Nina Guyon
email: nina.guyon@nus.edu.sg

Elise Huillery
email: elise.huillery@dauphine.fr

Séverine Chauvel

Denis Cogneau

Marie Duru-Bellat

Andrew Foster

Marc Gurgand

Emeric Henry

John Ham

Karla Ho

Rachel Kranton

Julien Labonne

Eric Maurin

Jessica Pan

Imran Rasul

Eve Shira

Research group "Educational policies" Biased Aspirations and Social Inequality at School: Evidence from French Teenagers

Keywords: I24, I21, J15, O15 School Aspirations, Social Stereotypes, Social Inequality, Aspirations failure

This paper provides the rst empirical evidence that adolescents' aspirations are socially biased not only because of taste or information issues, but also for psychological factors in line with social stereotypes. Using unique survey data combined with French administrative data, we nd large social inequalities in aspirations between 14-year-old classmates with equal achievement. We show that these inequalities are mainly due, rst, to biased dierences in awareness of existing academic tracks after junior high, and, second, to biased feelings about one's ability to pursue these tracks. We nd indeed that low-SES students underestimate their current academic capacity compared to their equally-achieving high-SES classmates, and that all students overestimate the inuence of social origin on future academic success.

The data also show that social inequalities in educational aspirations are not driven by dierences in professional aspirations, suggesting that they cannot be explained by students anticipating dierent returns on the labor market or by dierences in preferences for professional activities linked to social identity. Educational aspirations are thus socially biased, which matters as we also show that they do aect later school outcomes. Overall, such biases therefore prevent low-SES students from reaching their best educational outcomes in ways that are not compatible with maximized utility. The paper thus provides evidence of an aspirations failure that reinforces social inequalities at school, and calls for self-esteem building policies to strengthen the aspirations of the disadvantaged.

Introduction

Aspirations are the goals that individuals set for themselves in the future. Following the seminal paper of [START_REF] Appadurai | The Capacity to Aspire: Culture and the Terms of Recognition[END_REF], aspirations should be considered as the capacity to set appropriate goals for the future, i.e. goals in line with one's potential and that lead to the best possible outcome. The emergent theoretical literature on aspirations argues that the capacity to aspire is inherently unequal between rich and poor [START_REF] Appadurai | The Capacity to Aspire: Culture and the Terms of Recognition[END_REF][START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF][START_REF] Génicot | Aspirations and Inequality[END_REF][START_REF] Dalton | Poverty and Aspirations Failures, The Economic Journal[END_REF], see Section 2 for more details).

An aspiration-based poverty trap then occurs when biased aspirations induce suboptimal investments and eorts to better one's life, resulting in poor outcomes compared to that which would have been achieved with adequate aspirations, in turn leading to lower aspirations, etc. This paper provides the rst empirical evidence that adolescents' aspirations are socially biased due to psychological factors in line with social stereotypes, and that such biases reinforce social inequalities in educational attainment in ways that do not reconcile low outcomes and maximized utility. After a preliminary investigation of the eect of aspirations on later school outcomes, we provide a measure of social inequalities in aspirations and explore the mechanisms leading to these inequalities. This paper does not preclude that low socio-economic status (hereafter SES) students have good reasons to aspire lower than high-SES students, because they do. Instead, we question whether they correctly assess this objective disadvantage, i.e., whether the way students set their aspirations is fully rational. We provide evidence that they do not by exploring the importance of two mechanisms driving aspirations, namely awareness of existing academic tracks, and feelings about one's academic potential.

In France, the school curriculum is the same for all students up through junior high, but then gives way to a stratied system of high schools, where students pursue either an academic or a vocational track. At the end of junior high, students thus reach the rst crossroads of their educational paths: based on their preferences, their parents' preferences, their achievements, and their teachers' opinions, a choice is made at the end of 9th grade that will, with some degree of irreversibility, determine their future academic and professional paths. In this paper, we study a sample of 3,415 students in their last year of junior high (i.e. 9th grade) in 59 French schools. We measure students' educational and professional aspirations at the beginning of 9th grade through a survey designed specically for this study. To analyze the underlying mechanisms through which these aspirations are set, students were rst asked to list all the existing tracks they are aware of (hereafter salient tracks) then, among these, which they feel capable of pursuing (hereafter attainable tracks), and nally, among the latter, which they would prefer to pursue (hereafter preferred tracks). To the best of our knowledge, this paper is the rst to de-construct preferred options as embedded in the zone of self-perceived attainable and salient options (aspiration window in Ray's terminology). The survey also measures their scholastic self-esteem and beliefs about the inuence of social origin on future academic success, which allows us to investigate the importance of social stereotypes in explaining social dierences in aspirations.

Social inequalities in educational aspirations would not matter if aspirations did not inuence later outcomes. To this regard, we rst examine the relationship between aspirations at the beginning of grade 9 and later school outcomes, and discuss the extent to which this relationship is driven by confounding factors. Our survey and administrative data allow us to control for three categories of confounding factors: school-neighborhood quality (using class xed eects), parents' SES and immigration status, and students' academic capacity at the beginning of the year. Academic capacity includes both cognitive and non-cognitive skills of students that can predict their future academic outcomes; our exceptionally rich survey data allow us to control extensively for this dimension. 1 Although we do not have an experimental source of variation in aspirations that would allow us to perfectly identify the causal impact of aspirations on school achievement, we observe that once academic capacity and class xed eects are included, 2 adding rough or detailed controls for parents' SES and immigration status does not aect our estimates of the remaining correlation between aspirations and later academic outcomes. This result is not due to poor quality measures as these variables are strong predictors of our outcomes and are highly correlated with aspirations in the rst place. Moreover, we also nd that aspirations are still correlated with later outcomes within SES (if anything, the eect is bigger for low-SES), or when we control for teachers' grades on top of everything else. Given these results and the quality and variety of our controls, we argue that these estimates can reasonably be considered as causal.

We nd that, among equally-achieving classmates with similar parental SES and immigration status, aspiring to attend an academic high school (compared to a vocational high school or having no aspiration) at the beginning of grade 9 induces signicant increases in both the annual average grade and the test score at the end of grade 9 of respectively 0.17 and 0.22 standard deviation, as well as increases the probability of entering an academic high school in grade 10 by 37 percents. These estimates measure the impact of aspirations over a maximum of one year. Our data are thus consistent with the hypothesis that aspirations are not simply a consequence of realized outcomes, but also a cause of later outcomes. As the existing literature on the impact of aspirations on future outcomes is currently quite scarce (see Section 2 for a 1 Our survey data include: two academic tests given one week apart, a Raven Progressive Matrices test to measure uid intelligence, a questionnaire measuring self-perception of behavioral conduct, a measure of the eort put into the two academic tests as an additional proxy of dutifulness, and nally, indicators of whether the student is female, skipped a grade, or repeated a grade. review), these new estimates contribute to furthering current knowledge on this topic.

Secondly, we nd clear evidence of large social dierences in aspirations that are not only due to dierences in academic capacity and school environment. For instance, taking these dimensions into account, low-SES students are still twice more likely to prefer vocational high school than high-SES students. One might thus question whether students set their aspirations in a way that allows them to achieve their best possible outcome -i.e. their highest possible level of welfare-given the constraints they face: are low-SES students indeed right to aspire lower? Likely, they are. Unsurprisingly, we nd, for example, that low-SES students make less academic progress over the year compared to their high-SES classmates who have the same aspirations and the same academic capacity in the rst place. More generally, even among students with equal academic potential, having dierent aspirations may still lead to the best possible outcome if students have dierent liquidity constraints in terms of the cost of education, dierent actual returns to education, or identity concerns. However, this does not mean that students do set their aspirations at the level that will lead them to their best possible outcomes. This is why this paper asks the question: do low-SES students correctly assess their objective disadvantages?

In answering this question, our paper is the rst to provide empirical evidence of two key mechanisms of the theoretical literature on aspiration-based poverty traps leading to biases in adolescents' aspirations, namely levels of awareness of existing academic tracks and feelings about one's academic potential. Specifically, we show that low-SES students have dierent salient and attainable tracks than high-SES students, even once academic capacity and class xed eects are controlled for. Relative to equally-achieving high-SES classmates, low-SES students are, for instance, 7% more likely to mention vocational high school and 15% less likely to mention a master's degree as part of the existing options. And once salient tracks are controlled for, low-SES students are still 4% less likely to state that academic high school is attainable, and 15% less likely to state that a master's degree is attainable, relative to equally-achieving high-SES classmates. Interestingly, these social dierences in attainable and salient tracks concern both high, medium, and low-achieving students.

While dierences in awareness of existing tracks can directly prevent low-SES students from reaching their best possible outcomes, it is necessary to further examine whether students correctly assess their attainable tracks, which involves both current academic capacity and future academic progress. We nd evidence that they fail at both tasks. First, students exhibit excessively fatalistic views on the extent to which future academic success is determined by social background, overestimating this link compared to reality. Secondly, low-SES students -in particular the high-achievers -have lower current scholastic self-esteem compared to equally-achieving high-SES classmates. More specically, our measure of self-esteem explains 25% of the decit in high-achieving low-SES students mentioning a master's degree among their attainable tracks. These ndings highlight the role of social stereotypes in shaping students' perceptions and cognition, with important consequences for educational aspirations and later outcomes.

We then show that social dierences in academic aspirations cannot be explained by dierences in professional aspirations. Overall, academic aspirations are not consistent with professional aspirations, suggesting that teenagers do not see education as a pure investment for future employment, perhaps due to an ignorance of specic educational pathways to jobs. While this is true for high-SES students, it is stronger for low-SES students. For instance, low-SES students are as likely to prefer a job that requires a master's degree as their equally-achieving high-SES classmates, while they are 26% less likely to prefer to pursue a master's degree. Similarly, they are only 11% more likely to prefer a job that does not require a higher education, while they are 69% more likely to prefer nding a job right after high school. At 14 years-old, social groups dier much more in the ways they plan to invest in their educations than in the ways they think about their future occupations, suggesting that social inequalities cannot be explained by students anticipating dierent returns on the labor market or by dierences in preferences for professional activities linked to social identity.

These results thus cast further doubt on the fact that students set their aspirations at the exact level that will lead them to their highest possible level of welfare.

Finally, once socio-economic status is taken into account, students from immigrant families notably have generally more ambitious aspirations (both educational and professional) and similar academic paths compared to students from non-immigrant families, consistently with the existing literature.This result suggests that the aspiration-based educational trap demonstrated in this paper concerns socio-economic inequalities, but not necessarily ethnic inequalities.

