The effect of birth order on occupational choice.
The idea that birth order affects personality, and therefore occupational choice, has a strong hold on popular beliefs, but academic research has come to conflicting conclusions. Psychologists such as Frank Sulloway and others argue that birth order predisposes people to certain types of behavior, which then leads them to choose suitable occupations. However, a number of economists (Khanam and Rahman 2007; Blake 1981), argue that it is family structure, not birth order, that affects how much time and resources parents invest in their children, and that occupational choice is a result of this parental investment. In this paper, we conduct statistical and logical tests of these competing theories.
In doing so, we make three contributions to the literature. First, the great majority of studies on birth order and career choice have used small convenience samples, such as college students (Leong et al. 2001) or residents of a particular town or city (Shaver et al. 1970). In contrast, we use a large, high quality, nationally-representative survey funded by the Bureau of Labor Statistics, the National Longitudinal Study of Youth 1979 (NLSY79) (Bureau of Labor Statistics 2012).
Second, most studies have examined the relationship between careers and birth order at a single point in time (Very and Prull 1970), the time when the data were collected. But people often change careers many times during their lives. The occupation they happen to have when speaking to the researcher may not represent their eventual, long-term occupation. The NLSY79 allows us to observe each occupation of the respondent from their teenage years to their early fifties.
Third, all prior studies of which we are aware control for family size (Price 2008; Hauser and Sewell 1985), which is a key confounding variable when studying the effects of birth order. "Family size" is either included as a variable in the analysis or restricted to families of a particular size, which is basically the same method. But family size may be correlated with a host of unobserved factors that influence occupational choice. If so, merely including family size in the analysis may produce biased estimates of the effects of other covariates. To determine the true effect of family size, the researcher needs variation in family size that is uncorrelated with unobserved factors. In other words, one needs random variation in family size. We take advantage of a source of random variation in family size due to the gender composition of the first two children in a family (Angrist and Evans 1996).
In his book, Born to Rebel'. Birth Order, Family Dynamics, and Creative Lives (Sulloway 1996), Sulloway argues that birth order has a profound effect on a child's personality. Sulloway identifies a lengthy list of personality traits that are unique to first-born and last-born children. First-borns are more responsible, traditional, assertive, achievement-oriented, antagonistic, conforming, jealous, neurotic, and organized, whereas last-born children are easygoing, adventurous, altruistic, cooperative, sociable, unconventional, and rebellious (Sulloway 1996).
Sulloway attributes these differences in personality to differences in the way firstborns and last-boms are raised. For example, younger parents tend to be more anxious than older parents because of their inexperience with parenting. As a result, anxious parents tend to have anxious children. By the time the youngest is born, his or her parents are experienced and are more easy-going with their children. Younger children are more leniently disciplined, are often pampered by their parents, and are more accustomed to getting their way than first-borns (Sulloway 1996).
Other factors have been identified that might account for the personality profiles highlighted by Sulloway, including parental anxiety, dethronement, and only-child uniqueness (Claxton 1994). For example, first-borns are more "adult" because they are raised exclusively by adults, whereas younger children are "less adult" because their older siblings participated in their upbringing thereby influencing their socialization (Claxton 1994). A second theory involves feedback. Earley et al. (1990) proposed that the type of feedback a child receives from others might affect his or her development. Earley et al. (1990) suggested that first-borns are more likely than their younger brothers and sisters to receive process feedback, in which they are instructed how to accomplish a task, while younger siblings receive outcome feedback, in which they are merely ordered to do something without instruction. Children receive process feedback from patient and attentive adults and outcome feedback from their peers. Since firstborns are raised by adults, they receive process feedback and are more comfortable and receptive to instruction than younger children (Claxton 1994).
Sulloway suggests that birth order will not only affect an individual's personality, but also his or her career choice. In this paper, we investigate whether this is true. Does birth order make some people more suitable than others for managerial positions? The purpose of this study is to investigate the relationship between birth order and managerial position. Are first-borns natural leaders, as Sulloway says? Are first-borns over-represented in the management population, or are first-borns, middle-borns and last-borns equally represented?
