Long-term Economic Benefits Attributed to IVF-conceived Children: A Lifetime Tax Calculation

We estimate the future net tax contributions from an IVF-conceived child to highlight that removing barriers to fertility treatments can have long-term economic benefits.
Published Online: September 15, 2008
Mark P. Connolly, MHE; Michael S. Pollard, PhD; Stijn Hoorens, MSc; Brian R. Kaplan, MD; Selwyn P. Oskowitz, MD; and Sherman J. Silber, MD

Objective: To evaluate whether lifetime future net tax revenues from an in vitro fertilization (IVF)-conceived child are substantial enough to warrant public subsidy relative to the mean IVF treatment costs required to obtain 1 live birth.

Study Design: Mathematical generational accounting model.

Methods: The model estimates direct financial interactions between the IVF-conceived child and the government during the child’s projected lifetime. In the model, we accrue IVF costs required to conceive the child to the government, and then we estimate future net tax revenue to the federal and state governments from this individual, offset by direct financial transfers from the government (eg, child allowances, education, Medicare, and Social Security). We discount lifetime costs and gross tax payments at Treasury Department rates to establish the present value of investing in IVF. We applied US Congressional Budget Office projected changes in tax rates over the course of the model.

Results: An IVF-conceived child, average in every respect (eg, future earnings, healthcare consumption, and life expectancy), represents a net positive return to the government. Based on an average employed individual born in 2005, the projected net lifetime tax contribution is US $606,200. Taking into consideration IVF costs and all direct financial interactions, the net present value is US $155,870.

Conclusions: Lifetime net taxes paid from a child relative to the child’s initial IVF investment represent a 700% net return to the government in discounted US dollars from fully employed individuals. This suggests that removing barriers to IVF would have positive tax benefits for the government, notwithstanding its beneficial effect on overall economic growth.

(Am J Manag Care. 2008;14(9):598-604)

  • Financial and legislative barriers to fertility treatments prevent many couples from achieving their desired family size, resulting in fewer children being born.
  • Taking the perspective of the government, fewer children born in current generations
    represents a loss in future tax revenue that would arise from these children after they enter the workforce.
  • The costs attributed to in vitro fertilization (IVF) treatment are insignificant in light of the lifetime net tax contributions of IVF-conceived children.
  • Minimizing barriers to fertility treatments is likely to have long-term economic benefits
    that need to be considered when making IVF funding decisions.
The past decade has witnessed a dramatic increase in the demand for assisted reproductive technology (ART ) such as in vitro fertilization (IVF).1,2 Increasing demand for ART is related to increased infertility in modern populations, which may be attributed to couples’ delaying efforts to get pregnant until they are older and less fertile, increasing obesity in the United States, sexually transmitted diseases, low sperm count, and the stress of modern daily life.3-6 In countries where generous funding for fertility treatments is available, ART accounts for 4% to 6% of national births every year.1,2 When the proportion of children born every year from ART is couched within the population aging debate faced by many countries and the economic consequences this creates, policy analysts have started to investigate the role that fertility treatments could play in solving severe demographic issues associated with an aging population and the resulting insolvency of Social Security.7-10

Despite increasing demand for ART treatments, financial constraints are causing many national health providers and private insurers to limit access, and most couples must pay out-of-pocket for these services.11 For couples unable to afford ART , the options are limited; consequently, many withdraw from treatment or choose not to pursue treatment because of costs.12-14 Furthermore, the established relationship between affordability and utilization of services would suggest that many couples are unable to receive treatment, with the likely consequence of fewer children being born every year.15

The economic and health consequences of financial barriers to medical treatment are frequent topics of interest for health economists and policy analysts.16-18 With respect to ART services, treatment barriers create an additional issue, as successful use of this technology leads to the creation of human life that would not have been born were the technology not available. The immediate benefit of ART success is to fulfill a couple’s desired family size, which leads to quality-of-life improvements. However, what is less well characterized is the economic effect that IVF-conceived children will make once they become economically active adults.

To assess the economic consequences of IVF-conceived children, we developed a mathematical model that explores the lifetime financial transactions between a single individual conceived by IVF and the government under a theoretical assumption that the government paid standard fees for that IVF treatment. To evaluate whether investing in IVF represents sound fiscal policy for the government, we theoretically assigned IVF costs to the US government in the model. The methods applied herein are based on generational accounting (GA) methods developed by Kotlikoff et al19,20 and Sturrock21 and used by treasury departments, including the US Congressional Budget Office, to assess whether current fiscal policies will adversely affect future generations (ie, shift costs to future generations). In this article, we describe a GA model to assess future net tax revenues derived from a hypothetical IVF-conceived child to establish whether policies that increase access to IVF treatment would generate long-term economic benefits. It is envisaged that this analysis can inform government and nongovernment agencies with a vested interest in future population age structures. Such an analysis is urgently needed in view of declining birthrates, increasing numbers of aging retired persons, and the predicted insolvency of Social Security.

