March 2, DOI: The incidence of abortion is found to be lower in states where access to providers is reduced and state policies are restrictive. In addition, birthrates are elevated where the costs of contraception are higher because access to obstetrician-gynecologists and family planning services is reduced.
Economic factors showed no consistent relationship with abortion rates. Family Planning Perspectives, Especially controversial have been discussions regarding the effects of Medicaid funding restrictions, hour waiting periods and parental consent requirements for minors on the incidence of abortion; the effects of family planning programs on rates of births and abortions; and incentives for out-of-wedlock childbearing attributed to the Aid to Families with Dependent Children AFDC program.
These questions reflect more general but perhaps less widely publicized issues that are well suited to economic analysis, such as the cost and accessibility of reproductive health services and changes in women's and men's economic opportunities.
Economic models are particularly useful for sorting out the determinants of reproductive behavior in the United States because of the substantial heterogeneity that characterizes not only the population's values and preferences, but also its economic resources and access to different types of health care.
This literature, which is summarized elsewhere, 1 has recently expanded to include research on the determinants of abortion.
However, there remain unexplored issues and weaknesses in the literature. An important shortcoming of many studies is the omission of relevant economic and policy variables. For instance, analyses of women's abortion decision-making have failed to include the gender-specific measures of economic resources and labor-market opportunities that have commonly appeared in studies of fertility.
Both types of studies have tended to include only limited measures reflecting access to reproductive health services. A related problem, which recent analyses have begun to address, involves potentially confounding effects from unobserved and imperfectly measured variables.
Finally, only a few studies have examined abortion and fertility behavior in tandem. The analysis is based on an economic model in which the behavior leading to pregnancy and to pregnant women's decisions on whether to carry the pregnancy to term depends on the women's resources, direct costs, opportunity costs, attitudes and preferences for children.
Our empirical analysis complements and extends previous research in several respects. First, we consider a comprehensive set of explanatory variables. To describe the direct costs of contraception, abortion and births, we include longitudinal variables for the number and geographic distribution of family planning clinics, abortion providers and obstetrician-gynecologists within states.
State policy indicators are used to measure access to reproductive health services. To describe resources and opportunity costs, we include state- and year-specific measures of women's and men's property incomes i. To gauge the political and social climate, we examine party affiliations of state executives, legislators' voting records and attitude measures drawn from opinion surveys.
For many of our primary variables, we have identified supplemental measures that permit us to check the robustness of our results i. Second, although the use of such elaborate controls accounts for a considerable portion of the cross-state differences in abortion rates and birthrates, standard regression estimates may still be biased by the omission of relevant variables.
Hence, in our empirical analysis, we employ fixed-effects regression methods i. Third, the study examines abortion rates and birthrates together, allowing us to consider the logical consistency of the results, check for "cross-policy" effects e. Furthermore, since the presence of measurement error in an independent variable should bias the estimates for both abortion rates and birthrates toward zero, this parallel analysis may help us distinguish a small effect of an independent variable from an artifact of measurement error.
Theoretical Framework We begin by sketching a simple, stylized model of the economic determinants of behavior that may lead to pregnancy and the decision of how to resolve a pregnancy. The model is offered to generate broad predictions and motivate the empirical analysis that follows. Because economic models of fertility have been extensively discussed elsewhere, 4 and since data limitations preclude us from undertaking a detailed structural analysis, we keep the theoretical discussion brief.
A live birth results from a number of behavioral and biological factors. For simplicity, our theoretical analysis groups the behavioral determinants of fertility into two decisions. The first decision is the level of effort used to avoid or achieve a pregnancy contraceptive effort. This decision reflects such behavioral factors as entry into a sexual relationship, frequency of intercourse and choice of contraceptive method, and such biological factors as postpartum infecundability and onset of sterility.
The second decision, faced by women who conceive, is how to resolve the pregnancy. These decisions can be examined through a straightforward economic analysis of fertility. These preferences embody women's personal, cultural and religious values. We also assume that women's preferences are constrained by their available time and economic resources, the availability and costs of alternative reproductive health services, and the time and financial requirements of raising children and producing household commodities.
This approach reveals that contraceptive effort and pregnancy resolution are related and that each involves direct expenditures of time and money, as well as opportunity costs in terms of forgone earnings and consumption possibilities.
To examine the implications of the model, we first consider conditional predictions regarding pregnancy resolution. The model predicts that if the direct costs of abortion are increased by such factors as higher service fees, reduced availability or tighter legal restrictions, pregnant women will be deterred from obtaining abortions.
On the other hand, if the direct costs of having children are increased by such factors as higher delivery costs and less generous AFDC and Medicaid payments, women will be more likely to terminate unintended pregnancies. Higher levels of wealth from sources other than earnings increase the affordability of both abortions and children; however, we assume that the presence of children is an economic "good," and we therefore expect childbearing to dominate.
The opposite relationship is possible if income increases the demand for child "quality"—e. Returning to contraceptive effort, the model suggests that the above factors affect the unconditional rates of abortions and births to the extent that they affect the likelihood of pregnancy. For instance, higher costs associated with obtaining an abortion or having a child reduce the expected indirect utility associated with pregnancy i. Thus, policies that restrict access to abortion not only deter pregnant women from obtaining abortions but also deter women from becoming pregnant in the first place.
Because these effects are reinforcing, such policies would lower the incidence of abortions. For births, however, the separate effects of these policies run counter to one another, leading to ambiguous net effects. A similar analysis can be used to examine other policy changes. For example, we would expect more generous AFDC benefits to be associated with increased rates of pregnancies and births, but the overall effect on abortion rates would be less clear.