When considering birth order and employment, Sulloway and his supporters argue that first-borns are attracted to managerial positions because their relative birth order fosters personality traits needed for management (Sulloway 1996). In contrast, last-borns are entrepreneurs, because their birth order position has made them adventurous, easygoing, and rebellious. Sulloway suggests that first-borns make good managers but poor innovators because they are authoritarian and slow to change. In contrast, lastborns make great entrepreneurs but poor managers because they are "headstrong and impulsive. These qualities may serve them well creating companies but not necessarily running them" (Sulloway 1996).
While some researchers find clear and compelling evidence for the birth order effect, other researchers find no convincing evidence for it (Herrera et al. 2003; Ernst and Angst 1985). In 1983, two Swiss psychologists, Ernst and Angst (1985), reviewed over a thousand birth order studies and found many were methodologically flawed. They did not control for variables that could account for the differences in outcomes between first-and later-born children, such as family size.
Several economists argue that the relationship between birth order and career choice is better explained by family size and the allocation of limited resources (Kessler 1991; Becker and Lewis 1974). Becker and Tomes (1976) investigated the trade-off between the quantity and quality of children. They found that parents tend to allocate their resources toward first-borns because they will generate the most immediate contribution to the family's finances and because there is no guarantee, yet, that other children will be produced (Kessler 1991).
Once enough children have been produced who can satisfy the parents' most pressing needs, the parents, can afford to be more generous and allow the children to pursue their own life choices, such as employment. These findings were corroborated by a sample of families in Bangladesh, in which first-born sons were expected to work and rarely offered the opportunity to attend school (Khanam 2008). In contrast, parents were much more generous with their lastborn sons, who were offered the choice of going to school, working, or not working (Khanam 2008).
Economists suggest that children create utility but their degree of utility differs from child to child, and that the resources that parents allocate to each child depend on the child's contribution to the parents' utility. The most important resource allocated between children is parental attention. Becker and Tomes (1976) argue that first-borns and last-borns achieve more in life because parents devote more time and attention to them than they do to their middle-born siblings. First-borns receive more resources because in their early years, at least, they have no siblings with whom they have to compete for parental time and attention.
But birth order is only one of two factors that determine the allocation of resources. The other is family size (Kessler 1991). There is only a limited amount of time that parents can devote to their children, and the larger the number of children, the smaller the amount of this resource they can allocate to each of them (Kessler 1991). Researchers have confirmed the negative effect of family size on intelligence and achievement. Blake (1981) examined the effect of family size on intelligence test scores and life achievement and found that individuals from large families generally do worse on these measures than children from smaller families (Blake 1981).
If success in school and in life depends on early parental attention, then first and last-borns should do better academically and financially than their siblings, and children from larger families should do worse in school and in career than children from smaller families. Hauser and Sewell (1985) found that this is true regarding success in school. They found that academic success in large families followed a U-shaped pattern, with the oldest child doing best and with each additional child doing worse until the final child, whose achievement was on the level of the first-born (Hauser and Sewell 1985). Other studies have found similar results (Black et al. 2005; Iacovou 2008).
But other researchers have pointed out that family size alone might not account for this pattern. Educated people tend to have smaller families (Black et al. 2005). If less educated people tend to have larger families, then the failure of their children in school may be due more to genetics than to the size of their families (Black et al. 2005)
While prior research on birth order, family size, and labor market success informs our research in this paper, it does not directly indicate whether Sulloway's theory is correct. According to his theory, first-borns are more successful not because they receive more parental resources but because they are called upon to be more responsible than later siblings. Thus, a first-born, according to Sulloway's theory, should be more likely to become a manager the more siblings he or she has, since having more siblings provides more managerial experience.