METHODS
Based on the US GA model developed by Kotlikoff,19 a basic mathematical model was developed taking the perspective of the US government to estimate the discounted lifetime net tax contribution derived from a single individual. The model describes the financial position between the child and the government during the child’s projected lifetime. For comparison, the model estimates lifetime net tax contributions for a naturally conceived versus an IVF-conceived child, where the major cost difference is assumed to be IVF treatment costs and any extra costs related to the child’s care. In this model, we assign IVF costs to the government to assess the merits of funding such a policy. All direct government expenditures and tax contributions were discounted using Treasury Department rates.

Conceptually, there are 3 broad stages in lifetime financial interactions, each with differing components of the financial exchange, as follows: (1) early life, when the government primarily contributes resources to individuals through child tax credits, healthcare, and educational expenses; (2) employment, when individuals begin returning resources to the government through federal, state, and local taxes; and (3) retirement, when the government expends additional resources on Social Security and old-age programs. Two general models are estimated. The first model assumes that individuals graduate from high school and then follow the average higher education, employment, and unemployment trends (hereafter referred to as average employment). The second model assumes full-time education from ages 6 to 19 years, with full-time employment from age 20 years until  retirement at age 65 years (hereafter referred to as full employment). The models assume that successful IVF treatment results in a single live birth (with a mean life expectancy of 79 years) and that the child is identical to a naturally conceived individual.22,23 In all scenarios, the model includes hospital delivery costs, taking into consideration additional costs frequently accrued to IVF-conceived children attributed to low birth weight.24,25 Age-graded government expenses and tax contributions were assessed across a hypothetical individual’s lifetime to derive discounted lifetime net tax contributions using net present value (NPV) calculations and undiscounted lifetime net tax contributions. Following similar GA calculations used to assess US immigration policy, we consider various costs generated and taxes paid.26,27

Expenditures
Two broad categories of federal and state government expenditures are considered, congestible goods and transfer programs.28 Congestible goods have nonzero marginal costs and include expenditures such as roads, fire and police protection, airports, and sewers. Transfer programs include all government expenditures that can be assigned to specific individuals such as Social Security, Supplemental Security Income, Medicare, Medicaid, Aid to Families With Dependent Children, public assistance, food stamps, unemployment benefits, disability benefits, subsidized school lunch programs, and public education at all levels. There is also a child tax credit associated with individuals until age 17 years.

Revenues
Revenues collected by the government include federal and state income tax (the national mean rate in this model), corporate tax, excise tax, Federal Insurance Contributions Act tax, Supplemental Medical Insurance contributions, federal retirement tax, property tax, and sales tax. To calculate the accounting models, age profiles of each expenditure and revenue component were identified from existing data sources. Because the models describe financial interactions across an individual’s lifetime, these age profiles are adjusted to account for depreciation of money over time through the application of a discount rate. The US Congressional Budget Office 2007 projections were used as the basis for estimates of inflation, individual earnings increases, tax rate increases, increases in Supplemental Medical Insurance revenue, and Medicare and Medicaid expenditures.29 Increases in expenditures on schooling are based on historical rates of increase.30 Beyond the period for which these long-term forecasts are available, we assume that particular components grow to keep pace with demographic and productivity growth. A discount rate of 4% was applied to lifetime tax revenue and transfer payments. The discount rate was compounded continuously.

IVF Treatment Costs. The mean IVF treatment costs to produce a live birth are considered herein as a further expense unique to an individual conceived using IVF. The national mean cost per IVF treatment cycle in 2003 is US $12,400.31 Cost per live birth is calculated as the mean cost per cycle divided by the age-adjusted probability of a live birth, where the treatment efficacy is known to vary primarily by the age of the mother (ie, lower success rates with older age) and by other factors.31-34 The age-adjusted cost per live birth is given in Table 1.



Data Sources. Analyses are based primarily on 2 waves of the annual March Current Population Survey.35 The Current Population Survey is a monthly survey of about 50,000 households conducted by the Bureau of the Census for the Bureau of Labor Statistics and is the primary source of information on the labor force characteristics of the US population. The sample is representative of the civilian noninstitutional population. Estimated sales tax revenue is obtained from the Consumer Expenditure Survey, also conducted by the Bureau of Labor Statistics. Government expenditures on congestible goods are obtained from the US Statistical Abstract, following prior work.26 Educational expenditures are taken from the Digest of Education Statistics.30

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