Working Paper Series

Congressional Budget Office

Washington, D.C.

Will Health Insurance Mandates Increase Coverage?

Synthesizing Perspectives from the Literature in Health Economics, 

Tax Compliance, and Behavioral Economics

David Auerbach

Congressional Budget Office

Washington, D.C.

david.auerbach@cbo.gov

Janet Holtzblatt

Congressional Budget Office

Washington, D.C.

janet.holtzblatt@cbo.gov

Paul Jacobs

Congressional Budget Office

Washington, D.C.

paul.jacobs@cbo.gov

Alexandra Minicozzi

Congressional Budget Office

Washington, D.C.

alexandra.minicozzi@cbo.gov

Pamela Moomau

Joint Committee on Taxation

Washington, D.C.

pamela.moomau@mail.house.gov

Chapin White

Congressional Budget Office

Washington, D.C.

chapin.white@cbo.gov

August 2010

Working Paper 2010-05

Working papers in this series are preliminary and are circulated to stimulate discussion and critical 

comment. These papers are not subject to CBO’s formal review and editing processes. References in 

publications should be cleared with the authors. Papers in this series can be obtained at www.cbo.gov 

(select Publications and then Working Papers).
Abstract

This paper provides an analytical framework for evaluating the effects of individual health 

insurance mandates on coverage. That framework draws from the literature in three disciplines—

health economics, tax compliance, and behavioral economics—to identify the factors that affect 

people’s responses to health insurance mandates. The health economics literature examines how 

people value health insurance and how changes in its costs affect coverage. The tax compliance 

literature indicates that the probability of detection and people’s attitudes toward risk affect 

perceptions of those costs. The salience of the mandate and social norms—factors identified in

the literature of behavioral economics—are also important factors in decisions about coverage.

Acknowledgment

This paper was prepared for the 40th Symposium of the National Tax Association in 

Washington, D.C., May 13, 2010. The authors thank James Baumgardner, Adam Block, Philip

Ellis, Marjorie Hoffman, Rachel Levy, Bernard Schmitt, and Gene Steuerle for their comments. 

A version of this paper will be published in the December 2010 edition of the National Tax 

Journal.
I. Introduction

Two laws enacted in March 2010, the Patient Protection and Affordable Care Act 

(PPACA, Public Law 111-148) and the Health Care and Education Reconciliation Act of 2010 

(HCERA, P.L. 111-152), require almost every resident of the United States to have health

insurance by January 1, 2014. Failure to comply with what is known as the individual mandate 

can carry a financial penalty, which—when the provisions are fully implemented in 2016—will

range from $695 for a single person with low or moderate income to as much as $12,500 for a 

high-income family. This paper provides an overview of the analytical framework used by the 

Congressional Budget Office (CBO) and the staff of the Joint Committee on Taxation (JCT) to

model the effects of an individual mandate on health insurance coverage.

Over the next decade, the two laws also will provide for about $900 billion in new 

subsidies, including a substantial expansion of Medicaid and new tax credits to offset the cost of 

health insurance premiums for low- and middle-income families and small businesses. In each 

state, exchanges will be established to facilitate the purchase of coverage and the delivery of the 

subsidies. Some companies whose workers receive subsidies for health insurance through the

exchanges could be required to pay penalties. Changes to the existing health insurance system

include provisions that guarantee access to health insurance, regardless of preexisting conditions

(although that provision would tend to increase the cost for healthier applicants). CBO estimates 

that, by the end of the decade, policies contained in the two new laws will reduce the size of the 

uninsured nonelderly population by more than 30 million people, from 54 million to 23 million 

U.S. residents (CBO, 2010b).

The legislative debate on health reform gave expression to a wide range of views 

regarding the consequences of the individual mandate. Some analysts argued that a mandate 
2

would encourage more people—especially the young and the healthy—to purchase insurance 

(for example, Gruber, 2010). Others wondered whether uninsured people—especially the young 

and the healthy—would forgo coverage even with the mandate, particularly if they could spend 

less on a penalty than they would to purchase health insurance (Cassidy, 2010; Kling, 2010). 

Another focus of debate concerned the mandate’s enforceability. Some observers predicted that 

people would enroll out of fear that an expanded tax agency would have new powers; others 

suggested that many people would not comply as long as they believed that the Internal Revenue 

Service (IRS) did not have sufficient authority or resources to enforce the new requirement

(Block, 2010; Cassidy, 2010).

Estimating the results of legislative proposals to expand health insurance coverage is 

challenging, partly because there is so little empirical evidence concerning individual people’s

responsiveness to health insurance mandates. Since 2007, adults in Massachusetts have been 

required to have health insurance or face penalties for noncompliance, but it may be too soon to 

infer the effect of mandates from that experience. Moreover, that experience itself could be 

unique to Massachusetts. In the absence of direct empirical evidence, research from three 

different disciplines—health economics, tax compliance, and behavioral economics—provide 

alternative perspectives on the effect of the mandate on coverage.

• The literature on health economics examines how people value health insurance and how 

changes in cost can influence decisions to obtain coverage. Penalties, like subsidies, can 

affect decisions by making it cost more to be uninsured relative to the cost of being 

insured.

• The tax compliance literature indicates that the effectiveness of mandates can depend on

people’s feelings about risk, about the likelihood of detection for noncompliance, and 
3

about the size of penalties relative to the cost of compliance. But that literature also 

suggests that models of compliance behavior could consider additional factors, including 

people’s tendencies to be honest; their propensity to feel guilt or shame when they break 

rules; and their perceptions about the desirability of promoting fairness.

• The literature on behavioral economics provides a framework for explaining why people 

do not always appear to act rationally or in their own self-interest. The salience of the 

mandate and social norms—factors identified in the literature of behavioral economics—

are important factors in decisions about coverage.

CBO and JCT’s analysis of individual mandates represents a synthesis of the three perspectives.

This paper describes how those perspectives shaped the development of a model used to estimate

the effect of the individual mandate on people’s decisions to enroll in health insurance plans.