Data and Methods
The NLSY79 is a nationally-representative longitudinal survey of labor market and other activities that began in 1979. At its inception, it included 12,686 men and women ages 14 to 22. From 1979 to 1993, participants were interviewed every year. Since 1994, they have been interviewed biennially. Data collected include the dates and lengths of employment, the positions held, the lengths of periods of unemployment, and the lengths of time spent looking for jobs. Additionally, the surveys include data on marital status, family size, income and wealth, academic achievement, health, substance abuse, sexual activity, and dependence on public assistance. The NLSY79 was used because it includes the participants' scores on the Armed Forces Qualifying Test (AFQT), a series of ten tests measuring general knowledge and skills in subjects like language and math (Bureau of Labor Statistics 2012).
Since 1979, the number of respondents in the NLSY79 has shrunk due to the dropping of a minority sample and a military sample, as well as to attrition, incarceration, and death. By 2010, the most recent survey, the sample size declined to 7502. All of the analyses pertain to this sample. Since our dependent variable is whether the respondent's occupation is managerial, we drop observations for respondents who were not working in 2010 or whose occupation was not given, bringing the sample to 6865 persons. Missing values of independent variables result in a final analysis sample of 6430.
The NLSY79 records the occupation of respondents during each interview since 1979. Our main dependent variable is a dummy that equals one if the respondent ever had a managerial occupation, as defined by the 1970 and 2000 occupational codes. The definition of "manager" differs somewhat between the two classification systems. This introduces some measurement error, but since it is error in the dependent variable, it should not distort our results, since the error is unlikely to be correlated with respondents' unmeasured characteristics.
Our primary independent variable is a dummy variable that equals one if the respondent is first-born and had one or more siblings. We drop only children, since the theory we are testing refers to the effect of being first-born among a number of children. Other independent variables include the AFQT score, the number of siblings, the region of the country where the respondent currently lives, the amount of education of the mother and father, age, gender, race, and Hispanic origin.
The equation in which we are primarily interested is the following:
[Manager.sub.i] = [alpha]'[X.sub.i] + [beta] x [Firstborn.sub.i] + [u.sub.i] (1)
where [Manager.sub.i] equals 1 if person V has ever been a manager, [X.sub.i] includes the respondent's demographic and other characteristics, and [u.sub.i] is the error term, which includes all the factors that affect whether the respondent has been a manager other than the characteristics included in [X.sub.i]. According to Sulloway, [beta] should be positive.
We estimate Eq. (1) using Ordinary Least Squares (OLS). When the dependent variable is binary, using OLS means using a Linear Probability Model (LPM). Some researchers might object that when the dependent variable is binary one should use a non-linear model such as a logit or probit or one of a variety of other models. This would be true if we were interested in estimating a log-odds ratio or the coefficients of a probit. But we are interested in estimating the marginal effect of being first-born on the probability of being a manager, and the LPM generally estimates the marginal effects well, and quite similarly to a logit or probit. All models are estimated using heteroskedasticity-robust standard errors.
Note that we do not include the AFQT score in the primary model because it is an outcome of being first-born. Including such an outcome would bias the estimated effect of being first-born. Suppose, for example, that being first-born is random. Then the coefficient on first-born shows the unbiased effect of being a manager. Also, suppose that being first-born raises one's AFQT score, and we include AFQT in the regression. The problem with this is that among persons with a particular AFQT score, being firstborn is no longer random. It cannot be, since on average being first-born raises the AFQT score. Therefore, controlling for AFQT biases the coefficient on first-born. We do, however, separately analyze the AFQT score as an outcome in itself to see the pathways through which being first-born may affect being a manager.
Another key independent variable is family size. According to economic theory, family size influences the resources available to each child. Hence, the effect of being first-born may really represent the effect of consuming a large proportion of family resources relative to later children. Therefore, family size should have a significant and independent effect on being a manager, since ability is relatively high in managerial occupations.
