1. How schools influence students' academic achievements? A behavioral approach and using data from Add health Yuemei JI University of Leuven

2. Motivation Since the 1980, educational differentials have expanded. Despite substantial increasing premiums to high education, there are high drop-out rates at high school among the economically disadvantaged youth. This could be the result of the social segregation and the deteriorating schools in poor neighborhoods. The school resources literature (class size, per pupil expenditure, teacher education and experience) empirically has not identified any noticeable impacts that explain significant gap between schools.

3. Akerlof and Kranton (2002) and Ji (2008) both argue that emotions such as self-esteem driven by educational identity influence educational choice process. This paper proposes a behavioral model of educational choice and test it using Add health data from U.S.

4. Theoretical Model Educational production function: Educational utility function:, Self-esteem concerns for engaging in school is the intensity (or salience) of this educational identity

5. Results Three equilibria: 1)When, 2)When, 3)When,

6. q r S1S1 S2S2 S 1 < S 2 High effort equilibrium Low effort equilibrium Mixed equilibrium

7. Empirical Hypothesis The effects on effort choice The effects on academic achievement

8. Add health Data A longitudinal study of a nationally representative sample of adolescents in grades 9-12 in the United States, including information on individual characteristics, family backgrounds, academic records and school-level indicators.

9. Summary statistics of individual characteristics and family background:

10. Relevant Variables Two consecutive Math test scores in each academic year How much skills school imparts to its students? Student-level curriculum indicator (provided by AHAA studies) which measures the scope and challenge in the courses. Educational identity 1) School social compositions: race, migration status and students whose mother has a college degree. 2) Student-teacher relationship: “how frequent do you have trouble getting along with teachers?” 3) School-level feeling of happiness at school.

11. Considerations Clusters and correlation in the error term: individuals and schools Chow test for pooling two-wave data

12. Empirical Results: marginal effects on math GPA

13. Marginal effects on skip class

14. Conclusion 1. School-resources studies on school only identify limited impacts on how teachers and average class size influence students’ academic behaviors and performance. 2. A behavioral approach (allowing adaptive preference for schooling) empirically identify that the quality of school (r, q), the previous achievement are determinants of educational performances (math GPA). It suggests the direction to school reform based on a more realistic and concrete framework.