Advertisement

Social Indicators Research

, Volume 97, Issue 2, pp 177–189 | Cite as

The Impact of State Abortion Policies on Teen Pregnancy Rates

  • Marshall MedoffEmail author
Article

Abstract

The availability of abortion provides insurance against unwanted pregnancies since abortion is the only birth control method which allows women to avoid an unwanted birth once they are pregnant. Restrictive state abortion policies, which increase the cost of obtaining an abortion, may increase women’s incentive to alter their pregnancy avoidance behavior, thereby reducing the likelihood of unwanted pregnancies. This study, using state-level data for the years 1982, 1992, and 2000, examines the impact of restrictive state abortion laws on teen pregnancy rates. The empirical results indicate that the price of an abortion, Medicaid funding restrictions, and informed consent laws reduce teen, minor teen and non-minor teen pregnancy rates. The empirical results suggest that these abortion policy restrictions affect the unprotected sexual activity of teens resulting in fewer unwanted teen pregnancies.

Keywords

Restrictive abortion policies Teen pregnancy rates 

1 Introduction

Teen pregnancy is among the most important social problems in the United States. Each year approximately 9% of teens between the ages of 15 and 19 get pregnant and among sexually active teens the figure is 17%. Over 850,000 teens become pregnant each year, more than 90% of teen pregnancies are unwanted and half of all teen pregnancies result in a live birth (Henshaw 2004). The costs to society from teen births have received considerable attention from social scientists. Virtually all of the research indicates that adolescent parenthood has adverse consequences for the teen mother, the child and society. Infants born to teens are more likely to be of low birth weight, preterm, at greater risk of serious and long-term illness, developmentally slow, maltreated, abused and living in poverty. Teen mothers are less likely to complete their education, to be employed, to have high occupational attainment, to earn high wages and they are more likely to be in poverty and receive welfare assistance (Hoffman 2006).

Because the prevention of teen pregnancy is a public health priority the research literature on the causes and correlates of teen pregnancies is extensive. Researchers from sociology, psychology and social work have concentrated primarily on teen personal characteristics, family background, biological, health, environmental, community and peer factors as fundamental causes of teen pregnancy (Moore et al. 1995). Teens who are not academically motivated and do poorly in school are more likely to become pregnant than are their high-achieving peers (Hofferth 1987). Teen pregnancy is also linked to other problematic adolescent behaviors such as alcohol and drug use (Yamaguchi and Kandel 1987: Urdy et al. 1996). Teens who are raised in poverty by single parents and by parents with low educational attainment are more prone to become pregnant (Furstenberg and Teitler 1994). Teens who reside in neighborhoods with high rates of poverty, welfare and single-parent households are also at higher risk (Wilson 1987). Daughters of teenage mothers or single-parent families face significantly higher risks of teen pregnancy than the daughters of older mothers or intact families (Kahn and Anderson 1992; McLanahan and Bumpass 1988). A teen’s likelihood of becoming pregnant is inversely related to the years of education of the mother of the teenager (An et al. 1993). Stressful life events such as divorce and sexual, psychological and physical abuse have a strong influence on the likelihood of a teen pregnancy (Moore et al. 1995). Teens who have high family income and attend church frequently have lower rates of teen pregnancy (Afxentiou and Hawley 1997). Life experiences associated with poverty, such as alienation at school and prevalent models of unmarried parenthood and unemployment are factors related to teen pregnancy (Moore et al. 1995). Teen peers (best friends and siblings) who are sexually active affect the likelihood of teen pregnancy (Yamaguchi and Kandel 1987). Teens who have parents who do not stress responsibility and self-discipline are more likely to have a nonmarital pregnancy (Hanson et al. 1987).

In contrast to these disciplines, economics focuses on the relevant costs considered by individuals when making decisions about their sexual activity and contraceptive use, with a particular emphasis on the impact of public policies that affect the costs of risky sexual activity to a teen. A focus on the costs created by public policies does not deny that sociological and psychological factors also influence teen pregnancies. Rather, this approach suggests that the costs created by public policies may also play a role in the complex set of factors that cause teen pregnancies. If public policies have an effect on teen pregnancies, then the manner in which these public policies alter teens’ pregnancy avoidance behavior is of obvious interest to policymakers.

One public policy that affects the costs of risky sexual activity (i.e., unprotected) to a teen are restrictive state abortion laws that reduce the access or availability of an abortion. The cost to a teen of engaging in risky sexual activity is an unwanted pregnancy. A seminal article by Kane and Staiger (1996) argues that state laws regulating abortion access or availability may alter teens’ decisions to engage in risky sexual activity that affect the likelihood of an unwanted pregnancy. Pregnancy is not an exogenous or predetermined event, but is an outcome based on prior decisions made by teens regarding their risky sexual behavior (i.e., frequency of unprotected sexual activity and/or contraceptive use). Over the past twenty-five-years there has been a noteworthy increase in states enacting laws restricting access or availability to an abortion. Restrictive abortion laws raise the out-of-pocket costs and the emotional costs (e.g., guilt, regret, humiliation, shame) to teens of terminating an unwanted pregnancy and concomitantly the costs of unprotected sexual activity (i.e., the risk of an unwanted pregnancy). Kane and Staiger argue that the consequence is that restrictive abortion laws may alter the initial decisions made by teens about the frequency of their unprotected sexual activity and/or contraceptive use, thereby reducing the likelihood of an unwanted teen pregnancy.