The drawback of including a measure of family size is that this variable may be correlated with a number of unmeasured variables that also affect occupational choice, such as the family background of the parents and grandparents, personality and physical characteristics that are inherited genetically, and others. We do not know a priori if family size is actually correlated with these variables. Therefore, we would like to compare the effect of family size with another variable that is positively correlated with family size but is likely not correlated with the other characteristics mentioned above. One such variable is the gender of the first two children. Westoff et al. (1963) observed that prospective U.S. parents often want at least one child of each gender. Thus, some couples whose first two children are girls will have a third child in the hopes of having a boy. The same occurs if the first two children are boys. But gender is random. Thus, the occurrence of the first two children being of the same gender is a random event that tends to increase family size. This is just the sort of random variation in family size we need to identify its effect on occupational choice. Therefore, we create a variable that equals one if the two oldest children in the respondent's family are of the same gender, and zero if otherwise. The coefficient on this variable should be positive if a larger family reduces the chances of being a manager. One difficulty with this variable is that the number of the respondent's siblings, their ages, and their genders were obtained from the respondent and not from his or her parents. A number of respondents either did not know or appear to have misreported their siblings' ages, based on other variables describing the family. The result is that for about a quarter of the sample, we could not be confident of the gender of the oldest two siblings. Therefore, in the regressions using this variable, we use only those respondents whose reported sibling data appear consistent with other variables describing his or her family. Also, this variable may be only weakly correlated with family size. Thus, it is possible that this variable will show a weaker correlation with AFQT and with being a manager than family size even if, when perfectly measured, this variable would show a strong correlation. We estimate regressions using family size and using the dummy for the first two children being of the same gender to see if they are both negatively correlated with the outcomes. If so, this gives some evidence that family size, as well as a random proxy for family size, reduces the chance of being a manager.
We create a variable that equals one if the respondents' mother had less than a high school education, and zero otherwise. We create a similar variable for the father, but since this variable has more missing observations, we focus on the models that control for mother's education. The effect on being first-born may differ by educational status of the mother for several reasons. One is that more educated mothers most likely make higher incomes than other mothers, or marry men with higher incomes, and therefore, when they devote more resources to first-borns, they have more resources to devote. Or, perhaps because the resource constraint is sharper with lower-income women, the relative difference in resources devoted to first- versus later-born children is greater among lower-educated women. Which effect dominates can only be determined empirically. The resources available to a family are usually measured by family income. But since this variable is missing for so many observations, we use maternal education as a proxy. Maternal education may, however, have a direct effect of respondents' occupational choices. Higher-educated mothers and their husbands are themselves more likely to be managers, which may affect the occupational choice of the respondent.
Table 1 show the means for the whole sample and is stratified by whether the respondent was first-born. Not controlling for any other characteristics, columns 2 and 3 shows that first-borns are about 2.5 percentage points more likely to have been managers at some point in their careers than later-borns. First-borns also have higher average AFQT scores, have mothers with slightly higher amounts of education, and are more highly educated themselves than later-borns.
Table 2 shows the effect of being first-born on the likelihood of being a manager after controlling for a number of demographic and family characteristics. Column 1 confirms the results of Table 1, that being first-born has a significant effect on the likelihood of being a manager, as Sulloway hypothesized. On average, first-borns are 2.51 percentage points more likely to be managers than later-borns. This finding is significant at the 10 % level.
Once we control for demographic characteristics, however, the effect of being firstborn becomes smaller and insignificant even without controlling for family size or our proxy for family size. This is likely true because Table 2 (unlike Table 3, discussed below) shows results from the whole population, most of which is not poor and whose resources may not be meaningfully constrained by family size. Column 3 shows that even controlling for demographic characteristics, the number of siblings the respondent lived with during the initial interview is a significant determinant of the likelihood of becoming a manager, while being first-born remains insignificant. More specifically, the likelihood of being a manager decreases by 1.6 percentage points for every additional sibling in the household. This supports Becker's hypothesis that access to parental resources, not birth order rank, is the primary determinant of becoming a manager.
Other results are similar to those in column 2. Non-Hispanic blacks are 19.5 percentage points less likely to be managers and Hispanics are 12.4 percentage points less likely to be managers when compared with non-Hispanic whites. Both were found to be significant at the one percent level. Across geographic regions, respondents living in North Central United States are 4.53 percentage points less likely to be managers than respondents living in the Northeast. This is significant at the five percent level. Age was found to be statistically significant at the ten percent level when controlling for family size. The likelihood of being a manager decreases by 0.51 percentage points with every additional year of age.