Our paper sheds light on several dierent strands of the literature. First, it adds to the literature concerning the intergenerational transmission of social inequalities. Numerous studies have shown that family background inuences student academic achievement through a variety of channels including: inherited ability [START_REF] Black | Why the Apple Doesn't Fall Far: Understanding Intergenerational Transmission of Human Capital[END_REF], parental involvement [START_REF] Avvisati | Getting Parents Involved: a Field Experiment in Deprived Schools[END_REF], and school and neighborhood quality [START_REF] Goux | Close neighbours matter: neighbourhood eects on early performance at school[END_REF][START_REF] Chetty | How does your kindergarten aect your earnings? Evidence from Project STAR[END_REF][START_REF] Chetty | The eects of exposure to better neighborhoods on children: Evidence from the Moving to Opportunity Experiment[END_REF]. This paper explores a dierent and complementary channel of transmission, namely educational aspirations, and is thus highly related to Figlio et al.'s paper (2016) on the eect of long term orientation on educational performance. Second, it brings new evidence on the social determination of aspirations, a topic on which empirical studies remains scarce (Sewell et al. 1969, Sewell et al. 1970, Jencks et al. 1983[START_REF] Hoxby | The Missing "One-Os[END_REF][START_REF] Pasquier-Doumer | Aspiration Failure: A Poverty Trap for Indigenous Children in Peru?[END_REF]. Thanks to our rich survey data, we are able to explore detailed measures of aspirations in the short, medium, and long term, as well as shed light on several mechanisms through which aspirations are set. Our paper also adds to the empirical literature on the consequences of aspirations on economic outcomes [START_REF] Oyserman | Possible Selves and Academic Outcomes: How and When Possible Selves Impel Action[END_REF][START_REF] Beaman | Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India[END_REF][START_REF] Bernard | Learning with Others: A Field Experiment on the Formation of Aspirations in Rural Ethiopia[END_REF][START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF]) by exploring their eects on academic progress and track assignment. This paper also contributes to the behavioral economics of education, which highlights various biases in the ways students make decisions on education. Our ndings are particularly relevant to the literature on the role of social identity in economic behavior [START_REF] Akerlof | Economics and Identity[END_REF][START_REF] Akerlof | Identity and Schooling: Some Lessons for the Economics of Education[END_REF], Ho and Pandey 2006, 2012;[START_REF] Fehr | Tastes, castes, and culture: The inuence of society on preferences[END_REF][START_REF] Ho | Equilibrium Fictions: A Cognitive Approach to Societal Rigidity[END_REF]and 2016). Thanks to the ability to distinguish between salient, attainable, and preferred tracks, and to measure scholastic self-esteem and social fatalism 3 , we are able to show that identity-based preferences are formed partly on the basis of dierential awareness of existing tracks and dierential self-perceived academic potential, casting doubt on the optimality of these preferences.

The policy implications of this paper are important. Since low-SES students have lower aspirations than high-SES students, they are more likely to suer from the negative consequences of low aspirations combined with the negative consequences of their social origin. We consequently see a rapid divergence in school outcomes between high-and low-SES students. Educational interventions aimed at reducing social inequalities in academic performance by improving school quality (e.g. extra-tutoring or reduced class sizes) in disadvantaged areas, are therefore insucient to close the gap. They must instead be combined with actions that strengthen the capacity to aspire, otherwise failure in aspirations will continue to dampen the academic outcomes of the disadvantaged. That said, strengthening the capacity to aspire is not equivalent to raising aspirations for all low-SES students, which may in fact produce worse outcomes among the weakest students [START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF]. Reducing social inequalities in education requires an adjustment in aspirations that brings them in line with students' actual potential, independent of their social background. This may in turn imply downward adjustments for low-achieving students and upward adjustments for medium and high-achieving students, especially low-SES students.

The remainder of the paper is organized as follows. Section 2 discusses the existing literature on aspirations, while Section 3 presents the data. Section 4 rst introduces our empirical strategy for estimating the impact of aspirations on later school outcomes and then presents our results. Similarly, Section 5 rst presents our empirical strategy for both estimating social dierences in aspirations and disentangling some mechanisms leading to these dierences, and then describes our results. Section 6 discusses the implications 3 We dene social fatalism as the overestimation of the inuence of social origin on future academic success compared to its real inuence.

of our results on the optimality of aspirations in the short and long terms. Section 7 concludes.

Related Literature

This section presents the literature related to our paper. We begin with a review of emerging theories on aspiration-based poverty traps. We then present the empirical literature related to our two sets of ndings: the consequences of aspirations on economic outcomes, and the social determination of aspirations. Finally, we present the literature on the optimality of socially-dependent preferences.

Theories on aspiration-based poverty traps

The theoretical literature on aspirations emerged a decade ago at the intersection of anthropology and economics [START_REF] Appadurai | The Capacity to Aspire: Culture and the Terms of Recognition[END_REF][START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF]. According to Appadurai and Ray, the capacity to aspire is a specic future-oriented instance of culture that is socially determined because experiences are formed in the thick of social life. Poor people's possible selves are dierent from rich people's possible selves because individuals use comparisons and similarities with peers and relatives in forming their aspirations.

An aspirational trap occurs when low aspirations induce low investments and eorts to better one's life, resulting in poor outcomes. Embedding this theory in a macroeconomic growth model, Genicot and Ray (2015) show that the social determination of aspirations can be the source of divergent income inequalities 4 .

In this rst class of models, social background has a direct impact on aspirations. [START_REF] Dalton | Poverty and Aspirations Failures, The Economic Journal[END_REF] develop a dierent model in which aspirations are not inherently socially determined but still contribute to a poverty trap: at a given initial aspiration level, a poor person will choose a lower level of eort than a rich person because poverty imposes external constraints that make eort less productive. This lower eort induces lower realized outcomes, which in turn results in lower aspirations in the next period. Hence, the aspiration level of the poor person diverges from the aspiration level of the rich person, as do the realized outcomes, starting a vicious cycle that locks individuals in a poverty trap.

These dierent theories of aspiration-based poverty traps draw on a common dynamic, which cycles from aspirations to eort, realized outcomes, and back to aspirations. They dier, however, in terms of the impact of social origin: either directly on aspirations [START_REF] Appadurai | The Capacity to Aspire: Culture and the Terms of Recognition[END_REF][START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF][START_REF] Génicot | Aspirations and Inequality[END_REF], or on returns to eort [START_REF] Dalton | Poverty and Aspirations Failures, The Economic Journal[END_REF]. Our paper provides the rst empirical evidence on these theories.

4 Aspirations are inuenced by a society-wide distribution of income within the current generation. In relatively equal societies, aspirations are more equally distributed and easier to satisfy, which creates convergence. In contrast, in unequal societies aspirations of the poor are more often frustrated, inducing lower aspirations, investment and growth for the poor, and widening society-wide inequalities.

Empirical evidence on the impact of aspirations on economic outcomes

To the best of our knowledge, four papers provide experimental evidence on the impact of aspirations on subsequent behavior and outcomes [START_REF] Oyserman | Possible Selves and Academic Outcomes: How and When Possible Selves Impel Action[END_REF][START_REF] Beaman | Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India[END_REF][START_REF] Bernard | Learning with Others: A Field Experiment on the Formation of Aspirations in Rural Ethiopia[END_REF][START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF]. To draw a causal link between change in aspirations and change in outcomes, the eect of the randomly assigned treatment on realized outcomes has to go entirely through its eect on aspirations.

In [START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF], the treatment 5 credibly aects outcomes through parental aspirations. Students' aspirations were not, however, observed as the experiment was not designed to measure the impact of students' aspirations on later eort and outcomes. The impact of this intervention may go entirely through parents' preferences and decisions, with little or no inuence on the relationship between students' aspirations and their eorts at school.

6

In the other experiments, aspirations do credibly play a central role in changing behaviors and outcomes, although additional eects of the intervention may contribute to the improved outcomes in ways that may not be related to aspirations. For example, in [START_REF] Oyserman | Possible Selves and Academic Outcomes: How and When Possible Selves Impel Action[END_REF], the intervention 7 aected both aspirations and the capacity to perform better in school. In [START_REF] Bernard | Learning with Others: A Field Experiment on the Formation of Aspirations in Rural Ethiopia[END_REF], Ethiopian farmers were invited to watch video documentaries about people who had succeeded in agriculture or small businesses which included both a role model eect and an informational eect on how to succeed. Finally, [START_REF] Beaman | Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India[END_REF] show that the reservation of leadership positions for women on Indian village councils increased both girls' aspirations and their educational attainment. However, Chattopadhyay and Duo (2004) show that this policy also aected public good provision -increasing, for instance, the number of drinking water facilities -which could explain the increase in school participation of girls (given that girls are generally responsable for water duties).

To the best of our knowledge, there is no intervention that aects only students aspirations with no eect on other elements that potentially contribute directly to better school outcomes.

Empirical evidence on the social determination of aspirations

The empirical literature showing that aspirations are inuenced by individuals' social background is quite limited. The rst evidence was provided in the 1960s using US data in what is known as the Wisconsin Model: at equal IQ test score and rank in the class, 11th grade students whose fathers' had a low education level 8 were less likely to aspire to and reach college than those whose fathers' had a higher education level (Sewell and al. 1969). Additional papers have extended this rst result using broader populations and better measurements of academic achievement -both a test score and teachers' grades (Sewell et al. 1970, Jencks et al. 1983). More recently, [START_REF] Hoxby | The Missing "One-Os[END_REF] show that among the highest-achieving US students (top 4% on college assessment test scores 9 ), low-income students are less likely to apply to selective universities than high-income students, even if the cost of attending a highly selective university would not have been greater.

10 Finally, Pasquier-Doumer and Risso-Brandon (2015) examines dierences in occupational aspirations between indigenous and non-indigenous children at age 12 in Peru, as well as the eect of aspirations on educational outcomes. They show rst that being indigenous is not a signicant determinant of occupational aspirations while socioeconomic status is, and second that the level of aspiration in turn impacts progress in language acquisition. In the French case, sociologists have developed a related literature on social inequalities in track assignment: low-SES French students are less likely to enter selective tracks than high-SES students who have similar academic performances (Girard and Bastide 1963[START_REF] Duru-Bellat | Le fonctionnement de l'orientation. Genèse des inégalités sociales à l'école[END_REF], Davaillon and Nauze-Fichet 2004). Yet there is little evidence on mechanisms, either teacher discrimination, parental preferences, or pupil inhibition, as students' aspirations are not observed.

Our paper contributes to this literature by using unique data on students' aspirations that allow us to decompose aspirations into salient, attainable, and preferred tracks. This is the rst paper providing evidence that social dierences in aspirations are driven by dierences in awareness of existing tracks and feelings about one's potential.

Optimality of socially-dependent preferences

The identity literature provides various explanations for socially-dependent preferences, leading to dierent views on their optimality in terms of welfare. A rst class of theoretical models reconcile low economic outcomes and maximized utility. Individuals may increase their utility by investing in identity-reinforcing attitudes, because it limits disruption and maintains a sense of unity (Akerlof and[START_REF] Akerlof | Economics and Identity[END_REF][START_REF] Akerlof | Identity and Schooling: Some Lessons for the Economics of Education[END_REF].

8 The sample was constructed based on a survey done in 1957 including all high school seniors in Wisconsin. Out of this database, only 929 male high school seniors whose fathers were farmers in 1957 and who accepted to respond to a survey in 1964 are included in the sample. 9 Their paper thus focuses on a very specic group of high-school students, whereas our paper provides results on the entire distribution of middle-school students.

10 [START_REF] Hoxby | What High-Achieving Low-Income Students Know About College[END_REF] then provide evidence of three potential mechanisms that can explain this gap: i) resource- intensive colleges and universities net prices were dicult to ascertain, ii) students found it dicult to navigate the vast quantity of information about college attributes, and iii) the application process itself appeared daunting. In Ray's setting, such mechanisms would be reected by social dierences in preferred tracks, and not by dierences in attainable tracks. While in our context, in which we are studying aspirations of the whole distribution of end of middle-school students in France, we nd large dierences in attainable tracks and thus focus on providing evidence of some mechanisms leading to these dierences.

Identity-reinforcing attitudes are also a way to invest in one's social network so as to secure interactions and cooperation in the future [START_REF] Fryer | An Economic Analysis of Acting White[END_REF][START_REF] Fang | Dysfunctional Identities" Can Be Rational[END_REF][START_REF] Fryer | A Model of Social Interactions and Endogenous Poverty Traps[END_REF]), or to signal and arm values and beliefs and avoid cognitive dissonance [START_REF] Bénabou | Identity, Morals and Taboos: Beliefs as Assets[END_REF]. Finally, resisting education may be a reaction to the threat of losing one's culture (Carvalho and Koyama 2014). In the view of these papers, identity-based behaviors may be detrimental in terms of economic outcomes but still optimal for individuals, since they obtain the highest utility from economically-lower, identity-conformed outcomes.

