Graphs on teen marriage-early teen marriage: Topics by abwoodenwatches.com

The minimum legal marriage age for Muslims is 18 for men and 16 for women. For non-Muslims, it is 18 for both men and women. The Law Reform Marriage and Divorce Act of stipulates that under no circumstances can the marriage of non-Muslims below 16 years old be legally approved. Crucially, Muslims are exempted from this Act, hence in practice, there is no written absolute minimum age for them. Child marriage is not a fringe issue in Malaysia.

Graphs on teen marriage

Graphs on teen marriage

Graphs on teen marriage

Graphs on teen marriage

The consequences of early childbearing on the growth and nutritional status of women in India has not been quantified in previous studies. Additional concerns due to the informality of the relationship — in terms of inheritance, citizenship and social recognition, for example — may make children in informal unions vulnerable in different ways than those who are formally married. The implications are a longer gap between successive generations and Graphs on teen marriage shorter period of. All findings held controlling for self-esteem and neuroticism. Many countries also collect data on the marital status teenn age at Meg griffin boobs marriage for boys and men, thereby allowing a comparison of gender differentials related to child marriage. Notes on the data. The attempts to establish an equity in marriage with no Graphs on teen marriage lambnot the husband, the wife or the childrenhas received little attention in professional journals. Child Marriage Rate 21 per 10, married.

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Additional Estimates To further investigate heterogeneity in the returns to marrying young and dropping out of school, the first two panels in Table 6 present additional IV estimates by race and mariage of country. Child Marriage Rate 33 per 10, married. Indeed, fewer of the women facing an age minimum of 16 left their residence states to marry. I begin by presenting estimates similar to those in column 4 of Table 1but with an additional variable for whether a woman is currently divorced. While issues of causality have received little attention in the context of teenage marriage, a related line of research has attempted to disentangle the Graphs on teen marriage of teenage child-bearing on education and wages from preexisting differences between those who parent early and those who delay childbearing. In Massachusettsgirls can legally marry at 12, while boys can at However, for some outcomes, part of the observed effects might be due to changes in marriage laws and early marriage Graohs but Sex toys restaints attributed to changes in compulsory schooling laws and education levels instead. Of course, if appropriate instruments can be found, misspecification due to omitted variables or measurement error can be eliminated at both the individual and aggregate level. Fewer Minors Are Getting Married 23, married in Child Marriage Rate 7 per 10, Graphs on teen marriage. Following Garen and Cardfurther assume that.

Child marriage is a truly global problem that cuts across countries, cultures, religions and ethnicities.

  • In Ancient Rome, people didn't marry because they were in love.
  • Both early teen marriage and dropping out of high school have historically been associated with a variety of negative outcomes, including higher poverty rates throughout life.
  • But the laws in every state allow minors to get married under certain circumstances.

Early Teen Marriage and Future Poverty. PubMed Central. Both early teen marriage and dropping out of high school have historically been associated with a variety of negative outcomes, including higher poverty rates throughout life. Are these negative outcomes due to preexisting differences, or do they represent the causal effect of marriage and schooling choices?

While grouped ordinary least squares OLS estimates for the early teen marriage variable are also large, OLS estimates based on individual-level data are small, consistent with a large amount of measurement error.

Early teen marriage and future poverty. Is Teen Marriage a Solution? Many policy proposals related to welfare will have the effect, intended or unintended, of encouraging teens to marry.

This paper discusses the implications of teen marriage. Marriage is one route to reducing out-of-wedlock births to teens who become pregnant, but there is reason to believe such marriages are often unstable. A review of the…. Are female orphans at risk for early marriage , early sexual debut, and teen pregnancy? Evidence from sub-Saharan Africa. Female orphans are widely cited as being at risk for early marriage , early childbearing, and risky sexual behavior; however, to date no studies have examined these linkages using population-level data across multiple countries.

This study draws from recent Demographic and Health Surveys from ten sub-Saharan African countries to examine the relationship between orphanhood status and measures of early marriage , early sexual debut, and teen pregnancy among adolescent girls aged 15 to Findings are sensitive to the use of multivariate models, type of orphan, and country setting. In addition, the relationship between marital status and education among teen mothers is explored.

At 36 months after giving…. Adolescents who use the Internet regularly the "e- teen " present a new set of challenges for marriage and family therapists. This article introduces marriage and family therapists to a the basic technological concepts and unique psychological characteristics of the Internet important in understanding and addressing adolescent online sexual….

Substance Use and Early Marriage. Prior work indicates that substance use is related to adolescent marriage. We describe two different processes that may account for this relationship and hypothesize patterns of association that would be consistent or inconsistent with each.

