The effects of economic conditions and access to reproductive health services on state abortion rates and birthrates. (ARTICLES).The effects that such factors as wages, welfare policies and access to physicians, family planning family planning
Use of measures designed to regulate the number and spacing of children within a family, largely to curb population growth and ensure each family’s access to limited resources. clinics and abortion providers have on abortion rates and birthrates are examined in analyses based on 1978-1988 state-level data and longitudinal regression techniques. The incidence of abortion is found to be lower in states where access to providers is reduced and state policies are restrictive. Calculations indicate that decreased access may have accounted for about one-quarter of the 5% decline in abortion rates between 1988 and 1992. In addition, birthrates are elevated where the costs of contraception contraception: see birth control.
Birth control by prevention of conception or impregnation. The most common method is sterilization. The most effective temporary methods are nearly 99% effective if used consistently and correctly. are higher because access to obstetrician-gynecologists and family planning services is reduced. Economic resources such as higher wages for men and women and generous welfare benefits are significantly and consistently related to increased birthrates; however, even a 10% cut in public assistance benefits would result in only one birth fewer for every 2l2 women on welfare. Economic factors showed no consiste nt relationship with abortion rates.
Policy discussions concerning factors that influence reproductive behavior Reproductive behavior
Behavior related to the production of offspring; it includes such patterns as the establishment of mating systems, courtship, sexual behavior, parturition, and the care of young. reach a level of intensity seldom matched by other matters of public discourse. Especially controversial have been discussions regarding the effects of Medicaid funding restrictions, 24-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 Aid to Families with Dependent Children (AFDC) was the name of a federal assistance program in effect from 1935 to 1997, which was administered by the United States Department of Health and Human Services. (AFDC AFDC
Aid to Families with Dependent Children
AFDC n abbr (US) (= Aid to Families with Dependent Children) → ayuda a familias con hijos menores
AFDC n abbr ) program.
These questions reflect more general but perhaps less widely publicized pub·li·cize
tr.v. pub·li·cized, pub·li·ciz·ing, pub·li·ciz·es
To give publicity to.
Adj. 1. publicized - made known; especially made widely known
publicised issues that are well suited to economic analysis, such as the cost and accessibility of reproductive health Within the framework of WHO's definition of health as a state of complete physical, mental and social well-being, and not merely the absence of disease or infirmity, reproductive health, or sexual health/hygiene 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 United States, officially United States of America, republic (2005 est. pop. 295,734,000), 3,539,227 sq mi (9,166,598 sq km), North America. The United States is the world's third largest country in population and the fourth largest country in area. because of the substantial heterogeneity het·er·o·ge·ne·i·ty
The quality or state of being heterogeneous.
the state of being heterogeneous. that characterizes not only the population's values and preferences, but also its economic resources and access to different types of health care. (*)
Accordingly, economists have conducted numerous empirical studies Empirical studies in social sciences are when the research ends are based on evidence and not just theory. This is done to comply with the scientific method that asserts the objective discovery of knowledge based on verifiable facts of evidence. of the socioeconomic and political determinants of fertility in the United States. This literature, which is summarized elsewhere,  has recently expanded to include research on the determinants of abortion. (2) While researchers have generally found support for basic economic hypotheses, a number of specific results, including most of the policy questions raised above, remain in dispute.
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 confounding
when the effects of two, or more, processes on results cannot be separated, the results are said to be confounded, a cause of bias in disease studies.
confounding factor effects from unobserved and imperfectly im·per·fect
1. Not perfect.
2. Grammar Of or being the tense of a verb that shows, usually in the past, an action or a condition as incomplete, continuous, or coincident with another action.
3. measured variables. Finally, only a few studies have examined abortion and fertility behavior in tandem Adv. 1. in tandem - one behind the other; "ride tandem on a bicycle built for two"; "riding horses down the path in tandem"
tandem . 
In this article, we investigate the determinants of annual abortion rates and birthrates using state-level data from the years 1978-1988. 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 Opportunity costs
The difference in the actual performance of a particular investment and some other desired investment adjusted for fixed costs and execution costs. It often refers to the most valuable alternative that is given up. , 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.e., nonwage) and available wage rates. 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.e., we check whether the estimated effect of each variable maintains its si gn and magnitude and remains significant when assumptions underlying the analytic model change).
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.e., we account for state-specific dummy Sham; make-believe; pretended; imitation. Person who serves in place of another, or who serves until the proper person is named or available to take his place (e.g., dummy corporate directors; dummy owners of real estate). variables) to control for unobserved heterogeneity in attitudes and institutions across states.
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.g., the effect of abortion policy on fertility) and examine whether policies affect reproductive outcomes by altering the number of pregnancies that occur. 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 A distortion in an image or sound caused by a limitation or malfunction in the hardware or software. Artifacts may or may not be easily detectable. Under intense inspection, one might find artifacts all the time, but a few pixels out of balance or a few milliseconds of abnormal sound of measurement error.
We begin by sketching a simple, stylized styl·ize
tr.v. styl·ized, styl·iz·ing, styl·iz·es
1. To restrict or make conform to a particular style.
2. To represent conventionally; conventionalize. 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 contraceptive /con·tra·cep·tive/ (-sep´tiv)
1. diminishing the likelihood of or preventing conception.
2. an agent that so acts. effort). This decision reflects such behavioral factors as entry into a sexual relationship, frequency of intercourse and choice of contraceptive method Noun 1. contraceptive method - birth control by the use of devices (diaphragm or intrauterine device or condom) or drugs or surgery
birth control, birth prevention, family planning - limiting the number of children born , and such biological factors as postpartum postpartum /post·par·tum/ (post-pahr´tum) occurring after childbirth, with reference to the mother.
Of or occurring in the period shortly after childbirth. 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. (5) We assume that women have preferences regarding contraceptive use, abortion, the presence of children and the consumption of commodities. These preferences embody women's personal, cultural and religious values. We also assume that women's preferences are constrained con·strain
tr.v. con·strained, con·strain·ing, con·strains
1. To compel by physical, moral, or circumstantial force; oblige: felt constrained to object. See Synonyms at force.
2. 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.g., improved health and education--and, in turn, raises the price of having more children. (6) An increase in women's wages raises both wealth and the opportunity costs of childbearing; consequently, its effect on pregnancy resolution is ambiguous.
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.e., the woman's valuation of alternatives) and thereby encourage contraceptive effort. 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.
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.g., the effect of policy restrictions on abortion levels),(7) but other results have been less conclusive (e.g., the effect of AFDC benefits on birthrates). (8) A number of careful reviews of the literature are available. (9) For brevity Brevity
of short life. [Br. Lit.: I Henry IV]
symbolic of transitoriness of life. [Art: Hall, 54]
cherry orchards where fruit was briefly sold; symbolic of transience. , we focus on two studies (by Blank and colleagues (10) and by Jackson and Klerman (11)) that have addressed methodological issues from previous research, plus a few others that address economic hypotheses.
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 Regression equation
An equation that describes the average relationship between a dependent variable and a set of explanatory variables. . 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 This article is not about "dummy variables" as that term is usually understood in mathematics. See free variables and bound variables.
In regression analysis, a dummy variable controls for unobserved heterogeneity (fixed effects). They also showed that both parental involvement and funding restrictions had negative but statistically nonsignificant non·sig·nif·i·cant
1. Not significant.
2. Having, producing, or being a value obtained from a statistical test that lies within the limits for being of random occurrence. 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. (12) However, other studies found that both types of restrictions significantly reduced the incidence of abortion among minors. (13)
These fixed-effects studies have had more uniform results in other areas: 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 Noun 1. per capita income - the total national income divided by the number of people in the nation
income - the financial gain (earned or unearned) accruing over a given period of time .
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 1994 cross sectional sec·tion·al
1. Of, relating to, or characteristic of a particular district.
2. Composed of or divided into component sections.
n. 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. (15) As in most fertility analyses, the study found a significant negative relationship between women's wages and fertility; unexpectedly, however, property income also had negative effects. 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 birth·rate or birth rate
The ratio of total live births to total population in a specified community or area over a specified period of time, often expressed as the number of live births per 1,000 of the population per year. 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. (16) However, evidence regarding the fertility effects of Medicaid funding restrictions has been mixed. (17)
Data and Variables
We employ an extensive collection of state-level data covering the period 1978-1988. Detailed descriptions of the data and their sources appear in the appendix (page 59). 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 micro-level 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.g., the effects of Medicaid restrictions only among poor women). 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. (18) Obtaining accurate data on abortions is more problematic. The best available information comes from The Alan Guttmacher Alan Frank Guttmacher (1898-1974) was an American physician.