Another class of papers, from the behavioral economics literature, sees the role of identity as driven byinecient factors, leading to sub-optimal outcomes. Avery and Kane (2004) and Oeropoulos and Dunn (2013) nd that low investment in higher education by low-income students can partly be attributed to misinformation about its returns and costs. Ho andPandey (2006, 2012) and [START_REF] Fehr | Tastes, castes, and culture: The inuence of society on preferences[END_REF] show that identity shapes preferences due to stereotype susceptibility and point to the risk that endogenous preferences perpetuate social inequalities. [START_REF] Ho | Equilibrium Fictions: A Cognitive Approach to Societal Rigidity[END_REF] build a theoretical model of an identitybased poverty trap where beliefs related to social inferiority aect the perceived probability of success (or self-condence) and so change behavior in ways that make the beliefs come true. In a subsequent paper, [START_REF] Ho | Striving for Balance in Economics: Towards a Theory of the Social Determination of Behavior[END_REF] describe how social identity creates mental models, aecting how an individual experiences what he experiences, and making preferences, perceptions, and cognition subject to deep social inuences. Our paper contributes to this literature by isolating the role of information and perception in shaping social dierences in educational preferences.

3 Context and Data

Background on the French education system

The French education system is such that the curriculum is the same across schools from kindergarten up until the end of junior high. Junior high runs from grades 6 to 9. After nishing junior high, 60% of pupils enroll in an academic high school while 40% of pupils enroll in a vocational high school [START_REF] Afsa | La moitié d'une génération accède à l'enseignement supérieur[END_REF].

Academic high schools are more selective than vocational high schools: the distributions of test scores at the end of grade 9 show that students who enroll in an academic high school have much better academic performances that students who enroll in vocational high schools (Online Appendix Figure 1). Academic and vocational high schools also dier in their link to higher education. Academic high schools do not provide a professional degree, such that students are expected to go on to some form of higher education.

In contrast, vocational high schools provide students with a professional degree, allowing them to nd work with no further education. In fact, 92% of students who graduate from an academic high school enroll in higher education 11 , while only 25% of students who graduate from the 3-year vocational track get some higher education, while no students in the 2-year vocational track enroll in higher education 12 . Early specialization in vocational high schools makes changing tracks later dicult, and many higher education pathways are not accessible to students in vocational high schools.

The process of track assignment starts in March and ends in June of grade 9 (see more details on the French educational system and the procedure of track assignment in Online Appendix). Students thus reach an important crossroads in ninth grade in terms of their educational paths: the high school decision is a crucial milestone with important consequences for nal educational and occupational attainment.

Sample

Our data concern 59 junior highs from the Paris metropolitan area that are not representative of Parisian junior highs. Our sample diers from the national junior high population in terms of social composition as shown in Online Appendix Figure 2. This implies that our results may not be generalizable to all areas of France. To construct our sample, we merged data from two sources: (i) a research survey administered to ninth graders in the sampled junior highs in November 2012, and (ii) administrative data collected by the statistical unit of the Ministry of Education. Our nal matched sample consists of 3,415 students, i.e. nearly half of the students registered in grade 9 in the sampled junior highs. Our sample is thus not representative of the original junior high population, so our ndings on the role of aspirations may not generalize to all students. That said, our nal sample looks quite similar to the initial population and is not statistically signicantly dierent in terms of family background, test scores in June 2013, yearly grade average, gender, probability of having repeated a grade, or probability of having skipped a grade.

In summary, the administrative data provide information on parental SES, teachers' grades averaged over grade 9, score on the national exam taken at the end of grade 9 (in June 2013), and track assignment at the beginning of grade 10 (in September 2013). The survey data provide information on aspirations, academic capacity in November 2012, parents' immigration status, students' self-esteem, and students' beliefs on social fatalism. Both datasets also include gender and age. The survey questionnaire was administered at the beginning of grade 9 in order to capture students' aspirations at a point in time when discussions about 11 Within academic high schools (Lycée Général et Technologique), 67% of students graduate from the Général track, of which almost 100% get some higher education, while 33% of students graduate from the Technologique track, of which 75% get some higher education [START_REF] Afsa | La moitié d'une génération accède à l'enseignement supérieur[END_REF]. track assignment at school had not yet begun. More specically, while students might have discussed track assignment with their parents, families would not yet have made a formal decision. Moreover, no information on teachers' opinions is ocially provided during the rst term, so that when students took the survey they were unlikely to know which track their teachers thought would be most appropriate for them.

Variables of interest

Aspirations Following [START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF], we dene aspirations as the preferred track within the zone of attainable tracks.

To measure students' educational aspirations, they were asked rst which tracks they are aware of (salient tracks) then, among these tracks, which they feel capable of pursuing (attainable tracks) and nally, among these tracks, which they would prefer (preferred track, or aspiration). By construction, the preferred track is included among the attainable tracks 13 , which in turn are included among the salient tracks 14 . These questions were rst asked with regard to high school tracks, and then for higher education tracks. The questions were entirely open, representing a fundamental value of this paper relative to papers using MCQ in that we are able to capture as closely as possible students' salient, attainable, and preferred academic tracks and occupations; the measure of the aspiration window is not distorted by a provided set of existing tracks.

For each set of salient, attainable, and preferred tracks, we code the answers to indicate whether No high school track is in the answer, Vocational high school is in the answer, and Academic high school is in the answer for aspirations for high school; and whether No higher education track is in the answer, 1-4 year of college is in the answer, and 5 or more year of collegeis in the answer for aspirations for higher education. The questionnaire also included a question on whether the student preferred to nd a job directly after high school or pursue a higher education. To measure professional aspirations, students were asked which job(s) they would like to do in the future. On average, students provided 1.7 jobs. We coded responses according to the number of years of education required to prepare for the job and ranked them according to ve categories: No Response, No higher education, 1-2 years of college, 3-4 years of college, or 5 or more years of college. We provide detailed information on data construction in the Online Appendix.

13 There are few exceptions since it may be natural for students who are asked about the tracks they feel capable of pursuing to just answer the highest (most selective) track they feel capable of pursuing, instead of all of them. 14 A fth of the students were randomly chosen within each class to complete a dierent questionnaire, which includes a list of existing tracks both at the high school and higher education levels. These students were not asked which tracks they know, but directly which tracks they feel capable of pursuing. The number of observations for salient tracks is thus smaller than for attainable and preferred tracks. Note that this feature of the questionnaires is not exploited in this paper.

Academic capacity in November 2012

The starting point of this paper is that aspiration is the capacity to set goals for the future that are in line with one's potential. A key variable is thus students' academic capacity, that we proxy by their current capacity at performing at academic tasks, together with other measures of cognitive and non-cognitive skills.

We use academic test scores in November 2012 to measure academic performance at the same time as aspirations. Two tests (a 45-minute and a 20-minute test) covering grade 8's math curriculum were administered one week apart in class by the research team in November 2012. The use of tests administered on two dierent days, one week apart, allows to limit measurement error due to personal temporary dispositions. We average individual scores on the two tests (see more information about these two tests and the construction of the score in Online Appendix). We are condent about the quality of the measure of academic performance in November 2012 given that the two tests were administered under strict and rigourous conditions, and designed to avoid ceiling eects (as shown on Online Appendix Figure 3).

15

We also have additional proxies of cognitive and non-cognitive skills in November 2012. We rst use the Raven Progressive Matrices (RPM) test to measure students' cognitive ability independent of any prior knowledge. This test is a non-verbal multiple choice test using drawings [START_REF] Raven | Section 1: General Overview[END_REF] and is one of the most commonly used measures of uid intelligence, which is seen by psychologists as a measure of the capacity to acquire more knowledge and at faster rates.

We also use dummies indicating whether the student ever repeated or skipped a grade (based on age), as well as two measures of student behavioral conduct: rst, the total number of questions that students attempted to solve on the two academic tests (independent of whether they answered correctly), reecting the eort that the students invested in taking the tests 16 . The second measure is the score of self-perceived behavioral conduct based on the Self-Perception Prole for Adolescents (SPPA) scale developped by Susan Harter in its French version [START_REF] Bariaud | Le Self-perception prole for adolescents (SPPA) de S. Harter[END_REF]. The Behavioral Conduct subscale taps the degree to which one likes the way s/he behaves, does the right thing, acts the way s/he is supposed to act, and avoids getting into trouble.

Later school outcomes

To study the inuence of aspirations in November 2012 on later performances, we use three outcomes provided by the administrative data. The rst is individual test scores on the national exam administered in June 2013. This test is anonymously and externally graded and includes math, French, history and geography. While the June test has a higher academic resonance than the test administered in November, it has no impact on later academic paths. 17 The second is the average annual teachers' grade. This grade is the average of all the grades a student received from all teachers over the course of grade 9 (from September to June). In our empirical analysis, we use class xed-eects to account for between-classroom and between-school variation in the grading system. The last one is track assignment in high school.This information comes from the administrative data and indicates whether the student Entered vocational high school, Entered academic high school, or Repeated grade 9.

Family characteristics

Our data contains information on both guardians (parents) type of occupation. We dene high-SES students as students for whom at least one guardian has an occupation that corresponds to ve or more years of education, and other students are called low-SES students. Overall, 69% of the families are in the low-SES category, i.e. both parents have intermediate or low-skilled occupations. We also use more detailed controls for parents' occupation (see next section). Our survey data also provide information on the employment status (employed, unemployed, retired), and country of birth of both parents. We dene immigrant families as families in which both parents were born abroad. In our sample, 38% of families are immigrants (for further information, see the Online Appendix).

Students' perceptions: scholastic self-esteem and social fatalism Students' self-perception of their scholastic competence, or scholastic self-esteem, is measured using the Self-Perception Prole for Adolescents (SPPA) conceived by Susan Harter (Harter 1988). The Scholastic Competence subscale includes ve items: being just as smart as others, doing school work quickly, doing well at class work, feeling pretty intelligent, and almost always guring out the answers in class. Our measure of scholastic self-esteem uses the standardized score over all ve items.

Students were asked to assess the probability of success in high school of a hypothetical high-achieving student on a scale from 0 to 10 in two situations: (i) if s/he lives in an advantaged neighborhood, or (ii) if s/he lives in a disadvantaged neighborhood. To measure fatalism, we compute the gap in assessed probabilities of success in these two situations (perceived gap), and compare it to eight actual gaps in order to map the dierent interpretations students may have had of the exercise (real gaps, see Online Appendix 17 Decisions on the assignment of high schools are made before the exam, and it is not necessary to pass the test to enter high school.

for details). Fatalism happens when the perceived gap is greater than the real gaps.

Do Aspirations Matter?

In this section, we examine how aspirations inuence later school outcomes. While estimating the causal link from aspirations to later school outcomes would ideally require a randomized controlled manipulation of aspirations, our survey and administrative data provide exceptionally rich control variables that allow to control for a large number of confounding factors. Our results suggest that our estimates are close to the causal ones, showing that aspirations do inuence later economic outcomes.

Empirical strategy

Our analysis focuses on the eect of the most ambitious aspirations -i.e. academic high school (versus vocational or no relevant response), and a master's degree (versus no relevant response, no higher education, or maximum 4 years in higher education) -on school achievement over the year or at the end of the year.

Obviously, a simple correlation between aspirations and later school outcomes does not reect the causal impact of aspirations, as aspirations and later school outcomes are both the products of other common factors.

There are three categories of factors that can aect both aspirations and later school outcomes independently of aspirations : school-neighborhood characteristics, family characteristics, and students' academic skills. Our model is thus the following:

Y ijt1 = α + βAsp it0 + 10 d=2 γ d T estScore dit0 + λOtherSkills it0 + δF E j + µF am i + ijt0 (1)
where Y ijt1 stands for the outcome of student i in class j, i.e. either the average annual teachers' grade, test score on the national exam in June 2013, or the track assignment for the following year measured in September 2013. t 0 indicates that the variable is measured in November 2012 (all right-hand side variables)

and t 1 indicates that the variable is measured later. Asp it0 is a vector of two dummies indicating whether academic high school and a master's degree are included among student i's preferences in November 201218 .

Our coecients of interest are thus embodied in the β vector.

F E j are class xed eects: they are used to neutralize class, school, and neighborhood characteristics19 .