Using data from a study that followed west coast youth from 7th grade to young adulthood N3,, we…. Early Marriage in the United States. Despite drastic changes in the American family, a significant minority of Americans marry early. Do adolescents support early marriage in Bangladesh?

Evidence from study. Adolescence is a critical period for female adolescents as they have to make decisions regarding their marriage , education and work which would influence and determine their future course of life. Although, early marriage has negative consequences, still a proportion of female adolescents favour early marriage because of prevailing cultural norms. This paper attempts to investigate the factors influencing the adolescents' attitude towards early marriage among the married and unmarried female adolescents.

This is a quantitative and qualitative study. Analysis revealed that one fourth A number of societal factors influenced them towards early marriage , despite the fact that adolescents are aware of the consequences of maternal and child health.

Multivariate logistic regression analysis showed that current marital status, years of schooling, work status and parental marital decision are important predictors of early marriage p marriage. Therefore, opportunities and scope of education beyond secondary would helps to bring change in the attitude towards early marriage. Circular on early marriage , March This Circular calls on government at all levels in Hunan, China, to summon the departments concerned thoroughly to investigate the problem of early child-bearing so that they can do a good job in managing the problems of unregistered cohabiting and of unmarried mothers.

The Circular recommends that: "It is necessary to criticize and educate, and even punish by discipline, those parents who connive with their sons and daughters in practicing unregistered cohabiting. Those who violate laws and discipline, engage in malpractices for selfish ends, and practice bribery and corruption, resulting in early marriage and child-bearing, must be dealt with strictly. Legal sanctions must be enforced against those who break the law.

Divorce in Ethiopia: the impact of early marriage and childlessness. Forty-five per cent of first marriages in Ethiopia end in divorce within 30 years, and two-thirds of women who divorce do so within the first 5 years of marriage. This paper looks at two factors that may have an impact on the risk of divorce in Ethiopia: early age of first marriage , and childlessness within the first marriage.

A total of women of reproductive age were analysed. Life table analysis was used to determine the median age at first marriage , first birth and the median duration of marriage. Cox models were analysed to determine the differentials of divorce. An inverse relationship was found between age at marriage and risk of divorce. Having a child within the first marriage also significantly reduced the risk of divorce.

In addition, several cultural and socioeconomic variables were significant predictors of divorce. China has been an agricultural society for over 2, years. Due to its traditionally rich natural resources, large size, and sparse population density, manpower has become a main source of wealth. Consequently, down through the ages, births have been encouraged and early marriages have become a tradition.

After the Chinese communists' takeover of the Mainland, planned birth and population control measures were implemented. And in , regulations were set for men to marry only after age 28 and for women after age However, during the Cultural Revolution, youths of the Mainland were strongly against the excessive restrictions on early marriage. They pointed out that advocating late marriage was a counter-revolutionary move by the bourgeoisie. Under conditions of despair and uncertain future, many youths married early as an escape from reality, establishing small families.

Thus, a trend of early marriages was set. This was called "evil wind of early marriage " and was vigorously attacked by Chinese authorities in official publications. To control this "evil wind," the Chinese communists also utilized Mao's thoughts in re-educating the educated youths.

They pointed out that youths who married early and concentrated on building a family were selfish because by concentrating on personal matters they could not attend to state matters nor participate in class struggles. It is clear that in attacking early marriage and advocating late marriage , the Chinese communists had both planned birth and politics in mind.

The demographic cost of early marriage. The IPPF Biomedical Workshop held in London in November , heard 16 speakers present papers on widely varied aspects of the problem of pregnancy during adolescence. These expert studies found that over the world teenagers face greater risks from pregnancy and the infants greater risks from low birth weight and birth defects.

Religious beliefs and economic incentives, particularly gifts to the family of the bride, play a part. Demography also increases adolescent marriage. As soon as a girl reaches puberty she is sought as a bride. In the U. This means 1 in 10 adolescents and 1 in 4 sexually active teenagers conceived. These young mothers also had higher rates of toxemia, neonatal deaths, and maternal mortality than women in the optimal childbearing age bracket of The social problems encountered, including lack of schooling, few job opportunities, and low income prospects, also hamper both mother and child.

The problem in the U. Stress resilience in early marriage : can practice make perfect? As all couples experience stressful life events, addressing how couples adapt to stress is imperative for understanding marital development. In Study 1, 61 newlywed couples provided data regarding their stressful life events, relationship resources i. Study 2 examined stress resilience following the transition to parenthood in a new sample of 50 newlywed couples.