He served as president of Planned Parenthood and vice-president of the American Eugenics Society, founded the Association for the Study of Abortion in 1964, was a member of the Association for Voluntary Institute (AGI (Artificial General Intelligence) A machine intelligence that resembles that of a human being. Considered impossible by many, most artificial intelligence (AI) research, projects and products deal with specific applications such as industrial robots, playing chess, ), which regularly surveyed abortion providers through the 1970s and 1980s.'9 (However, provider information was not collected for 1983, 1986, 1989 or 1990.) 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. According to according to
1. As stated or indicated by; on the authority of: according to historians.
2. In keeping with: according to instructions.
3. the Centers for Disease Control and Prevention Centers for Disease Control and Prevention (CDC), agency of the U.S. Public Health Service since 1973, with headquarters in Atlanta; it was established in 1946 as the Communicable Disease Center. , which also collects state-level abortion data, the proportion of abortions obtained out of state declined from 44% in 1972 to less than 10% after 1980.20 However, the low proportion in later years masks considerable variation across states. For example, AGI estimates that in 1985, nonresidents accounted for roughly half of the abortions performed in North Dakota North Dakota, state in the N central United States. It is bordered by Minnesota, across the Red River of the North (E), South Dakota (S), Montana (W), and the Canadian provinces of Saskatchewan and Manitoba (N). and the District of Columbia District of Columbia, federal district (2000 pop. 572,059, a 5.7% decrease in population since the 1990 census), 69 sq mi (179 sq km), on the east bank of the Potomac River, coextensive with the city of Washington, D.C. (the capital of the United States). but fewer than 1% of those performed in California. (21)
The AGI data by patients' state of residence may contain more error than the figures based on state of occurrence; furthermore, since the procedure used to estimate residence changed in 1978, we excluded state-of-residence data from earlier years. 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 health services Managed care The benefits covered under a health contract . These are the numbers of abortion providers, family planning clinics and obstetrician-gynecologists per 1,000 women aged 15-44; the proportion of women living in counties with each service; the average distance to the nearest in-state and out-of-state abortion provider a`bor´tion pro`vid´er
n. 1. same as abortionist. ; and the proportion of the population enrolled in a health maintenance organization (HMO HMO health maintenance organization.
A corporation that is financed by insurance premiums and has member physicians and professional staff who provide curative and preventive medicine within certain financial, ).
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 primary data are calculated from the 1979-1989 March supplements of the Current Population Survey (CPS (1) (Characters Per Second) The measurement of the speed of a serial printer or the speed of a data transfer between hardware devices or over a communications channel. CPS is equivalent to bytes per second. ). (22) Pooling individual-level data from these CPS files, we have averaged property incomes by sex, state and year to form gender-specific, longitudinal estimates of wealth. 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.e., imputations that account for the fact that not all women and men work).
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 [Latin, By the heads or polls.] A term used in the Descent and Distribution of the estate of one who dies without a will. It means to share and share alike according to the number of individuals. total personal income and on average annual manufacturing and retail earinings. (23) An advantage of these measures is that they are representative for all states. (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 endogenous /en·dog·e·nous/ (en-doj´e-nus) produced within or caused by factors within the organism.
1. Originating or produced within an organism, tissue, or cell. 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.
In this article, we use regression analysis In statistics, a mathematical method of modeling the relationships among three or more variables. It is used to predict the value of one variable given the values of the others. For example, a model might estimate sales based on age and gender. 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.e., time and state fixed effects). The second adds interactions of each state dummy variable with a linear time trend. To make the results nationally representative, we have weighted each state's observations by the number of women aged 15-44 in 1980. (We also ran models that omitted the state dummy variables and treated the state-specific controls as random effects Random effects can refer to:
These two models, which account for potential confounding influences of omitted state-specific factors, generate estimates that are robust under a broad set of circumstances. The models may be especially useful in reducing biases among the potentially related health service accessibility and policy variables. Specifically, changes in the availability of health care providers and shifts in policy probably both influence and are influenced by changes in reproductive behavior. However, endogeneity in these variables seems more likely to stem from shifts in long-term rather than short-term conditions. To the extent that the models control for such long-term movements, biases in the service provision and policy variables should be mitigated.
There are disadvantages to this approach. First, these procedures can exacerbate biases associated with measurement error and simultaneity in the explanatory variables. Second, influences of time-invariant observed variables cannot be identified separately from the state dummies. A related issue is that because the analysis involves data for a relatively short time period, it may be difficult to identify the effects of variables that change only gradually within states, such as the population measures. For the regressions including both state dummies and state-time interactions, this difficulty becomes even greater because the model does not easily distinguish the effects of variables that, within states, follow an essentially linear trend, such as the abortion policy measures.
In the first regression for determinants of state abortion rates (Table 2, page 56), the significant positive coefficient for abortion provider access and significant negative coefficients for Medicaid funding restrictions and parental consent or notification laws indicate that abortion demand is negatively associated with the procedure's direct costs. The significant positive coefficient for HMO membership suggests that this variable may also be a proxy for the immediate costs of obtaining an abortion or an abortion referral. Of the other health service measures, access to family planning clinics has a small and marginally significant positive association with abortions (p<.10), while access to an obstetrician-gynecologist has no significant effect.
There is little evidence of effects of income or opportunity cost. Neither the gender-specific economic variables, AFDC benefits nor Medicaid coverage has a significant effect on the abortion rate. Among the remaining control variables, the proportions of blacks and women aged 35-44 have significant effects in the anticipated direction. Unexpectedly, however, the presence of a Republican governor is associated with a significant increase in the abortion rate.
The results for the second model indicate that the added interactions of state dummies and linear time trends are jointly significant. Nevertheless, several results are consistent with those of the first model. The coefficient for accessibility to abortion providers remains positive and significant, confirming that the direct cost of abortion services, as measured by proximity to providers, affects the incidence of abortions. The models are likewise consistent in generating nonsignificant results for the economic variables. Although this partly reflects imprecision im·pre·cise
impre·cisely adv. in the estimates, it also reflects some genuinely small effects. A final consistent result, and a puzzling one, is the apparent positive effect of Republican governors on abortion rates. We can offer no explanation for this result beyond suggesting that it may reflect that other conditions in states with Republican governors indirectly influence abortion, such as stricter eligibility and work requirements for welfare or increased incarceration Confinement in a jail or prison; imprisonment.
Police officers and other law enforcement officers are authorized by federal, state, and local lawmakers to arrest and confine persons suspected of crimes. The judicial system is authorized to confine persons convicted of crimes. rat es for young men. (*)
Some differences in the two models' results indicate that a number of variables are sensitive to the inclusion of state-time controls for unobserved heterogeneity. The effect of the proportion of women aged 15-19 becomes significant when state-time interactions are included. The effects of access to obstetrician-gynecologists, congressional voting records and Medicaid generosity become marginally significant, although for Medicaid generosity, the effect is in the opposite direction of what would be expected. As anticipated, the effect of parental consent or notification laws loses significance.
In the analysis showing effects on birthrates, three consistent results appear. First, the effect of obstetrician-gynecologist availability is significant (although only marginally so in the second regression) and negative, which suggests that the effects of contraceptive cost captured by this variable dominate those of delivery costs. Second, several economic and policy-related variables are positively associated with birthrates. Women's and men's wages and AFDC benefits have significant positive coefficients in both models; women's property income has a significant positive effect in the first model. Men's property income also has positive coefficients, but the results fall slightly short of attaining statistical significance. The positive coefficients for AFDC benefits and the men's variables are anticipated. However, the positive associations of women's wages are somewhat surprising and suggest that the income effects of wages dominate the effects of opportunity costs. Third, the proportion of teenagers a nd women aged 35-44 are each estimated to have significant negative effects on birthrates in both models. As in the abortion regressions, the state-time interactions are jointly significant (not shown).
For the remaining variables, either the sign of the coefficient changes between models or the measure attains or loses statistical significance. These inconsistencies prevent us from drawing firm conclusions.
Alternative Access Measures
In the following analyses, we modify the access measures, but retain the other explanatory variables. We present only the coefficients for the alternative measures, since those for the other explanatory variables do not change appreciably ap·pre·cia·ble
Possible to estimate, measure, or perceive: appreciable changes in temperature. See Synonyms at perceptible. across the respecifications.
Table 3 shows the results of analyses using alternative measures of access to health services. For the first set of regressions, all measures of service access except the proportion of women living in counties with an abortion provider are excluded. The estimated effects of provider access on both abortion rates and birthrates are consistent with those shown in Table 2.