Class xed-eects primarily capture the impact of peer and teacher quality on both students' aspirations and later school performances. However, they also capture the impact of some parental characteristics, such as parental involvment in education, that lead to sorting between schools and classes and inuence later school performance.

Academic performance is the product of both intellectual ability (cognitive skills) and eort put into learning, the result of non-cognitive skills such as motivation, persistence, self-esteem, diligence, etc. Our One concern is that dierential progression is not only the consequence of dierential aspirations, but also the consequence of dierential academic skills that are not reected in the November 2012 academic test scores, especially intelligence and Conscientiousness (in the terminology of the Five-Factor Personality model). In fact, the literature shows that Openness, Extraversion, or Agreeableness do not correlate with school achievement once intelligence is controlled for [START_REF] Poropat | A Meta-Analysis of the Five-Factor Model of Personality and Academic Performance[END_REF]. Importantly, concerning Neuroticism (the fth factor), we argue that traits related to this dimension aect later school achievement in ways that cannot be distinguished from aspirations 20 .

rst
In order to address this concern, we add additional control variables for both intelligence and conscientiousness (OtherSkills it0 ), and examine the sensitivity of our estimates to their inclusion: the score on the Raven Progressive Matrices test to proxy general intelligence; dummies for whether the student ever repeated or skipped a grade to control for observed extreme learning speeds 21 ; a dummy for gender, because it has been proven that teenage girls are more self-disciplined and conscientious than boys [START_REF] Duckworth | Self-Discipline Gives Girls the Edge: Gender in Self-Discipline, Grades, and Achievement Test Scores[END_REF]; dummies indicating the number of questions that the students tried to solve on the two academic tests as a measure of eort (especially in this context where the test had no academic consequences);

and dummies for levels of self-perceived behavioral conduct to partly capture diligence and dutifulness.

Finally, F am i is a set of family characteristics. We use two dierent sets of control variables: basic and detailed. The rst set includes just a dummy for low-SES indicating that none of the parents are high-skilled 20 [START_REF] Heckman | The Eects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior[END_REF] shows that Neuroticism correlates with school achievement. We postulate here that Neuroticism is not a confounding factor because this domain is inherent to aspirations: traits related to this domain (e.g. self-evaluation, selfesteem, self-ecacy, and optimism) aect later school outcomes only through their interaction with aspirations. For instance, low self-esteem causes inhibition, which we take as inseparable from low aspirations. Similarly, fatalism reduces the perceived return to eort and limits ambition and motivation, which similarly cannot be distinguished from low aspirations. Optimism works the opposite direction on ambition and motivation, but also inseparably from high aspirations.

21 The French procedure to skip a grade requires IQ tests and psychological interviews to precisely assess the cognitive and non-cognitive skills of the student.

workers and a dummy for immigrant family indicating that both parents were born abroad. The second set includes ve dummies for each sub-category of low-SES occupation 22 , two dummies indicating whether each parent is employed, unemployed, or retired, two dummies indicating whether each parent was born in a non-OECD country, and a dummy indicating whether one of the parents has darker skin (based on country of birth). Together these variables proxy parental education and income levels, as well as knowledge of the French curriculum; this detailed set of controls should capture these dimensions better than the basic set of variables. We do not claim that these variables fully capture the impact of family on both aspirations and later school outcomes as parental involvement can vary once these variables are taken into account (e.g.

assistance with assignments, monitoring of homework schedule, management of sleep time). That said, the sensitivity of the coecients on aspirations to replacing the basic set with the detailed set indicates whether unobserved family characteristics seem to bias our estimates.

Importantly, we also provide shorter-term estimates of the impact of aspirations 22 See the Online Appendix for further information on how we dene these variables.

Results

Table 1 presents the correlation between aspirations and average annual grade. Columns 1 to 6 show how the addition of our control variables aects this correlation. 23 November 2012 academic test scores explain a large part of the variation in average annual grade (the R-squared rises from 0.15 to 0.45), and reduce by 58% the coecient on aspirations (column 2), conrming that academic performance is a major determinant of both aspirations and later academic performance. The additional proxies for cognitive and non-cognitive skills (column 3) also add to the explanatory power of the model (from 0.45 to 0.52) and substantially reduce the coecient on aspirations for academic high school (from 0.29 down to 0.22). While adding class xed eects and family characteristics does improve the explanatory power of the model, it does not signicantly aect the coecient on aspirations (columns 4-5-6). Importantly, this is not due to poor quality measures as Appendix Table A1.a shows that the contribution of family characteristics is important when we include them rst as control variables 24 . The lack of impact of class xed eects and family characterictics on the coecients of aspirations thus means that our measures of academic, cognitive, and non-cognitive skills are doing a good job capturing students' academic potential, and that unobserved characteristics do not seem to bias our estimates. Consequently, we interpret the estimates in column 6 as the impact of aspirations on average annual grade, where we compare students who are in the same class, show similar academic, cognitive and non-cognitive measures in November 2012, and are from similar social backgrounds. We nd that students who prefer an academic high school at the beginning of the year have a 0.21 standard deviations higher average annual grade compared to those who prefer a vocational high school or have no preference.

Students who also prefer a master's degree have an additional 0.12 standard deviations higher average annual grade than those who do not. Both dierences are signicant at the 1% level.

Tables 2 and3 show similar results for our two other outcomes. Controlling for initial academic capacity, class xed eects, and family characteristics, students who aspire to an academic high school have a 0.17 standard deviation higher score in June 2013 and an 18 percentage point (37%) higher probability of entering an academic high school the following year compared to students who prefer vocational high school or have no preference (columns 6).

25 Moreover, students who also prefer a master's degree have an additional

23 Interestingly, all control variables are highly signicant and inuence the average annual grade as expected. The only notable exception may be immigrant family, which sees no particular relationship with average annual grade once initial academic skills, class xed eects and family characteristics have been taken into account. This nding -conrmed in Table 2 and 3 -suggests that being from an immigrant family does not aect academic progress and high school track assignment separately from initial academic performances, school quality, and family SES.

24 The adjusted R-squared goes from 0.15 up to 0.24, meaning that they are strong predictors of our outcomes, and the coecient on aspirations goes from 0.69 down to 0.58, meaning that they are highly correlated with aspirations in the rst place (columns 2-3)

25 Students who initially aspire to academic high school have a symmetrically lower probability to enter in vocational high school the next year than those who prefer vocational high school or have no preference: -0.172 o 0.482. We nd no dierence 0.09 standard deviations higher score in June 2013 than those who do not. On the contrary, aspiring to a master's degree doesn't increase the chance of entering an academic high school, consistent with the fact that aspiration to a master's degree is not directly relevant to high school assignment (as noted above, almost all students who aspire to a master's degree also aspire to an academic high school). Once again, adding family characteristics (in a rough or detailed way) does not aect substantially nor signicantly the coecients of aspirations for high school and higher education for these two outcomes (columns 4-6), while they largely increase the explanatory power of the model when they are included rst, as shown in Appendix Tables A1.a

and A1.b 26 . Adding class xed eects and rough controls for family characteristics decreases substantially the coecients of aspiring to a master's degree, but not signicantly (columns 3-4 of Tables 2 and3).

Interestingly, a subgroup analysis also shows that aspirations and academic outcomes are also signicantly correlated within students' SES, given all other controls (Appendix Table A4). If anything, we nd that the impact of aspirations are even larger for low-SES students. These results also hold for all three terciles of initial academic test score (results available upon request).

Finally, Table 4 shows the shorter term eect of aspirations on the score on the national exam in June 2013 and on track assignment for the following year controlling for average annual teachers' grade. Our preferred estimates in columns 3 and 6 show that students who are in the same class and have similar social background and academic skills both in November 2012 and all year long, have dierent later outcomes depending on their initial aspirations. More specically, those who initially aspired to an academic high school in November 2012 obtain a 0.067 standard deviation higher score in June 2013 (column 3) and an 11 percentage point (23%) higher probability of entering an academic high school the following year (column 6) compared to those who preferred vocational high school or had no preference. These results thus show that initial aspirations impact performance on the national exam even when annual school performance is taken into account, and that track assignment is not based only on available information on academic performance (teachers' grades) but that students' preferences play an important role independently of their performances.

Consequently, given the quality and the variety of our other controls, we are condent that our estimates show that aspirations signicantly aect academic achievement.

Interpretation

Overall, our estimates suggest that aspirations aect academic paths in two ways. First, aspirations aect academic progress in 9th grade. Second, aspirations aect decisions independently of academic performance.

in the probability to repeat, which concerns only 4.6% of students (results available upon request).

26 From 0.17 to 0.36 for test score in June 2013, and from 0.17 to 0.23 for track assignment in September 2013

These results provide empirical evidence that aspirations determine eort as modelled in [START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF], Genicot and [START_REF] Génicot | Aspirations and Inequality[END_REF], and [START_REF] Dalton | Poverty and Aspirations Failures, The Economic Journal[END_REF]: students who have lower aspirations seem to invest less eort in their academic work, and thus achieve less and less compared to initially equally-able classmates from similar social backgrounds who had higher aspirations. Low aspirations become a source of disadvantage in their own right. [START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF] proposes that aspirations are not optimal when they are either too modest (easily satised) or too ambitious (unreachable) because such aspirations induce less eort than intermediate aspirations.

Our results indicate that, on average in France, the aspiration gap 27 at school is too small rather than too large for both low-and high-SES students: those who aspire higher achieve higher outcomes. If the average aspiration gap was too large relative to the optimal level of aspirations, academic progress would be smaller for those who aspire higher. In France, the fatalistic failure in aspirations thus dominates the frustration failure. We now turn to the question of whether this failure interacts with social inequalities, i.e.

whether students who suer from an aspirations failure more commonly hail from a low social background.

Social Inequality in Aspirations and Underlying Mechanisms

In this section, we present our results on social inequality in aspirations and on the mechanisms driving these inequalities.

Empirical strategy

We begin by measuring social inequalities in aspirations. Our identication relies on the fact that family background is determined by the accident of birth. More specically, the reasons why aspirations are correlated with parental SES are all consequences of family characteristics correlated with SES: parents' level of education, parents' involvement in their child's education, parents' choice of housing and school location, characteristics of parents' friends and networks, genetics, etc. Any dierence in aspirations between low-SES and high-SES students is thus the consequence of these family characteristics correlated with parental SES. Here, we are not interested in the pure eect of SES on aspirations everything else being equal, but in the ecological eect of SES which incorporates all SES-related dimensions. The only exception is the family immigration status. To this regard, [START_REF] Caille | Perception du système éducatif et projets d'avenir des enfants d'immigrés[END_REF] shows that rst-generation immigrants have higher aspirations than non-immigrants. To replicate this result and separate the eect of social background from the eect of immigration status, our specication includes a dummy indicating whether students come from immigrant families. The eect of socio-economic status is thus considered independently of whether students 27 Following [START_REF] Ray | Aspirations, Poverty and Economic Change[END_REF], the aspiration gap is the gap between one's current situation and his/her aspired situation. 20 are immigrants.

Aspirations are the product of a three-step process: 1) individual's awareness of existing tracks (salient tracks), 2) perceived capacity of pursuing these tracks (attainable tracks), and 3) personal preference (preferred track). We rst present raw dierences in salient, attainable, and preferred tracks between students from low and high-SES families:

[Salient/Attain/P ref ]T rack ijt = α + βLowSES i + γImmigrant i + ε ijt (2)
where [Salient/Attain/P ref ]T rack ij is a dummy indicating if Track (vocational high school, academic high school, no track in higher education, nding a job, or master's degree) is salient to / attainable for / preferred by students i in class j at time t. LowSES i indicates that none of the parents are high-skilled workers, and Immigrant i indicates that both parents were born abroad. We interpret β as the ecological eect of parental SES (once immigration status is taken into account), and γ as the independent ecological eect of being born in an immigrant family (once SES is taken into account). β is thus our measure of raw social inequality in aspirations.