Column 4 shows the effect of the respondent being from a family in which the oldest two siblings had the same gender. Since this tends to increase family size, the coefficient would be expected to have the same sign as family size, which it does, though the effect is not significant. Also, the inclusion of this variable causes the coefficient on first-born to be about -0.02, the same as in column 3. These results suggest that independent increases in family size tend to lower the probability of being a manager.
As expected, Table 3 shows that the effect of being firstborn is stronger among low-income families, defined as families whose mother had less than a high school education. Firstborns are 5.6 percentage points more likely to be managers than later-borns, not controlling for any demographic characteristics. This finding was significant at the five percent level (column 1). The effect of being firstborn declined, but remained significant, when controlling for ethnicity, geographic region, gender, and age at the initial interview. First-born are 4.3 percentage points more likely to be managers than later-borns (column 2). Across ethnic groups, the probability of being a manager is 16.1 percentage points lower for non-Hispanic blacks and 9.2 percentage points lower for Hispanics when compared with non-Hispanic whites. Both findings were significant at the one percent level. There were no regional, gender, or age differences observed among respondents whose mothers had less than a high school degree.
The effect of being firstborn on the likelihood of being a manager among respondents whose mothers had less than a high school education disappears when controlling for family size (column 3). The likelihood of being a manager declines by 0.8 percentage points with every additional sibling in the household. This finding was significant at the one percent level.
Column 4 shows that the effect of family size remains when it is plausibly independent of other family characteristics. The coefficient on same-gender siblings is -0.04 and it is statistically significant at the 10 % level. Also, the coefficient is larger among women with less than a high school degree than among all women, suggesting that an independent increase in family size reduces the likelihood of being a manager the greatest among women of limited means.
To understand why the effect is eliminated by family size, we investigate the channels through which birth order might affect the likelihood of being a manager. One such channel is through cognitive development. That is, being a first-born raises the general intellect or IQ, as measured by the AFQT. In addition, a higher IQ raises the likelihood of being a manager. As such, family size can mediate either stage in the model: family size can mediate the relationship between being first born and IQ, or the relationship between IQ and the likelihood of being a manager.
Based on Table 4, family size appears to mediate the first stage. The average AFQT score decreases by 0.951 points for every additional sibling in the household, holding birth order, ethnicity, geographic region, gender and age constant. This finding was significant at the one percent level. Simply put, a household has a fixed amount of resources divided among the children. The amount received reduces with each additional sibling, which manifests in a lower IQ, which in turn reduces the likelihood of a person becoming a manager.
According to Sulloway, it is the managerial experience of being a firstborn that predisposes firstborns to becoming managers (Sulloway 1996; United States Census Bureau 2010). Therefore, firstborns from larger families should be more likely to become managers than firstborns from smaller families. Yet, as we found in column 3 of Tables 2 and 3, when holding birth order constant, a larger family makes it less likely that a person becomes a manager.
Further, if Sulloway is correct that birth order, in itself, predisposes a person to certain occupations, the effect of birth order should be independent of family income. But we found that, when not controlling for family size, the effect of birth order is strongest among lower-income families, defined as families whose mothers had less than a high-school degree. The effect persists among these families even when family size is largely due to plausibly independent reasons. This suggests that it is the availability of family resources, and not birth order itself, that affects the likelihood of being a manager.
Despite the clear results we found, a number of aspects of the data may introduce some error into the models. First, we designate a person as firstborn if he or she had no siblings born before him or her. It is possible, however, that later-borns were raised as firstborns if their older siblings left the home early in their lives. The data do not enable us to distinguish such respondents. Second, a person may be second-born but, due to much older siblings, be essentially first-born. For example, a person may be second-born with a sibling who is 15 years older. Such a respondent would essentially get the resources and parental attention of a first-born. This distinction would not be picked up in our analysis. Third, we do not distinguish between step-children, adopted children, and half-siblings, differences which may affect parental investment and subsequently the results.