II. Overview of PPACA and HCERA 

PPACA, in combination with HCERA, uses incentives, as well as penalties, to help 

achieve the goal of increasing health insurance coverage for U.S. residents. Detailed descriptions 

of those provisions have been presented by JCT (2010). The laws’ incentives to encourage 

people to obtain health insurance coverage include the following:

• Within each state, health insurance exchanges are established to link people with 

insurance plans and to enroll eligible applicants in new subsidy programs. Four standard

health plans, labeled “bronze,” “silver,” “gold,” and “platinum,” will cover a specified set 

of benefits, paying (on average) 60 percent, 70 percent, 80 percent, or 90 percent, 

respectively, of a beneficiary’s claims.
4

• Medicaid will be extended to most nonelderly legal residents of the United States whose 

income is below 138 percent of the federal poverty guideline, often called the federal 

poverty level.

1

• A new premium assistance tax credit will be offered to taxpayers, depending on their 

circumstances. Some individuals and families whose income is between 138 and 400 

percent of the federal poverty level will be eligible for the new credit. (People who have 

offers of coverage from their employers generally will not be eligible.) The refundable 

tax credit equals the difference between a “reference premium” and a specified 

percentage of income—initially ranging from about 3 percent for people whose income is 

138 percent of the poverty level to 9.5 percent for people whose income is 400 percent of 

the poverty level. The reference premium is based on the silver plan with the secondlowest cost offered in a locality. Some lower income people also will be eligible for 

subsidies that would reduce the cost-sharing requirements under their insurance plans.

• Changes to the insurance market ensure that people will be offered coverage even if they 

have preexisting medical conditions; insurers will not be allowed to vary premiums on 

the basis of applicants’ health.

 1 Legal noncitizen residents who have resided in the United States for less than five years are not eligible for 

Medicaid but could be eligible for refundable tax credits provided through the exchange. Although PPACA by itself 

requires states to cover most people whose modified adjusted gross income is below 133 percent of the federal 

poverty level (in 2009, for most of the United States, that amount was $10,830 for a one-person household), 

HCERA added a provision that instructs states to reduce the gross income of applicants by an amount equal to 

5 percent of the federal poverty level, thus effectively raising the Medicaid income eligibility threshold to 

138 percent of the federal poverty level. 
5

• Some small businesses will receive tax credits to offset their contributions to premiums. 

To be eligible, a company cannot employ more than 25 workers, and, in 2010, those 

workers must earn less than $50,000, on average. Beginning in 2014, the earnings 

threshold will be indexed to the consumer price index for urban workers (CPI-U).

The legislation’s penalties apply to certain employers, as well as to individual people who

do not obtain coverage. In particular, a company with at least 50 full-time employees that does 

not offer insurance could be subject to penalties. Other penalties can be imposed if the insurance 

offered is deemed unaffordable. In all cases, penalties apply when at least one employee receives

a premium assistance credit or cost-sharing subsidy through the state exchange.

III. The Health Insurance Mandate

By January 1, 2014, nearly every resident of the United States will be required to have 

health insurance coverage. To comply with the new rules, people generally must be enrolled in 

qualifying plans that provide minimum essential coverage.

2 Subject to certain requirements, the 

Secretary of Health and Human Services will define “essential” benefits, ensuring that their

scope is consistent with what is currently offered by typical employers. Qualifying coverage 

includes government-sponsored programs, such as Medicare and Medicaid, eligible employersponsored plans, and individual plans offered in the state’s individual market. Penalties are to be 

assessed through the individual income tax system.

 2 Employer-sponsored and individually purchased plans that provide less extensive benefits are also eligible if they 

were grandfathered under the acts.
6

A. Penalty Amounts

People who do not comply with the mandate will be assessed the greater of two amounts,

either a flat rate or a percentage of income:

• Flat dollar amount. The flat amount per uninsured adult initially is set in 2014 at $95 but 

rises to $325 in 2015 and to $695 in 2016. After that, the penalty will be indexed to the 

CPI-U. For dependent children under the age of 18, the penalty is half the amount a 

single adult would pay. The penalty for the entire filing unit—that is, the taxpayer, his or 

her spouse (if married), and any dependents—is capped at three times the amount for one 

adult ($2,085 in 2016).

• Percentage of income. A penalty also can be set at a percentage of income that is in 

excess of the filing threshold: 1 percent in 2014, 2 percent in 2015, and 2.5 percent in 

2016 and subsequent years. The “income” in question is the sum of the modified adjusted 

gross incomes of the taxpayer and any dependents who are required to file their own tax 

returns.3

The total penalty for the filing unit cannot exceed the average national cost of a bronze plan 

offered through the exchange that year. Projections for that value in 2016 range from $4,500 to

$5,000 for a single plan and from $12,000 to $12,500 for a family plan (CBO, 2010a).

Some people can obtain an exemption from the mandate, and some people who are 

subject to the mandate could be exempt from the penalty. Noncitizens who reside in the United 

States illegally, members of certain religious groups, and prisoners are not required to have 

 3 Modified adjusted gross income is adjusted gross income increased by the amount (if any) that normally is 

excluded by section 911of the Internal Revenue Code (the exclusion from gross income for citizens or residents 

living abroad) plus any tax-exempt interest received or accrued during the tax year.
7

health insurance coverage.

4

• Low income. Anyone in a filing unit whose income is below the income tax filing 

threshold is exempt from paying a penalty. The tax filing threshold equals the sum of the 

applicable standard deduction and the personal exemptions for the taxpayer and his or her 

spouse. The threshold amount does not include the exemptions for the taxpayer’s 

dependents, so it declines as a percentage of the federal poverty level as family size 

increases. The filing threshold is typically under the federal poverty level—except for 

married couples who have no dependents (see Table 1).

People who are subject to the mandate but exempt from the penalty 

constitute a much larger group:

Table 1

Thresholds for Filing Returns and Becoming Subject to Mandate Penalties, 2016

Filing Status

Number of 

Dependents

Filing and Penalty Thresholds

Income 

Threshold ($)

Relative to 

Federal 

Poverty Level

(%)

Single 0 10,250 88

Head of Household 1 13,150 84

2 13,150 66

Married Filing Jointly 0 18,400 117

2 18,400 77

Source: Authors’ calculations.

Note: The filing thresholds were calculated under the assumption that the provisions of the Economic Growth and Tax 

Relief Act of 2001 would expire. 