Then, we want to measure the remaining social gap once we control for academic capacity. Indeed, the capacity to aspire is the capacity to set goals in line with one's potential, and current academic capacity is an obvious determinant of one's academic and professional potential. We consider that students who show similar measures of academic performance, and cognitive and non-cognitive skills that are relevant for academic success, have similar current academic capacities. We thus add to the previous model a vector AcadCap it which includes deciles of November 2012 academic scores, dummies for Raven Progressive Matrices scores, dummies for the number of questions that students tried to solve on the two tests (eort put into the tests), and deciles of self-perception of behavioral conduct 28 . Note that we do not assume that similar current academic capacity means similar future academic potential. We discuss students' anticipations about future academic potential later in the paper.

Another way parental SES may inuence students' aspirations is through the quality of the school environment (neighborhood, teacher, and peer quality). School environment may indeed aect educational and professional preferences if students take their peers' preferences into account when forming their own preferences for instance, or through dierences in the provision of information, in perceptions of one's academic 28 In this model, we do not include dummies for skipping or repeating a grade since the probability that a student repeats or skips a grade is highly related to her family characteristics in addition to academic skills. With these dummies included, the results are qualitatively similar and quantitatively very close (available upon request). As we are interested in social dierences in aspirations, we prefer to exclude these variables which encapsulate part of social inequality. In addition, we do not need to include gender since gender is orthogonal to family SES and immigration status.

capacity due to school stigma, or in actual school quality. We add to the previous model class xed-eects F E j in order to isolate the role of school and class environment in explaining raw dierences in aspirations. 29 We are aware that class xed-eects capture not only the role of peer and teacher quality in explaining students' aspirations, but also the role of some parental characteristics inuencing the choice of neighborhood, school and class (e.g. parental concern for education or involvement in education). In the interest of simplication, we qualify this mechanism as the role of class environment. As a result, we present estimates from the following model:

[Salient/Attain/P ref ]T rack ijt = α + βLowSES i + γImmigrant i + λAcadCap it + δF E j + ε ijt (3)
This model provides evidence on the degree to which the raw social dierences observed in equation 2 are explained by academic capacity and school environment. The remaining coecient on low-SES (resp.

immigrant) family represents the dierences between equally-performing classmates from low-and high-SES.

Interestingly, the data allow to disentangle additional mechanisms leading to these dierences in aspirations. Once current academic capacity and class environment are taken into account, dierences in preferences for track X indeed come from either dierences in salience of existing tracks, in self-perceived academic ability, or in personal taste. To disentangle the relative contributions of these three mechanisms, we rst add dummies indicating student i's salient tracks in the regression of attainable tracks:

Attain.T rack ijt = α + βLowSES i + γImmigrant i + λAcadCap it + δF E j + µSalient.T rack it + ε ijt (4)

We interpret the coecient on low-SES as the dierence in attainable tracks between low and high-SES students due to perception of one's academic potential as we compare students who are in the same class, have similar academic capacity, similar immigration background, and importantly, similar salient tracks.

And similarly we then add dummies for student i's attainable tracks in the regression of preferred tracks, and interpret the coecient on low-SES as the dierence in preferred tracks between low and high-SES students not due to awareness of academic tracks and self-perception of academic ability as we compare students who are in the same class, have similar academic capacity, similar immigration background, and similar attainable tracks. This remaining gap in preferred tracks may be due, for instance, to dierent liquidity constraints in facing the cost of education, to dierent expected returns to education, or to identity concerns. Comparison with equation (3) gives the degree to which dierences in preferred tracks are the 29 When we implement this model using class xed-eect, 25% of the classes are not used in the identication as 24% include 100% of low-SES, and 1% includes 100% of high-SES.

consequence of self-perceived academic potential.

Social dierences in aspirations and underlying mechanisms

Aspirations for high school

Table 5 presents dierences in aspirations for high school (vocational or academic high school) and investigates whether these aspirations are sourced in a lack of salient and/or attainable tracks in high school.

30

Column 1 shows that low-SES students are as likely as high-SES to include vocational high school among their salient tracks (84% among low-SES students versus 81% among high-SES students, dierence not signicant), but much more likely to refer to vocational high school as an attainable and preferred track: 29% of low-SES students refer to vocational high school as an attainable track, and 16% as a preferred track, compared respectively to 15% and 4.5% of high-SES students. On the contrary, column 5 shows that low-SES students are slightly less likely to mention an academic high school among their salient tracks (89% versus 94% among high-SES students), and much less likely to refer to academic high school as attainable and preferred tracks: 72% of low-SES students refer to academic high school as an attainable track, 61% as a preferred track, compared respectively to 89% and 80% of high-SES students.

A large part of these dierences can be attributed to dierences in academic capacity and school environment (columns 2-3 and 6-7): among students who show similar capacity and belong to the same class, the gaps between low and high-SES students are generally smallerHowever, low-SES students are slightly more likely to mention vocational high school among their salient tracks (+ 6.8%), and as likely to mention academic high school compared to their equally-performing high-SES classmates (columns 3 and 7, panel

3). This indicates that high-SES students have a decit in information (or awareness) at the beginning of grade 9 with regard to vocational high school. For attainable tracks, low-SES students have a 42% higher probability of citing vocational high school, and a 4.4% lower probability of citing academic high school, than equally-performing high-SES classmates (columns 3 and 7, panel 2). The fact that low-SES students more often cite vocational high school as attainable may seem surprising, but this is explained by students only citing the highest track that they nd attainable, without bothering to mention other lower tracks that are obviously also attainable.

31 Finally, low-SES students have a 111% higher probability of prefering a vocational high school, and a 4.5% lower probability of prefering an academic high school, than equally-30 For simplicity, we do not report or comment on results for the remaining outcome no high school track, although they are performing high-SES classmates (columns 3 and 7, panel 1). In contrast, it should be noticed that students from immigrant families have similar salient options, a lower probability of refering to vocational high school as attainable, and similar preferred tracks, than non-immigrant students, validating [START_REF] Caille | Perception du système éducatif et projets d'avenir des enfants d'immigrés[END_REF] ndings that rst-generation immigrants have higher aspirations than non-immigrants.

Once salient tracks are controlled for, low-SES students are still 4% less likely to cite academic high school as attainable relative to their equally-performing high-SES classmates (column 8, panel 2) 32 They are also 37% more likely to refer to vocational high school as attainable (column 4, panel 2) but this is entirely due to the fact that students generally cite only the highest track that they nd attainable, not bothering to cite other lower tracks that are obviously also attainable.

33

Once attainable tracks are controlled for, low-SES students are still 49% more likely to prefer vocational high school than equally-performing high-SES classmates (column 4, panel 1), compared to 111% when attainable tracks are not controlled for. This result indicates that about half of the dierence in aspirations for vocational high school among equally-achieving classmates is due to dierences in self-perceived academic potential. The other half is attributable to dierences in pure preferences, which may relate to dierential liquidity constraints vis-à-vis the cost of education, dierential returns to education, or identity concerns.

Moreover, the social gap in preference for academic high school is entirely due to dierences in self-perceived academic potential. 34 Overall, our results show that aspirations for high school are dierent among low and high-SES students not only due to dierences in academic capacity, school environment, and preferences (which all play an important role), but also largely to dierences in self-perception of academic potential.

A subgroup analysis by terciles of academic test score shows that these results come from students in the bottom and medium terciles. In the top tercile, there are actually no dierences in attainable and preferred tracks between low-and high-SES students.

Aspirations for Higher Education

Table 6 presents the dierences in aspirations for higher education. For simplicity, we focus on the two extreme aspirations: nding a job right after high school and master's degree. 35 Column 1 shows that low-SES students are much more likely to cite no salient track (41%, versus 28% among high-SES students), as well as no attainable track in higher education (65%, versus 50% among high-SES students), and to 32 Note that, in Tables 5 and6, the results stay qualitatively the same when we restrict the sample to students who were not provided with the list of existing options.

33 When we impose vocational high school to be attainable when academic high school is (and when the student mentions vocational high school among the existing tracks), we no longer nd a gap in attainable track for vocational high school once we control for salient tracks; other results on preferred tracks remain qualitatively similar.

34 The same holds for the dierence in the preference for vocational high school between immigrants and non-immigrants. 35 The results for the remaining intermediate outcome 1-4 years of college are available upon request.

prefer nding a job right after high school (22%, versus 8% among high-SES students). On the contrary, column 5 shows that low-SES students are less likely to bring up a master's degree among their salient tracks (20%, versus 38% among high-SES students), in their attainable tracks (11%, versus 26% among high-SES students), and in their preferred track (10%, versus 23% among high-SES students). Of note, immigrant students are remarkably similar to non-immigrant students with respect to salient, attainable, and preferred tracks in higher education.

Much of the dierence between low and high-SES students can be attributed to dierences in academic capacity and school environment, and yet the gaps remain substantial even among equally-achieving classmates (columns 2-3 and 6-7). Low-SES students have a 12% higher probability of citing no salient track and a 12% smaller probability of citing a master's degree as a salient track than equally-performing high-SES classmates (although these dierences are not statistically signicant) (panel 3), they have about the same probability of citing no attainable tracks, but still a 26% lower probability of mentioning a master's degree as an attainable track (panel 2), and nally they are 64% more likely to prefer nding a job right after high school, and 20% less likely to prefer a master's degree (panel 1). In contrast, immigrants' preferences are biased against nding a job relative to equally-achieving non-immigrant classmates (columns 2-4 panel 1).

The stronger preference for nding a job right after high school among low-SES students is not driven much by dierences in salient and attainable tracks: once attainable tracks are controlled for, low-SES students are still 53% more likely to prefer nding a job than equally-performing high-SES classmates (column 4, panel 1). In contrast, the bias against master's degree among low-SES students is entirely driven by a master's degree being both less salient and less attainable. Dierences in master's degree as salient account for half of the dierences in master's degree as attainable (columns 7-8, panel 2), and dierences in master's degree as attainable account for the totality of dierences in preference for a master's degree (columns 7-8, panel 1).

Social dierences in aspirations for a master's degree are thus not due to personal taste, and not only due to social dierences in academic capacity and school environment, but also to dierences in awareness and self-perceived academic potential. A subgroup analysis by terciles of academic test score shows that low-SES students in the top tercile are the most concerned by these decits in information and self-perceived academic potential regarding a master's degree, while the excess probability of preferring to nd a job right after high school for low-SES students is mostly driven by the bottom tercile.

Professional aspirations

The rst thing to notice about professional aspirations is that, for all students, academic aspirations are not even close to being consistent with professional aspirations. For instance, among high-SES students, 23.3% aspire to a master's degree as an educational track, while 44.6% aspire to a job that requires at least a master's degree. This dynamic is similarly true for low-SES students. This suggests that teenagers do not see education as a pure investment for a future job, perhaps due to ignorance of specic educational pathways to employment. At this age, educational aspirations are not entirely driven by professional aspirations. This lack of realism is important, as it may lead students to make irreversible decisions in the short-term like entering vocational high school while aspiring to a job that requires at least a master's degree (vocational high school does not, for example, allow to enroll in medecine; more generally, only 5% of students completing vocational high school go to university). The observed inconsistencies between educational and professional aspirations suggest that these consequences are not fully anticipated and internalized by teenagers, potentially creating frustration when students realize that their educational choices do not match their professional aspirations.

To add to this, Table 7 36 shows that social dierences in professional aspirations are also not aligned with the social dierences in academic aspirations that we nd above. As soon as academic performance and class xed-eects are controlled for (columns 2-3, 5-6, 8-9, and 11-12), social dierences in professional aspirations disappear. Professional aspirations thus do not drive the gap in academic aspirations that we nd above. For instance, while low-SES students are as likely to prefer a job that requires a master's degree as their equallyachieving high-SES classmates, they are also 26% less likely to prefer a master's degree as an educational track. And while they are as likely to prefer a job that does not require any higher education, they are 69% more likely to say that they prefer nding a job right after high school. These ndings are important in interpreting the dierences in educational aspirations between low and high-SES students: social groups dier much more in the way they plan to invest in education than in the way they think about their future occupation. At 15 years-old, social dierences in educational aspirations among equally-achieving students are not driven by social dierences in professional aspirations.