Again, spouses who experienced moderate stress during the early months of marriage and had good initial relationship resources i. Marital processes in early marriage are important for understanding couples' future marital quality. Spouses' attributions about a partner's behavior have been linked to marital quality, yet the mechanisms underlying this association remain largely unknown. Early marriage has important consequences for individuals in the United States. Several studies have linked religion to early marriage but have not examined this relationship in depth.

Using data from Waves 1, 3, and 4 of the National Longitudinal Study of Adolescent Health, I conduct multilevel event-history analysis to examine how religion, at both individual and contextual levels, is associated with early marriage.

Further, I test mediators of the religion- early marriage relationship. I find significant variation in early marriage by religious tradition, religious service attendance, religious salience, belief in scriptural inerrancy, and religious context in high school. The individual religious effects-but not the school context effects-are explained in part by differential attitudes toward marriage and cohabitation.

The individual religious effects—but not the school context effects—are explained in part by differential attitudes toward marriage and cohabitation. To address this question, we compared trajectories of marital satisfaction among couples with a wide range of household incomes. According to a growing body of literature, some orphans are at heightened risk of early sexual debut and early marriage. This study examines a rarely explored aspect of orphanhood: the timing and type of parental death and their relationship to these outcomes.

The data are drawn from the National Survey of Adolescents, which includes interviews with 12—year-old adolescents in Burkina Faso, Ghana, Malawi, and Uganda. Education explains little of their increased risk. In contrast, male orphans of any type reveal no increased vulnerability to early sexual debut. Uganda is the only country where female orphans, specifically double orphans and those who are paternal orphans before age 10, have greater odds of early marriage , with education accounting for a small portion of the risk.

How they see it: young women's views on early marriage in a post-conflict setting. Current understandings of early marriage in conflict and post-conflict settings are incomplete and under-researched, and do not sufficiently take into consideration the views and experiences of adolescent girls. While much of the literature, development reports and mainstream media emphasise the poverty, health risks and lack of agency of young women married early , they seldom provide these teenagers an open platform from which to speak.

In , a Palestinian refugee camp in North Lebanon was destroyed and its residents forced to flee.

Subsequent approaches attempting to deal with selection bias have reached disparate conclusions. Delaware Total Children Married The Consequences of Teenage Childbearing. The amount of measurement error in the census is likely to be even larger because the NFS sampled only women who had never divorced and had women answer questions about themselves. Instrumental Variables in Economics and Statistics; pp. To construct the estimate, I first compare the fraction of women who married in a state with a lower minimum versus a higher minimum.

Graphs on teen marriage

Graphs on teen marriage

Graphs on teen marriage

Graphs on teen marriage

Graphs on teen marriage. History, statistics, and things to consider

Additionally, according to the Center for Law and Social Policy, "Compared to girls who marry later, teenage brides have less schooling, less independence, and less experience of life and work. There is another side to the story of teen marriage, though. That is the number of success stories that married teens share. Ask yourselves why you want to get married. All of these reasons are red flags in your relationship and are not valid reasons for getting married.

Marriage should be a "want to" and not a "have to". Being on your own does free you from parental control, but this change in lifestyle brings along a whole new set of responsibilities in your lives. You will have to deal with financial issues, where to live, jobs, grocery shopping, cooking, cleaning, decision making, in-laws, continuing your education, and if pregnant, child care along with learning how to communicate with your spouse.

Updated March 29, Attend a premarital education class or an Engaged Encounter weekend. Work out together a realistic budget. Volunteer together to work with young kids at a homeless shelter for a few months. Or volunteer your time at a soup kitchen facility. Continue Reading. Two closely related explanations are that teens have time-inconsistent preferences or projection bias. These models provide an explanation for why teenagers engage in risky behavior, such as drinking, smoking, drug use, unprotected sex, and criminal activity, even though these behaviors can have substantial negative consequences in the long run Gruber Looking at schooling decisions, Oreopoulos argued that myopia helps explain why some teens drop out of school early.

The various psychological explanations for poor decision-making by youth generally share the feature that teens make choices they will later regret. Although teen marriage and low education are associated with a variety of below-average outcomes, it is not necessarily true that these choices caused the bad outcomes.

For example, differences may be due to preexisting characteristics of women who marry young versus later, rather than any causal relationship between teen marriage and negative adult outcomes. To my knowledge, no previous research has studied the causal effect of early marriage. If teenage marriage and dropping out of high school are largely driven by unobserved personal characteristics that are the primary cause of negative outcomes, legal interventions to prevent these choices may make little difference.

While issues of causality have received little attention in the context of teenage marriage, a related line of research has attempted to disentangle the effects of teenage child-bearing on education and wages from preexisting differences between those who parent early and those who delay childbearing. Early research using OLS revealed large and significant consequences associated with teenage childbearing Moore and Waite Subsequent approaches attempting to deal with selection bias have reached disparate conclusions.