• Insurance is deemed unaffordable. Someone who has an offer of employment-based 

insurance will be eligible for an affordability exemption if the required contribution for a 

self-only policy (which covers the worker but not his or her family) exceeds 8 percent of 

the worker’s income. Someone without an employment-based offer will be eligible for an 

 4 People who are exempt from the mandate for religious reasons must be members of and adhere to the tenets of a 

recognized religious sect that is exempt from self-employment taxes.
8

affordability exemption if the cost (net of subsidies) of the least expensive bronze plan in 

the local exchange exceeds 8 percent of his or her income.

• Hardship. People who experience hardship in obtaining coverage also are eligible for an 

exemption. How hardship is defined or proven is to be determined by the Secretary of 

Health and Human Services through regulations. 

• Members of Indian tribes. All members of Indian tribes are exempt from the penalty.

• Short coverage gaps. Penalties are waived for one gap in coverage during a year, as long 

as the gap is not longer than three consecutive months.

CBO and JCT have estimated that 13 million to 14 million of the 21 million nonelderly people 

who will be uninsured in 2016 will be exempt from the mandate or its penalties because they are 

unauthorized immigrants, have low income, have an offer of coverage that is deemed 

unaffordable, or are members of Indian tribes. Other exemptions, such as those for hardship or 

religious beliefs, will further contract the population that is subject to penalties (CBO, 2010c).

The effects of those provisions can be illustrated for unmarried people and for fourperson families (see Figure 1). A single childless person whose income is less than $10,250 in 

2016 (roughly 90 percent of the projected federal poverty level for that year) will be exempt 

from penalties because he or she will not have earned enough to be required to file a tax return. 

Uninsured people whose income is roughly between 90 percent and 300 percent of the federal 

poverty level amount typically would be subject to the flat dollar penalty of $695; they also 

would be likely to be eligible for Medicaid or for tax credits. People whose income was higher 

would pay a penalty equal to 2.5 percent of family income. For people whose income was above

about $200,000, penalties would be capped at the cost of the lowest-cost bronze plan for an 

individual (perhaps between $4,500 and $5,000 per year). In 2016, a married couple with two 
9

children—if all four family members lacked insurance—would begin paying penalties when 

their income exceeded $18,500 (or about 80 percent of the federal poverty level); for families 

whose income was above that threshold but below 400 percent of the poverty level, the 

combined penalty would equal $2,085. Above 400 percent, uninsured families would begin

paying 2.5 percent of their income until the maximum penalty—which would equal the cost of 

the least expensive family bronze plan (estimated at $12,000 to $12,500, on average)—is reached 

when the family’s income exceeds about $500,000.

B. Enforcing the Mandate 

The IRS will be responsible for enforcing the mandate and collecting fines. By January 

31 each year, the agency will receive enrollment information from private insurers and public 

programs for the previous calendar year; that information will include the name and Social 

Security number of every person covered by each plan and the dates of coverage. Policyholders 

will receive similar information from insurers. The exchanges will be required to report to the 

IRS the name and taxpayer identification number of every person who receives an affordability 

or hardship exemption.

The reporting requirements should provide the IRS with the tools it needs to identify 

noncompliant people in the same way that it detects underreported income from W-2 forms and 

other reports. PPACA constrains somewhat the way the IRS may respond to noncompliance: 

Neither liens nor levies are to be used to collect penalties, nor is the IRS permitted to seek 

criminal penalties against people who do not comply with the mandate. However, the provisions 

of the laws do not prevent the IRS from using other common enforcement tools, such as datamatching programs, deficiency procedures (typically, audits), offsets to tax refunds or other 
10

government payments, and civil penalties.5

IV. Experience with Mandates

It is not yet known how the IRS will actually 

implement enforcement of the mandate; as is typically the case with authorizing legislation,

neither of the acts includes appropriations to cover the costs of enforcement. 

There is little empirical evidence regarding the responsiveness of individuals to health 

insurance mandates. Two states (Hawaii and Massachusetts) require many of their employers to 

provide coverage for employees or face penalties, but the responsiveness to a mandate requiring 

employers to offer insurance is likely to be different from the reaction to a broader mandate that 

individual people obtain coverage. Although Massachusetts currently requires adults to have 

health insurance, that mandate has been in existence for less than four years. State and local 

governments mandate other types of behavior, however, from requiring drivers to buy auto 

insurance to requiring school-age children to be vaccinated against a variety of diseases. 

Moreover, the federal government and many states require workers to pay income taxes and 

employers to pay minimum wages. Nevertheless, the comparability of such mandates to a health 

insurance mandate is debatable.

A. The Massachusetts Experience

As a result of a law enacted in 2006, every Massachusetts resident who is age 18 or older 

must have health insurance. Implementation of the individual mandate was phased in over three 

years. By May 1, 2007, everyone had to have health insurance — but there were no penalties for 

failure to comply during that year as long as coverage was in place on December 31. In 2008, 

 5 In 2009, the IRS Criminal Investigation Program initiated 3,368 investigations (excluding narcotics-related 

financial crimes) and referred 2,038 cases for prosecution. Fewer than 1 million federal tax liens were filed in 2009, 

and about 3.5 million notices of levies were served on third parties. In contrast, the IRS assessed more than 

26 million civil penalties related to individual income tax liabilities in 2009 (about 3 million of them were abated) 

(IRS, 2009).
11

however, everyone had to have coverage each month. In 2009, everyone was required to have 

coverage under a health plan with specific benefits. Penalty amounts also were phased in over 

the first three years—beginning at about $219 per adult in 2007 and currently ranging from about 

$200 to $1,100 per year for each uninsured adult.

6

Although similar to the new national mandate, the Massachusetts mandate is more 

limited. First, it applies only to adults. Second, penalties begin to be imposed on people at higher 

incomes (beginning at 150 percent of the federal poverty level instead of somewhat below the 

level, as under the national mandate), and the maximum penalty in Massachusetts is substantially 

below the federal amount. Finally, although the Massachusetts Department of Revenue enforces

the mandate, its ability to detect noncompliance is somewhat limited by a lack of documentation; 

in particular, the Social Security numbers of the insured are not included in reports provided by 

the insurers. Without that information, it is difficult to match tax returns and reports from 

insurers and thus to detect noncompliance.

Massachusetts subsidizes insurance purchased 

for people in low-income households, and changes were also made to regulation of the insurance 

markets.