In the next set of regressions, the variables describing the proportions of women living in counties with abortion providers, family planning clinics and obstetrician-gynecologists are replaced with logarithms of the statewide numbers of these providers per 1,000 women. The statewide counts may capture problems of lines and waiting at facilities more accurately than the original measures do. However, given the increasing geographic isolation and urban concentration over the 1980s of some types of facilities, especially abortion clinics, the statewide count variables may not adequately reflect physical proximity.
As in Table 2, the results in the second panel of Table 3 show that abortion provider access has a significant positive effect on abortion rates. In contrast to our earlier results, however, access to family planning clinics and to obstetrician-gynecologists now have no significant effect in either model, and the magnitude of the coefficients for HMO membership changes somewhat. Two substantial changes are evident in the birthrate regressions. Abortion provider access is now estimated to have a small and nonsignificant effect in each model, while access to family planning clinics is estimated to have a significant negative association with birthrates.
The next regressions examine the effects of the distance to the nearest in-state and out-of-state providers. (Regressions that included either the in-state measure alone or both measures plus the other health service variables were also run; the reported results are not sensitive to either respecification.) These variables represent refined measures of access for women who live in counties without an abortion provider. Consistent with our previous findings, these results show that as distance to an abortion provider (in-state or out-of-state) increases, the abortion rate declines significantly. These measures have no statistically significant effects on birthrates.
In the final set of regressions in Table 3, we replace the variable for the proportion of women living in counties with any abortion provider with variables representing the proportions in counties with small, medium and large facilities (defined as those with annual caseloads of fewer than 25 abortions, 25--400 abortions and more than 400 abortions, respectively). By doing this, we can examine the extent of endogeneity bias in the abortion access results. (Specifically, smaller facilities, which presumably pre·sum·a·ble
That can be presumed or taken for granted; reasonable as a supposition: presumable causes of the disaster. have lower fixed operating costs operating costs npl → gastos mpl operacionales , are going to be more sensitive to short-term shifts in abortion demand than their larger counterparts.) The estimates, which indicate that the access results in the longitudinal models are driven primarily by large facilities, provide evidence that our findings reflect the effects of exogenous Exogenous
Describes facts outside the control of the firm. Converse of endogenous. variation. These measures generally have no statistically significant effects on birthrates.
Alternative Economic Measures
As with the access measures, we conducted analyses based on alternative sets of economic variables; Table 4 (page 58) shows the results. For the first set of regressions, gender-specific unemployment rates replace the CPS wage measures. Because the unemployment rates are based on representative state-level surveys, they provide a check on whether the wage results come about because of possible problems with representativeness in the CPS data. The unemployment variables also measure an alternative dimension of labor-market opportunities.
In the abortion regressions, the results confirm our earlier findings that women's wages have no significant effects. However, whereas Table 2 showed positive but nonsignificant effects of men's wages, the coefficient in the first model in Table 4 is negative and significant, implying a positive effect of men's wages on abortions. (While this result runs counter to the predictions of most economic models, it conforms with some recent game theoretic results. (24)) As for birthrates, assuming that wages are higher when employment is high and vice versa VICE VERSA. On the contrary; on opposite sides. , the estimates support our earlier findings of a positive association between both women's and men's wages and birthrates.
For the next set of regressions, we substituted measures of annual earnings in the retail and manufacturing sectors for the wage variables for women and men, respectively. Like the unemployment measures, the sector-specific earnings variables are representative at the state level and may better capture both wage and employment opportunities. However, they may only roughly approximate gender-specific opportunities. Both models indicate that retail earnings have a strong positive effect on abortion rates, while manufacturing earnings have no significant effect. Assuming that retail and manufacturing earnings are suitable proxies for women's and men's salaries, the results suggest that the abortion rate is influenced more by effects associated with either the immediate affordability of abortions or women's opportunity costs than by the standard income effects (long-term resources available for childrearing).
Large effects of opportunity costs, however, seem to be ruled out by estimates indicating strong positive effects of retail earnings on birthrates; these results support our earlier findings regarding the positive effects of women's wages. The findings for manufacturing earnings support our earlier results for men's wages, in that the coefficients are both positive, but they differ in that only the coefficient for the second model attains statistical significance.
In the last set of regressions in Table 4, we have replaced the gender-specific property income variables with a single measure of total per capita personal income. Because we feel that the total income variable is problematic, this exercise is performed mostly for comparability with previous research. As in the results reported by Blank and colleagues, (25) per capita income has a strong, positive association with abortion rates.
Total per capita income also has a large and significantly positive effect on birthrates in both models. The pattern of results is consistent with the income variable, capturing the effects of immediate affordability for abortions and either immediate affordability of obstetric services or long-term affordability of births. Interestingly, the respecification leads to a negative and significant estimate for women's wages m the abortion model with only state dummies, a result that accords with the positive effects found for births.
Alternative Dependent Variables
As a final sensitivity analysis, we examined alternative regressions in which the dependent variable was the natural logarithm Natural logarithm
Logarithm to the base e (approximately 2.7183). of the sum of the abortion rate and the birthrate (the approximate pregnancy rate); the number of abortions by state of occurrence; and the proportion of pregnancies that end in abortion. For brevity, detailed results from these regressions are not reported here, but are available upon request from the authors. Although some changes occurred across specifications, the results for the pregnancy models are mostly similar to those reported here for births; the few noticeable differences can be traced to differences in results for abortion rates and birthrates. The results for the other two outcomes generally conform with our estimates for abortions by state of residence.
For the period 1988--1992, AGI documented substantial declines in both the incidence and the availability of abortions in the United States. (26) Nationwide, the abortion rate fell by 5%, from 27.3 abortions per 1,000 women of reproductive age to 25.9 per 1,000. At the same time, the proportion of women living in counties with an abortion provider fell from 71% to 69%, and the number of providers per 100,000 women fell from 4.4 to 4.0. (*) Our results, which consistently indicate that decreased access to providers leads to lower rates of abortion, conform with the broad directions of these trends. They also can be used to determine how much of the decline in the incidence of abortion was directly attributable to reductions in access.
The dependent variables in our models are expressed as logarithms. Accordingly, coefficients for the variables expressed as levels indicate the estimated percentage change of the abortion rate or birthrate due to a unit change in the independent variable. Coefficients for variables expressed as logarithms indicate the percentage change in the dependent variable due to a percentage change in the independent variable.
Thus, given the coefficient in the second model in Table 2 for the proportion of women living in counties with an abortion provider (.587), the two-point drop in this measure between 1988 and 1992 reduced the abortion rate by an estimated 1.2%, to 27.0 abortions per 1,000. Similarly, the 9% decline in the number of providers per 100,000 women, applied to the coefficient for this variable in the second column of Table 3 (.170), suggests that the decline in accessibility reduced the abortion rate by 1.5%, to 26.9 per 1,000. Hence, our results indicate that decreased access accounted for roughly 24--30% of the 5% decline in the abortion rate. Our data also indicate that the drop in the proportion of women in their late teens accounts for most of the remaining decline. (+)
In addition, the regression results indicate that the availability of reproductive health services affects fertility. Decreased access to obstetrician-gynecologists is associated with higher birthrates, and more restrictive abortion policies and greater access to obstetric and gynecologic gynecologic /gy·ne·co·log·ic/ (gi?ne-) (jin?e-kah-loj´ik) pertaining to the female reproductive tract or to gynecology. services are consistently estimated to have negative effects on abortion rates, although the results are not significant in all specifications.
Our findings suggest that higher wages for women and men and more generous AFDC benefits are associated with increased fertility rates. There is also weak evidence that higher property incomes for women and men are linked to elevated birthrates. The estimated effects of women's wages are a little surprising because they imply that income effects dominate opportunity-cost effects for women's fertility decisions; however, our sensitivity tests indicated that the results for women's wages are robust.
For abortion outcomes, the economic results are much more sensitive to the particular measures employed, and no consistent pattern appears. The AFDC results suggest that the effects of welfare on reproductive behavior have been greatly exaggerated by some in the current policy debate. According to these findings, a 10% cut in AFDC benefits would have reduced the birthrate by 0.45%, implying a reduction of roughly one birth for every 212 women receiving AFDC. (++)
Because we have presented estimates of abortion and birth models in parallel, the results can be used to infer whether changes in abortions and births reflect changes in contraceptive effort. For instance, the finding that higher wages increase birthrates but do not significantly affect abortion rates suggests that when women's economic conditions improve, their contraceptive effort declines. Similarly, in the models including interactions between state and time, a change in contraceptive effort resulting from access to abortion can be inferred from the results indicating that access increases abortion rates but does not significantly lower birthrates.
