How Do Young People Choose College Majors ?
AbstractPrevious studies on the determinants of the choice of college major have assumed a constant probability of success across majors or a constant earnings stream across majors. Our model disregards these two restrictive assumptions in computing an expected earnings variable to explain the probability that a student will choose a specific major among four choices of concentrations. The construction of an expected earnings variable requires information on the student's perceived probability of success, the predicted earnings of graduates in all majors and the student's expected earnings if he (she) fails to complete a college program. Using data from the National Longitudinal Survey of Youth, we evaluate the chances of success in all majors for all the individuals in the sample. Second, the individuals' predicted earnings of graduates in all majors are obtained using Rumberger and Thomas's (1993) regression estimates from a 1987 Survey of Recent College Graduates. Third, we obtain idiosyncratic estimates of earnings alternative of not attending college or by dropping out with a condition derived from our college major decision-making model applied to our sample of college students. Finally, with a mixed multinominal logit model, we explain the individuals' choice of a major. The results of the paper show that the expected earnings variable is essential in the choice of a college major. There are, however, significant differences in the impact of expected earnings by gender and race. Les études antérieures sur les déterminants du choix d'une filière universitaire ont présumé une probabilité constante de succès entre les différentes filières d'études ou des revenus constants entre les filières. Notre modèle dépasse ces deux hypothèses restrictives en construisant une variable de revenus anticipés pour expliquer la probabilité qu'un étudiant choisisse une filière parmi quatre domaines de spécialisation. La construction d'une variable de revenus anticipés exige de l'information sur la probabilité de succès perçue par l'étudiant, sur les revenus estimés des diplômés dans toutes les spécialisations et sur les revenus alternatifs de l'étudiant s'il échoue à l'obtention de son diplôme. En utilisant des données du National Longitudinal Survey of Youth, nous évaluons les chances de succès dans toutes les filières d'études pour tous les individus de l'échantillon. D'autre part, les revenus individuels estimés des diplômés dans toutes les filières sont obtenus en utilisant les coefficients des régressions de Rumberger et Thomas (1993) obtenus de l'enquête Survey of Recent College Graduates de 1987. Puis nous calculons des revenus alternatifs idiosyncratiques avec une condition dérivée de notre modèle de choix de filière
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Bibliographic InfoPaper provided by CIRANO in its series CIRANO Working Papers with number 97s-38.
Date of creation: 01 Nov 1997
Date of revision:
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College majors; expected idiosyncratic earnings; mixed multinominal logit model; Choix de filières; revenus anticipés idiosyncratiques; modèle polytomique mixte;
Other versions of this item:
- Montmarquette, C. & Cannings, C. & Mahseredjian,S., 1997. "How do Young People Choose College Majors?," Cahiers de recherche 9719, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- MONTMARQUETTE, Claude & CANNINGS, Kathy & MAHSEREDJIAN, Sophie, 1997. "How do Young People Choose College Majors?," Cahiers de recherche 9719, Universite de Montreal, Departement de sciences economiques.
- J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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