The same does not hold true in the comparison of immigrants and non-immigrants: our results show that immigrants are more likely to aspire to occupations that require a master's degree than equally-achieving non-immigrant classmates. This is consistent with [START_REF] Caille | Perception du système éducatif et projets d'avenir des enfants d'immigrés[END_REF] nding that immigrants exhibit an excess of ambition relative to non-immigrants. Teenagers' lack of realism is thus even more pronounced among 36 In this table, the level corresponding to job preference after high school is the lower level required for the job mentioned by the student.

immigrants: 11.7% aspire to a master's degree while 43.5% aspire to a job that requires master's degree (a 32 points gap); and among non-immigrants, 15.6% aspire to master's degree while 38.2% aspire to a job that requires a master's degree (a 23 points gap). As long as students do not make irreversible decisions in the short-term like entering a vocational high school, aspirations for higher education may adjust to professional aspirations later on when students receive additional information on higher education in high school. Our results thus suggest that immigration status is not such a concern in terms of inequality, in that immigrant students have 1. the same probability of aspiring to an academic high school (Table 5, panel 1 column 7), and 2. the same probability of entering an academic high school given their aspiration (Table 3 column 8) as equally-achieving non-immigrant classmates.

5.2.4

Evidence on self-perceived academic capacity and social fatalism

Our previous results show that low-SES and high-SES students dier in their educational aspirations not only because they have dierent current academic capacity, school environnment, and preferences towards education, but also due to dierent levels of awareness of academic tracks and dierent self-perceived academic potential. Tables 8.a and 8.b provide additional evidence on the ways family SES can inuence self-perceived academic potential.

Table 8.a rst shows that students have fatalistic views on the extent to which social origin aects later success in high school. Part (a) reports the eight real gaps described in the Online Appendix that correspond to the gap estimated by the students of our sample which is reported in part (b). It clearly shows that the perceived social gap for high-achieving students is much larger that the actual gap, whatever the exact denition of the actual gap. Specically, we see that high-achieving students in priority education actually have both a higher probability to enter academic high school right after junior high than those in non-priority education, and a higher probability to pass the national exam at the end of academic high school.

37 When one compares low-and high-SES students 38 , the results are less surprising. It shows that top-quartile (resp. above median) low-SES students are 4.1 (resp. 10.0) percentage points less likely to enter an academic high school right after junior high, and 6.1 (resp. 13.2) percentage points less likely to pass the high school nal exam than high-SES students. Being from a low-SES family is thus associated with a real disadvantage in terms of later success. However, the perceived disadvantage is disproportionately larger: column (b) shows that, on average, students perceive that the gap in the probability of succeeding in high school for a hypothetical high-achieving student is 33.5 points lower when s/he lives in a disadvantaged neighborhood relative to an advantaged neighborhood. Whatever the interpretation students have of the question, they thus perceive a much higher correlation between social background and later success in high school than the actual correlation. Interestingly, Table 8.b. column 1 shows that equally achieving classmates from dierent social backgrounds have exactly the same fatalistic views. Overall, our data show that social fatalism regarding education is excessive and similar between low and high-SES students who perform equally and are in the same class, which may explain the observed dierences in their attainable tracks. The issue is that fatalistic anticipations are self-fullling: overly fatalistic anticipations of future academic success may cause low aspirations, in turn leading to lower school outcomes than what would have been achieved with higher aspirations (as shown in Section 4). The lack of accuracy in one's perception of his/her academic potential can thus be the source of an aspirations failure.

Moreover, column 2 of Table 8.b shows that low-SES students have a 0.12 standard deviation lower scholastic self-esteem than equally-achieving high-SES classmates. As our measure of scholastic self-esteem is based on perceptions of one's current academic capacity, there is nothing here related to anticipations of the future. This means that students who have similar objective current academic capacities, simultaneously have dierent subjective current academic capacities. Interestingly, this result is true for students of all school prociency levels, although more pronounced for low-SES students in the top tercile for whom the gap in scholastic self-esteem is 0.15 standard deviations relative to equally-achieving high-SES classmates.

For students in the top tercile, we nd that the decit in aspirations due to family SES concerns the master's degree, and is partly due to ignorance and partly due to self-perceptions of academic potential.

By introducing our measure of scholastic self-esteem in equation ( 4) for students in the top tercile, we nd that scholastic self-esteem explains 27% of the decit in low-SES top-students mentioning a master's degree among their attainable tracks 39 .

These ndings provide evidence that social identity creates mental models aecting how an individual experiences what he experiences, as proposed in Karla Ho and co-authors' models: beliefs related to social inferiority aect self-condence, self-perceived probability of success, and behavior (aspirations) in ways that make the beliefs come true (Ho andPandey 2006, 2012;[START_REF] Fehr | Tastes, castes, and culture: The inuence of society on preferences[END_REF][START_REF] Ho | Striving for Balance in Economics: Towards a Theory of the Social Determination of Behavior[END_REF]. Our empirical results support this view: scholastic self-esteem is prone to stereotype susceptibility related to 39 More specically, we add deciles of scholastic self-esteem and deciles of scholastic self-esteem interacted with SES in model ( 4) on the subgroup of students in the top tercile with master's degree as attainable as the dependent variable. In model ( 4), the coecient on low-SES is -0.064, signicant at the 10% level. In the augmented version, the coecient on low-SES is -0.047 and no longer signicant, which represents a 27% reduction in the coecient on low-SES.

parental SES, which results in dierent sets of attainable tracks, which in turn result in dierent preferred tracks, and eventually aects school outcomes.

6 Discussion: Are Aspirations Optimal?

From the students' perspective, aspirations are optimal if they lead to maximum welfare. Our ndings provide three reasons why aspirations may not, in fact, lead to maximum welfare.

First, some dierences in aspirations between equally-achieving low and the high-SES classmates are due to dierences in awareness of existing tracks, particularly regarding a master's degree among students in the top-tercile. This result likely reects a lack of information, a simple reason why preferences may not be optimal, i.e. may not lead to maximum welfare.

Second, social dierences in aspirations for vocational high school, academic high school, and master's degree among equally-achieving classmates are mostly due to dierences in the tracks that students feel capable of pursuing (attainable tracks), i.e. to dierences in self-perceived potential. Low-SES students are correct to anticipate lower academic capacity in the future relative to high-SES students that perform equally in the present: their social background is indeed a clear factual disadvantage, as shown by the negative coecient of low-SES family on short-term academic progress in Tables 1, 2 and 4. They do not, however, correctly assess this objective disadvantage. They are indeed likely to underestimate their future academic potential since they both underestimate their present academic capacity and overestimate the way social background inuences their future probability of success (Table 8). For this reason, it should not be taken for granted that students assess their academic potential at its true value. Social stereotypes and fatalism bias students' perceptions, casting doubt on the accuracy of their perceptions of their academic potential.

Finally, low aspirations are a source of suboptimality in their own right. In section 4, we show that low aspirations lead to lower school performance in the short-term. There is a negative impact of being from a low-SES family on short-term outcomes, but there is also an additional negative impact of having low aspirations ceteris paribus that is observed for both high and low-SES students (Appendix Table A4). If school attainment has a positive return on the labor market, this mechanism can lead to suboptimal job market outcomes. The vast literature on the returns to education shows, in fact, that returns are substantial: about 10% higher wages per additional year of higher education (see Oreopoulos and Petronijevic 2013 for a review), with no evidence that returns are dierent for low and high-SES students. Moreover, the cost of education in France is particularly low: 79% of students enrolled in academic high schools attend public (tuition-free) high schools 40 , and most higher education institutions are entirely free for low-SES students (including the most selective schools). Reduced educational attainment is thus likely to result in suboptimal job market outcomes.

There may be some situations where low aspirations are not detrimental in terms of long-term welfare.

For example, if better school performance in the short-term does not lead to greater school attainment later on. This may be true for weak students who would not succeed in an academic high school. To this regard, [START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF] show that weaker students would be better o entering a vocational high school instead of trying an academic high school, and then needing to drop out. While this result may well apply to a subsample of students in our bottom tercile 41 , medium and top-achievers should, however, be able to complete academic high school and some higher education, such that reduced school outcomes in grade 9 due to low aspirations will likely eventually lead to lower school attainment and job market outcomes for many of these students. To add to this, lower school and job market outcomes may be compatible with higher welfare due to identity concerns and social preferences. The identity literature provides several explanations of this phenomenon including: resembling and conforming to friends' behavior, arming one's social identity to maintain a sense of unity, or ghting a threat of losing one's culture [START_REF] Akerlof | Identity and Schooling: Some Lessons for the Economics of Education[END_REF], Fryer 2006[START_REF] Fang | Dysfunctional Identities" Can Be Rational[END_REF][START_REF] Bénabou | Identity, Morals and Taboos: Beliefs as Assets[END_REF][START_REF] Carvalho | Resisting Education[END_REF]. However, both the fact that low-SES students aspire to jobs that require many more years of education than what they plan to invest (Tables 5, 6 and7), and the observation that social groups dier much more in the way they plan to invest in education than in the way they think about their future occupation, caste doubt on whether lower school attainment and job market outcomes will lead to maximum welfare.

Conclusion

This paper provides evidence that students' educational aspirations are inuenced by their parents' SES, and that these aspirations contribute to the short-term evolution of school outcomes. As school outcomes are themselves a determinant of aspirations, our results reveal the existence of an aspiration-based inequality trap which concerns low-SES students of all academic prociency levels. While low-SES students have a clear factual disadvantage from the beginning, this aspiration trap drags them down even further. By contrast, being from a rst-generation-immigrant family actually boosts educational and professional aspirations.

A natural question is whether these results reect a market failure that would rationalize some form of 40 http://www.education.gouv.fr/cid57111/l-education-nationale-en-chires.html#Le second degré 41 The academic performance of the students in [START_REF] Goux | Adjusting your dreams? The Eect of School and Peers on Dropout Behaviour[END_REF] are slightly worse than those of the bottom tercile students in this paper.

policy intervention. Do students have suboptimal aspirations that in turn lead to suboptimal educational, job market, and welfare outcomes? This paper provides evidence of three reasons why aspirations may not be optimal. First, it cannot be taken for granted that students assess their academic potential at its true value, as suggested by the fact that low-SES students underestimate their present academic ability relative to their equally-achieving high-SES classmates, and by the fact that their views appear excessively fatalistic.

Such stereotyped beliefs may aect the perception of attainable options in ways that perpetuate social inequalities. Second, we show that non-awareness of some existing academic tracks, particularly master's degrees, plays a role in shaping socially dierential aspirations. Finally, the very fact that one aspires low creates a disadvantage in its own right. Students would benet from higher aspirations in terms of short-term school outcomes, which would likely result in higher school attainment and job outcomes in the longer term, except perhaps for very weak students.

The question of welfare is somewhat more dicult. Whether higher aspirations, school attainement, and job outcomes would ultimately make low-SES students happier, remains an open question. They may, for example, feel socially isolated or at odds with their cultural values, as suggested by the identity literature.

Our results, however, show that low-SES students have professionnal aspirations that are much higher in terms of required diploma than what they plan to invest in education, a result that is not quite consistent with the view that increased educational and professional levels would hurt their welfare.

This paper begs further discussion of whether preferences are optimal. Most of the economic literature concurs with the latin maxim, de gustibus non est disputandum 42 , such that personal preferences are merely subjective opinions that cannot be right or wrong. If preferences are formed on a clear-sighted and informed basis, this may be true. But if preferences are formed on the basis of misperceptions and a lack of information, preferences may be the root of a market failure. It is along these lines that this paper encourages further research on the long-term consequences of educational aspirations, particularly their consequences on welfare, and the design of appropriate interventions to help disadvantaged students aspire at their true potential to increase upward mobility.