This paper is a public policy analysis, with the goal of providing better information to policymakers, about the effects of various restrictive abortion laws on teen pregnancies. The primary focus is on how teens respond to state abortion policies that alter teens’ costs of engaging in risky sexual activity (i.e., unprotected sexual activity and/or contraceptive use). Whether restrictive abortion laws affect the likelihood of teen pregnancy is a largely unexplored public and social policy issue. The highly controversial status of abortion in the United States makes this a particularly compelling and relevant question, especially given the move towards more restrictions being placed on abortion access at the state level and the public policy goal of reducing teen pregnancies. This paper uses the tools of economic analysis, which focuses on the role of costs as important determinants of individual behavior, to empirically examine the important public and social policy question: Do restrictive abortion laws reduce the incidence of teen pregnancy?

2 State Restrictive Abortion Laws

The US Supreme Court’s 1973 Roe v. Wade (410 US 113) abortion decision held that there exists a constitutional right to privacy that encompasses a woman’s decision whether or not to terminate an unwanted pregnancy. However, the decision did not mandate unrestricted access to an abortion. Subsequent Supreme Court decisions (for a complete historical overview see Mezey 1992) permitted states to enact laws restricting women’s access provided that the laws did not impose an undue burden on women seeking an abortion. The Supreme Court has ruled that there are four types of state laws restricting a woman’s access to an abortion that are constitutionally permitted.

Medicaid is a joint federal and state health insurance program that funds medical services for the poor. In 1980 the Supreme Court ruled in Harris v. McRae (448 US 297) that the federal government was not constitutionally obligated to fund abortions for low-income women. The decision of whether to fund Medicaid abortions was left solely to the discretion of each individual state. Many states enacted laws that prohibited public funding of Medicaid abortions.

The Supreme Court in 1979 in Bellotti v. Baird (443 US 622) and continuing in 1981 in H. L. v. Matheson (450 US 398) limited the reproductive rights of unmarried teen minors (i.e., those less than 18 years of age) by permitting states to require that a parent be involved in a minor’s abortion decision. Parental involvement laws require that a parent be notified or give permission before an abortion is performed on an unmarried teen minor. However, a state may implement a parental involvement law only if the state provides a judicial bypass process that allows the teen minor to appear before a judge and obtain a judicial ruling that the teen minor is mature enough or there are extenuating circumstances that require the teen minor to make the abortion decision on her own.

Mandatory delay laws dictate that women requesting an abortion must wait a specified time period (usually 24–48 h) before the abortion can be performed. It is noteworthy that in the decision allowing states to enact mandatory delay laws the Supreme Court acknowledged that, because many states have only a small number of providers who offer abortion services only 1 or 2 days a week, one of the consequences of mandatory delay laws would be to impose substantial travel expenses and time costs on women seeking an abortion, especially low-income women (Planned Parenthood of Southeastern Pennsylvania v. Casey 112 US 2791 at 2825).

Informed consent laws compel providers give to women seeking an abortion state-mandated information (either written or orally) about the abortion procedure and alternatives to an abortion (Webster v. Reproductive Health Services 492 US 490, 1989). Typically, a doctor must inform each patient that having an abortion entails possible medical risks and side effects (e.g., infection, infertility, death, breast cancer, psychological distress). In addition, some states also require doctors to provide to women information about the fetus (e.g., ultrasound, age, potential viability, pain).

3 The Economic Model of Fertility Control

Economic models of teen sexual activity are based on rational choice theory. Rational choice theory is a framework for understanding and modeling social behavior. Models of teen social behavior which emerge from this approach are predicated on the assumption that teens make rational decisions about sexual activity, contraceptive usage and pregnancy resolution based on a comparison of the respective costs and benefits of each alternative. The economic costs typically involve opportunities a teen gives up by becoming pregnant (Posner 1997). Teens choose the optimal alternative depending on their values and the information they have available to them (i.e., make an economically rational decision). The underlying premise of rational choice theory is that teens make choices that are rewarding to them and avoid those that are not. In other words, rational choice theory expects teens to respond to incentives. This framework has been applied to the risky sexual activity of teens and the empirical results are generally supportive of the rational choice theoretical approach.

Levine (2001), using data from the Youth Risk Behavior Survey, found that economic costs as measured by labor market conditions (an opportunity cost of becoming pregnant), the incidence of AIDS (a health risk cost) and the generosity of the welfare system (cost of pregnancy is reduced) are significantly related to changes in teens’ risky sexual activity. In particular, decreases in unemployment and welfare benefits and increases in the incidence of AIDS are associated with a decline in teen girls’ likelihood of sexual activity, risky sexual activity, noncontracepted sexual activity and pregnancy risk. Averett et al. (2002), using data from the National Survey of Family Growth, found that the median family income (an opportunity cost) in a teen’s census tract neighborhood was negatively related to the probability of a teen being sexually active and positively related to the probability of the teen using contraception. Sen (2006), using data from the National Longitudinal Survey of Youth, found that the family income of a teen (an opportunity cost) had a significantly negative effect on the frequency of teen sexual activity. Afxentiou and Hawley (1997), using data from the National Longitudinal Survey of Youth, found that welfare benefits and family income play a significant role in the decision of a teen becoming sexually active. The results of these empirical studies provide some support that economic costs do affect teens’ decisions regarding risky sexual activity and contraceptive use.