In addition, a number of the variables only approximately represent their ideal measures. For example, in order to have a sufficient number of managers in the sample, we define "manager" using the Census Bureau's rather broad definition (United States Census Bureau 2010). Thus, a "manager" can manage a two-employee grocery store or a 200-person hedge fund. Also, the analysis assumes that ability in school and at work can be proxied by the AFQT but this is a crude measure of IQ. The AFQT is a brief, 20item test that measures general knowledge in mathematics and language arts. These skills are only a hint of what modern IQ tests comprise, which typically take three hours to administer. For example, the AFQT does not include measures of fluid reasoning, or impromptu problem-solving ability, working memory, or processing speed, all of which are advantageous for a manager to have.
In this paper, we investigated the claim that firstborn children are predisposed and thus more likely to become managers in their later lives due to their early experience of helping their parents take care of their younger children. We found that firstborns are indeed more likely to become managers. However, it is the result of receiving larger amounts of parental investment rather than their unique personality traits that are believed to transfer into managerial and leadership positions. Firstborns receive more time, resources, and attention from their parents before their younger siblings are born. Firstborns from smaller families are more likely to become managers because each child in a smaller family is rationed a larger portion of parental resources. Therefore, children from lower-income families, as proxied by the mother's years of education, are less likely to become managers because there are fewer resources to distribute to each child. We also found that family size appears to account for the higher measured mental ability of firstborns, which contributes to their greater probability of becoming managers.
Angrist, J. D., & Evans, W. N. (1996). Children and their parents' labor supply: Evidence from exogenous variation in family size. National Bureau of Economic Research, (w5778).
Becker, G. S., & Lewis, H. G. (1974). Interaction between quantity and quality of children. In T. W. Schultz (Ed.), Economics of the family: Marriage, children, and human capital (pp. 81-90). Chicago: University of Chicago Press.
Becker, G., & Tomes, N. (1976). Child endowments and the quantity and quality of children. Journal of Political Economy, 84(4), S143-S162.
Black, S. E., Devereux, P. J., & Salvanes, K. G. (2005). The more the merrier? The effect of family size and birth order on children's education. The Quarterly Journal of Economics, 669-700.
Blake, J. (1981). Family size and the quality of children. Demography, 18(4), 421-142.
Bureau of Labor Statistics. (2012). National longitudinal survey of youth 1979 cohort, 1979-2010 (rounds 1-24). Columbus: Center for Human Resource Research.
Claxton, R. P. (1994). Empirical relationshships between birth order and two types of parental feedback. The Psychological Record, 44(4), 475.
Earley, P. C., Northcraft, G. B., Lee, C., & Lituchy, T. R. (1990). Impact of process and outcome feedback on the relation of goal setting to task performance. Academy of Management Journal, 35(1), 87-105.
Ernst, C., & Angst, J. (1985). Birth order: its influence on personality. Social Forces, 63(4), 1117-1119. Hauser, R. M., & Sewell, W. H. (1985). Birth order and educational attainment in fall sibships. American Educational Research Journal, 22(1), 1-23.
Herrera, N. C., Zajonc, R., Wieczorkowska, G., & Cichomski, B. (2003). Beliefs about birth rank and their reflection in reality. Journal of Personality and Social Psychology, S5(l), 142.
Iacovou, M. (2008). Family size, birth order, and educational attainment. Marriage & Family Review, 42(3), 35-57.
Kessler, D. (1991). Birth order, family size, and achievement: family structure and wage determination. Journal of Labor Economics, 9(4), 413-426.
Khanam, R. (2008). Child labour and school attendance: evidence from Bangladesh. International Journal of Social Economics, 35(1/2), 77-98.
Khanam, R., & Rahman, M. (2007). Child work and schooling in Bangladesh: the role of birth order. Journal of Biosocial Science, 39(05), 641-656.
Leong, F. T., Hartung, P. J., Goh, D., & Gaylor, M. (2001). Appraising birth order in career assessment: linkages to Holland's and Super's models. Journal of Career Assessment, 9(1), 25-39.
Price, J. (2008). Parent-child quality time does birth order matter? Journal of Human Resources, 43(1), 240-265.
Shaver, R, French, J. R., & Cobb, S. (1970). Birth order of medical students and the occupational ambitions of their parents. International Journal of Psychology, 5(3), 197-207.