42 In matters of taste, there can be no disputes -0.512 Mean among students whose pref. tracks do not include a Master's degree:

-0.089

Each column reports the coefficients of a different OLS regression. The dependent variable is the standardized annual average of teachers' grades. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth). Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. 'Proxy for Conscientiousness' corresponds to dummies indicating the number of questions that the student tried to solve for each test in November. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. -0.521 Mean among students whose pref. tracks do not include a Master's degree:

-0.081

Each column reports the coefficients of a different OLS regression. The dependent variable is the standardized test score at the national exam in June. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student were born outside of France. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth). Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. 'Proxy for Conscientiousness' corresponds to dummies indicating the number of questions that the student tried to solve for each test in November. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy indicating whether the student has been assigned to the academic track. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student were born outside of France. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth). Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. 'Proxy for Conscientiousness' corresponds to dummies indicating the number of questions that the student tried to solve for each test in November. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy indicating whether the student has been assigned to the academic track. "Pref. tracks include Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth). Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. 'Proxy for Conscientiousness' corresponds to dummies indicating the number of questions that the student tried to solve for each test in November. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. Reading note: The "probability of success" is the probability that the hypothetical high achieving student follows his preferred track; on average, students estimate this probability to be 85.5%. If s/he lives in a disadvantaged neighborhood, students from high-SES families estimate this probability to be 36.6 percentage points lower (row "Mean among high-SES families"). This gap is not statistically significantly different for students from low-SES families.

APPENDIX TABLES Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy indicating whether the student has been assigned to the academic track. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student were born outside of France. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth).

Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level. Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy indicating whether the student has been assigned to the academic track. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student were born outside of France. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth).

Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level. -0.512 -0.521 0.472 Mean among students whose pref. tracks do not include a Master's degree:

-0.089 -0.081 0.698

Each column reports the coefficients of a different OLS regression. The dependent variable is either the standardized annual average of teachers' grades, either the standardized test score at the national exam in June, either a dummy indicating whether the student has been assigned to the academic track after 9th grade. "Pref. tracks include an Academic HS" is a dummy indicating that preferred tracks after middle school include an academic high school. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. Controls for "Detailed SES" correspond to controls for each family's socioeconomic status (SES) stratified into six categories based on the parents' occupation, together with controls for whether the student has one parent who is unemployed and for whether she has one parent who is retired, separately for each parent when there are two. Controls for "Detailed immigration status" correspond to controls for whether the student has one parent or both who were born in a non-OECD country, and at least one parent colored (defined base on the country of birth). Students' score at Raven matrices is controlled for using dummies indicating the number of wrong answers. 'Proxy for Conscientiousness' corresponds to dummies indicating the number of questions that the student tried to solve for each test in November. When controlling for the immigration status, for the employment status, and for the score at Raven matrices, we also add controls for missing data for each characteristic.

  control variable is current (November 2012) academic performance as measured by students' scores on our two independent tests: T estScore dit0 is a dummy indicating whether the student's academic test score in November 2012 is in decile d. We argue that our tests provide a good measure of academic level because they are taken one week apart (minimizing measurement error), and because the correlation between our test score and the score on the national exam at age 15 is 0.78. InDalton et al.'s (2016) model, the current academic performance represents the realized outcome at the basis of aspirations.

  Grade git1 is a dummy indicating whether the student's average annual grade is in decileg, and all other variables are similar to those in equation (1). Note that the interpretation of this new estimate is dierent from the earlier one in that it leaves very little time for aspirations to aect school outcomes since we compare students who not only have similar characteristics in November 2012 but also similar average teachers' grade for the entire year. In addition, it provides a lower bound of the true estimate since it excludes the impact of aspirations on June 2013 and September 2013 outcomes going through average annual grade.

on June 2013 academic test scores and September 2013 track assignements by controlling for average annual grade on top of all other controls. The advantage of this new estimation is that the average annual teachers' grade provides an excellent control for students' skills and family characteristics aecting academic achievement as it is based on multiple academic tests on all topics including both in-class and at-home assignments, as well as student behavior and conscientiousness (see the Online Appendix for a deeper discussion on teachers' grades). Both measurement error and omitted variable bias are therefore well addressed. Our model is the following:

Y ijt2 = α+βAsp it0 + 10 g=2 θ g Grade git1 + 10 d=2 γ d T estScore dit0 +λOtherSkills it0 +δF E j +µF am i + ijt0

(1 )

where t 0 indicates that the variable is measured in November 2012, t 1 indicates that the variable is measured between September 2012 and June 2013, and t 2 indicates that the variable is measured later, i.e.

in June or September 2013.

Table 1 :

 1 Correlation between Aspirations and Annual Average Grade

	Variable			Annual teachers' grade
		(1)	(2)	(3)	(4)	(5)	(6)
	Preferred tracks include an Academic HS	0.689*** 0.291*** 0.223***	0.219***	0.216***	0.211***
		(0.036)	(0.034)	(0.030)	(0.028)	(0.028)	(0.028)
	Preferred tracks include a Master's degree 0.465*** 0.197*** 0.166***	0.134***	0.122***	0.120***
		(0.040)	(0.035)	(0.035)	(0.042)	(0.040)	(0.041)
	Repeated a grade			-0.281*** -0.289*** -0.271*** -0.274***
				(0.038)	(0.041)	(0.041)	(0.041)
	Skipped a grade			0.271***	0.220***	0.204***	0.211***
				(0.056)	(0.060)	(0.060)	(0.058)
	Girl			0.245***	0.244***	0.249***	0.249***
				(0.030)	(0.029)	(0.029)	(0.028)
	Low-SES family					-0.248***
						(0.031)
	Immigrant family					0.015
						(0.033)
	Detailed SES						Y
	Detailed immigration status						Y
	Deciles in test scores in Nov. 2012		Y	Y	Y	Y	Y
	Score on Raven matrices			Y	Y	Y	Y
	Effort put into the test			Y	Y	Y	Y
	Self-Perception of Behavioral Conduct			Y	Y	Y	Y
	Class fixed effects				Y	Y	Y
	Nb Obs	3101	3101	3101	3101	3101	3101
	Adjusted R-squared	0.153	0.449	0.516	0.570	0.579	0.581
	Mean among students whose pref. tracks do not include an Academic High School:

  The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 2 :

 2 Correlation between Aspirations and Test Score at the National Exam

	Variable			Test scores in June 2013
		(1)	(2)	(3)	(4)	(5)	(6)
	Preferred tracks include an Academic HS	0.718*** 0.240*** 0.190***	0.177***	0.173***	0.171***
		(0.034)	(0.028)	(0.025)	(0.021)	(0.021)	(0.021)
	Preferred tracks include a Master's degree 0.506*** 0.165*** 0.147***	0.109***	0.097***	0.092***
		(0.053)	(0.037)	(0.036)	(0.036)	(0.033)	(0.033)
	Repeated a grade			-0.319*** -0.316*** -0.299*** -0.293***
				(0.028)	(0.031)	(0.031)	(0.032)
	Skipped a grade			0.278***	0.266***	0.248***	0.253***
				(0.052)	(0.058)	(0.057)	(0.055)
	Girl			0.082***	0.071***	0.073***	0.072***
				(0.023)	(0.023)	(0.023)	(0.022)
	Low-SES family					-0.245***
						(0.028)
	Immigrant family					0.025
						(0.024)
	Detailed SES						Y
	Detailed immigration status						Y
	Deciles in test scores in Nov. 2012		Y	Y	Y	Y	Y
	Score on Raven matrices			Y	Y	Y	Y
	Effort put into the test			Y	Y	Y	Y
	Self-Perception of Behavioral Conduct			Y	Y	Y	Y
	Class fixed effects				Y	Y	Y
	Nb Obs	3101	3101	3101	3101	3101	3101
	Adjusted R-squared	0.170	0.616	0.651	0.699	0.707	0.709
	Mean among students whose pref. tracks do not include an Academic High School:

  The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 3 :

 3 Correlation between Aspirations and Assignment to the Academic Track

	Variable		Entered an Academic High School
		(1)	(2)	(3)	(4)	(5)	(6)
	Preferred tracks include an Academic HS	0.364*** 0.222*** 0.197***	0.182***	0.180***	0.176***
		(0.018)	(0.022)	(0.020)	(0.020)	(0.019)	(0.020)
	Preferred tracks include a Master's degree 0.115*** 0.044*** 0.040***	0.029	0.022	0.020
		(0.016)	(0.015)	(0.015)	(0.018)	(0.017)	(0.018)
	Repeated a grade			-0.182*** -0.182*** -0.175*** -0.174***
				(0.020)	(0.021)	(0.021)	(0.021)
	Skipped a grade			0.034*	0.032	0.024	0.021
				(0.018)	(0.021)	(0.020)	(0.019)
	Girl			0.052***	0.050***	0.050***	0.048***
				(0.015)	(0.015)	(0.015)	(0.015)
	Low-SES family					-0.110***
						(0.015)
	Immigrant family					0.028
						(0.017)
	Detailed SES						Y
	Detailed immigration status						Y
	Deciles in test scores in Nov. 2012		Y	Y	Y	Y	Y
	Score on Raven matrices			Y	Y	Y	Y
	Effort put into the test			Y	Y	Y	Y
	Self-Perception of Behavioral Conduct			Y	Y	Y	Y
	Class fixed effects				Y	Y	Y
	Nb Obs	3101	3101	3101	3101	3101	3101
	Adjusted R-squared	0.171	0.354	0.392	0.418	0.426	0.428
	Mean among students whose pref. tracks do not include an Academic High School:	0.472
	Mean among students whose pref. tracks do not include a Master's degree:		0.698

  The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 4 :

 4 Shorter term correlation between Aspirations and Academic Outcomes, Controlling for Annual Average Grade

	Variable	Test scores in June 2013	Entered an Academic HS
		(1)	(2)	(3)	(4)	(5)	(6)
	Preferred tracks include an Academic HS	0.088***	0.067***	0.067***	0.128***	0.114***	0.111***
		(0.022)	(0.020)	(0.020)	(0.014)	(0.014)	(0.014)
	Preferred tracks include a Master's degree	0.057*	0.028	0.020	0.013	0.010	0.005
		(0.031)	(0.025)	(0.025)	(0.012)	(0.012)	(0.012)
	Repeated a grade	-0.177*** -0.161*** -0.147*** -0.080*** -0.076*** -0.073***
		(0.024)	(0.024)	(0.024)	(0.014)	(0.016)	(0.016)
	Skipped a grade	0.152***	0.149***	0.145***	0.018	0.025	0.018
		(0.037)	(0.041)	(0.040)	(0.015)	(0.016)	(0.016)
	Girl	-0.040** -0.065*** -0.064***	-0.010	-0.013	-0.014
		(0.019)	(0.017)	(0.018)	(0.012)	(0.013)	(0.013)
	Detailed SES			Y			Y
	Detailed immigration status			Y			Y
	Deciles in test scores in Nov. 2012	Y	Y	Y	Y	Y	Y
	Score at Raven matrices	Y	Y	Y	Y	Y	Y
	Effort put into the test	Y	Y	Y	Y	Y	Y
	Self-Perception of Behavioral Conduct	Y	Y	Y	Y	Y	Y
	Class fixed effects		Y	Y		Y	Y
	Deciles in average annual grade	Y	Y	Y	Y	Y	Y
	Nb Obs	3101	3101	3101	3101	3101	3101
	Adjusted R-squared	0.771	0.829	0.831	0.632	0.650	0.653
	Mean among students whose pref. tracks do not include...
	... an Academic HS:	-0.521	-0.521	-0.521	0.472	0.472	0.472
	... a Master's degree:	-0.081	-0.081	-0.081	0.698	0.698	0.698

  The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 5 :

 5 Academic Aspirations after Junior High

	Vocational High School	Academic High School

Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy variable indicating whether the preferred (panel 1) / attainable (panel 2) / salient (panel 3) tracks include a vocational HS (columns 1-4) or an Academic HS (columns 5-8). 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student are born outside of France. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 6 :

 6 Academic Aspirations after High School

	Finding a job	Master's degree

Each column reports the coefficients of a different OLS regression. The dependent variable is a dummy variable indicating whether the preferred (panel 1) / attainable (panel 2) / salient (panel 3) tracks include finding a job (columns 1-4) or a Master's degree (columns 5-8). 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student are born outside of France. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Table 7 :

 7 Professional AspirationsEach column reports the coefficients of a different OLS regression. The "Level corresponding to job preference after HS" is the lower level required for the job mentioned by the student. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student are born outside of France. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

	Level corresponding to job preference after High School

Table 8 .