The standard approach in disciplines other than economics is to maintain that teens do not respond rationally to incentives because their decisions about their sexual behavior are random. The rationale underlying this approach is that it is argued that teens do not have complete information about each alternative or the cognitive ability to weigh the ramifications of each alternative. While it may be doubtful that teens have complete information about the benefits and costs of every option, they may still act as if they were comparing the costs and benefits of different courses of action. In addition, criticisms of economic rational choice models are attributable to a fundamental misunderstanding of the reasons for a rational choice theoretical approach. Proponents of rational choice theory do not contend that it is a complete description of reality. Nevertheless, by assuming teens make decisions in a rational manner implies that their behavior can be modeled and empirically verifiable hypotheses can be formulated even if this may not be the exact manner in which decisions are made. A focus on economic costs does not imply that social, cultural, attitudinal, family or community factors do not influence a teen’s risky sexual behavior, rather, this approach suggests that economic costs may have an independent effect on teens’ risky sexual activity. In particular, an economic rational choice model of teen risky sexual activity suggests that economic costs will affect the decisions individual teens make regarding fertility and contraception in a predictable manner and the aggregated effects of these decisions will be evident in teen pregnancy rates at the state level.

One of the most notable costs to a teen from unprotected sexual activity is an unwanted pregnancy and its attendant lost opportunities (earnings, education, employment, occupation, and marital). The relationship between restrictive abortion laws and unprotected teen sexual activity depends on whether the restrictions increase teens’ incentives to use anticipatory methods of birth control to prevent unwanted pregnancies from occurring. The Kane and Staiger (1996) model argues that restrictive abortion laws may affect the antecedents of teen pregnancy—the frequency of unprotected sexual activity and contraceptive use by teens.

Abortion is an ex post birth control method—an insurance policy that reduces the probability of an unwanted pregnancy to zero—that lowers the cost of engaging in unprotected sexual activity. Abortion is different from other methods of birth control because it is the only method that permits teens to avoid an unwanted birth once pregnant. Restrictive abortion laws, by making abortion less accessible and more costly to teens, raise the cost of engaging in noncontracepted sexual activity relative to the cost of contracepted sexual activity and may induce fecund teens to substitute away from the abortion option and towards ex ante birth control methods (e.g., birth control pills, IUD, condom, abstinence, and less frequent sexual activity). In other words, restrictive abortion laws may alter sexually active teens’ initial decisions regarding unprotected sexual activity and contraceptive use and encourage safe sexual activity. Restrictive abortion laws may increase sexually active teens’ incentive to adopt antecedent birth control methods (other than abortion) in order to avoid becoming pregnant resulting in a decrease in the number of unwanted teen pregnancies.

4 Literature Review

A number of previous studies have examined the impact of restrictive abortion laws on teen pregnancies indirectly. These studies have focused exclusively on Medicaid funding restrictions and parental involvement laws.

These studies used pooled cross-section time-series data to examine whether a state Medicaid funding restriction or a parental involvement law affects teen birth rates. Levine (2003) found that parental involvement laws have a negative impact on teen birth rates in some model specifications and a positive impact in other model specifications. Kane and Staiger (1996) presented evidence that a state Medicaid funding restriction and parental involvement laws are associated with fewer births for white teenagers, but Medicaid funding restrictions have a positive effect and parental involvement laws have no effect on births for black teens. Tomal (1999) found that a state Medicaid funding restriction and parental involvement laws were positively related to higher birth rates of teens.

The above three studies all use regression models in order to control for other factors that may influence teens’ sexual behavior. Duncan and Hoffman (1990); Lundberg and Plotnick 1995) and Levine (2001) all argue that teens have very poor information about their future and are heavily influenced by what adult women have achieved in the labor market. Accordingly, teens use the socioeconomic characteristics of adult women as proxies in their assessment of the costs and consequences of unprotected sexual activity/unwanted pregnancies. The cost of an unwanted pregnancy is higher for adult women who have greater human capital (i.e., education, employment, and income). Thus, greater human capital is predicted to be negatively related to birth rates. In general, the empirical results from the aforementioned three studies tend to find that education, labor force participation and income are negatively related to teen birth rates.

5 Data and Empirical Model

States have enacted restrictive abortion laws at different times and, as a consequence, during any given year some states enforced restrictive abortion laws and other states did not. Thus, one can think of the effects of restrictive abortion laws on the incidence of teen pregnancy as a natural experiment with a treatment group (states with restrictive abortion laws) and a control group (states without restrictive abortion laws). State data is the appropriate unit of analysis because it is restrictive state abortion laws that are responsible for restricting women’s access to obtaining an abortion and it is the heterogeneity of state abortion laws that change the effective cost of an abortion to a woman. State differences in the effective cost of obtaining an abortion are due, in part, to state differences in restrictive abortion laws.