Previous Research Nearly every social science discipline has contributed to examinations of various aspects of this theoretical model.
In some cases, the model's predictions have been confirmed e. A central methodological issue is that ordinary regression estimates are biased if important determinants of reproductive behavior, such as the values underlying women's preferences, are correlated with the observed independent variables but are omitted or only partially accounted for in the regression equation.
Indeed, Blank and collaborators found that the estimated effects of parental involvement laws and Medicaid funding restrictions on abortions were sensitive to the use of state-specific dummy variable controls for unobserved heterogeneity fixed effects. They also showed that both parental involvement and funding restrictions had negative but statistically nonsignificant effects on abortion rates classified by the woman's state of residence; Medicaid restrictions had significant effects on rates by the state in which the abortion occurred, a finding confirmed by at least one other study.
They have found that the incidence of abortion is positively and significantly associated with both the availability of providers and women's per capita income. Unfortunately, several issues have been ignored or only lightly researched.
For example, only one fixed-effects abortion study has examined access to reproductive health services other than abortions, 14 and no abortion study—fixed-effects or otherwise—has separately examined the economic resources of women and men. Although women's and men's economic resources and opportunities have not been considered in the abortion studies, measures of these characteristics have figured prominently in empirical analyses of fertility. For example, a cross-sectional analysis of welfare and fertility included women's wages and property incomes and potential spouses' wages, arguing that omitting these conditions would likely bias the estimated effects of AFDC generosity on births.
Men's wages had a positive association with childbearing among younger women, while AFDC generosity typically had nonsignificant effects. These results, however, also appear to be sensitive to the inclusion of fixed effects. Preliminary results from Jackson and Klerman based on fixed-effects regressions indicated that AFDC benefits had large positive effects on the birthrate among white women but no association among blacks. In addition, men's earnings had positive effects on births among whites and mixed effects among blacks; however, the earnings results were very sensitive to the inclusion of other economic variables.
With respect to other policy variables, preliminary evidence suggests that parental involvement laws are associated with reduced levels of childbearing. Detailed descriptions of the data and their sources appear in the appendix page The use of state-level information confers some advantages over using data that are less aggregated. Primarily, it permits us to examine a wide array of measures covering a moderately long period.
The data, which describe behavior related to highly personal issues, also are less susceptible to reporting problems than are some microlevel data sets and can be made nationally representative. On the other hand, when using aggregate data, we lack individual-level controls and cannot isolate effects among particular groups of women e. In addition, with these data, we can make only limited inferences about individual behavior. The study focuses on two reproductive outcomes—births and abortions.
Annual data on total births are available from several sources; we use information from the Area Resource File. The best available information comes from The Alan Guttmacher Institute AGI , which regularly surveyed abortion providers through the s and s. On the basis of these provider reports, AGI estimated the numbers of abortions by state of occurrence and by state of residence. Unfortunately, the rates by state of occurrence are difficult to analyze, since unknown numbers of women cross state borders to obtain an abortion.
Nevertheless, we use the state-of-residence estimates because they allow us to match information on abortion incidence with data on the characteristics of women who may have an abortion. The explanatory variables for our analysis shown with their population-weighted mean values for the United States in Table 1 can be grouped into a few broad categories.
A key set of measures describes the accessibility of reproductive and general health services. These are the numbers of abortion providers, family planning clinics and obstetrician-gynecologists per 1, women aged ; the proportion of women living in counties with each service; the average distance to the nearest in-state and out-of-state abortion provider; and the proportion of the population enrolled in a health maintenance organization HMO.
We interpreted accessibility as a proxy for the direct cost of a service. For the family planning and abortion availability measures, the implications are straightforward: Increased access reduces the effective costs and should increase reliance on contraception and abortion, respectively. For obstetrician-gynecologist availability and HMO membership, the implications are less clear, because access to these services reduces the costs of all types of reproductive health care. Another set of variables describes women's and men's economic resources and opportunities.
The pooled data are also used to construct ordinary averages and selectivity-adjusted imputations of women's and men's hourly wages for each state and year i. To assess whether the estimation results are sensitive to the specification of the CPS variables and for general purposes of comparability, we supplemented the CPS measures with longitudinal state-level data on gender-specific unemployment rates and per capita total personal income and on average annual manufacturing and retail earnings.
Although the CPS is nationally representative, weighted observations from it may not be representative at the state level. The disadvantages are that they only indirectly measure the variables of interest, they may be more endogenous than the measures of wage or property income, and the variables for total income and sector-specific earnings may not accurately reflect gender-specific opportunities.
A third group of explanatory variables describes state policies that may influence reproductive decisions. Some of these—restrictions on Medicaid funding for abortion, and parental consent and notification laws for abortion—are intended to do so. Others—AFDC benefits for a family of four and average Medicaid benefits distributed to AFDC recipients—may alter incentives for childbearing even if that is not their purpose.
To control for attitudes toward abortion and other institutional and population characteristics, we include in the analysis several political and demographic variables. These generally have standard interpretations, and many have appeared in previous studies. Analytic Approach In this article, we use regression analysis to examine the determinants of state abortion rates and birthrates. For each outcome, we report estimates from two ordinary least-squares regressions.
The first incorporates the explanatory variables and dummy variables for each year and each state i. The second adds interactions of each state dummy variable with a linear time trend.