The evidence from the Massachusetts mandate is not easy to interpret at this point, in 

large part because of the number of changes that occurred simultaneously. Among working-age 

adults, the uninsurance rate fell by 70 percent after the passage of the state’s health reform 

legislation—from 13 percent in the fall of 2006 to 4 percent two years later (see Table 2). That 

drop, however, reflects all aspects of Massachusetts’ health reform initiatives—including a 

Medicaid expansion, creation of new subsidies, market reforms, and extensive outreach—and 

 6 Those penalties are adjusted annually and will remain in effect after the federal individual mandate is implemented 

unless the Massachusetts legislature takes action to reverse the 2006 state law.
12

thus would be an overestimate of the effect of the mandate itself. Notably, the largest decline in 

insurance coverage occurred between the fall of 2006 and the fall of 2007, after the requirement 

to obtain coverage and the subsidies had become effective but several months before imposition 

of the first penalties for noncompliance. Still, although the most substantial increase in coverage 

occurred in that first year and among people whose income was below 300 percent of the federal 

poverty level (and who thus were eligible for subsidies), coverage also expanded throughout the 

period among people in higher income groups.

Table 2

Uninsurance Rates in Massachusetts Among Adults, Aged 18 to 64

Family Income Fall 2006

(%)

Fall 2007

(%)

Fall 2008

(%)

Less Than 300 Percent of the Federal Poverty Level 23.8 12.8 7.6

More Than 300 Percent of the Federal Poverty Level 5.3 2.9 1.4

Total 13.0 7.1 4.0

Source: Long and Stockley (2009).

B. Other Types of Mandates

Although experience with enforcing mandates for health insurance is limited, some 

lessons can be drawn from other types of enforcement. National compliance rates for certain 

other mandates—such as provisions requiring that workers receive at least the minimum wage, 

children be vaccinated, drivers purchase auto insurance and wear seat belts, and people pay 

taxes—range from 63 percent to 85 percent, and the rates appear to improve as enforcement

intensifies (Ashenfelter and Smith, 1979; Davis and Gaglia, 2005; Insurance Research Council, 

2006; IRS, 2007; NHTSA, 2008). The data from those studies of compliance can provide some 

insight about compliance overall. The rates of compliance do not necessarily clearly identify the 

effect of a mandate itself, however, because the figures can include people who might have 

complied even without a legal requirement to do so. Their actions could be attributable to the 
13

value of a mandated item (such as automobile insurance), the existence of a subsidy (for free or 

low-cost vaccinations, for example), or changes in social attitudes (for example, when certain 

behavior—such as driving without ensuring that child passengers have fastened their seat belts—

is no longer deemed acceptable and is, instead, frowned upon).

V. Perspectives from Health, Tax, and Behavioral Economics

Data concerning existing federal and state mandates provide insight about compliance

generally, but that information alone cannot explain why people comply at all or how different 

features of a mandate might affect coverage. The economics literature in three disciplines—

health economics, tax compliance, and behavioral economics—reveals a variety of perspectives 

on how and why people might respond to a health insurance mandate. 

A. Health Economics

Some analysts have wondered why uninsured people would purchase health insurance as 

the result of a mandate (Cassidy, 2010; Kling, 2010). After all, for many people the penalty 

would cost less (at least in the very short-term) than a policy. Health insurance mandates differ 

from some other requirements, such as the requirement to pay taxes: In exchange for compliance, 

enrollees individually receive a tangible good—health insurance—that they value.

Health economics provides a framework for considering how changes in the price of 

health insurance affect coverage.7 People compare the price of health insurance with their 

perception of its value. Those who are currently insured have decided that the value of coverage 

is greater than its cost (including the costs involved with finding and enrolling in a plan).8

 7

A

reduction in the price would cause currently uninsured people to obtain coverage if the new price 

Key Issues in Analyzing Major Health Insurance Proposals (CBO, 2008) provides information on how CBO 

estimates that changes in the price of health insurance could affect coverage. 

8 Some people with significant health problems might not be able to obtain insurance coverage at any price unless 

they are guaranteed coverage through the individual market in their state.
14

is less than or equal to the value they place on health care coverage. Given the tremendous 

variation in individual “valuations” of health insurance and in the wide range of prices for 

insurance policies, some people are likely to be near the cusp of the “buy/don’t buy” decision,

and moderate changes in price could induce them to purchase coverage. Empirical studies 

support this notion, suggesting that a new 25 percent subsidy for individually purchased 

coverage would cause between 2 percent and 6 percent of the uninsured population to buy that 

coverage (Auerbach and Ohri, 2006; Marquis and Long, 1995). 

Because of the pervasiveness of employment-based insurance, the effects of any proposal 

that changes the opportunity cost of insurance depend not only on how people respond directly to 

those provisions but also on how businesses respond in their decisions about offering insurance

coverage to employees and about paying part of the cost of that coverage. In general, businesses 

compete for workers by offering wage and benefit packages designed to attract and retain 

employees. Employers offer health insurance if they believe employees prefer such coverage to 

cash wages. Consequently, an employer’s response to a change in government policy will be a 

function of how that policy affects the attractiveness of health insurance to its workforce, on 

average (Monheit and Vistnes, 1999). 

As with employers’ decisions to offer health insurance, workers’ choices to enroll in a 

plan will depend on the price of employment-based health insurance and alternative coverage 

options available to them or their spouses. From an employee’s point of view, the relevant price 

is the portion of the premium paid by the employee, not the total cost of coverage (Cutler, 2003; 
15

Jacobs, 2009).9

Generally, empirical studies have considered the effect of subsidies on health insurance 

coverage. But mandates to obtain health insurance often include monetary penalties for 

noncompliance, and thus a mandate with a penalty also affects the relative price of health 

insurance by making it costlier to be uninsured. In this respect, the health economics literature is 

an obvious starting point to search for information about the possible effects of mandates on 

coverage choices. When viewed as analogous to subsidies, there can be a straightforward 

integration of mandate penalties into models of individual and business behavior regarding 

choices about health benefits. For example, a model of companies’ decisions to offer health 

insurance in response to subsidies can be modified to reflect the average penalty people would 

face if workers became uninsured. Such penalties could cause a business to offer health coverage

if it does not already do so. Likewise, models designed to identify the effects of subsidies on 

individual choices to obtain insurance or not can be altered to incorporate the effects of penalties.