In order to explore the relationship between restrictive abortion laws and teen pregnancy rates, observations are needed on three key variables: teen pregnancy rates, abortion variables (restrictive abortion laws and the price of obtaining an abortion) and socioeconomic characteristics. Abortion data is available from two sources: the Centers for Disease Control (CDC) and the Alan Guttmacher Institute (AGI). The CDC reports abortion figures supplied by state public health agencies. The CDC concedes that its state abortion figures are incomplete and underreported: not all states provide abortion figures to the CDC (e.g., California) and there is considerable variation in the collection procedures used by each of the state public health agencies. The AGI is generally acknowledged (even by the CDC) to collect more accurate and comprehensive state abortion data because their figures are obtained directly from abortion providers. However, the AGI does not collect abortion figures every year, only periodically. Teen pregnancy rates by state are only available from the AGI for the years 1982, 1992 and 2000. One advantage of using the years 1982, 1992 and 2000 is that the time span is sufficiently long enough to detect causal changes in teens’ sexual behavior in a state as a result of a state’s enactment of restrictive abortion laws.

The dependent variable in this study is a state’s teen pregnancy rate: the number of teen pregnancies per 1,000 teens (ages 15–19) for the years 1982, 1992 and 2000. Using the Alan Guttmacher Institute’s data on teen pregnancy rates, the 50 US states are analyzed for the years 1982, 1992 and 2000. Thus the data set consists of 150 observations. Four indicator (dummy) abortion policy variables are used to denote whether or not a state had in effect a (1) Medicaid Funding Restriction; (2) Parental Involvement Law; (3) Mandatory Delay Law; or an (4) Informed Consent Law during the years 1982, 1992 and 2000. The status of restrictive abortion laws in a state is available in Merz et al. (1995) and the Alan Guttmacher Institute (2004), State Policies in Brief. The cross-state and year variations in restrictive state abortion laws are used to estimate their impact on the incidence of teen pregnancy.

However, to more accurately determine the relationship between restrictive abortion laws and teen pregnancy rates, multivariate regression analysis must be used in order to control for state differences in their socioeconomic characteristics and social policies that have been found in the literature to be determinants of teen pregnancy rates. For example, if the generosity of a state’s welfare benefits creates an incentive for unmarried women to have children, then the pregnancy rate in a state with restrictive abortion laws cannot be directly compared to the rate in a state without restrictive abortion laws without controlling for the differences in welfare benefits in the two states. The consequence of failing to control for welfare benefits is that any inferences drawn about the estimated impact of restrictive abortion laws may be an artifact of the omitted welfare benefits. The inclusion of control variables helps identify whether the estimated relationship between restrictive abortion laws and teen pregnancy rates is truly causal.

The regression model contains controls for the abortion price (in year 2000 dollars), the average full-time female income (in year 2000 dollars), the labor force participation rate, education (percent who have completed 12 years or more of schooling), marital status (percent married), and religiosity (percent who are Evangelical Christians) in each state. All the socioeconomic variables measure only the cohort of adult women of childbearing ages 20–44 years and the data are available in the US Bureau of the Census, US Census of Population, State Reports (1983, 1993, 2003) and the Statistical Abstract of the United States (1983, 1993, 2003) and the abortion price was provided by the Alan Guttmacher Institute.

The regression model also controls for state social policies: the welfare generosity of a state (the average TANF (Temporary Assistance to Needy Families) benefit received by an unmarried woman with one child, in year 2000 dollars) and two variables that control for possible travel by teens to nearby border states that do not have a parental involvement law or do not have a mandatory delay law (see Blank et al. 1996 for a complete description of these variables). Time trend variables for the year 2000 and for the year 1992 are included to control for health factors, such as the awareness of the possible harmful and deadly effects from unprotected sexual activity, that affects the sexual behavior of teens equally in all states.

Lastly, another factor that must be controlled for is a state’s unobserved public attitudes towards nonmarital teen sexual activity and abortion. These attitudes may have a significant impact on the sexual behavior of teens residing in that state. A state’s public abortion attitudes may affect both a state’s restrictive abortion policies and the state’s teen pregnancy rate. There may be less teen pregnancies in states with restrictive abortion policies because states that enact these restrictions may be the states that would have fewer teen pregnancies, regardless. In other words, the abortion restrictions may be correlated with the residuals in an empirical model that does not control for state differences in antiabortion attitudes. Antiabortion attitudes within a state are controlled for by using the Erikson et al. (1993) measure of a state’s political ideology—the percentage of respondents who identify themselves as conservative minus the percentage who identify themselves as liberal in the CBS/New York Times Opinion Polls for each state in the years 1982, 1992 and 2000.