Several implications for public policy emerge from our results. The consistent findings regarding the negative effects of obstetrician-gynecologist availability on birthrates suggest that convenient access to prescription contraceptives is an important determinant determinant, a polynomial expression that is inherent in the entries of a square matrix. The size n of the square matrix, as determined from the number of entries in any row or column, is called the order of the determinant. of reproductive behavior. This interpretation receives modest support from weaker evidence indicating that obstetrician-gynecologist availability may also reduce the incidence of abortions.
Our results also indicate that policies that either expressly or indirectly reduce women's access to abortion services decrease their use of the procedure. The Supreme Court has generally held regulations to be invalid if they place substantial obstacles in the path of women seeking abortions prior to fetal viability. The contentious issue of whether policies go too far in restricting access is being resolved by the Court under its standard of "undue burden." While the Court has applied its test one restriction at a time, our findings of independent effects from several aspects of availability suggest another approach--namely, that the standard be broadened to consider the entire constellation Constellation, ship
Constellation (kŏnstĭlā`shən), U.S. frigate, launched in 1797. It was named by President Washington for the constellation of 15 stars in the U.S. flag of that time. of restrictions and factors affecting abortion access within states.
Stephen Matthews Stephen Matthews, a linguist and typologist, specialises in language typology, syntax and semantics. His current interests include the word order typology of Chinese; the grammar of Chinese dialects, notably Cantonese, Chaozhou and other Minnan dialects; language contact and is a research associate, Population Research Institute, and Mark Wilhelm is a research associate, Population Research Institute, and an assistant professor of economics, The Pennsylvania State University Pennsylvania State University, main campus at University Park, State College; land-grant and state supported; coeducational; chartered 1855, opened 1859 as Farmers' High School. , University Park, Penn.; David Ribar is an assistant professor of economics, The George Washington University Washington, D.C. An earlier version of this article was presented at the annual meeting of the Population Association of America, San Francisco San Francisco (săn frănsĭs`kō), city (1990 pop. 723,959), coextensive with San Francisco co., W Calif., on the tip of a peninsula between the Pacific Ocean and San Francisco Bay, which are connected by the strait known as the Golden , Apr. 6-8, 1995. The authors gratefully acknowledge research support from the National Institute of Child Health and Human Development (NICHD NICHD National Institute of Child Health and Human Development. ) under grant 1-P30-HD28263-01. David Ribar also acknowledges support from the William T. Grant Foundation and NICHD under grant 1-R01-HD30711-01. The authors thank Lynne Ackerman, Denise Duffy, Daniel Henry HeeSung Kim, Julie Kraut kraut
2. often Kraut Offensive Slang Used as a disparaging term for a German.
[German; see sauerkraut.]
Noun 1. , Gerald Mills and Jeanne Spicer for programming and research assistance; Robert Moffitt and officials at The Alan Guttmacher Institute, National Abortion Federation, National Abortion Rights Action League, National Committee for a Human Life Amendment, National Right to Life Committee and United States Catholic Conference for providing various unpublished data; and Stanley Henshaw, Shelly Lundberg, Mark Roberts
Mark Roberts (born December 12, 1964 in Liverpool, England) is a famous British streaker who has run naked during several , David Shapiro David Shapiro may refer to:
(*.) Geographic heterogeneity in the effective costs of reproductive health services seems likely to increase in view of a series of Supreme Court decisions increasing states' authority to regulate abortion and the government's general authority to control procedures within publicly funded family planning clinics. See: Webster v. Reproductive Health Services In Webster v. Reproductive Health Services, 492 U.S. 490, 109 S. Ct. 3040, 106 L. Ed. 2d 410 (1989), the United States Supreme Court reviewed the constitutionality of several Missouri statutes restricting access to Abortion services and counseling. , 492 U.S. 490 (1989); Hodgson v. Minnesota Hodgson v. Minnesota, 497 U.S. 417 (1990), was a United States Supreme Court abortion rights case that dealt with according to which a state law may require notification of both parents before a minor can obtain an abortion, as long as a judicial alternative is present. , 497 U.S. 417 (1990); Ohio v. Center for Reproductive Health, 497 U.S. 502 (1990); Planned Parenthood Planned Parenthood
A service mark used for an organization that provides family planning services. of Southeastern Pennsylvania v. Casey, 112 S. Ct. 1759 (1991); and Rust v. Sullivan Rust v. Sullivan, 500 U.S. 173 (1991), was a United States Supreme Court case decided in 1991. The case concerned the legality and constitutionality of Department of Health and Human Services regulations on the use of funds spent by the U.S. , 59 U.S. L.W. 4451 (May 21, 1991).
(*.) This factor remained significant in models including alternative slate policy, health service access and economic controls. In regressions disaggregated Broken up into parts. over time, the effect was significantly positive in all periods and became stronger in later periods, results that run counter to the evolution of the Republican abortion platform. Blank and colleagues also obtained counterintuitive coun·ter·in·tu·i·tive
Contrary to what intuition or common sense would indicate: "Scientists made clear what may at first seem counterintuitive, that the capacity to be pleasant toward a fellow creature is ... results for some party affiliation variables (see: reference 2).
(*.) AGI reported that 70% of women lived in counties with an abortion provider in 1992; we believe that this figure, which is based on the number of women recorded in the 1990 census rather than the 1992 intercensal estimate, is slightly high.
(+.) AGI attributed a smaller role to age composition; the difference in the proportion of teenagers between the 1990 census and the 1992 intercensal estimates accounts for much of the difference between AGI's conclusion and ours.
(++.) In 1988, a 0.45% drop in the birthrate would have meant 0.3 fewer births per 1,000 women. That year, 58.1 million women were of reproductive age and 3.7 million families received AFDC. Thus, approximately 6.37% (or 63.7 per 1,000) women of reproductive age were receiving AFDC. Assuming that the reduction in births occurred only among these women, there would have been 0.3 fewer births per 63.7 AFDC recipients of reproductive age, or one birth fewer per 212 AFDC recipients.
(1.) C. Jackson and J. Klerman, "Welfare, Abortion and Teenage Fertility," Rand Rand
See Table at currency.
[Afrikaans, after(Witwaters)rand. , Santa Monica, Calif., 1994.
(2.) R. Blank, C. George and R. London, "State Abortion Rates: The Impact of Policies, Providers, Politics, Demographics The attributes of people in a particular geographic area. Used for marketing purposes, population, ethnic origins, religion, spoken language, income and age range are examples of demographic data. , and Economic Environment," Northwestern University Northwestern University, mainly at Evanston, Ill.; coeducational; chartered 1851, opened 1855 by Methodists. In 1873 it absorbed Evanston College for Ladies. , Evanston, Ill., 1994; T. Deyak and V. Smith, "The Economic Value of Statute Reform: The Case of Liberalized Abortion," Journal of Political Economy, 84:83-99, 1976; C. Garbacz, "Abortion Demand," Population Research and Policy Review, 9:151-160,1990; S. Gohmann and R. Ohsfeldt, "Effects of Price and Availability on Abortion Demand," Contemporary Policy Issues, 11:42-55,1993; D. Haas-Wilson, "The Economic Impact of State Restrictions on Abortion: Parental Consent and Notification Laws and Medicaid Funding Restrictions," Journal of Policy Analysis and Management, 12:498-511, 1993; D. Haas-Wilson, "The Impact of State Abortion Restrictions on Minors' Demand for Abortions," Journal of Human Resources The fancy word for "people." The human resources department within an organization, years ago known as the "personnel department," manages the administrative aspects of the employees. , 31:140-158,1996; T. Joyce and R. Kaestner, "The Effect of Parental involvement Laws on Pregnancy Resolution," paper presented at the annual mee ting ting
A single light metallic sound, as of a small bell.
intr.v. tinged , ting·ing, tings
To give forth a light metallic sound. of the Population Association of America, San Francisco, Apr. 6-8, 1995; A. Leibowitz, M. Eisen and W. Chow, "An Economic Model of Teenage Pregnancy teenage pregnancy Adolescent pregnancy, teen pregnancy Social medicine Pregnancy by a ♀, age 13 to 19; TP is usually understood to occur in a ♀ who has not completed her core education–secondary school, has few or no marketable skills, is Decision-Making," Demography demography (dĭmŏg`rəfē), science of human population. Demography represents a fundamental approach to the understanding of human society. , 23:67-77, 1986; P. Levine, A. Trainor and D. Zimmerman, "The Effect of Medicaid Abortion Funding Restrictions on Abortions, Pregnancies, and Births," National Bureau of Economic Research, Cambridge, Mass., 1995; S. Lundberg and R.D. Plotnick, "Effects of State Welfare, Abortion and Family Planning Policies on Premarital Childbearing Among White Adolescents," Family Planning Perspectives, 22:246-251 & 275, 1990; M. Medoff, "An Economic Analysis of the Demand for Abortion," Economic Inquiry, 36:353-359, 1988; R. Ohsfeldt and S. Gohmann, "Do Parental Involvement Laws Reduce Adolescent Abortion Rates?" Contemporary Economic Policy, 12:65-76, 1994; and J. Trussell et al., "The Impact of Restricting Medicaid Funding for Abortion," Family Planning Perspectives, 12:120-130, 1980.