 8 a: Evidence of Social Fatalism: Real and Perceived Gaps in the Probability of Success of Good Students from Different Social Backgrounds

	(a) Real gaps in the probability of...

The real gaps are calculated on the whole population of French 9th grade students excluding those who already repeated 9th grade (when we include them the gaps are very similar). The probability of entering academic High School right after Junior High and the probability of passing the end of academic High School exam are defined without repeating a grade (and gaps calculated by allowing students to repeat a grade are even smaller). The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level. Standard deviations are reported in square brackets.

Table 8

 8 Each column reports the coefficients of a different OLS regression. 'Low-SES family' is a dummy variable indicating that none of the parents are high-skilled workers. 'Immigrant Family' is a dummy variable indicating that both parents of a student are born outside of France. The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

	.b: Gaps in Social Fatalism and Self-Perceived Academic Capacity
		For a hypothetical high achieving student:
		Perceived gap between her/his prob. of success	Scholastic
		if s/he lives in an advantaged neighborhood	self-esteem
		and if s/he lives in a disadvantaged neighborhood
		(1)	(2)
	Low-SES family	-0.011	-0.120***
		(0.012)	(0.040)
	Immigrant family	-0.003	-0.039
		(0.012)	(0.037)
	Deciles in test scores in Nov. 2012	Y	Y
	Dummies for score on Raven matrices in Nov. 2012	Y	Y
	Effort put into the test	Y	Y
	Self-Perception of Behavioral Conduct	Y	Y
	Class fixed effects	Y	Y
	Nb Obs	3245	3271
	Adjusted R-squared	0.041	0.347
	Mean among high-SES families	0.365	0.306
	Mean among non-immigrant families	0.346	0.082

  Table A.1.a: Correlation between Aspirations and Academic outcomes: quality of the measure of parents' social background Preferred tracks include a Master's degree 0.465*** 0.344*** 0.337*** 0.289*** 0.120*** 0.506*** 0.333*** 0.323*** 0.267*** 0.092***

	Variable		Annual teachers' grade			Test scores in June 2013
		(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
	Preferred tracks include an Academic HS	0.689*** 0.599*** 0.577*** 0.574*** 0.211*** 0.718*** 0.588*** 0.563*** 0.527*** 0.171***
		(0.036)	(0.037)	(0.038)	(0.039)	(0.028)	(0.034)	(0.032)	(0.031)	(0.033)	(0.021)
		(0.040)	(0.042)	(0.042)	(0.048)	(0.041)	(0.053)	(0.046)	(0.047)	(0.044)	(0.033)
	Low-SES family		-0.570***					-0.784***
			(0.039)					(0.044)
	Immigrant family		-0.104***					-0.207***
			(0.040)					(0.034)
	Repeated a grade					-0.274***					-0.293***
						(0.041)					(0.032)
	Skipped a grade					0.211***					0.253***
						(0.058)					(0.055)
	Girl					0.249***					0.072***
						(0.028)					(0.022)
	Detailed SES			Y	Y	Y			Y	Y	Y
	Detailed immigration status			Y	Y	Y			Y	Y	Y
	Deciles in test scores in Nov. 2012					Y					Y
	Score at Raven matrices					Y					Y
	Effort put into the test					Y					Y
	Self-Perception of Behavioral Conduct					Y					Y
	Class fixed effects				Y	Y				Y	Y
	Nb Obs	3101	3101	3101	3101	3101	3101	3101	3101	3101	3101
	Adjusted R-squared	0.153	0.231	0.244	0.293	0.581	0.170	0.335	0.360	0.425	0.709
	Mean among students whose pref. tracks do not include...
	... an Academic High School:	-0.512	-0.512	-0.512	-0.512	-0.512	-0.521	-0.521	-0.521	-0.521	-0.521
	... a Master's degree:	-0.089	-0.089	-0.089	-0.089	-0.089	-0.081	-0.081	-0.081	-0.081	-0.081

  Table A.1.b: Correlation between Aspirations and Academic outcomes: quality of the measure of parents' social background (3rd outcome)

	Variable		Entered an Academic HS
		(1)	(2)	(3)	(4)	(5)
	Preferred tracks include an Academic HS	0.364*** 0.332*** 0.321*** 0.309*** 0.176***
		(0.018)	(0.020)	(0.020)	(0.021)	(0.020)
	Preferred tracks include a Master's degree 0.115*** 0.071*** 0.067*** 0.054***	0.020
		(0.016)	(0.016)	(0.016)	(0.018)	(0.018)
	Low-SES family		-0.210***
			(0.017)
	Immigrant family		-0.019
			(0.018)
	Repeated a grade					-0.174***
						(0.021)
	Skipped a grade					0.021
						(0.019)
	Girl					0.048***
						(0.015)
	Detailed SES			Y	Y	Y
	Detailed immigration status			Y	Y	Y
	Deciles in test scores in Nov. 2012					Y
	Dummies for score on Raven matrices					Y
	Effort put into the test					Y
	Self-Perception of Behavioral Conduct					Y
	Class fixed effects				Y	Y
	Nb Obs	3101	3101	3101	3101	3101
	Adjusted R-squared	0.171	0.222	0.233	0.251	0.428
	Mean among students whose pref. tracks do not include...
	... an Academic High School:	0.472	0.472	0.472	0.472	0.472
	... a Master's degree:	0.698	0.698	0.698	0.698	0.698

  Table A.2: Correlation between Aspirations and Educational Outcomes, by SES Mean among students whose pref. tracks do not include an Academic HS:

		Annual	Test Scores	Entered an
		Average Grade	in June	Academic HS
	Variable	(1)	(2)	(3)
	Preferred tracks include an Academic HS	0.120**	0.125***	0.089**
		(0.052)	(0.047)	(0.036)
	Preferred tracks include a Master's degree	0.160***	0.089	0.023
		(0.046)	(0.054)	(0.014)
	Pref. tracks include an Academic HS * Low-SES family	0.132**	0.061	0.112**
		(0.067)	(0.055)	(0.044)
	Pref. tracks include an Academic HS * Immigrant family	-0.012	0.009	0.025
		(0.073)	(0.053)	(0.048)
	Pref. tracks include a Master's degree * Low-SES family	0.004	0.056	0.051
		(0.076)	(0.079)	(0.036)
	Pref. tracks include a Master's degree * Immigrant family	-0.118	-0.081	-0.083*
		(0.081)	(0.076)	(0.044)
	Low-SES family	Y	Y	Y
	Immigrant family	Y	Y	Y
	Other controls: per se and interacted with low-SES family
	and immigrant family:
	Repeated a grade	Y	Y	Y
	Skipped a grade	Y	Y	Y
	Girl	Y	Y	Y
	Deciles in test scores in Nov. 2012	Y	Y	Y
	Dummies for score on Raven matrices	Y	Y	Y
	Effort put into the test	Y	Y	Y
	Self-Perception of Behavioral Conduct	Y	Y	Y
	Class fixed effects (without interactions)	Y	Y	Y
	Nb Obs	3101	3101	3101
	Adjusted R-squared	0.579	0.706	0.430

Laboratoire interdisciplinaire d'évaluation des politiques publiques) est un laboratoire d'excellence (Labex). Ce projet est distingué par le jury scientifique international désigné par l'Agence nationale de la recherche (ANR). Il est financé dans le cadre des investissements d'avenir.

	(ANR-11-LABX-0091, ANR-11-IDEX-0005-02)
	www.sciencespo.fr/liepp
	Sciences Po -LIEPP
	27 rue Saint Guillaume
	75007 Paris -France
	+33(0)1.45.49.83.61
	liepp@sciencespo.fr

The standard errors are clustered at the school level and robust; they are reported in parenthesis. * indicates significance at the 10% level, ** indicates significance at the 5% level, *** indicates significance at the 1% level.

Le LIEPP (

Note that measuring the eect within class allows to exclude any confounding factors linked to sorting between schools and classes, but it also makes the identication very demanding as we exclude any real eect that may exist across classes.

Parents of low-achieving grade 9 students were invited to an individual meeting with the school principal, where they were informed about the vocational and academic track options available after middle school, and sensitized to the importance of adjusting expectations to student performance.

This experiment focuses exclusively on low-achieving students, whereas our paper provides results on the entire distribution of students.

12 individual meetings providing low-SES students with new Academic Possible Selves together with strategies to attain these selves, specically methods to perform better in school.

3-year vocational-track (Lycée Professionnel) students have formal access to universities with their professional Baccalaureate, but they are not academically prepared for university, so in practice less than 5% actually enroll in a classic curriculum at university. The other 20% enroll in 2-year technical programs in institutes that are not located inside a university (even if they are ocially part of it). And as access to higher education requires the completion of a Baccalaureate (Baccalauréat ), students from 2-year vocational-track (Centre de Formation par l'Apprentissage) cannot access higher education (their diploma is Certicat d'Aptitude Professionnelle).[START_REF] Afsa | La moitié d'une génération accède à l'enseignement supérieur[END_REF]

The correlation between the test scores in November 2012 and in June 2013 is 0.78.

As questions on the math tests are open questions, a student is considered as having attempted to solve the question if s/he wrote down some calculation and/or provided an answer, independent of whether the answer was right or not.

Note that 93% of those who aspire to master's degree also aspire to an academic high school, while only 20% of those who aspire to an academic high school also aspire to a master's degree.

Neighborhood characteristics are neutralized using class xed eects because in this study all the schools are public schools, and thus the great majority of the school population is dened by geographical zoning.

available upon request.31 Indeed, we nd that only 13% of students who cite academic high school as attainable also cite vocational high school as attainable, and this proportion is similar for both high-and low-SES students (gap of 2 percentage points, non-signicant).Along these lines, when we impose vocational high school to be attainable when academic high school is (and when the student mentions vocational high school among the existing tracks), the previous results on attainable and preferred tracks remain qualitatively similar.

The fact that high-achieving students are more likely to pass the national exam at the end of academic high school in priority education schools is entirely explained by the fact that they have a higher probability to enter academic high school. This last result is probably due to the fact that a high-achieving student is seen as more able in a low-achieving school than in other schools.

We report these results because, while answering the survey, students may have interpreted lives in an advan- taged/disadvantaged neighborhood as being from a low/high-SES family.

* We wish to acknowledge the support of LIEPP (Interdisciplinary Research Center for the Evaluation of Public Policies), the Sciences Po Scientic Advisory Board, the Direction de l'évaluation, de la prospective et de la performance in the French Ministry of Education, and the French National Research Agency (ANR-11-LABX-0091, ANR-11-IDEX-0005-02, and ANR-10-BLANC-1819-01-EVALPOLPUB). We are grateful to Yann Algan, Pierre-Henri Bono,

 Sewell, William, Archibald Haller, and Alejandro Portes. 1969. The Educational and Early Occupational Attainment Process, American Sociological Review, 34(1): 82-92.

Sewell, William, Archibald Haller, and George Ohlendorf. 1970. "The educational and early occupational status attainment process: replication and revision", American Sociological Review, 35: 1014-1027.