6 Empirical Results

The price of an abortion in the teen pregnancy equation cannot be treated as exogenous since teens’ risky sexual behavior partially determines the abortion price. Since the price of an abortion is determined simultaneously with the teen pregnancy rate, the econometric solution to this problem is to find instruments for the abortion price that are correlated with the abortion price, but do not directly affect the teen pregnancy rate (Gujarati 2007). The instruments selected for the abortion price are similar to those used by Blank et al. (1996) who argue that the following instruments are related to the overall level of availability, accessibility, and the cost of health care providers of general medical services in a state, but are unlikely to be affected by the teen pregnancy rate within a state. The instruments utilized are: (1) the number of non-OBGYN physicians per 100,000 females ages 15–44; (2) the number of nurses per 100,000 females ages 15–44; (3) the number of hospitals; and (4) the average weekly wage of employees in the offices of physicians. The teen pregnancy rate equation was estimated with two-stage least squares and the empirical results for teens (ages 15–19) are reported in Table 1, column 1. In the interest of brevity, only the regression coefficients for the abortion variables are reported (the complete empirical results are available upon request). Each entry in Table 1 represents the estimated regression coefficient of the abortion price or the four restrictive abortion laws (as well as the absolute value of the t-statistic in parentheses below the coefficient).
Table 1

Regression coefficients of abortion variables on teen pregnancy rates

Abortion cost variables

Dependent variable

Number of teen pregnancies/1,000 teens ages 15–19

(1)

(2)

Abortion price

−.4301 (3.51)***

−.4235 (3.36)***

Medicaid funding restriction

−27.0456 (3.38)***

−26.7360 (3.34)***

Parental involvement law

−5.0442 (.82)

Mandatory delay law

8.2251 (.59)

8.0644 (.59)

Informed consent Law

−42.3283 (4.93)***

−42.2462 (4.94)***

Parental notification law

−4.9367 (.70)

Parental consent law

−5.1365 (.73)

Note: Absolute value of t-statistics in parentheses: *** p < .01. Each cell entry represents the coefficient from a regression model where the dependent variable is the number of teen pregnancies per 1,000 teens (ages 15–19) and the other independent variables are income, labor force participation rate, marital status, education, religiosity, welfare generosity, border state parental involvement law policies, border state mandatory delay law policies, year indicators, and state antiabortion attitudes as described in the text

The empirical results reported in Table 1, column 1 indicate strong policy effects on the likelihood of teen pregnancy. Both the price of obtaining an abortion and a Medicaid funding restriction have a significantly negative impact on a state’s teen pregnancy rate. This implies that teen contraceptive use responded positively or the frequency of teen unprotected sexual activity negatively to state policies that increase the cost of an abortion to teens. The estimated coefficient of the abortion price and the Medicaid funding restriction variable suggests that teens’ pregnancy avoidance behavior is highly sensitive to increases in the cost of an abortion. A fifty dollar increase in the price of an abortion reduces a state’s teen pregnancy rate by 21.5 pregnancies per 1,000 teens (or equivalently, a reduction in a state’s teen pregnancy rate by 2.15 percentage points). A Medicaid funding restriction reduces a state’s teen pregnancy rate by 27 pregnancies per 1,000 teens (or equivalently, a reduction in a state’s teen pregnancy rate by 2.7 percentage points) as compared to states without a Medicaid funding restriction of abortion.

Parental involvement laws are found not to significantly alter teens’ pregnancy avoidance behavior. This suggests that parental involvement laws represent a negligible increase in the effective total cost to teens of obtaining an abortion. There are two possible explanations for this result. First teens, if they become pregnant, may invariably involve a parent in their pregnancy resolution decision (Henshaw and Kost 1992). Second, judges may be routinely waiving parental involvement requirements and granting all teen bypass petitions (Sanger 2004).

A mandatory delay law does not significantly deter teens from becoming pregnant. States that enacted informed consent laws experienced a reduction in their state’s teen pregnancy rate by 4.2 percentage points as compared to states without an informed consent law.

There are two types of parental involvement laws. Parental notification laws require that a parent be notified of a teen minor’s intent to have an abortion, but the parent may not prevent the minor from obtaining an abortion. Parental consent laws require permission of a parent before the abortion procedure. Parental consent laws give a parent the legal right to deny their teen minor from having an abortion. Parental consent laws, in theory, are more restrictive than parental notification laws. This suggests that there may be empirical differences between the two types of parental involvement laws with parental consent laws having a stronger impact on teen minors’ pregnancy avoidance behavior.

In order to test if there are empirical differences between the two types of parental involvement laws the Parental Involvement Law variable was disaggregated into two separate dummy variables: Parental Consent Law (=1) if a state had a parental consent law in effect and a Parental Notification Law (=1) if a state had a parental notification law in effect during 1982, 1992 or 2000. The empirical results when the Parental Consent Law and the Parental Notification Law variables replace the Parental Involvement variable appear in Table 1, column 2. Neither of the two types of parental involvement laws significantly alters teen pregnancy avoidance behavior. Parental consent and parental notification laws are not effective public policy measures in reducing teen pregnancy rates.