(3.) S. Gohmann and R. Ohsfeldt, 1993, op. cit. (see reference 2); P. Levine, A. Trainor and T. Zimmerman, 1995, op. cit. (see reference 2); and S. Lundberg and R. D. Plotnick, 1990, op. cit. (see reference 2).
(4.) M. Montgomery and J. Trussell, "Models of Marital Status marital status,
n the legal standing of a person in regard to his or her marriage state. and Childbearing," in O. Ashenfelter and R. Layard, eds., Handbook of Labor Economics, North Holland, Amsterdam, 1986.
(5.) R. Willis, "A New Approach to the Economic Theory of Fertility Behavior," Journal of Political Economy, Vol. 81, Supplement, 1973, pp. 14-64; and G. Becker, A Treatise A scholarly legal publication containing all the law relating to a particular area, such as Criminal Law or Land-Use Control.
Lawyers commonly use treatises in order to review the law and update their knowledge of pertinent case decisions and statutes. on the Family, Harvard University Press The Harvard University Press is a publishing house, a division of Harvard University, that is highly respected in academic publishing. It was established on January 13, 1913. In 2005, it published 220 new titles. , Cambridge, Mass., 1981.
(6.) G. Becker and H. Lewis, "On the interaction Between the Quantity and Quality of Children," Journal of Political Economy, Vol. 81, Supplement, 1973, pp. 279-288; G. Becker, 1981, op. cit. (see reference 5); and W. Bryant, The Economic Organization of the Household, Cambridge University Press Cambridge University Press (known colloquially as CUP) is a publisher given a Royal Charter by Henry VIII in 1534, and one of the two privileged presses (the other being Oxford University Press). , New York New York, state, United States
New York, Middle Atlantic state of the United States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of , 1990.
(7.) V. Cartoof and L. Klerman, "Parental Consent for Abortion: Impact of the Massachusetts Law," American Journal of Public Health, 76:397-400,1986; C. Garbacz, 1990, op. cit. (see reference 2); D. Haas-Wilson, 1993, op. cit. (see reference 2); R. Ohsfeldt and S. Gohmann, 1994, op. cit. (see reference 2);J. Rogers et al., "Impact of the Minnesota Parental Notification Law on Abortion and Birth," American Journal of Public Health, 81:294-298, 1991; and J. Trussell et al., 1980, op. cit. (see reference 2).
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(10.) R. Blank, C. George and R London, 1994, op. cit. (see reference 2).
(11.) C. Jackson and J. Klerman, 1994, op. cit. (see reference 1).
(12.) P. Levine, A. Trainor and D. Zimmerman, 1995, op. cit. (see reference 2).
(13.) R. Blank, C. George and R. London, 1994, op. cit. (see reference 2); and D. Haas-Wilson, 1996, op. cit. (see reference 2).
(14.) S. Gohmann and R. Ohsfeldt, 1993, op. cit. (see reference 2).
(15.) T.P. Schultz, "Marital Status and Fertility in the United States," Journal of Human Resources, 29:637-669, 1994.
(16.) C. Jackson and J. Klerman, 1994, op. cit. (see reference 1); and T. Kane and D. Staiger, "Teen Motherhood and Abortion Access," Harvard University Harvard University, mainly at Cambridge, Mass., including Harvard College, the oldest American college. Harvard College
Harvard College, originally for men, was founded in 1636 with a grant from the General Court of the Massachusetts Bay Colony. , Cambridge, Mass., 1994.
(17.) J. Currie cur·rie
Variant of curry2. et al., "Restrictions on Medicaid Funding of Abortion," Journal of Human Resources, 31:159-188, 1996; C. Jackson and J. Klerman, 1994, op. cit. (see reference 1); T. Kane and D. Staiger, 1994, op. cit. (see reference 16); and P. Levine, A. Trainor and D. Zimmerman, 1995, op. cit. (see reference 2).
(18.) U. S. Bureau of Health Professions, Area Resource File, National Technical Information Service, Springfield, Va., 1991 and 1993.
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(20.) L. Koonin et al., "Abortion Surveillance-United States, 1989," Morbidity and Mortality Weekly Report Morbidity and Mortality Weekly Report (MMWR) is a weekly epidemiological digest for the United States published by the Centers for Disease Control and Prevention. The 5 June 1981 issue of the MMWR published the cases of five men in what turned out to be the first report of AIDS. , 41:1, 1992.
(21.) S. K. Henshaw, J. D. Forrest and J. Van Vort, "Abortion Services in the United States, 1985," Family Planning Perspectives, 19:63-70, 1987.
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Census Bureau , Current Population Survey: Annual Demographic Files (March), Washington, D.C., 1979-1989.
(23.) U.S. Bureau of Labor Statistics Bureau of Labor Statistics (BLS)
A research agency of the U.S. Department of Labor; it compiles statistics on hours of work, average hourly earnings, employment and unemployment, consumer prices and many other variables. , Geographic Profile of Employment and Unemployment, U.S. Government Printing Office, Washington, D.C., 1978-1988; and U.S. Bureau of Economic Analysis, Regional Economic Information System, U.S. Department of Commerce, Washington, D.C., 1992.
(24.) C. Akerlof, J. Yellen and M. Katz, "An Analysis of Out-of-Wedlock Childbearing in the United States," University of California, Berkeley The University of California, Berkeley is a public research university located in Berkeley, California, United States. Commonly referred to as UC Berkeley, Berkeley and Cal , 1994; and R. Willis, "A Theory of Out-of-Wedlock Childbearing," University of Michigan (body, education) University of Michigan - A large cosmopolitan university in the Midwest USA. Over 50000 students are enrolled at the University of Michigan's three campuses. The students come from 50 states and over 100 foreign countries. , Ann Arbor Ann Arbor, city (1990 pop. 109,592), seat of Washtenaw co., S Mich., on the Huron River; inc. 1851. It is a research and educational center, with a large number of government and industrial research and development firms, many in high-technology fields such as , 1995.
(25.) R. Blank, C. George and R. London, 1994, op. cit. (see reference 2).
(26.) S. K. Henshaw and J. Van Vort, "Abortion Services in the United States, 1991 and 1992," Family Planning Perspectives, 26:100-106 & 112,1994.