For example, studies by Angrist and Evans , Grogger and Bronars , and Klepinger, Lundberg, and Plotnick that used a variety of instrumental variables concluded that teenage childbearing has negative consequences. However, Geronimus and Korenman , using sister fixed effects, and Hotz, McElroy, and Sanders and Hotz, McElroy, and Sanders and Hotz, Mullin, and Sanders , using random miscarriages as an instrument, found little evidence of a negative effect.

The debate is ongoing, with recent work by Ashcraft and Lang and Fletcher and Wolfe using variations on the miscarriage instrument and finding negative effects. The data for this article combine information on state-specific marriage, schooling, and labor laws with data from the , , and decennial censuses Ruggles et al. Supplementary data is obtained from Vital Statistics marriage certificate data and the National Fertility Surveys.

The U. Even though the census data sets are cross-sectional surveys conducted every 10 years, they contain information about women from a variety of cohorts. Because the surveys ask retrospective questions about age at first marriage and women are different ages when the survey is administered, a large data set with time-varying information can be created from the cross sections.

All three census years are combined to create a data set for women born between and These women were age 15 during the period to , which corresponds to the approximate age they were at risk for becoming early teen brides. The sample is further restricted to U. Data are also restricted to the 41 states with available data on marriage laws, compulsory schooling laws, and child labor laws.

The census data reveal that early teen marriage, which I define as marrying before the age of 16, has historically accounted for a nontrivial fraction of all marriages in the United States.

In the sample used in this article, 3. The top two series in Figure 1 graph the fraction of women marrying at these ages over time. This pattern is mirrored for the fraction of women marrying at age 16 or All other data series are from various tables in Carter et al.

Vertical lines denote the time period analyzed in this article — To put these patterns into perspective, the bottom series in Figure 1 graphs the median age at first marriage for a long time horizon. The plot reveals that the time period of interest in this article — corresponds to a period in history when marriage ages were remarkably low by historical standards. Since the s, the median age has risen dramatically, so that by the end of the s, the median age was Figure 2 plots other well-known secular trends that were also occurring in the middle of the s.

There was a sharp decline in overall fertility during World War II, followed by a dramatic increase in the postwar period. Fertility started to decline by the end of the s, reaching a low in the late s, during which the rate was half that of the peak.

The trends in the top half of Figure 2 —couples starting their marriages and bearing children sooner in the postwar period—are recognized as being largely responsible for the baby boom between and Similarly, the baby bust resulted from delayed marriage and fertility.

The same fertility pattern holds for teenage childbearing as well. At the peak in , there were 96 births per 1, to year-old women in the United States.

Notes: Data are from various tables in Carter et al. To add further perspective, the bottom half of Figure 2 plots marriage and divorce rates over time. Divorce rates also rose sharply starting in the late s before reaching a plateau in the s. Further insights into the changes in and possible causes of these dramatic shifts in marriage and divorce can be found in Stevenson and Wolfers These secular trends have several implications for the current study.

First, it will be important to allow for different effects by time period. In the regression analyses that follow, separate dummy variables will be included for year of birth, current age in year intervals , and census year. Second, the findings should be interpreted in the appropriate historical context because the cultural, legal, and economic environment is very different today. In addition to early marriage, another key variable for the analysis is the high school dropout rate.

Carter et al. Of the women born between and , As a summary measure of well-being, I use a variable that indicates whether the woman lives in a poor family according to the government definition of poverty. Whether a woman lives in poverty depends on family income, family size including the number of children in the family , and whether the householder is over age This poverty variable captures the cumulative impact of a variety of past decisions by a woman.

As such, it is a useful summary measure of the consequences of early marriage and dropping out of high school. For example, a woman who marries young may have additional children, gain less work experience, and divorce sooner, all of which likely increase the chances of future poverty.

The large fraction of early teen marriages for the women in the sample is ideal for this article. There are over , of these early teen marriages in the combined census sample. The large number of high school dropouts and the dramatic decrease over time, which does not parallel the pattern in early marriage rates, make the data well-suited to separate the two effects.

These laws are discussed in the next section, after the OLS estimates are presented. How are poverty, early teen marriage, and dropping out of high school related? I begin by presenting OLS estimates of the effect of early teen marriage and dropout status on poverty. These estimates suggest that dropping out of high school has a sizable impact on future poverty, but that teen marriage has relatively small effect.

Notes: Standard errors, adjusted for clustering by state of birth to account for arbitrary autocorrelation over time, are shown in parentheses.