Sulloway, F. J. (1996). Born to rebel; Birth order, family dynamics, and creative lives. New York: Pantheon Books.
United States Census Bureau (2010). Decennial management division glossary. From https://www.census.gov/ dmd/www/glossary.html.
Very, P. S., & Prull, R. W. (1970). Birth order, personality development, and the choice of law as a profession. Journal of Genetic Psychology, 116(2), 219-221.
Westoff, C. F., Potter, R. G., & Sagi, P. C. (1963). The third child: A study in the prediction of fertility. New Jersey: Princeton University Press.
Alice Grinberg (1)
[mail] Alice Grinberg
(1) Pace University, New York, NY, USA
Table 1 Means of analysis sample Full First Later Variable sample -borns -borns R ever a manager (%) 45.8 47.7 45.2 R a manager in 2010 (%) 10.6 10.7 10.6 Armed Forces Qualifying Test score 41.9 48.6 40.0 (0-100) Number of siblings in 1979 4.0 2.5 4.4 excluding non-response First borns with siblings (%) 21.7 100.0 0.0 Last borns with siblings (%) 25.2 0.0 32.2 Non-Hispanic white (%) 49.6 55.3 48.0 Non-Hispanic black (%) 30.2 24.3 31.8 Non-Hispanic other (%) 0.7 0.6 0.8 Hispanic (%) 19.0 19.3 18.9 R lived in Northeast in 2010 (%) 14.9 16.0 14.7 R lived in North Central in 2010 23.4 21.5 24.0 (%) R lived in South in 2010 (%) 41.5 41.2 41.6 R lived in West in 2010 (%) 19.3 20.3 19.1 R Female (%) 50.7 51.6 50.4 Age at interview (years) 48.6 48.5 48.6 Father had less than HS (%) 42.9 32.8 45.8 Mother had less than HS (%) 43.5 33.2 46.4 Highest grade completed by R 13.4 13.8 13.3 Highest grade completed by Mother 10.8 11.5 10.6 Highest grade completed by Father 10.9 11.8 10.6 Oldest two siblings of same gender 48.1 48.6 48.0 (%) Table 2 The effect of being first-born on the likelihood of being a manager All respondents (1) (2) First born with at least one sibling 0.0251 * 0.00769 (1.66) (0.52) Non-Hispanic black -0.221 *** (-15.15) Non-Hispanic other -0.0842 (-1.18) Hispanic -0.150 *** (-8.67) R lived in North Central in 2010 -0.0528 *** (-2.64) R lived in South in 2010 -0.0236 (-1.29) R lived in West in 2010 -0.00102 (-0.05) R Female -0.0131 (-1.07) Age at interview (years) 0.00420 (1.54) Number of siblings in 1979 excluding non-response Oldest two siblings of same gender Constant 0.452 *** 0.377 *** (64.39) (2.81) Observations 6426 6426 Adjusted R-squared 0.000 0.039 (3) (4) First born with at least one sibling -0.0202 -0.0161 (-1.31) (-0.94) Non-Hispanic black -0.195 *** -0.228 *** (-12.81) (-13.16) Non-Hispanic other -0.0723 -0.0281 (-1.02) (-0.30) Hispanic -0.124 *** -0.113 *** (-7.00) (-5.40) R lived in North Central in 2010 -0.0453 ** -0.0619 *** (-2.26) (-2.69) R lived in South in 2010 -0.0189 -0.00580 (-1.04) (-0.27) R lived in West in 2010 0.000661 -0.0207 (0.03) (-0.83) R Female -0.0118 -0.0165 (-0.97) (-1.16) Age at interview (years) 0.00514 * 0.00441 (1.88) (1.37) Number of siblings in 1979 excluding -0.0158 *** non-response (-6.10) Oldest two siblings of same gender -0.0114 (-0.80) Constant 0.383 *** 0.392 ** (2.86) (2.48) Observations 6426 4780 Adjusted R-squared 0.045 0.036 t statistics in parentheses * p<0.10, ** p<0.05, *** p<0.01 Table 3 The effect of being first-born