Table 1 Variables used in regression analyses of factors influencing abortion rates and birthrates, and nationally representative means (and standard deviations) Outcome Variable Mean Abortion rate (by state 28.12 (10.54) of residence) Birthrate 66.58 (7.93) Service accessibility Variable Mean Proportion of women in 0.72 (0.22) counties with abortion providers Proportion of women in 0.53 (0.27) counties with small providers (+) Proportion of women in 0.62 (0.25) counties with medium providers (#) Proportion of women in 0.57 (0.22) counties with large providers (ss) No. of abortion providers 0.05 (0.03) per 1,000 women Avg. miles to nearest 0.14 (0.15) in-state provider (hundreds) (++) Avg. miles to nearest 0.94 (0.68) out-of-state provider (hundreds) (++) Proportion of women in 0.92 (0.10) counties with family planning clinics No. of family planning 0.10 (0.05) clinics per 1,000 women Proportion of women in counties with obstetrician- 0.91 (0.10) gynecologists No. of obstetrician- 0.48 (0.11) gynecologists per 1,000 women Per capita HMO membership 0.07 (0.07) Economic Variable Mean Avg. female property 0.29 (0.12) income (000s of $) Avg. male property 0.36 (0.11) income (000s of $) Avg. selectivity-adjusted 4.44 (1.06) imputed female wage ($) Avg. unadjusted female 7.34 (0.76) wage ($) Avg. selectivity-adjusted 9.38 (1.14) imputed male wage ($) Avg. unadjusted male wage 10.41 (0.91) ($) Avg. per capita total 14.53 (2.05) personal income (000s of $) Avg. annual retail 12.91 (1.36) earnings (000s of $) Avg. annual manufacturing 28.30 (4.01) earnings (000s of $) Female unemployment rate 0.07 (0.02) Male unemployment rate 0.07 (0.02) State policy Variable Mean Medicaid abortion funding 0.52 (0.48) restrictions (##) Parental consent or 0.11 (0.31) notification law (##) Maximum monthly AFDC 474.08 (182.87) benefits for family of four ($) Avg. monthly Medicaid 63.69 (18.07) benefits per AFDC recipient ($) Political and attitudinal Variable Mean Republican governor (##) 0.44 (0.50) Antiabortion voting index for state's congressional 0.47 (0.23) delegation (ssss) Antiabortion attitude 4.21 (0.84) index (+)(#) Demographic and other Variable Mean Proportion of population 0.12 (0.08) black Women 15-19 as proportion 0.18 (0.02) of women of reproductive age Women 35-44 as proportion 0.27 (0.02) of women of reproductive age No. of rapes per 100,000 35.44 (12.33) individuals (+)Providers that perform fewer than 25 abortions per year. (#)providers that perform 25-400 abortions per year. (ss)Providers that perform more than 400 abortions per year. (++)Excluding Alaska and Hawaii. (##)When states with this variable in effect are coded as 1.0. (ssss)When pro-choice votes are coded as 1.0. (+)(#)On a scale of 0-12, with 0 indicating approval of each of six circumstances for abortion and 12 indicating approval for none. Notes: In this and subsequent tables, unless noted otherwise, statistics are based on 1978-1982, 1984-1985 and 1987-1988 data from the 50 states and the District of Columbia; data are weighted by the number of women aged 15-44 in 1980 in each state; and percentages and rates are based on women aged 15-44. For a detailed description of the data and sources, see the appendix (page 59). Table 2 Ordinary least-squares regression results (and standard errors) indicating effects of selected variables on state abortion rates and birthrates Service accessibility Variable Abortion rate Fixed state- Adj. for state- time effects time interaction % of women in counties with abortion providers 0.329 (**)(0.129) 0.587 (***)(0.150) % of women in counties with family planning clinics 0.120 (*)(0.066) 0.120(0.091) % of women in counties with obstetrician- gynecologists -0.372(0.255) -0.523 (*)(0.302) Per capita HMO membership 0.698 (***)(0.218) -0.180(0.418) Variable Birthrate Fixed state- Adj. for state- time effects time interaction % of women in counties with abortion providers -0.089 (**)(0.044) 0.021(0.035) % of women in counties with family planning clinics 0.004(0.022) 0.008(0.021) % of women in counties with obstetrician- gynecologists -0.814 (***)(0.087) -0.136 (*)(0.071) Per capita HMO membership 0.182 (**)(0.074) 0.100(0.099) Economic Variable Abortion rate Fixed state- Adj. for state- time effects time interaction Log of female property income -0.007(0.013) -0.019(0.012) Log of male property income -0.009(0.016) -0.011(0.015) Log of female wage -0.032(0.078) 0.123(0.080) Log of male wage 0.166(0.103) 0.083(0.105) Variable Birthrate Fixed state- Adj. for state- time effects time interaction Log of female property income 0.009 (**)(0.004) 0.001(0.003) Log of male property income 0.009(0.006) 0.005(0.003) Log of female wage 0.152 (***)(0.027) 0.080 (***)(0.019) Log of male wage 0.178 (***)(0.035) 0.053 (**)(0.025) State policy Variable Abortion rate Fixed state- Adj. for state- time effects time interaction Medicaid abortion funding restrictions -0.056 (***)(0.020) -0.029(0.022) Parental consent or notification law -0.032 (**)(0.016) -0.012(0.021) Log of AFDC benefits -0.037(0.051) 0.025(0.069) Log of Medicaid benefits -0.016(0.024) 0.049 (*)(0.029) Variable Birthrate Fixed state- Adj. for state- time effects time interaction Medicaid abortion funding restrictions -0.019 (***)(0.007) -0.005(0.005) Parental consent or notification law -0.021 (***)(0.006) 0.008 (*)(0.005) Log of AFDC benefits 0.124 (***)(0.017) 0.045 (***)(0.016) Log of Medicaid benefits -0.022 (***)(0.008) 0.025 (***)(0.007) Political and attitudinal Variable Abortion rate Fixed state- Adj. for state- time effects time interaction Republican governor 0.051 (***)(0.009) 0.029 (***)(0.010) Antiabortion congression al voting index -0.029(0.034) -0.064 (*)(0.035) Antiabortion attitude index 0.008(0.010) 0.011(0.010) Variable Birthrate Fixed state- Adj. for state- time effects time interaction Republican governor 0.005(0.003) -0.001(0.002) Antiabortion congression al voting index -0.014(0.012) -0.009(0.008) Antiabortion attitude index 0.001(0.003) -0.002(0.002) Demographic and other Variable Abortion rate Fixed state- Adj. for state- time effects time interaction % of population black 2.552 (**)(1.161) -9.734(6.149) % of women 15-19 1.998(1.334) 3.928 (**)(1.858) % of women 35-44 -3.853 (***)(0.951) -0.925(2.903) Log of rape rate -0.008(0.033) 0.025 (0.048) [R.sup.2] 0.974 0.984 Variable Birthrate Fixed state- Adj. for state- time effects time interaction % of population black 1.163 (***)(0.397) -0.157(1.450) % of women 15-19 -2.667 (***)(0.456) -2.329 (***)(0.438) % of women 35-44 -1.593 (***)(0.325) -3.140 (***)(0.684) Log of rape rate -0.075 (***)(0.011) 0.037 (***)(0.011) [R.sup.2] 0.966 0.990 (*)P<.10. (**)P<.05. (***)P<.01. Notes: In this and subsequent tables, the dependent variables are the natural logarithms of the state-level abortion rate and birthrate. All regressions include year-specific dummy variables. Table 3. Ordinary least-squares regression results (and standard errors) indicating effects of various measures of access to reproductive health services on abortion rates and birthrates Variable Abortion rate Fixed state- time effects Excluding other access measures % of women in counties with abortion providers 0.396 (***) (0.130) Variable Abortion rate Adj. for state- time interaction Excluding other access measures % of women in counties with abortion providers 0.573 (***) (0.150) Variable Birtrate Fixed state- time effects Excluding other access measures % of women in counties with abortion providers -0.098 (**) (0.9 Variable Birtrate Adj. for state- time intertctin Excluding other access measures % of women in counties with abortion providers 0.023 (0.035) "Per woman" access Variable Abortion rate Fixed state- time effects Log of abortion providers per 1,000 women 0.131 (***) (0.035) Log of family planning clinics per 1,000 women -0.007 (0.120) Log of obsterician-gynecologists per 1,000 women -0.194 (0.120) Per capita HMO membership 0.534 (**) (0.225) Variable Abortion rate Adj. for state- time interaction Log of abortion providers per 1,000 women 0.170 (***) (0.037) Log of family planning clinics per 1,000 women -0.015 (0.44) Log of obsterician-gynecologists per 1,000 women -0.207 (0.148) Per capita HMO membership -0.541 (0.427) Variable Birtrate Fixed state- time effects Log of abortion providers per 1,000 women 0.010 (0.013) Log of family planning clinics per 1,000 women -0.042 (***) (0.007) Log of obsterician-gynecologists per 1,000 women -0.189 (***) (0.043) Per capita HMO membership 0.202 (***) (0.080) Variable Birtrate Adj. for state- time intertctin Log of abortion providers per 1,000 women 0.0003 (0.009) Log of family planning clinics per 1,000 women -0.037 (***) 0.010) Log of obsterician-gynecologists per 1,000 women 0.041 (0.034) Per capita HMO membership 0.052 (0.099) Abortion provider distance (+) Variable Abortion rate Fixed state- time effects Avg. miles to nearest in-state provider -0.217 (***) (0.081) Avg. mites to nearest out-of-state provider -0.155 (***) (0.070) Variable Abortion rate Adj. for state- time interaction Avg. miles to nearest in-state provider -0.136 (*) (0.079) Avg. mites to nearest out-of-state provider -0.270 (***) (0.083) Variable Birtrate Fixed state- time effects Avg. miles to nearest in-state provider -0.045 (0.031) Avg. mites to nearest out-of-state provider 0.015 (0.027) Variable Birtrate Adj. for state- time intertctin Avg. miles to nearest in-state provider -0.010 (0.019) Avg. mites to nearest out-of-state provider -0.008 (0.019) Size of abortion provider Variable Abortion rate Fixed state- time effects % of women in counties with small providers 0.012(0.041) % of women in counties with medium providers 