Researchers have generally treated teens (15–19 years of ages) as a homogenous group. However, as noted by Moore et al. (1995), as teens get older they become more forward looking in their decision-making regarding the costs and consequences of having unprotected sexual activity. This suggests that sexually active non-minor teens (18–19 years of age) react differently to restrictive abortion laws than sexually active teen minors (less than 18 years of age). In order to determine whether the effects of restrictive abortion policies are significantly different for minor teens and non-minor teens, the regression model was estimated separately for each teen age group. The empirical results for the pregnancy rates of minor teens (ages 15–17) and for non-minor teens (ages 18–19) appear in Tables 2 and 3, column 1 when the Parental Involvement Law variable is included and in column 2 when the disaggregated Parental Consent Law and the Parental Notification Law variables are used in the regression model, respectively.
Table 2

Regression coefficients of abortion variables on minor teen pregnancy rates

Abortion cost variables

Dependent variable

Number of minor teen pregnancies/1,000 teens (15–17)

(1)

(2)

Abortion price

−.2371 (3.28)***

−.2322 (3.14)***

Medicaid funding restriction

−18.6168 (3.98)***

−18.3855 (3.95)***

Parental involvement law

−2.0593 (.57)

Mandatory delay law

6.5805 (.82)

6.4574 (.82)

Informed consent law

−27.4327 (5.57)***

−27.3642 (5.60)***

Parental notification Law

-1.9505 (.48)

Parental consent law

−2.1453 (.51)

Note: Absolute value of t-statistics in parentheses: *** p < .01. Each cell entry represents the coefficient from a regression model where the dependent variable is the number of minor teen pregnancies per 1,000 minor teens (ages 15–17) and the other independent variables are income, labor force participation rate, marital status, education, religiosity, welfare generosity, border state parental involvement law policies, border state mandatory delay law policies, year indicators, and state antiabortion attitudes as described in the text

Table 3

Regression coefficients for abortion variables on non-minor teen pregnancy rates

Abortion cost variables

Dependent variable

Number of non-minor teen pregnancies/1,000 teens ages 18–19

(1)

(2)

Abortion price

−.7180 (3.70)***

−.7168 (3.57)***

Medicaid funding restriction

−38.9819 (3.01)***

−38.7981 (2.97)***

Parental involvement law

−10.3831 (1.04)

Mandatory delay law

11.2484 (.49)

11.1454 (.48)

Informed consent law

−64.6315 (4.48)***

−64.1645 (4.42)***

Parental notification law

−8.9621 (.76)

Parental consent law

−11.7314 (1.02)

Note: Absolute value of t-statistics in parentheses: *** p < .01. Each cell entry represents the coefficient from a regression model where the dependent variable is the number of non-minor teen pregnancies per 1,000 non-minor teens (ages 18–19) and the other independent variables are income, labor force participation rate, marital status, education, religiosity, welfare generosity, border state parental involvement law policies, border state mandatory delay law policies, year indicators, and state antiabortion attitudes as described in the text

The empirical results that are reported in Tables 2 and 3 are robust with the previously reported results in Table 1. The price of an abortion, Medicaid funding restrictions and an informed consent law each has a significantly negative impact on both minor teen and non-minor teen pregnancy rates. The empirical results again support the hypothesis that these abortion policies cause a change in the sexual/contraceptive practices of both minor and non-minor teens reducing the likelihood of an unwanted teen pregnancy.

The regression coefficients reported in Tables 2 and 3 also indicate that the unprotected sexual activity of non-minor teens is much more sensitive to increases in the costs of an abortion than the unprotected sexual activity of minor teens. For example, a 50 dollar increase in the price of an abortion causes a reduction in a state’s non-minor teen pregnancy rate by 35.9 pregnancies per 1,000 non-minor teens versus a reduction of 11.45 pregnancies in a state’s minor teen pregnancy rate. An F-test (F = 11.92) showed that the price of an abortion, Medicaid funding restrictions and informed consent laws have a significantly greater impact reducing the incidence of the non-minor teen pregnancy rate than the incidence of the minor teen pregnancy rate.

7 Limitations

The empirical results reported in this article are subject to several caveats. One potential problem is that it is possible that some other factor that affects teens’ pregnancy avoidance behavior changed at the same time as the enactment of a restrictive abortion law. If this other factor were controlled for in the multivariate regression model there would be no bias in the empirical results. However, if this other factor is not controlled for, then the impact of this other factor would be incorrectly attributed to a state’s restrictive abortion law and overstate the impact of a state’s restrictive abortion laws (Gujarati 2007).

The estimated teen pregnancy equation does not include a control variable for the emotional costs of a teen pregnancy (e.g., regret, humiliation, shame, and guilt). While some of the emotional costs of a teen pregnancy may have been captured by the antiabortion attitude variable included in the estimation of the teen pregnancy equation, it is possible that a state’s residents’ antiabortion sentiment changes both the emotional costs of a teen pregnancy and the restrictiveness of a state’s abortion policies. If this were the case, then the estimated effect of a state’s restrictive abortion policies will be biased upwards.

Another potential problem is that a state’s restrictive abortion laws may not be exogenous, but a reaction by state legislators to the level of abortion demand (unprotected sexual activity) in their state. If this were the case, then the empirical results will be biased estimates of the impact of the restrictive abortion laws. However, Cohen and Barrilleaux (1993) and Medoff (2002) found that a state’s passage of restrictive abortion laws was not a reaction to a state’s abortion rates. These studies each found that a state’s restrictive abortion policy was a function of the political strength of well-organized and highly mobilized groups opposed to abortion.