on the likelihood of being a manager Among respondents whose mothers had less than a high school degree (1) (2) First born with at least one sibling 0.0567 ** 0.0432 * (2.25) (1.72) Non-Hispanic black -0.161 *** (-6.88) Non-Hispanic other -0.00160 (-0.01) Hispanic -0.0927 *** (-3.63) R lived in North Central in 2010 -0.0447 (-1.37) R lived in South in 2010 -0.0116 (-0.41) R lived in West in 2010 0.0196 (0.58) R Female 0.0214 (1.14) Age at interview (years) 0.00416 (0.98) Number of siblings in 1979 excluding non-response Oldest two siblings of same gender Constant 0.363 *** 0.250 (35.08) (1.20) Observations 2624 2624 Adjusted R-squared 0.002 0.019 (3) (4) First born with at least one sibling 0.0259 0.0211 (0.99) (0.68) Non-Hispanic black -0.147 *** -0.159 *** (-6.09) (-5.68) Non-Hispanic other 0.00830 0.000212 (0.08) (0.00) Hispanic -0.0794 *** -0.0487 (-3.04) (-1.54) R lived in North Central in 2010 -0.0387 -0.0525 (-1.18) (-1.32) R lived in South in 2010 -0.00763 0.00366 (-0.27) (0.11) R lived in West in 2010 0.0211 -0.0245 (0.63) (-0.58) R Female 0.0219 0.0354 (1.17) (1.53) Age at interview (years) 0.00460 0.00831 (1-09) (1.60) Number of siblings in 1979 excluding -0.00820 ** non-response (-2.32) Oldest two siblings of same gender -0.0407 * (-1.77) Constant 0.258 0.0761 (1.24) (0.30) Observations 2624 1801 Adjusted R-squared 0.021 0.018 t statistics in parentheses * p<0.10, ** p<0.05, *** p<0.01 Table 4 The effect of being first-born on the Armed Forces Qualifying Test Among respondents whose mothers had less than a high school degree (1) (2) First born with at least one sibling 3.530 *** 2.240 * (2.85) (1.94) Non-Hispanic black -19.37 *** (-18.09) Non-Hispanic other -9.658 * (-1.96) Hispanic -14.58 *** (-12.29) R lived in North Central in 2010 0.0341 (0.02) R lived in South in 2010 -3.347 ** (-2.57) R lived in West in 2010 2.425 (1.55) R Female 0.481 (0.56) Age at interview (years) -0.288 (-1-48) Number of siblings in 1979 excluding non-response Oldest two siblings of same gender Constant 28.42 *** 55.18 *** (55.82) (5.77) Observations 2513 2513 Adjusted R-squared 0.003 0.142 (3) (4) First born with at least one sibling 0.230 2.085 (0.19) (1.45) Non-Hispanic black -17.73 *** -19.30 *** (-16.12) (-14.82) Non-Hispanic other -8.440 * -6.811 (-1.72) (-1.08) Hispanic -13.09 *** -13.85 *** (-10.85) (-9.35) R lived in North Central in 2010 0.763 -0.845 (0.51) (-0.45) R lived in South in 2010 -2.859 ** -4.127 ** (-2.21) (-2.55) R lived in West in 2010 2.632 * 1.370 (1.69) (0.70) R Female 0.556 -0.426 (0.65) (-0.40) Age at interview (years) -0.234 -0.386 (-1.21) (-1.59) Number of siblings in 1979 excluding -0.957 *** non-response (-5.87) Oldest two siblings of same gender 0.0337 (0.03) Constant 56.09 *** 62.76 *** (5.90) (5.25) Observations 2513 1749 Adjusted R-squared 0.153 0.137 t statistics in parentheses * p<0.10, ** p<0.05, *** p<0.01
|Printer friendly Cite/link Email Feedback|
|Publication:||Atlantic Economic Journal|
|Date:||Dec 1, 2015|
|Previous Article:||Regulating Cournot oligopoly with environmental externalities.|
|Next Article:||The impact of market share on health insurance premiums.|