states with 26 or
fewer benefits. All of these findings achieve conventional
standards of statistical significance.
This analysis can be furthered through regression analysis,
which isolates the effects of each individual type of regulation by
"holding constant" other factors. Three sets of regressions
were run. Separate regressions were run on premium data obtained in
2005 and 2006. The third regression was run on a combined
dataset that included premium data from both 2005 and 2006. In each
regression, indicator variables were included to hold constant the
price differences among the different types of health
insurance plans. The results are shown in Table 2.
Overall, these results provide solid evidence that the
state-level regulations of health insurance are correlated with
higher premiums. The regression model estimates that the presence
of health plan liability laws increases monthly premiums by $21.84.
Laws that give subscribers direct access to specialists increase
monthly premiums by $31.15. Provider due process laws increase
premiums by $16.62. Finally, each additional mandated benefit
increases premiums by $0.75. All of these findings achieve
The robustness of these findings is demonstrated by the fact
that each of these four variables is positive and
statistically significant in the two regressions run on
premium data exclusively from 2005 and 2006. To further demonstrate
the robustness of these findings, three additional regressions on
premium data obtained from Celtic, Golden Rule, and Fortis
were conducted. The results are shown in Table 3. Once again, the
coefficients for variables indicating the presence of
direct-access-to-specialists laws, provider due process laws,
and the number of mandated benefits are positive and
statistically significant in all three regressions.
Furthermore, the coefficients for the variables
indicating the presence of health plan liability laws are
positive and statistically significant in two of the three
One limitation of this research is that some of the variation in
health insurance premiums could be due to regional differences in
the underlying cost of health care, which could be caused by
prevailing wages and professional fees, the volume of medical
services, or medical practice patterns. However, the premiums in
high-cost states are routinely 50 percent to 100 percent
higher than premiums in low-cost states, and it is extremely
unlikely that regional cost differences could account completely
for such disparities. Nonetheless, this is something that should be
considered in more detail in future research.
Another limitation of this study is that none of the three
companies studied offers health insurance in states with
guaranteed issue laws or strict community rating. Therefore, this
study provides no hard data on how these particular regulations
affect insurance prices. However, the CBO study provides evidence
that community rating laws result in higher premiums. Furthermore,
considerable anecdotal evidence indicates that both guaranteed
issue laws and strict community rating laws substantially increase
the cost of insurance. In addition, the fact that none of the three
companies studied offers policies in states with these laws
underscores the difficulty of providing individual health
insurance policies in these states.
An extensive time series dataset on both premiums and regulatory
policies would add considerable leverage to this analysis. Time
series data would enable researchers to determine with greater
confidence how changes in state regulatory policy affect the cost
of insurance. However, this study analyzed premium and regulatory
data from only two years because data covering a longer time-span
proved difficult to acquire. Nonetheless, this research still
contributes to the policy and academic literature that indicates
that state-level health insurance regulations are correlated
with higher prices for purchasers of health insurance.
Michael J. New, Ph.D., is Visiting
Health Policy Fellow at The Heritage Foundation and an Assistant
Professor at the University of Alabama. The author would like to
thank John Porter and Mark Jackson for their help with data
This paper is a
revised version of Michael J. New, Ph.D., "The Effect of State
Regulations on Health Insurance Premiums: A Preliminary
Analysis," Heritage Foundation Center for Data Analysis
Report No. 05-07, October 27, 2005, at http://www.heritage.org/Research/HealthCare/cda05-07.cfm.
Using 2005 data, the earlier report found that state-level health
insurance regulations are correlated with higher insurance
premiums. This revised version augments the original version
by analyzing similar data from both 2005 and 2006. These additional
data strengthen the finding that increased state-level regulation
of health insurance leads to higher premiums.
DeNavas-Walt, Bernadette D. Proctor, and Cheryl Hill Lee,
Income, Poverty, and Health Insurance Coverage in the United
States: 2004, U.S. Census Bureau, Current Population
Reports: Consumer Income, P60-229, August 2005, at /static/reportimages/AED357397B8DD1FD731B3EF92FD0E965.pdf
(October 18, 2005).
Studying Health System Change, Community Tracking Survey
Congdon, Amanda Kowalski, and Mark H. Showalter, "State Health
Insurance Regulations and the Price of High-Deductible Policies,"
January 12, 2005, at /static/reportimages/A1228516F751D40C9C7FC283CC51F0D3.pdf
(October 17, 2005).
Tracy LaPierre and
Chris Conover, "Estimating the Impact of State Health Mandates on
Premium Costs Using the Community Tracking Survey," working paper,
Budget Office, "The Price Sensitivity of Demand for Nongroup Health
Insurance," Background Paper, August 2005, at /static/reportimages/79ABB18D6301D4D3C26BE05FFABD90EC.pdf
(October 13, 2005).
Data from the
state of New Jersey indicate that when New Jersey adopted
guaranteed issue in 1993, premiums for a family policy with a $500
deductible and a 20 percent copayment increased anywhere from 500
percent to 700 percent. Premiums also increased in New York,
New Hampshire, and Kentucky when these states adopted guaranteed
issue laws. Victoria Craig Bunce, "What Were These States Thinking?
The Pitfalls of Guaranteed Issue," Council for Affordable Health
Insurance Issues & Answers No. 104, May 2002, at /static/reportimages/CDA182B905F1CCF7B20A2F28BF7790A9.pdf (October
17, 2005). Finally, eHealthInsurance.com periodically releases
state data on average premiums on policies sold through its Web
site. In October 2004, March 2003, and September 2003, the highest
average premiums were in New York and New Jersey, the only two
states included in the dataset that have both guaranteed issue laws
and strict community rating laws.
The premium data
were collected for a 30-year-old male who does not smoke and is not
Starting in 2006,
a company called Life began to underwrite the plans that previously
had been offered by Fortis. An attempt was made to select plans
that were similar in terms of deductibles and coinsurance rates;
however, there exist some differences between the plans that Life
offered in 2006 and the plans that Fortis offered in 2005. For a
complete listing of the plans, see Appendix B.
anecdotal data indicate that guaranteed issue rules and community
rating laws increase health insurance premiums. However, neither
regulation is considered in this study because Celtic, Fortis, and
Golden Rule do not sell insurance in states that have guaranteed
issue laws or strict community rating.
state-level regulations were obtained from BlueCross BlueShield,
"State Legislative Health Care and Insurance Issues," December
2004. For a listing of the states that have these various
regulations, see Appendix C.
In September 2004,
six states had guaranteed issue laws: New York, New Jersey,
Massachusetts, Maine, New Hampshire, and Vermont. During the
summer of 2005, Fortis, Celtic, and Golden Rule did not offer
policies in any of these states, and eHealthInsurance.com sold
insurance in only two of them (New York and New Jersey).
Many health policy analysts who cite Census Bureau statistics arguefor greater government intervention in health care as a way tocover a larger percentage of Americans. One commonly proposedsolution is "single payer" plans, in which the governmentwould directly pay for or subsidize various health services.Another proposal that continues to receive some attention is "payor play" plans, in which employers are required either to provide aspecified level of health insurance for their employees or to pay atax that is earmarked for providing coverage for the uninsured.
Michael J. New, Ph.D.
Assistant Professor of Political Science at the University of Alabama
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