The analytical framework of this paper, then, models the individual person’s decision to 

obtain insurance in response to a mandate as follows:

( ( )) Ei = Pr Vi ≥ Pi − M i (1)

where i indexes individuals, Ei indicates the likelihood of individual enrollment in health 

insurance, Pr (●) is the probability of enrolling, Vi is the valuation of health insurance by the 

individual, Pi is the premium (net of subsidies) an individual would pay, and Mi is the mandate’s 

 9 Even though workers, in the aggregate, ultimately “pay” for employers’ contributions to their health insurance,

primarily through reduced wages, employees’ decisions about enrollment in a plan that their employers have 

decided to offer are not as sensitive to the amount employers pay.
16

effect on the individual. Thus, the probability of enrolling in a health insurance plan depends on 

a person’s valuation of health insurance, the premium (net of subsidies), and the effect of the 

mandate. In this context, the mandate effect could simply be modeled as the amount of the 

statutory penalty.

Although health economics provides a useful starting point for such analyses of coverage, 

the ultimate effect of a mandate is not easily reduced to, and in fact could differ from, the 

predicted effect of treating penalty amounts as dollar-for-dollar equivalents to subsidies. People 

can respond to penalties and subsidies differently and in ways that are not considered in standard 

health economics models. As a result, modeling structures originally designed to estimate how 

coverage choices could change when subsidies are offered could be insufficient for examining 

mandates alone or in combination with other coverage-related policies.

B. Tax Compliance

Tax compliance researchers begin with the supposition that people compare the marginal 

benefit of noncompliance (reduced tax payments, for example) with the expected marginal costs, 

which account for both the likelihood of punishment and its severity. That perspective provides 

an approach for evaluating the effective penalties uninsured people could anticipate under an 

individual health mandate.

Allingham and Sandmo (1972) first analyzed tax compliance under the assumption that 

taxpayers are risk averse and policymakers have three policy tools: the marginal tax rate, the 

probability of audit, and the penalty for misreporting income. Changes in marginal tax rates can 

induce offsetting substitution and income effects (the former because the gain from cheating 

rises with income and the latter because people become more risk averse as after-tax income 
17

falls), and the evidence is mixed regarding which effect dominates (Andreoni, Erard, and 

Feinstein, 1998). Many of the early compliance models assumed that audits were expensive but 

that penalties could be imposed at low cost to the enforcing agency once an error had been 

detected. It is not surprising that those models typically showed that, subject to a fixed-budget 

constraint, the combination of high penalties and low audit rates was socially optimal 

(McCubbin, 2004). 

Those results are sensitive to several underlying assumptions. First, feelings about risk 

vary from one group to another; younger people, for example, could be less risk-averse than 

older people are. Second, penalties are not imposed without cost. If penalties are increased, 

administering agencies might devote more resources to ensuring that their determinations are 

correct, and individuals could be more vigorous in defending themselves against a charge of 

noncompliance as they seek to avoid penalties (McCubbin, 2004). Administrators might, in fact, 

be unwilling to impose penalties that are thought to be overly severe (Slemrod and Yitzhaki, 

1987). Third, taxpayers and tax authorities alike might shape their behavior in response to their 

best guesses regarding the likely actions of the other: Taxpayers could anticipate enforcement by 

the tax authorities and respond accordingly, and the tax authorities could try to keep taxpayers 

guessing about who will be audited, given limited resources (Andreoni, Erard, and Feinstein, 

1998).

Evidence gathered from the individual income tax system illustrates how compliance can 

vary with the likelihood of detection and enforcement. Taxpayers are generally subject to the 

same penalties for misreported income and deductions, regardless of the source of the error. In 

2001, about 84 percent of federal taxes were voluntarily paid on time. However, compliance 

rates vary substantially depending on a taxpayer’s sources of income, and there are differences
18

from one type to another in the IRS’s ability to detect reporting errors. Tax compliance is 

relatively high when the agency can match data from third parties (such as information on W-2 

forms supplied by employers and financial institutions) to income tax returns and notify

taxpayers of discrepancies. The net misreporting rate for income that is subject to third-party 

reporting is less than 5 percent. In contrast, the IRS in many cases cannot verify other forms of 

income, such as that from self-employment (including net income from nonfarm proprietors and 

farmers) because most third-party data are not independently reported to the IRS and resources 

for audits are limited.10

The findings suggest that penalties matter—but so do enforcement mechanisms. 

Increasing the likelihood that penalties will be imposed and collected increases the incentive to 

comply. By combining penalties with information-reporting requirements and matching 

programs, the new health insurance mandate would be expected to yield higher rates of 

compliance than is the case for equal-sized penalties under a weaker enforcement mechanism.

Largely as a consequence, the rate for misreporting self-employment 

income and other forms of income that are not subject to third-party reporting exceeds 50 percent 

(IRS, 2007).

Still, models of tax compliance that consider only the policymaker’s and administrator’s 

tools do not appear to fully explain the relatively high rate of voluntary compliance observed in 

the United States. Tax compliance researchers have addressed this question by considering 

factors that tend to fall outside conventional models. The research suggests that compliance is 

influenced by taxpayers’ willingness to be honest and their desire to comply with the law (Erard 

and Feinstein, 1994a), by the desire to avoid the feelings of guilt and shame that result from tax 

 10 For individual income tax returns, the audit rate is about 1 percent; audit rates are somewhat higher for returns that 

report business income.
19

evasion (Erard and Feinstein, 1994b), by their perceptions of the fairness of the tax system and 

the way it is administered (Sheffrin and Triest, 1992; Spicer and Becker, 1980), and by their 

overall satisfaction with government (Alm, Jackson, and McKee, 1992). How to quantify each 

piece is not obvious, and understanding how they all fit together in explaining people’s behavior 

is not fully explored in the compliance literature.

Nevertheless, the findings from the literature provide insights about how to refine the 

modeling of the mandate effect (Mi in Equation [1]). That effect can be divided into two terms:

the effective penalty (effpen) and a vector of other factors that affect compliance:

other i effpen

Mi = Mi, + M , (2)

The effective penalty is a function of the statutory penalty and the probability that it will be 

imposed and collected by the administering agency is shown by Equation (3):

M f (S D) i effpen i , , = (3)

where Si is the statutory penalty that applies to individual i, and D is the probability that the 

statutory penalty will be imposed and collected.