0.032(0.066) % of women in counties with large providers 0.190 (**)(0.087) % of women in counties with family planning clinics 0.142 (**) (0.067) % of women in counties with obstetrician-gynecologists -0.361 (0.256) Per capita HMO membership 0.744 (***) (0.218) Variable Abortion rate Adj. for state- time interaction % of women in counties with small providers 0.045(0.046) % of women in counties with medium providers 0.010(0.069) % of women in counties with large providers 0.157 (*) (0.090) % of women in counties with family planning clinics 0.124(0.093) % of women in counties with obstetrician-gynecologists -0.549 (*) (0.310) Per capita HMO membership -0.050(0.428) Variable Birtrate Fixed state- time effects % of women in counties with small providers 0.0002 (0.014) % of women in counties with medium providers -0.016(0.022) % of women in counties with large providers 0.035(0.030) % of women in counties with family planning clinics 0.003(0.023) % of women in counties with obstetrician-gynecologists -0.839 (***) (0.088) Per capita HMO membership 0.159 (**) (0.075) Variable Birtrate Adj. for state- time intertctin % of women in counties with small providers -0.020 (*) (0.011) % of women in counties with medium providers 0.017(0.016) % of women in counties with large providers 0.017(0.021) % of women in counties with family planning clinics 0.008(0.021) % of women in counties with obstetrician-gynecologists -0.148 (**) (0.071) Per capita HMO membership 0.092 (0.099) (*)p<.10. (**)p<.05. (***)p<.01. (+)Excluding Alaska and Hawail. Note: All regression also include co-efficients for economic, state policy, politial and attitudinal, demographic and time variable, as in Table 2. Table 4 Ordinary least-squares regression results (and standard errors) indicating effects of various economic measures on abortion rates and birthrates Unemployment Variable Abortion rate Fixed state- time effects Log of female property income -0.012 (0.013) Log of male property income -0.011 (0.016) Female unemployment rate -0.271 (0.575) Male unemployment rate -1.039 (**) (0.476) Variable Abortion rate Adj. for state- time interaction Log of female property income -0.018 (0.012) Log of male property income -0.009 (0.015) Female unemployment rate -0.129 (0.541) Male unemployment rate -0.538 (0.472) Variable Birth rate Fixed state- time effects Log of female property income 0.009 (**) (0.004) Log of male property income 0.012 (**) (0.005) Female unemployment rate -0.819 (***) (0.196) Male unemployment rate -0.379 (**) (0.162) Variable Birth rate Adj. for state- time interaction Log of female property income 0.001 (0.003) Log of male property income 0.006 (*) (0.003) Female unemployment rate -6.333 (***) (0.121) Male unemployment rate -0.093 (0.106) Wages Variable Abortion rate Fixed state- time effects Log of female property income -0.009 (0.013) Log of male property income -0.012 (0.016) Log of average annual retail earnings 0.467 (**) (0.185) Log of average annual manufacturing earnings -0.150 (0.220) Variable Abortion rate Adj. for state- time interaction Log of female property income -0.019 (0.012) Log of male property income -0.012 (0.014) Log of average annual retail earnings 1.002 (***) (0.287) Log of average annual manufacturing earnings -0.065 (0.300) Variable Birth rate Fixed state- time effects Log of female property income (0.012) (***) (0.004) Log of male property income 0.008 (0.005) Log of average annual retail earnings 0.496 (***) (0.059) Log of average annual manufacturing earnings 0.068 (0.069) Variable Birth rate Adj. for state- time interaction Log of female property income 0.001 (0.003) Log of male property income 0.004 (0.003) Log of average annual retail earnings 0.391 (***) (0.063) Log of average annual manufacturing earnings 0.270 (***) (0.066) Income Variable Abortion rate Fixed state- time effects Log of per capita total personal income 0.650 (***) (0.131) Log of female wages -0.170 (**) (0.079) Log of male wages -0.014 (0.105) Variable Abortion rate Adj. for state- time interaction Log of per capita total personal income 0.975 (***) (0.197) Log of female wages -0.009 (0.081) Log of male wages 0.059 (0.102) Variable Birth rate Fixed state- time effects Log of per capita total personal income 0.330 (***) (0.044) Log of female wages 0.100 (***) (0.026) Log of male wages 0.101 (***) (0.035) Variable Birth rate Adj. for state- time interaction Log of per capita total personal income 0.412 (***) (0.042) Log of female wages 0.032 (*) (0.017) Log of male wages 0.050 (**) (0.022) (*)p<.10. (**)p<.05. (***)p<.01. Note: All regressions also include coefficients for provider availability, state policy, political and attitudinal, demographic and other, and time variables, as in Table 2.
Appendix: Data Sources
* Abortion rates. Abortion rates per 1,000 women of reproductive age by state of occurrence and state of residence, 1978--1982, 1984--1985 and 1987--1988, were obtained from S. K. Henshaw and J. Van Vort, 1994 (see: reference 26); and AGI, unpublished data.
* Birthrates. Annual county-level data on number of births were obtained from the Area Resource File (see: reference 18), aggregated to state levels and divided by the number of women of reproductive age.
* Abortion providers. Numbers of providers of various sizes, by county, 1978--1982, 1984--1985 and 1987--1988, were obtained from AGI. These data were combined with data on women of reproductive age to calculate the number of women in counties with each type of provider. The number of providers and number of women in counties with providers were aggregated to state levels and divided by the total number of women of reproductive age to obtain the variables used in the analysis.
* Distance to abortion providers. AGI county-level abortion provider data were combined with distances calculated using the latitude and longitude latitude and longitude
Coordinate system by which the position or location of any place on the Earth's surface can be determined and described. Latitude is a measurement of location north or south of the Equator. coordinates of the population-weighted centroids The following diagrams depict a list of centroids. A centroid of an object in of each U.S. county at the time of the 1980 census. Distances between each pair of centroids were calculated along "great circle arcs." (See: A. Robinson et al., Elements of Cartography cartography: see map.
Art and science of representing a geographic area graphically, usually by means of a map or chart. Political, cultural, or other nongeographic features may be superimposed. , fifth ed., John Wiley John Wiley may refer to:
* Family planning clinics and obstetrician-gynecologists. County-level numbers of clinics in 1975, 1981 and 1983 were obtained from AGI; county-level numbers of nonfederal obstetrician-gynecologists in patient care in 1977--1981, 1983, 1985--1986 and 1988--1989 were obtained from Quality Resource Systems, Fairfax, Va. Quadratic quadratic, mathematical expression of the second degree in one or more unknowns (see polynomial). The general quadratic in one unknown has the form ax2+bx+c, where a, b, and c are constants and x is the variable. interpolation interpolation
In mathematics, estimation of a value between two known data points. A simple example is calculating the mean (see mean, median, and mode) of two population counts made 10 years apart to estimate the population in the fifth year. (rounded to integers and constrained to nonnegative non·neg·a·tive
Of, relating to, or being a quantity that is either positive or zero.
Adj. 1. nonnegative - either positive or zero values) was used to impute impute v. 1) to attach to a person responsibility (and therefore financial liability) for acts or injuries to another, because of a particular relationship, such as mother to child, guardian to ward, employer to employee, or business associates. provider counts for intermediate years and, for clinics, to extrapolate extrapolate - extrapolation data after 1983. Actual and imputed Attributed vicariously.
In the legal sense, the term imputed is used to describe an action, fact, or quality, the knowledge of which is charged to an individual based upon the actions of another for whom the individual is responsible rather than on the individual's data were combined with data on women of reproductive age to calculate the number of women in counties with providers. The number of providers and number of women in counties with providers were aggregated to state levels and divided by the total number of women of reproductive age to obtain the variables used in the analysis.
* Per capita HMO membership. Annual county-level numbers of HMO members were obtained from the Area Resource File (see: reference 18), aggregated to state levels and divided by the total state population.
* Property income. Individual-level interest, dividend, property, and estates and trusts income for women aged 15--44 and men aged 15--54 were obtained from the 1979--1989 March Current Population Survey (CPS) files (see: reference 22). Consistent top-coding was applied across all years, and the top-coded observations were eliminated. Data were aggregated to state and annual levels using the March CPS weights and then deflated de·flate
v. de·flat·ed, de·flat·ing, de·flates
a. To release contained air or gas from.
b. To collapse by releasing contained air or gas.
2. using the personal consumption deflator Deflator
A statistical factor used to convert current dollar purchasing power into inflation-adjusted purchasing power. Enables the comparison of prices while accounting for inflation in two different time periods. (PCD PCD
polycystic disease. ).