Data are from the , , and U. The sample is restricted to women between the ages of 20 and 60 who were born in one of the 41 states with valid marriage, compulsory schooling, and child labor laws.

The dependent variable, poor, is a dummy variable equal to 1 if the woman currently lives in a family that is at or below the poverty line. Early teen marriage is defined as marrying between the ages of 12 and 15 14 or 15 in the and censuses , and high school dropout is defined as fewer than 12 years of completed schooling.

Dummy variables for state of birth are indicators for each of the 41 states, and dummy variables for cohort of birth are single-year indicators for each birth cohort. Region of birth trends are separate linear cohort year trends for each of the four birth regions. Allocated observations refer to observations whose value for the variable age at first marriage has been logically edited or hot decked by the Census Bureau. In contrast to OLS, the estimates in columns 1—4 are much larger, and the inclusion of controls affects both the dropout and teenage marriage coefficients.

After including controls for 1 census year, race, and current age dummy variables, 2 state of birth and birth cohort dummy variables, and 3 region of birth trends, the coefficients on early teen marriage and dropout are A key question is whether there are additional omitted variables that would drive either of these coefficients closer to zero. Column 5 expands the sample to include allocated observations. The Census Bureau allocates values for age at first marriage when data are missing or inconsistent.

First, a logical edit is performed if possible, using information from other variables and other household members. When this is not possible, the census uses a hot-deck allocation method to assign a value from an individual with similar characteristics. Additionally, the hot-deck procedure used in and to a lesser extent in and suffers from bracketing issues for early teen marriages, with sharp spikes in marriage rates occurring for women whose current age is a multiple of five.

When these allocated marriages are included in column 5, the coefficient on early teen marriages drops, particularly in the grouped OLS panel.

As I show later, these allocated marriages do not have much of an impact on the IV estimates, suggesting that these allocated marriages are largely noise. Therefore, unless otherwise noted, all allocated marriages are dropped from the data. What explains the different estimates for early teen marriage when comparing the individual versus grouped data in Table 1?

An analysis of auxiliary data later in the article indicates a large amount of measurement error in the early marriage variable. This suggests the presence of attenuation bias in the individual-level OLS estimates, whereas aggregation should minimize this type of bias. Of course, if appropriate instruments can be found, misspecification due to omitted variables or measurement error can be eliminated at both the individual and aggregate level. As I show later, the individual-level IV and aggregate IV estimates are both large and remarkably similar.

The OLS estimates presented in the previous section potentially suffer from both omitted variable bias and measurement error.

One solution to these problems is to use an instrumental variables approach. Ideally, instruments would induce exogenous variation in early teen marriage but would be uncorrelated with unobserved characteristics that affect both poverty and the decision to marry young. Similarly, the instruments would induce exogenous variation in high school graduation but be orthogonal to the error term in the poverty equation.

I use changes in state marriage, schooling, and labor laws over time as instruments for early marriage and dropping out of high school. By preventing some teens who would like to marry or drop out of high school from doing so, these legal restrictions can help identify the causal effects on poverty free of selection bias. In the United States, wide variation has historically existed regarding the minimum age individuals are legally allowed to marry.

The laws that regulate teenage marriage have appeared in the World Almanac and Book of Facts starting in the late s. Since , information has consistently been reported on the minimum marriage age with parental or court consent, separately for males and females. I collected this information annually for the years to for the 41 states with reliable information on marriage laws during this time period.

There are two sets of laws specifying minimum age requirements for marriage. The first is the minimum age with parental or court consent, while the other is the minimum age without parental consent. In this article, I focus on the marriage age laws with parental consent, partly because there is little variation over time or across states in the laws without parental consent during the period of my data.

For a discussion and an interesting analysis of these laws, see Blank, Charles, and Sallee Laws with parental consent do not eliminate all early teenage marriages. Some teens may find ways to lie about their age or may travel to states with lower age requirements to get married.

These statutes imply that a judge could grant permission for an early teenage marriage if the teenage woman was pregnant. How often judges actually granted exceptions is hard to know ex post facto, but given the relatively low rate of illegitimate births and abortions during much of this period, exceptions for pregnancy were probably common.

Rather, the strength of the instrument set is that restrictive state laws make it harder to marry young, thereby preventing some fraction of teen marriages that otherwise would have occurred. I also use the compulsory schooling and labor laws originally collected by Acemoglu and Angrist and subsequently modified by Goldin and Katz These laws typically specify a minimum age or amount of schooling before a youth can drop out of school or obtain a work permit.