11

The mandate effect includes other factors that affect compliance:

( , ) i,other Ri Ci M = f (4)

 11 That probability itself could be partly a function of the size of the statutory penalty. It is likely that the 

administering agency would weigh the monetary costs of enforcement actions against the likely monetary gains to 

the government (in this case, the penalty) before taking action. Other factors that affect the probability of detection 

are the amounts of third-party information and resources available to the administrating agency for enforcement. 
20

where Ri is the individual’s attitude toward risk and Ci is the individual’s willingness to 

voluntarily comply with the mandate. The age of the individual is a proxy for attitude toward 

risk, with risk aversion assumed to increase with age. Ci represents other (largely unobservable) 

factors, such as shame, guilt, anxiety, and perceptions of fairness, that can be associated with 

voluntary compliance.

C. Behavioral Economics

Sometimes people do not respond in the way that health economics models or tax

compliance models would suggest. Behavioral economics can provide additional avenues to 

understanding a broader range of factors that influence decisions; in this case, decisions to obtain

health insurance. (For an overview of that literature, see Liebman and Zeckhauser, 2008.) 

Behavioral economics considers that the usual assumptions of rationality and self-interest are 

overstated in conventional economics studies. Instead, rationality is bounded by constraints—

decisions are affected by people’s limited cognitive skills, by their limited access to information, 

and by the limited amount of time they have to process that information. Moreover, people 

sometimes make choices that are guided by their connections to others rather than solely on the 

basis of self-interest.

From the perspective of behavioral economics, rationality is bounded by asymmetrical 

preferences. Consider, for example, status quo bias. Samuelson and Zeckhauser (1988) reported

that when Harvard University changed some of the health insurance options it offered

employees, newly hired personnel were more likely to enroll than were people already on the 

university’s payroll; those employees generally chose to keep their current plans. The appeal of 

the status quo can be explained, in part, by the concept of loss aversion. People appear to make 

decisions relative to a reference point—often, the status quo. When judging choices relative to 
21

that status quo, people might weigh losses more heavily than gains. For uninsured people who 

are deciding whether or not to obtain coverage, that choice can be seen as existing between a 

certain loss (money spent on premiums) and the status quo (and the risk of some loss if medical 

assistance is needed later). Loss aversion suggests that people act to avoid the certain loss and, in 

this case, to remain uninsured (Schoemaker and Kunreuther, 1979).

Incomplete or incorrect information about a mandate also can influence behavior in ways 

that are not commonly explained by typical assumptions of rationality. There is evidence that

people are more responsive the more salient—or more notable—is the true price (or other 

important attribute) of an item. At the grocery store, a tax that is incorporated into an item’s price 

(and displayed that way on the shelf) appears to have a greater influence on the decision not to 

purchase that item than will a sales tax that is added at the register (Chetty, Looney, and Kroft, 

2009); toll roads that require cars to stop to pay cash at the booth seem less traveled than roads 

on which tolls are collected electronically (Finkelstein, 2007); and posting calories on a menu of 

food items at Starbucks stores in New York City might have contributed to a drop in food 

consumption per transaction at those locations (Bollinger, Leslie, and Sorensen, 2010).12

Some researchers have examined how people respond to social norms—particularly to

the behavior of people they are most likely to compare themselves with (another “reference 

point”). A study of energy consumption in California showed that people who received messages 

about their neighbors’ utility use rates reduced their own energy consumption by more, on 

average, than did people who received messages appealing to self-interest, concerns about the 

environment, or social responsibility (Cialdini and Schultz, 2004). Indeed, results from another 

 12 Although calories also were posted for beverages, there was almost no change in purchases of beverage calories at 

the same stores.
22

study detailed not just reductions in use among people who overconsumed relative to the 

community average but increases in usage among people whose consumption had been below 

the group’s average (Schultz and others, 2007).

Research on behavioral economics is a relatively new area of inquiry. Some findings are 

derived from one-time experiments, and it is not clear whether all results could be replicated in 

other settings or with other types of consumers or products. There also is an identification 

problem inherent in many studies: There are plausible alternative explanations that could explain 

some results. Those caveats suggest that the results published in the emerging behavioral 

economics literature (and extrapolations from those findings) should be viewed with caution. 

Still, the behavioral economics literature augments the literatures on health economics 

and tax compliance by providing a perspective that helps explain how decisions to obtain health 

insurance coverage could be affected by factors other than valuation of health insurance, feelings 

about risk, or the prospect of larger or smaller penalties. For example, the literature on loss 

aversion suggests that a penalty has a larger effect on demand for insurance than will a subsidy 

of equal value; mandates can effectively change the status quo by increasing the certain costs 

associated with being uninsured (via the penalty). Extrapolating from the salience studies would 

suggest that the strength of people’s awareness of a mandate or the effective penalty could 

influence compliance. And the emerging studies of social norms imply that the existence of a 

mandate—independent of the penalty or the enforcement mechanism—could change attitudes 

toward the purchase of health insurance if people perceived the mandate as an expression of 

strongly held views within society.
23

Those perspectives are reflected in the modeling framework by refinements to the 

measures both of the effective penalty and of the factors that affect voluntary compliance. First, 

Equation (3), for the effective penalty, is expanded to include the effects of salience:

( ) i effpen i D Ai pen Ai enf M f S , , , = , , , (5)

where Ai,pen is the individual’s awareness of the statutory penalty, and Ai,enf is the individual’s 

awareness of the likelihood that a penalty will be imposed. The framework allows the salience of 

the mandate—and the salience of the enforcement mechanisms—to separately affect people’s 

perceptions of the effective penalties.13

Next, social norms are explicitly introduced into the variable representing the factors 

associated with voluntary compliance:

The effective penalty increases as awareness of the 

mandate expands among the population, and it declines as the vulnerabilities in the enforcement 

mechanisms become more visible to people who are subject to the mandate. 

( ) Ci F Xi X Zi = , , (6)

where Xi is an indicator for whether individual i is exempt from the penalty, X is the share of the 

reference group that is exempt from the penalty, and Zi is a vector of the remaining other factors

associated with voluntary compliance.

