October 27, 2005
By Michael J. New, Ph.D.
more up-to-date research on the state insurance markets,
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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.
Indeed, 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 a
"single payer" plan, 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 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.
Health insurance is
heavily regulated at the state level. Some states require insurance
plans to cover certain types of health care providers or 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 costly for many people.
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 individual health
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 were 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.
emerging economic trends will likely increase the share of the
working population without access to employer-sponsored insurance.
Beyond those who work in businesses where 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 policymakers.
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 during the past year
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 Web site.
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.
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
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
Congressional Budget Office (CBO) recently 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
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
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 Literature
All three studies
provide some evidence that state-level health insurance regulations
increase insurance premiums. However, these studies could all be
improved in some ways.
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 these 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 literature.
In this paper, I
address both of these shortcomings. I look at the costs of
identical health insurance plans across a number of states and
analyze a wider range of insurance regulations. This should provide
better and more accurate insights into how state-level regulations
affect the price of insurance policies.
To conduct this
study, I obtained data on health insurance premiums through the
eHealthInsurance.com Web site, including nine plans offered by
Celtic, six plans offered by Golden Rule, and seven plans offered
by Fortis. These plans exhibited significant variance
in terms of deductible, coinsurance, and coverage of doctors
visits. This allowed me to obtain data on health insurance premiums
from over 37 states. (For a list of the 22 health insurance plans,
see Appendix A; for a list of states in which the three insurance
providers sell insurance, see Appendix B.)
markets are regulated in a number of ways. However, I focus on four
sets of regulations that affect health insurance
To begin this
analysis, I compared 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, I also compared 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 Table
Table 1 shows that
premiums tend to be higher in states that regulate more heavily. On
average, states with health plan liability laws,
direct-access-to-specialist 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 easily achieve conventional
standards of statistical significance.
This analysis can be
furthered through regression analysis, which allows us to isolate
the effects of each individual type of regulation by "holding
constant" other factors. Four sets of regressions were run.
Separate regressions were run on premium data obtained from Celtic,
Golden Rule, and Fortis. The fourth regression was run on a
combined dataset that included premium data from all three
insurance companies. In each regression, indicator variables were
included to hold constant the price differences among the different
types of plans. The results are shown in Table 2.
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 $26.72. Laws that give
subscribers direct access to specialists increase monthly premiums
by $33.10. Provider due process laws increase premiums by $22.49.
Finally, each additional mandated benefit increases monthly
premiums by $0.89. All of these findings easily achieved
The three separate
regressions run on premium data exclusively obtained from Celtic,
Golden Rule, and Fortis indicate that these findings are robust.
The coefficients for variables indicating the presence of
direct-access-to-specialist laws and provider due process laws are
positive and statistically significant in all three regressions.
The coefficients for the variables indicating the presence of
health plan liability laws are positive in all three regressions
and statistically significant in two. Finally, the mandated
benefits coefficients are positive in all three regressions,
reaching statistical significance in one regression and approaching
statistical significance in a second.
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, it should be noted that 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.
of this study is that none of the three companies studied offers
health insurance in states with guaranteed issue laws or states
with strict community rating. Therefore, this study provides no
hard data on how these particular regulations affect these
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.
cross-sectional data 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 only from a single
period because time series data 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 Assistant Professor of Political Science at the University of
Show references in this report
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
www.census.gov/prod/2005pubs/p60-229.pdf (October 18,
Center for Studying
Health System Change, Community Tracking Survey
William J. Congdon,
Amanda Kowalski, and Mark H. Showalter, "State Health Insurance
Regulations and the Price of High-Deductible Policies," January 12,
(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,
Office, "The Price Sensitivity of Demand for Nongroup Health
Insurance," Background Paper, August 2005, at
(October 13, 2005).
Ibid., p. 12.
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
www.cagionline.org/cahidoc.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
The premium data
were collected for a 30-year-old male who does not smoke and is not
a student. The insurance policy would have been purchased sometime
in August 2005, and coverage would have begun on September 1,
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.
Data on state-level
regulations were obtained from Blue Cross Blue Shield, "State
Legislative Health Care and Insurance Issues," December 2004. For a
listing of the states that have these various regulations, see
In September 2004,
six states had guaranteed issue laws: New York, New Jersey,
Massachusetts, Maine, New Hampshire, and Vermont. Fortis, Celtic,
and Golden Rule did not offer policies in any of these states, and
eHealthInsurance.com sold insurance in only two of these states
(New York and New Jersey).
Those who argue for greater government intervention in health careoften overlook the fact that government policy, particularlyexcessive regulatory intervention, may price many Americans out ofcoverage and thus contribute to the high numbers of uninsured. Atthe state level, the evidence indicates that health insuranceregulations are correlated with higher prices for purchasers ofhealth insurance.
Michael J. New, Ph.D.
Assistant Professor of Political Science at the University of Alabama
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