The Impact of Parental Income on Early Schooling Transitions: A Re-examination Using Data over Three Generations
Eric Maurin[1]
CREST-INSEE, France.
Abstract:
This paper applyies new semi-parametric techniques to estimate the effects of the effects of parental income on the probability of being held back in elementary school in France. We use information on grandparent’s’ past socio-economic status and on parents’ education level to separate the parental income effectsof parental income from the effects of the unmeasured determinants of children’s performance at school that arethat are correlated with parental income. When considering the probability of being held back in elementary primary school, we find that the effects of parental poverty are is much larger than the effects of a child’s sex andor age (age within his/her class) or of the parents’ education level. Our findings suggest that -policy decisions that increase income transfers to relatively poor families have a potentially very large impact on children's early performances at school.
JEL code: J 240
The Impact of Parental Income on Early Schooling Transitions: A Re-eExamination Using Data over Three Generations
An increasing body of work based on American data suggests that the differences in children’s performance at school between childrenare not necessarily due to the family’s income levelfrom rich and poor families are not due to the differences in family income per se(see, for example, Shea, 2000 or Mayer, 1997). According to these studies, the inequalities between children from rich and poor families are mostly due to unmeasured factors that which simultaneously explain parents' income and their children's outcomes. They suggest that Iincome transfers to poor families wouldshould not have any effect on their children's performance at school.
In this paper, we come to very different conclusions using new French data,, new and instruments and estimation strategies. When considering the probability of being held back in elementary primary school[2], we find substantial differences between boys and girls or between children born during the first half of the year (the oldest in their class) and children born during the second half of the year (the youngest).But muchManA lot more differences exist, however, between children from rich and poor families than between boys and girls or children born at the beginning and the end of the year. According to our econometric analysis, a 10% increase in parental income is associated with an about a 6.5- points decrease in the probability of being held back in elementaryprimary school[3]. In France, public- policy decisions that increase income transfers to relatively poor families could have a potentially very large impact on children's early performances at school.
To obtain these results, this paper shows It shows that (a) standard cross-sectional households' surveys can be very used as very informative surveys onconcerning the schooling careers of children (i.e., children of the respondents)[4], (b) the impact of an endogenous factor (parental income) on children's schooling transitions can be analyszed without making any assumptions onabout the distribution of unobserved residuals, using the new semi-parametric estimators for qualitative response models introduced by Lewbel (2000), (c) information on parents' education and grandparents' past socio-economic status make it possible to correct for any biases that may arise from errors in the measurement of parental permanent income and to test for the existence of hereditary determinantsofin education and income.
The Iimportance and Ddifficulties of Iidentifying the Iimpact of Iincome
There are several reasons why parental income is potentially a very important determinant of children's performance at school. The most basic reason is perhaps that rich parents can purchase better food, better housing and medical care. In other words, they can purchase more of all the basic goods and services that favour children's development and help them perform well at school. Assuming that the parental demand for these specific goods and services actually increases with parental income, we should observe a substantial impact of income on children's performances.
It is very important to understand paramount to have a good understanding of the actual income elasticity of children's performance at school. Defining a policy that favours equal educational opportunities is directly dependent on this understanding. The young children of families with little financial means often have a difficult time when they start school. They seem condemned from the start to encounter the same dead -ends as their parents did. How can the social costs linked to the persistence of unemployment and poverty across generations be avoided ? What kind of policy is needed? Should a policy of transferring resources to the disadvantaged parents be adopted or should another kind of support be created for the advancement of their children's education? A very important issue is indeed the relative effectiveness of income transfers and direct intervention programs in augmenting the human capital of poor children.
These simple questions are much more difficult to answer than they may seem. A large body of considerable amount of research exists, which thatanalyzyses the relationships between parents' social status and their children's attainments (see the survey by Haveman and Wolfe, 1995). Rare, however, are the studies that have gone beyond the naive statistical analysis to test if the relationship between parents' income and their children's achievements is one of cause and effect.