 13 Salience also can be affected by the actions of mandate administrators: Massachusetts conducted an extensive 

public education campaign that included mailing out notices about the health insurance mandate and airing 

television ads during Red Sox broadcasts. Despite those efforts, in the fall of 2008, more than one in four uninsured 

nonelderly adults was unaware of the mandate (Long and Stockley, 2009). For people who would be aware of a

mandate, the gaps in enforcement might not be salient—and, indeed, tax authorities could try to prevent taxpayers 

from becoming aware of those gaps. One study documented an increase in the number of IRS press releases 

publicizing successful enforcement as the tax-filing deadline drew near, although the timing of the releases did not 

coincide with peaks in enforcement. Rather, IRS officials explained that the publicity was part of a deterrence 

strategy (Blank and Levin, 2010). The authors of the study did not discuss whether the increased press coverage 

affected taxpayers’ compliance.
24

The identification of social norms as affecting compliance provides a way to link specific 

features of a mandate with compliance, so that changes in those features could produce changes 

in coverage. One way that social norms could affect voluntary compliance is through the scope 

of the mandate. In particular, the treatment of different populations could have spillover effects.

For example, people whose income falls below the filing threshold will not be penalized for 

failing to comply with the mandate. Although it could be expected that people who were exempt 

from penalties would ignore the mandate, some could comply because they are affected by the 

prevailing social norm that directs everyone to obtain health insurance (possibly as a result of 

pressure from health care providers to enroll).

14

VI. Conclusions

In contrast, people who are subject to the 

penalties might be less willing to comply if they observe others who are like them but avoid the 

penalties through affordability or hardship exemptions. Thus, the extent to which other people 

are exempt from the mandate could diminish acceptance of a new social norm about health 

insurance, causing a decline in compliance with the mandate.

This paper presents an overview of a modeling framework that builds on the health, tax,

and behavioral economics literature and incorporates factors suggested by all three disciplines

that could influence compliance with the new health insurance mandate.

The health economics perspective provides the starting point by suggesting that penalties

raise the cost of being uninsured. That perspective alone implies that a penalty and subsidy of 

equal dollar amounts would have similar effects on coverage. The tax compliance literature 

 14 Other factors also might contribute to compliance among people who are exempt from the mandate. Consider 

people whose income falls just below the filing threshold. Typically, decisions about obtaining coverage would have 

to be made before a year began, but the exemption is based on total income throughout the year. Because of

uncertainty about their annual income, some people might comply because they believe they have a reasonable 

chance of earning more than the threshold and thus incurring the penalty.
25

demonstrates that the effective penalty will differ from the statutory penalty, and that the 

effective penalty generally will be lower because of gaps in enforcement. But that literature also 

opens the possibility that people respond to the mandate because of such factors as inherent 

honesty, shame, guilt, or anxiety. The behavioral economics perspective further refines the 

analysis and provides links between those factors to provisions in the mandate—the size of the

effective penalty is affected by the salience of the mandate and the lack of salience regarding IRS 

enforcement, whereas voluntary compliance is affected by social norms. 

To return to the question posed by the title of this paper, the response can be, “Yes, 

mandates will increase coverage.” The argument that most people would prefer to pay a penalty 

rather than purchase insurance if the penalty costs less than the premium ignores key 

considerations. First, most people get something in return when they purchase health insurance. 

Paying a penalty yields no such benefit. Second, people respond to laws because it is costly not 

to comply; the statutory penalty is only one determination of that cost, although the expected

penalty could be less than the statutory penalty because of gaps in enforcement. The size of those 

gaps will depend on the amount of information and resources provided to the IRS. Finally, 

people’s response will be influenced by other factors, including social norms and awareness of 

the mandate. Although they are more difficult to measure, those factors cannot be ignored in any 

analysis of the individual mandate to purchase health insurance.

Thus, coverage will increase with the size of penalties, the scope and awareness of a

mandate, and strength of enforcement (or at least people’s perception of its strength). In 

combination, those factors would probably increase health insurance coverage significantly from 

a policy that includes a mandate relative to an otherwise comparable policy that does not. 
26

References

Allingham, Michael G., and Agnar Sandmo. 1972. “Income Tax Evasion: A Theoretical 

Analysis.” Journal of Public Economics, 1(4), 323–338.

Alm, James, Betty Jackson, and Michael McKee. 1992. “Deterrence and Beyond: Toward a 

Kinder, Gentler IRS.” In Slemrod, Joel (ed.). Why People Pay Taxes: Tax Compliance and 

Enforcement. University of Michigan Press, Ann Arbor, Mich. 311–329.

Andreoni, James, Brian Erard, and Jonathan Feinstein. 1998. “Tax Compliance.” Journal of 

Economic Literature, XXXVI(2), 818–860.

Ashenfelter, Orley, and Robert S. Smith. 1979. “Compliance with the Minimum Wage Law.”

Journal of Political Economy, 87(2), 333–350.

Auerbach, David, and Sabina Ohri. 2006. “Price and the Demand for Nongroup Health 

Insurance.” Inquiry, 43(2), 122–134.

Blank, Joshua, and Daniel Levin. 2010. “When Is Tax Enforcement Publicized?” Law and 

Economics Research Working Paper 10-12. New York University School of Law, New York, 

N.Y.

Block, Sandra. 2010. “IRS Lacks Clout to Enforce Mandatory Health Insurance.” USA Today, 

April 29. www.usatoday.com/money/perfi/insurance/2010-04-29 

healthirs28_CV_N.htm?loc=interstitialskip.

Bollinger, Bryan, Phillip Leslie, and Alan Sorensen. 2010. “Calorie Posting in Chain 

Restaurants.” Working Paper 15648. National Bureau of Economic Research, Cambridge, Mass.

www.nber.org/papers/w15648.

Cassidy, John. 2010. “ObamaCare by the Numbers.” New Yorker, Posted March 26. 

www.newyorker.com/online/blogs/johncassidy/2010/03/obamacare-by-the-numbers-part-2.html.

Chetty, Raj, Adam Looney, and Kory Kroft. 2009. “Salience and Taxation: Theory and 

Evidence.” American Economic Review, 99(4), 1145–1177.

Cialdini, Robert, and Wesley Schultz. 2004. Understanding and Motivating Energy 

Conservation Via Social Norms. Report prepared for the William and Flora Hewlett Foundation.

www.opower.com/LinkClick.aspx?fileticket=LOsDr3HVWdU%3D&tabid=76. 

CBO (Congressional Budget Office). 2008. Key Issues in Analyzing Major Health Insurance 

Proposals, December. www.cbo.gov/doc.cfm?index=9924. 