* Wages. Individual-level hours and wage- or salary-income data for women aged 15--44 and men aged 15--54 were obtained from the March CPS files. Self-employed workers, farmers, unpaid workers and individuals with missing or inconsistent information were excluded. Consistent top-coding was applied, and the top-coded observations were eliminated. Hourly wages were computed by dividing annual earnings by annual hours and deflating by the PCD. Individuals whose deflated hourly wages were less than 25 cents or more than $250 were excluded. Wage regressions were estimated using a standard two-stage selectivity-correction procedure. In the first stage, individual-level employment probit In probability theory and statistics, the probit function is the inverse cumulative distribution function (CDF), or quantile function associated with the standard normal distribution. models were estimated for women and men separately by state. In the second stage, the logarithms of hourly wages were regressed on the predicted inverse (mathematics) inverse - Given a function, f : D -> C, a function g : C -> D is called a left inverse for f if for all d in D, g (f d) = d and a right inverse if, for all c in C, f (g c) = c and an inverse if both conditions hold. Mill's ratio; on annual dummy variables; on dummy variables for black and other origins; on potential work experience; on experience squared; on years of elementary, secondary and p ostsecondary schooling; and on interactions of experience, secondary schooling and postsecondary schooling with quadratic time trends. Like the probit models, the wage regressions were run separately by state. Results from the regressions were used to predict wages for the entire CPS sample (workers and nonworkers). Predicted wages were aggregated to state levels using the March weights.
* Per capita income and average annual earnings. Annual state-level data on total personal income and on total earnings and employment in the manufacturing and retail sectors were obtained from the U.S. Bureau of Economic Analysis, 1992 (see: reference 23). Personal income data were deflated by the PCD; total earnings were divided by total employment and deflated by the PCD to obtain average earnings.
* Medicaid funding restrictions. States with enforced Medicaid funding restrictions similar to those of the Hyde Amendment were coded 1, and other states were coded 0. States with restrictions for part of the year were assigned a fraction representing the amount of time the restriction was in effect. The data come primarily from J. Merz, "A Review of Abortion Policy: Legality le·gal·i·ty
n. pl. le·gal·i·ties
1. The state or quality of being legal; lawfulness.
2. Adherence to or observance of the law.
3. A requirement enjoined by law. Often used in the plural. , Medicaid Funding, and Parental Involvement, 1967--1994," Rand, Santa Monica, Calif., 1994. Where possible, the data have been reconciled with: D. Bush, "Fertility-Related State Laws Enacted in 1982," Family Planning Perspectives, 15:111--116, 1983; J. Currie et al., 1996 (see: reference 17); R. B. Gold, "Publicly Funded Abortions in FY 1980 and 1981," Family Planning Perspectives, 14:204--207; 1982; R. B. Gold and S. Guardado, "Public Funding Public funding is money given from tax revenue or other governmental sources to an individual, organization, or entity. See also
Any surgical procedure intended to end fertility permanently (see contraception). Such operations remove or interrupt the anatomical pathways through which the cells involved in fertilization travel (see reproductive system). and Abortion Services, 1987," Family Planning Perspectives, 20:228--233, 1988; R. B. Gold and J. Macias, "Public Funding of Contraceptive, Sterilization and Abort ion Services, 1985," Family Planning Perspectives, 18:259--264, 1986; R. B. Gold and B. Nestor, "Public Funding of Contraceptive, Sterilization and Abortion Services, 1983," Family Planning Perspectives, 17:25--30, 1985; and B. Nestor and R. B. Gold, "Public Funding of Contraceptive, Sterilization and Abortion Services, 1982," Family Planning Perspectives, 16:128--133, 1984.
* Parental notification and consent laws. States with enforced parental notification or consent laws were coded 1, and other states were coded 0. States with restrictions for part of the year were assigned a fraction representing the amount of time the restriction was in effect. The data come primarily from J. Merz, "A Review of Abortion Policy: Legality, Medicaid Funding, and Parental Involvement, 1967--1994," Rand, Santa Monica, Calif., 1994. Where possible, the data have been reconciled with: D. Bush and P. Donovan, "Fertility-Related State Laws Enacted in 1981," Family Planning Perspectives, 16:63--67, 1982; M.D. Greenberger and K. Connor, "Parental Notice and Consent for Abortion: Out of Step with Family Law Principles and Policies," Family Planning Perspectives, 23:31--35, 1991; and T. Sollom and P. Donovan, "State Laws and the Provision of Family Planning and Abortion Services in 1985," Family Planning Perspectives, 17:262--266, 1985.
* AFDC benefits. Data were obtained from the following sources and deflated by the PCD: U.S. House of Representatives, Committee on Ways and Means WAYS AND MEANS. In legislative assemblies there is usually appointed a committee whose duties are to inquire into, and propose to the house, the ways and means to be adopted to raise funds for the use of the government. This body is called the committee of ways and means. , Green Book: Background Material and Data on Programs Within the Jurisdiction of the Committee on Ways and Means, U.S. Government Printing Office (GPO), Washington, D.C., 1981--1990; and U.S. Social Security Administration, Characteristics of State Plans for Aid to Families with Dependent Children, GPO, Washington, D.C., various years.
* Medicaid benefits. Annual unpublished state-level data from the U.S. Health Care Financing Administration Health Care Financing Administration,
n.pr department in the U.S. agency of Health and Human Services responsible for the oversight of the Medicaid and Medicare benefit programs, including guidelines, payment, and coverage policies. on medical vendor payments made on behalf of AFDC recipients were divided by the number of AFDC recipients in each state, converted into monthly amounts and deflated by the PCD. The resulting figures approximate the insurance value of Medicaid to the average AFDC recipient.
* Republican governor. States with a Republican governor were coded 1, and other states were coded 0. (The District of Columbia was coded according to its mayor's party affiliation.) Data were obtained from R. Glashan, American Governors and Gubernatorial gu·ber·na·to·ri·al
Of or relating to a governor.
[From Latin gubern Elections, 1775-1978, Meckler Books, Westport, Conn,, 1979; and M. Mullaney, American Governors and Gubernatorial Elections, 1979-1987, Meckler Books, Westport, Conn., 1988.
* Congressional delegation voting index. Data on key abortion votes were obtained from National Committee for a Human Life Amendment, Key Votes on Abortion, U.S. Senate and U.S. House of Representatives, Washington, D.C., 1978-1989. Votes were coded 0 if prochoice, 1/2 if a nonvote (e.g., abstentions, votes of "present") and 1 if antiabortion, as reported in Inter-University Consortium for Political and Social Research, United States Congressional Roll Call Voting Records, University of Michigan, Ann Arbor, 1989. Annual averages of these indexed votes were constructed for each state's House and Senate delegation. A final index was formed using a simple average of the chamber-specific figures.
* Antiabortion attitudes index. In 1978, 1980 and each year from 1982 to 1988, the General Social Survey asked whether individuals approved of abortions under the following circumstances: the child would have a serious birth defect, the mother was married but wanted no more children, the mother's health was in danger, the mother could not afford more children, the pregnancy resulted from rape, and the mother was single and the father did not agree to marry her (see: National Opinion Research Center, General Social Survey, 1972-1991: Cumulative Codebook codebook - data dictionary , University of Chicago Press The University of Chicago Press is the largest university press in the United States. It is operated by the University of Chicago and publishes a wide variety of academic titles, including The Chicago Manual of Style, dozens of academic journals, including , Chicago, 1992). For each condition, individuals who approved were coded 0, individuals with no opinion were coded 1 and individuals who disapproved were coded 2. The scores for each individual were summed to form an index of opposition to abortion (Cronbach's alpha Cronbach's (alpha) has an important use as a measure of the reliability of a psychometric instrument. It was first named as alpha by Cronbach (1951), as he had intended to continue with further instruments. =.85), and this index was averaged across regions. Quadratic interpolation was used to impute data for 1979 and 1981.
Demographic and Other Characteristics
* Age and race. Annual county-level number of women in each age-group and number of black women were obtained from the following source and aggregated to state levels: U.S. Bureau of the Census, Intercensal Estimates of the Population of Counties by Age, Sex, and Race: 1970-1980 and 1980-1989, Washington, D.C., 1984 and 1992.
* Rape rates. Annual state-level data were obtained from U.S. Federal Bureau of Investigation Federal Bureau of Investigation (FBI), division of the U.S. Dept. of Justice charged with investigating all violations of federal laws except those assigned to some other federal agency. , Crime in the United States Crime in the United States is characterized by relatively high levels of gun violence and homicide, compared to other developed countries although this is explained by the fact that criminals in America are more likely to use firearms. , GPO, Washington, D.C., 1978-1988.