Child labor is defined as the maximum of 1 the required years of schooling before receiving a work permit and 2 the difference between the minimum work age and the maximum enrollment age lagged 8 years. The value of the marriage, schooling, and labor laws assigned to a woman are based on the set of laws for her birth state that are in force when she would have been age Table 2 summarizes the changes in these laws across five-year time periods in the regression analysis, year-by-year values are used.

Summarizing the law changes another way, the average minimum marriage age across states was There have also been similar increases in the requirements governing school attendance and child labor. Later in the article, I will also investigate the impact of divorce and use unilateral divorce laws as instruments, although the table reveals that few states enacted unilateral divorce laws prior to Notes: Entries are the fraction of states with a specified law averaged over the five-year time interval.

Sample size is the number of state-years; there are 41 states with laws available and 35 years, for a total of 1, observations. These tests all strongly reject the null hypothesis that the various state laws are independent. After time trends in the laws are regressed out, the state laws are still highly related. Since the marriage, schooling, and labor laws affecting youth are so highly correlated, it could be important to account for all three simultaneously when estimating instrumental variable regression models.

In many of these applications, there may not be a need to instrument for early teen marriage. However, for some outcomes, part of the observed effects might be due to changes in marriage laws and early marriage rates but mistakenly attributed to changes in compulsory schooling laws and education levels instead. In the IV regressions that follow, I use all three sets of laws in poverty regressions that instrument for early marriage and high school completion.

How effective are state-specific marriage laws at restricting the age individuals marry? The combined census samples reveal that restrictive laws are associated with a smaller number of early teen marriages i. In the IV regressions appearing in the next section, these factors will be accounted for.

Are the laws actually reducing the number of teen marriages, or would states with restrictive laws naturally have lower teen marriage rates anyway? I use the and Vital Statistics Marriage Detail files, which collect data from marriage certificates, to examine the timing of teen marriages.

Marriage rates are grouped in two-month intervals. The sample is restricted to women who married for the first time, who married between the ages of 14 and 16, and who were residents of and got married in a state that is in a marriage-reporting area MRA and has information on marriage laws.

The marriage certificate data include all records for small states and a random sample for larger states; the probabilities in the figure are weighted unweighted probabilites are very similar. Sharp increases in the fraction marrying occur where expected, assuming the laws are enforced. For example, in states where the legal minimum is 14 years, a fair number of women actually marry at this young age. In contrast, in states where the legal minimum is 15 years, there is a sudden rise in the number of marriages immediately after women reach the minimum age of For another example, consider women marrying at age In the third graph, where the legal minimum age is 16, there is a sharp and large increase in the number of marriages occurring immediately after women turn In comparison, the rise surrounding age 16 is much less pronounced in states with minimum ages of 14 or especially Another way to test whether state laws impact the probability of marrying young is to see whether teens travel to a state with a lower age requirement to get married.

If so, this is an indication that restrictive laws impose costs on those wishing to marry before the law in their state of residence allows. Some young teens will cross state lines, while others will be deterred by these costs. Before looking at the entire United States, first consider the case for women residing in Tennessee.

Tennessee is a long, narrow state, with population centers scattered throughout the state. Tennessee had an age requirement of 16 years for women to marry in and , the period for which Vital Statistics data are available. Tennessee is bordered by eight states with varying age minima. Six of these states have valid marriage certificate and marriage law information. However, we should not see as many prospective teen brides traveling to Georgia, Kentucky, or Virginia, where the age requirement of 16 was the same as in Tennessee.

Table 3 extends the Tennessee analysis of out-of-state marriages to all of the states in the sample. For women who married between the ages of 12 and 15, Notes: Standard errors are shown in parentheses.

Data were collected from marriage certificates by the National Center for Health Statistics. The sample is restricted to first marriages of women who are residents of and get married in 1 of the 32 states that are in a marriage-reporting area MRA and have information on marriage laws. See footnote 9 in the text for a list of available MRA states. The marriage certificate data include all records for small states and a random sample for larger states; the probabilities in the table are weighted unweighted probabilities are very similar.

Of course, the patterns observed in the top panel of Table 3 could be the result of the location of states with various laws or the general attractiveness of marrying in different states.

To control for this possibility, in the middle panel of Table 3 , I tabulate marriage patterns for women who married at age For these women, the marriage laws should not be binding.

Indeed, fewer of the women facing an age minimum of 16 left their residence states to marry. A simple difference-in-differences estimate makes clear that women crossed state lines to marry young. To construct the estimate, I first compare the fraction of women who married in a state with a lower minimum versus a higher minimum. Subtracting this difference for women who married between ages 12 and 15 from the difference for women who married at age 16 yields the estimate.