8 Conclusion

In 1992, the US Supreme Court in Planned Parenthood of Southeastern Pennsylvania v. Casey (112 US 2791) reaffirmed the constitutionality of abortion, but gave states considerable latitude to pass laws restricting women’s abortion access, as long as the restrictions do not constitute an “undue burden” on women seeking an abortion. This decision is controversial because the Court did not explicitly define the ambiguous phrase “undue burden.” A restrictive abortion law may not appear to be a prima facie “undue burden”, but in point of fact may impede a woman’s access to an abortion. Thus one crucial public policy question is does a restrictive abortion law alter women’s sexual behavior and, if so, how?

This article, using the tools of economic analysis, empirically examined how teens respond to restrictive abortion laws that alter their costs of engaging in risky (unprotected) sexual activity. The Kane and Staiger (1996) economic model argues that access to an abortion provides insurance against unwanted pregnancies since abortion is the only birth control method which allows women to avoid a birth once pregnant. Their theoretical model implies restrictive state abortion laws, by increasing the costs incurred by women in terminating an unwanted pregnancy, may increase the incentive of women to avoid becoming pregnant.

The empirical results reported in this paper provide new evidence about the policy effects of restrictive state abortion laws on teen pregnancy. The state abortion policies examined increase the financial and emotional costs of a teen engaging in risky (unprotected) sexual activity. The empirical results find that the abortion price, Medicaid funding restrictions and an informed consent law all reduce the pregnancy rates of teens, minor teens and non-minor teens. This implies that teens respond to public policies that increase the cost of an abortion by increasing their level of pregnancy avoidance.

From a public policy standpoint the empirical results suggest that sexually active teens respond to the imposition of Medicaid funding restrictions and informed consent laws by either reducing their frequency of unprotected sexual activity or increasing their use of ex ante contraceptives resulting in fewer unwanted teen pregnancies. However, whether the enactment of public policies which increase the effective cost of obtaining an abortion constitute an “undue burden”on the reproductive rights of women is a normative question that is well beyond the scope of economic analysis.