CBO (Congressional Budget Office). 2010a. Letter to the Honorable Olympia Snowe about 

estimated premiums for “Bronze” coverage under the Patent Protection and Affordable Care Act.

January 11. www.cbo.gov/ftpdocs/108xx/doc10884/01-11-Premiums_for_Bronze_Plan.pdf. 
27

CBO (Congressional Budget Office). 2010b. Cost estimate for H.R. 4872, Reconciliation Act of 

2010. March 20. http://www.cbo.gov/ftpdocs/113xx/doc11379/AmendReconProp.pdf.

CBO (Congressional Budget Office). 2010c. “Payments of Penalties for Being Uninsured Under 

the Patient Protection and Affordable Care Act.” Posted April 22, revised April 30.

www.cbo.gov/ftpdocs/113xx/doc11379/Individual_Mandate_Penalties-04-30.pdf.

Cutler, David M. 2003. “Employee Costs and the Decline in Health Insurance Coverage.”

Frontiers in Health Policy Research, 6(3), 27–53.

Davis, Matthew M., and Michael A. Gaglia. 2005. “Associations of Daycare and School Entry 

Vaccination Requirements with Varicella Immunization Rates.” Vaccine, 23(23), 3053–3060.

Erard, Brian, and Jonathan Feinstein. 1994a. “Honesty and Evasion in the Tax Compliance 

Game.” Rand Journal of Economics, 25(1), 1–19.

Erard, Brian, and Jonathan Feinstein. 1994b. “The Role of Moral Sentiments and Audit 

Perceptions in Tax Compliance.” Public Finance/Finances Publiques, 49(Supplement), 70–89.

Finkelstein, Amy. 2009. “EZTax: Tax Salience and Tax Rates.” Quarterly Journal of 

Economics, 124 (3), 969–1010.

Gruber, Jonathan. 2010. “Why We Need the Individual Mandate.” Posted April 8. Center for 

American Progress, Washington, D.C.

www.americanprogress.org/issues/2010/04/pdf/individual_mandate.pdf.

Insurance Research Council. 2006. Uninsured Motorists, 2006 Edition. Insurance Research 

Council, Malvern, Pa.

IRS (Internal Revenue Service). 2007. Reducing the Federal Tax Gap: A Report on Improving 

Voluntary Compliance. IR-2007-137. Department of the Treasury.

IRS (Internal Revenue Service). 2009. Internal Revenue Service Data Book. Publication 55B. 

Department of the Treasury.

Jacobs, Paul, 2009. “Health Insurance Demand and the Generosity of Benefits: Fixed Effects 

Estimates of the Price Elasticity.” Forum for Health Economics and Policy, 12 (2), 1–25.

www.bepress.com/fhep/12/2/3.

JCT (Joint Committee on Taxation). 2010. Technical Explanation of the Revenue Provisions of 

the “Reconciliation Act of 2010,” as Amended, in Combination with the “Patient Protection and 

Affordable Care Act. JCX-18-10. U.S. Congress.

www.jct.gov/publications.html?func=startdown&id=3673. 

Kling, Arnold, 2010. “Incentives vs. Intentions.” Posted March 24, Library of Economics and 

Literature, Indianapolis, Ind., http://econlog.econlib.org/archives/2010/03/incentives_vs_i.html.
28

Liebman, Jeffrey, and Richard Zeckhauser. 2008. “Simple Humans, Complex Insurance, Subtle 

Subsidies.” In Aaron, Henry, and Leonard Burman (eds.). Using Taxes to Reform Health 

Insurance: Pitfalls and Promises. Brookings Institution Press, Washington, D.C. 230–255.

Long, Sharon, and Karen Stockley. 2009. “An Update on Insurance Coverage and Support for 

Reform as of Fall 2008.” Massachusetts Health Reform Survey Policy Brief, Urban Institute, 

Washington, D.C.

Marquis, M. Susan, and Stephen Long.1995. “Worker Demand for Health Insurance in the NonGroup Market.” Journal of Health Economics, 14(1), 47–63.

McCubbin, Janet. 2004. “Optimal Tax Enforcement: A Review of the Literature and Practical 

Implications.” OTA Working Paper. 90. Department of the Treasury, Office of Tax Analysis.

Monheit, Alan, and Jessica Vistnes. 1999. “Health Insurance Availability at the Workplace: How 

Important Are Worker Preferences?” Journal of Human Resources, 34(4), 770–785.

NHTSA (National Highway Transportation Safety Administration). 2008. Seat Belt Use in 

2007—Use Rates in the States and Territories. DOT HS 810 949. Department of Transportation, 

National Center for Statistics and Analysis.

Samuelson, William and Richard Zeckhauser, 1988, “Status Quo Bias in Decision Making.” 

Journal of Risk and Uncertainty 1 (1), 7-59.

Schoemaker, Paul, and Howard Kunreuther. 1979. “An Experimental Study of Insurance 

Decisions.” Journal of Risk and Insurance, 46(4), 603–618.

Schultz, Wesley, Jessica Norma, Robert Cialdini, Noah Goldstein, and Vladas Griskevicius.

2007. “The Constructive, Destructive, and Reconstructive Power of Social Norms.”

Psychological Science, 18(5), 429–434.

Sheffrin, Steven, and Robert Triest. 1992. “Can Brute Deterrence Backfire? Perceptions and 

Attitudes in Taxpayer Compliance,” in Slemrod, Joel (ed.), Why People Pay Taxes: Tax 

Compliance and Enforcement. University of Michigan Press, Ann Arbor, Mich. 193–218.

Slemrod, Joel, and Shlomo Yitzhaki. 1987. “The Optimal Size of a Tax Collection Agency.”

Scandinavian Journal of Economics, 89(2), 183–192.

Spicer, Michael, and Lee Becker. 1980. “Fiscal Inequity and Tax Evasion: An Experimental 

Approach.” National Tax Journal, 33(2), 171–175.
29

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

0% 100% 200% 300% 400% 500% 600%

Individual Mandate Penalty

Household Modified Adjusted Gross Income (Percentage of Federal Poverty Level)

Figure 1.

Individual Mandate Penalty, by Income Relative to Projected Federal Poverty Level

Single person Family of 4 (2 adults, 2 children)

(2016 Dollars)

Source: Authors’calculations.