For states with a marriage age requirement of 13 or 14, the difference in difference is close to 0 and not significant, as expected. For states with an age minimum of 15, the estimated difference in difference is 4. An even greater contrast shows up for the states specifying a minimum age of 16, with a large and significant estimate of As a final check on the validity of the laws as instruments, I explore the timing of law changes. However, if law changes are exogenous, then future values of the laws should not affect current early marriage rates conditional on current laws.

The F statistic for the effect of future laws is 0. Notes: Standard errors, adjusted for clustering by state of birth, are shown in parentheses. All regressions include dummy variables for census year, race, age, state of birth, and cohort of birth, and region of birth trends. See the notes to Table 1. To investigate the effects of teenage marriage and high school completion on subsequent poverty, I use state marriage, schooling, and labor laws as instrumental variables.

Since I am instrumenting for both early marriage and dropout status, there are two sets of regression estimates. Column 2 regresses a dummy variable for early teen marriage on the set of marriage, schooling, and labor laws. Additional controls mirror those used in column 4 of Table 1. The marriage laws significantly reduce the number of teens who marry before the age of 16; ceteris paribus , states with a legislated minimum of 13 or less are between 0.

In states without a legislated minimum, common law which specifies a minimum of 12 years prevails; the estimated effect of a common law is similar to a legislated minimum of 13 or less. The third set of laws that deal with compulsory schooling is smaller and less significant. As expected, the compulsory schooling laws have a relatively large and jointly significant effect on whether a young woman finishes high school. The marriage laws have nontrivial coefficient estimates but are imprecisely estimated and therefore not significant.

One reason why dropout status might project onto the marriage laws is that the marriage laws are highly correlated with the compulsory schooling laws. The marriage laws are measured every year, but the schooling laws are only measured intermittently. For all of the estimates, F statistics are reported for the joint significance of the instruments. The F statistic is All of the standard errors reported in Table 4 and throughout the article are adjusted for clustering by state of birth to account for arbitrary correlation over time.

Bertrand, Duflo, and Mullainathan have shown that failure to account for such correlation can lead to severely biased confidence intervals for the estimated coefficients. This is particularly likely to be important in IV analyses, which use laws over time as instruments, because there is typically a long time component and plausible serial correlation. Early teen marriage and dropping out of high school both have sizable effects on the probability a woman will end up in poverty.

The estimates imply that marrying young is associated with a Dropping out of high school is associated with an I now present a series of alternative estimation approaches to assess the robustness of the baseline result.

The first column in Table 5 repeats the baseline IV analysis, but this time with grouped data. The grouped-data IV estimates are remarkably similar to the individual-level IV estimates 0. The similarity of the coefficient estimates is not surprising since the instruments are constant for all individuals in a state-cohort group, effectively aggregating both the individual-level and group-level estimates.

The migration-adjusted approach is described in the text and the control function approach is described in the text and the appendix. As is well known, weak instruments can lead to biased IV estimates; under general conditions and finite samples, weak instruments bias the estimates in the same direction as OLS estimates see Bound, Jaeger, and Baker ; Staiger and Stock The consensus in the literature is that when there are many instruments or weak instruments, LIML tends to exhibit less bias compared to least squares IV, and LIML confidence intervals typically also have better coverage rates Stock This suggests that weak instruments are not a major issue for estimation.

The next task is to assess the impact migration has on the assignment of state laws for marriage, schooling, and work and the subsequent IV estimates. Because some women have migrated out of their birth state and into a state with a different set of laws by age 15, the instruments are measured with error. I assess how this affects the IV estimates in column 3 of Table 5. To see how I examine the issue, notice that the expected value of the ideal but unobserved state laws can be calculated if migration probabilities are known.

The asterisk indicates that this variable is not observed, given that she may have moved from her birth state by age However, if migration probabilities are known, the expected value of this variable can be calculated as. The same logic applies when there are several variables for the state laws. The remaining issue is how to consistently estimate the conditional migration probabilities, p jk.

Although this information is not available for all women, the migration patterns for women who were age 15 at the time of the census enumeration can be estimated because the census records both state of birth and state of current residence.

I use year-old women in the census to estimate these migration probabilities. I then calculate the expected value of the laws based on the state a woman lived in at age 15 as outlined above and use these expected laws as instruments. To assess the impact of heterogeneous returns, I pursue a control function approach similar to the one proposed by Garen and discussed by Card The basic idea of a control function approach is to make some assumptions about the relationship between the observed variables controls and instruments and the individual-specific returns and individual-specific intercept term.

One then includes additional terms in the outcome regression to control for these relationships. The appendix details the assumptions and estimating equation. The resulting control function estimates appear in column 4 of Table 5.