References

  1. Afxentiou, D., & Hawley, C. B. (1997). Explaining female teenagers’ sexual behavior and outcomes: A bivariate probit analysis with selectivity correction. Journal of Family and Economic Issues, 18, 91–106. doi: 10.1023/A:1024925418314.CrossRefGoogle Scholar
  2. Alan Guttmacher Institute. (2004). State policies in brief. New York: Alan Guttmacher Institute.Google Scholar
  3. An, C. -B., Haveman, R., & Wolfe, B. (1993). Teen out-of-wedlock births and welfare receipt: The role of childhood events and economic circumstances. Review of Economics and Statistics, 75, 195–208.CrossRefGoogle Scholar
  4. Averett, S. L., Rees, D. I., & Argys, L. M. (2002). The impact of government policies and neighborhood characteristics on teenage sexual activity and contraceptive use. American Journal of Public Health, 92, 1773–1778. doi: 10.2105/AJPH.92.11.1773.CrossRefGoogle Scholar
  5. Bellotti v. Baird (1979) 443 US 622.Google Scholar
  6. Blank, R. M., George, C. C., & London, R. A. (1996). State abortion rates: The impact of policies, providers, politics, demographics, and economic environment. Journal of Health Economics, 15, 513–553. doi: 10.1016/S0167-6296(96)00494-8.CrossRefGoogle Scholar
  7. Cohen, J. E., & Barrilleaux, C. B. (1993). Public opinion, interest groups, and public policy making; Abortion policy in the American states. In M. L. Goggin (Ed.), Understanding the new politics of abortion (pp. 190–202). Newbury Park, CA: Sage Publications.Google Scholar
  8. Duncan, G. J., & Hoffman, S. D. (1990). Welfare benefits, economic opportunities, and out-of- wedlock births among black teenagers. Demography, 27, 519–535. doi: 10.2307/2061568.CrossRefGoogle Scholar
  9. Erikson, R. S., Wright, G. C., & McIver, J. P. (1993). Statehouse democracy. Cambridge, UK: Cambridge University Press.Google Scholar
  10. Furstenberg, F. F., & Teitler, J. O. (1994). Reconsidering the effects of marital disruption: What happens to children of divorce in early childhood. Journal of Family Issues, 15, 173–190. doi: 10.1177/0192513X94015002002.CrossRefGoogle Scholar
  11. Gujarati, D. N. (2007). Basic econometrics. New York: McGraw-Hill.Google Scholar
  12. Hanson, S. L., Myers, D. E., & Ginsburg, A. L. (1987). The role of responsibility and knowledge in reducing teenage out-of-wedlock childbearing. Journal of Marriage and the Family, 49, 241–256. doi: 10.2307/352297.CrossRefGoogle Scholar
  13. Harris v. McRae (1980) 448 US 297.Google Scholar
  14. Henshaw, S. K. (2004). US teenage pregnancy statistics with comparative statistics for women aged 20–24. New York: The Alan Guttmacher Institute.Google Scholar
  15. Henshaw, S. K., & Kost, K. (1992). Parental involvement in minors’ abortion decisions. Family Planning Perspectives, 24, 196–207. doi: 10.2307/2135870.CrossRefGoogle Scholar
  16. Hofferth, S. L. (1987). Factors affecting initiation of sexual intercourse. In S. L. Hofferth & C. D. Hayes (Eds.), Risking the future: Adolescent sexuality, pregnancy and childbearing (pp. 7–35). Washington, DC: National Academy Press.Google Scholar
  17. Hoffman, S. D. (2006). By the numbers: The public costs of teen childbearing. Washington, DC: The National Campaign to Prevent Teen Pregnancy.Google Scholar
  18. Kahn, J. R., & Anderson, K. E. (1992). Intergenerational pattern of teenage fertility. Demography, 29, 39–57. doi: 10.2307/2061362.CrossRefGoogle Scholar
  19. Kane, T. J., & Staiger, D. (1996). Teen motherhood and abortion access. The Quarterly Journal of Economics, 111, 467–506. doi: 10.2307/2946685.CrossRefGoogle Scholar
  20. Levine, P. B. (2001). The sexual activity and birth control use of American teenagers. In J. Gruber (Ed.), An economic analysis of risky behavior among youths (pp. 167–218). Chicago: University of Chicago Press.Google Scholar
  21. Levine, P. B. (2003). Parental involvement laws and fertility behavior. Journal of Health Economics, 22, 861–878. doi: 10.1016/S0167-6296(03)00063-8.CrossRefGoogle Scholar
  22. Lundberg, S., & Plotnick, R. D. (1995). Adolescent premarital childbearing: Do economic incentives matter? Journal of Labor Economics, 13, 177–200. doi: 10.1086/298372.CrossRefGoogle Scholar
  23. H. L. v. Matheson (1981) 450 US 398.Google Scholar
  24. McLanahan, S., & Bumpass, L. (1988). Intergenerational consequences of family disruption. American Journal of Sociology, 94, 130–152. doi: 10.1086/228954.CrossRefGoogle Scholar
  25. Medoff, M. H. (2002). The determinants and impact of state abortion restrictions. American Journal of Economics and Sociology, 61, 481–494. doi: 10.1111/1536-7150.00169.CrossRefGoogle Scholar
  26. Merz, J. F., Jackson, C. A., & Klerman, J. A. (1995). A review of abortion policy: Legality, Medicaid funding, and parental involvement, 1967–1994. Women’s Rights Law Reporter, 17, 1–61.Google Scholar
  27. Mezey, S. G. (1992). In pursuit of equality: Women, public policy, and the federal courts. New York: St. Martin’s Press.Google Scholar
  28. Moore, K. A., Miller, B. C., Glei, D., & Morrison, D. R. (1995a). Adolescent sex, contraception, and childbearing: A review of recent research. Washington, DC: Child Trends, Inc.Google Scholar
  29. Moore, K. A., Morrison, D. R., & Glei, D. (1995b). Welfare and adolescent sex: The effects of family history, benefit levels, and community context. Journal of Family and Economic Issues, 16, 207–237. doi: 10.1007/BF02353709.CrossRefGoogle Scholar
  30. Planned Parenthood of Southeastern Pennsylvania v. Casey (1992) 112 US 2791.Google Scholar
  31. Posner, R. (1997). Sex and reason. Chicago: University of Chicago Press.Google Scholar
  32. Roe v. Wade (1973) 410 US 113.Google Scholar
  33. Sanger, C. (2004). Regulating teenage abortion in the United States: Politics and Policy. International Journal of Law, Policy and the Family, 18, 305–318. doi: 10.1093/lawfam/18.3.305.CrossRefGoogle Scholar
  34. Sen, B. (2006). Frequency of sexual activity among unmarried adolescent girl: Do state policies pertaining to abortion access matter? Eastern Economic Journal, 32, 313–330.Google Scholar
  35. Statistical Abstract of the United States. (1983, 1993, 2003). Washington, DC: Government Printing Office.Google Scholar
  36. Tomal, A. (1999). Parental involvement laws and minor and non-minor teen abortion and birth rates. Journal of Family and Economic Issues, 20, 149–162. doi: 10.1023/A:1022154710245.CrossRefGoogle Scholar
  37. Urdy, J. R., Kovenock, J., & Morris, N. M. (1996). Early predictors of nonmarital first pregnancy and abortion. Family Planning Perspectives, 28, 113–116. doi: 10.2307/2136223.CrossRefGoogle Scholar
  38. US Bureau of the Census. (1983). US Census of Population, State Reports, 1993, 2003.Google Scholar
  39. Webster v. Reproductive Health Services (1989) 492 US 490.Google Scholar
  40. Wilson, W. J. (1987). The truly disadvantaged: The inner city, the underclass and public policy. Chicago: University of Chicago Press.Google Scholar
  41. Yamaguchi, K., & Kandel, D. (1987). Drug use and other determinants of premarital pregnancy and its outcomes: A dynamic analysis of competing life events. Journal of Marriage and the Family, 49, 257–270. doi: 10.2307/352298.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.California State UniversityLong BeachUSA

Personalised recommendations