The first challenge is to obtain a direct measurement of parents' income while the children are still in school. In France, the analysis of educational inequalities is based almost exclusively on what children have said - after becoming adults - on the kind of occupation their fathers had during their adolescence[5]. To our knowledge, no studies to date have been conducted on French data that link the inequalities of educational performance to the inequalities of family income[6]. The situation is very different in the United States where the Panel Study of Income Dynamics (PSID) or the National Longitudinal Survey of Youth (NLSY) have made it possible to obtain direct measurements of parents' income at the time their children arewere still in school[7].
The second challenge is to sort out the income effectsof income from the effects of unmeasured factors that are correlated with income. When unobserved factors (ultimately, hereditary traits) start determining both the parents' results as workers and the children's educational capacities, the children from rich families willdo better at school, even if their parents' income has no direct effect on their performance. To isolate the income effectsof income,, at least one factor of parental income variation must be identified that has nothing to do with the children's educational capacities.
A related issue is to correct for biases that arise from measurement errors. Our French survey only provides one single-year measurement ofof parental income. Because of transitory variations in earnings, single-year measurements for parental income only represent an approximation for the permanent income thathas actually constrainsed parental behaviour and determinesd children's material well-being/welfare duringtheir early childhood. To properly estimateproperly the true income effectsof income based on the short-term measurement of parental income, we also have to find instrumental variables must also be found, which arethat are correlated with the permanent component of parental income, not and uncorrelated with its transitory component. In this paperarticle, our goal is to provide an original answer to these problems and to test the consistency of our response compared to those from previous studies.
Re-evaluation Using New Data and Techniques
The rare studies that have tried to confront head-on the problems of identifying the '' true '' effects of parentals' income, are mostly American. These studies have heavily relied on the richness of the American PSID and NLSY data. In France, longitudinal data do not exist that compare with those of the PSID or NLSY. On the other hand, most of the national surveys conducted by the French statistical office (hereafter, INSEE, Institut National de la Statistique et des Etudes Economiques), contain relatively detailed information on respondents' children, including their sex, the year and month they were born and their grade in school. From these data, it is possible to make files on the respondents' children, containing information on (a) whether the children have been held back at school, and (b) their family situation, giving, in particular, their parents' income level. Notice that this income information is provided first-hand from the parents (i.e. the respondents).
In other words, standard data from a standard statistical office make it possible for family income to be directly measured while their children are still in schoolschool is in session. A supplementary advantage ofto the specific INSEE survey used infor this paper is that it contains high-quality, detailed information about the past occupation of the respondents' parents, that is meaning the children's grandparents. For the remainder of this study, we will mainly use this information to correct forfor biases that ariseing from measurement errors and to identify the parental income effects of parental income. Our basic identification assumption will beis that the unmeasured factors that simultaneously determine family income and school performance do not survive past two generations. We will develop a simple structural framework in which it is possible to test this identifying assumption.
Information about the respondents' social origins are also available from the PSID data. To our knowledge, this information has never been used to identify parental income the effects of the parents' income. This is perhaps due to the poor quality of the data collected on social origin.
As a matter of fact, the American studies that analysze income'sthe '' “true” ''income effects of income on children's outcomes usually use information provided by the parents' source of income (for example, see Shea 2000 or Mayer 1997) or by the variations in the income over time or within dynasties [8](Blau, 1999). In the first case, the children's outcomes are assumed to be sensitive to their parents' income level, but not to how theythe income is earned their income . In the second case, the identifying assumption is that the factors that simultaneously determine the parents' income and their children's performance do not vary over time or within dynasties[9].
This paper is organized in the following way. The first section is a review of recent literature on the true income effects of income. Section 2 develops a simple theoretical modelof of parental investment in young children's human capital. Our objective is to obtain a framework for our econometric analysis. Section 3 presents the econometric strategy, and sSection 4 describes our French data. The results are presented in In sSection 5, we present our results. The last section explains how our results compare to US recent US estimates ofonthe income elasticity of children's early performance at school.
I Literature Overlook
From an empirical viewpoint, there is a vast body of research showing that children's outcomes are correlated with parental income[10]. But oOnly a few studies, however,have tried try to deal with the potential endogeneity of parental income.