To further investigate heterogeneity in the returns to marrying young and dropping out of school, the first two panels in Table 6 present additional IV estimates by race and region of country. The IV estimate of the early teen marriage effect for the black sample is 0. The dropout coefficients are similar for whites and blacks, but statistically insignificant for blacks.

Child marriage - UNICEF DATA

But the laws in every state allow minors to get married under certain circumstances. Reiss wanted to know how often minors were getting married, so she went looking for an actual count. The spreadsheet showed nearly 3, minors married in New Jersey between and After New Jersey, she requested marriage license data from New York. We requested data from additional states in an effort to get a fuller picture of how many minors are getting married in the U.

This count is incomplete. The number of people marrying before the age of 18 fell by about 61 percent between and in states where we have records. Fewer Americans overall are getting married, according to the U. Note: , total minors, 38 states and three counties, from — Due to rounding, numbers don't add up to percent. Children as young as 12 were granted marriage licenses in Alaska , Louisiana and South Carolina.

A person can be charged with sexual abuse or statutory rape for having sex with a minor. Yet, we found numerous examples of children who were given marriage licenses before they could legally consent to sex.

While some minors married other minors, these cases were less common. In , a year-old girl married a year-old man in Idaho. One of the oldest people to marry a child was a year-old in Alabama. His bride was The state later raised its minimum marriage age to Source: Tahirih Justice Center. In Oregon , Nebraska and New York , minors have to be at least 17 years old to get married. Other states draw a line at 14, 15 or In New Hampshire , a law that has been on the books since allows girls as young as 13 and boys as young as 14 to marry.

In Massachusetts , girls can legally marry at 12, while boys can at Twelve states require all minors to petition a judge for a marriage license, according to a forthcoming Tahirih report.

We calculated the rate of child marriage in the U. Explore our database to learn how many children married in each state. Click on the cards to see the laws that allowed them to marry. The total number of minors married in Tennessee during that time has been updated from 8, to 8, Has child marriage affected you?

Share Your Story. Between and , at least , Note: Total includes data from 41 states and three counties. Fewer Minors Are Getting Married 23, married in Note: , total minors, 38 states and two counties, — Note: , total minors, 40 states and one county, from — The Youngest Children To Marry 6. Note: , total children, 33 states and three counties, — Note: , children, 39 states and three counties, — Note: , adults, 25 states, — States and years included in this chart:.

Alabama Total Children Married 8, Child Marriage Rate 43 per 10, married. Alaska Total Children Married Child Marriage Rate 25 per 10, married. Child Marriage Rate 58 per 10, married.

Arkansas Total Children Married 7, Child Marriage Rate 46 per 10, married. California Total Children Married Not available. Child Marriage Rate Not available. Colorado Total Children Married 4, Child Marriage Rate 37 per 10, married. Connecticut Total Children Married 1, Child Marriage Rate 17 per 10, married. Delaware Total Children Married Child Marriage Rate 2 per 10, married.

Florida Total Children Married 16, Child Marriage Rate 22 per 10, married. Georgia Total Children Married Not available. Hawaii Total Children Married Child Marriage Rate 7 per 10, married. Idaho Total Children Married 4, Child Marriage Rate 84 per 10, married. Illinois Total Children Married 7, Child Marriage Rate 21 per 10, married. Indiana Total Children Married 3, Iowa Total Children Married 1, Child Marriage Rate 11 per 10, married.

Kansas Total Children Married 2, Kentucky Total Children Married 10, Child Marriage Rate 73 per 10, married. Louisiana Total Children Married 4, Child Marriage Rate 27 per 10, married. Maine Total Children Married Not available.

Maryland Total Children Married 3, Child Marriage Rate 23 per 10, married. Massachusetts Total Children Married 1, Michigan Total Children Married 5, Child Marriage Rate 20 per 10, married.

Minnesota Total Children Married Mississippi Total Children Married 4, Child Marriage Rate 52 per 10, married. Missouri Total Children Married 7, Child Marriage Rate 49 per 10, married. Montana Total Children Married Child Marriage Rate 10 per 10, married. Nebraska Total Children Married 1, New Hampshire Total Children Married Child Marriage Rate 6 per 10, married.

New Jersey Total Children Married 2, New York Total Children Married 3, North Dakota Total Children Married Child Marriage Rate 13 per 10, married. Ohio Total Children Married 4, Child Marriage Rate 12 per 10, married. Oklahoma Total Children Married Not available. Oregon Total Children Married 3, Child Marriage Rate 31 per 10, married. Pennsylvania Total Children Married Not available.

Rhode Island Total Children Married

Graphs on teen marriage