One of the most influential studies is perhaps that of Scarr and Weinberg (1977), which compares adopted and biological children's outcomes[11] . Studying a sample of families from Minnesota, they found no correlation between parental income and adopted children's outcomes, whereas a positive correlation was found for biological children. The children's outcomes wereas thus not found to be linked to parental income, as such, but rather to genetic factors, that were not transmitted in adoption cases. One of the A problems with Scarr and Weinberg's approach is that their sample of adoptive families iswas very small (about 100) and homogenous (only relatively well-off families). Another problem with their approach is that adoptive parents may treat their children differently than average biological parents .
S. Mayer (1997) also analyzsesesthean American case, but usess very different estimation strategies. She assessess that capital income is not as strongly correlatedwith with the parents' education level as other forms of income. From there, S. Mayer goes goes on to make the assumption that capital income is not as less strongly correlated with parents' abilities (observed or unobserved) than other forms of income. Under this assumption, the variations in capital income makeke it possible to better identify the '' true '' income effects on children's performance at school better than the other forms of income variations[12] .. And yet, Mayer findsinds that the capital income hasve less effect on some children's outcomes,such as teenage childbearing, than other forms of income on some children's outcomes, such as teenage childbearing. According to the author, this result suggests that the '' true '' income effectsisare, in reality, much less significant than the apparent effects. For Mayer, it is not the income, per se, that matters, but the parents' unmeasured capacities that are correlated withwith their income.
At least two main weaknesses can be identified in her arguments. First, independent from children's behavioral problems, she finds found that capital income has just as much effect as work income on the number of years that children stay in schoolas work income on children's number of years of schooling, or subsequently on their wages (see Table 5.1, page 84). These results are difficult to reconcile with her main thesis.
Second, it is difficult to affirm confirm that capital income effects are the best representation of '' true '' income effects, based on the only basison the fact that capital income is the least correlated to the parents' education level. As university degrees are less useful on the financial market than on the job market, someone from a family closely linked to the financial market has less incentive and is less likely to obtain a higher degree than other children with similar schooling abilities. That could explain the stronger correlations between work income and degrees than capital income and degrees, regardless of all the other considerations concerning about measured or unmeasured capacities. Furthermore, families that access financial markets are a priori a priori much less representative of families as a whole than families that rely on their work incomes or unemployment benefits.
In her book, S. Mayer offers other strategies for identifyingthe '' true '' income effects. Most notably, she compares the income effects received before and after the measurement of children's outcomes. She interprets the net effect of income received after the measurement of the outcomes as the effect of the permanent factors, which simultaneously affect parental income and the children's performance.
Here again, the results obtained are ambiguous: the income received after the measurement of the outcomes appears to have a significant net effect on the children's reading tests or on the probability of them leaving school before getting their high school diplomas. However, post-outcome parental income has no significant effect on mathematics tests, the number of years spent in school, degrees obtained or the wages earned after leaving school. Notice that this second strategy assumes that the variables that affect both parental income and their children's outcomes are constant over time (i.e. have the same values before and after the measurement of the outcomes).
In another recent contribution, Blau (1999) analyszes children's scores on various development assessmentstests, which measureing academic achievement, verbal aptitude, memory performances, behavioral problems orand motor development. We should emphasize that these items do not cover end-of-the-grade test scores for school-aged children and are conceptually different from the measurement of early schooling performances analyszed in this paper. Blau (1999) estimates some models using a measurement of income that corresponds to the calendar year prior to the year of the development assessment tests. He also presents estimates using average parental income over about an abouta twelve -years -period. He finds that standard OLS estimates of using the single-year income measurement are about twice as small as the OLS estimates using the permanent income measurement.
To correct for endogeneity biases, Blau (1999) uses strategies that are based on the variations of single-year, income measurementsof income over time. He compares children's performances during high-income and low-income periods. In thatis case, no significant effect isis found: the variations ofin single-year income over time do not help hardly explain the variations in children's performances. Blau (1999) also compares pairs of cousins' performances (i.e., the mothers are sisters). Within this frameworkis, the estimated effects of permanent income are stronger than the effects obtained using the OLS method.
One problem inwith Blau's approach is that he limits his study to is constrained to only examininge the impact of transitory variations ofin income, or to only focuses on small, not very representative, sub-samples of cousins' pairs. His approach also assumes that some unobserved determinants ofin income variations are not simultaneously the explanatory factors of for the variations in test scores. This approach is only valid when some unobserved factors have the same properties as good instrumental variables.