Affirmative Action in Higher Education: How do Admission and Financial Aid Rules Affect Future Earnings?

By P. Arcidiacono. 2005

280 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Education

View Paper: https://www.semanticscholar.org/paper/602c2ea929f8547fd9cbe2d29770cae38934a8f2

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In Economics and Econometrics

In Education

Citations in the corpus

Affirmative Action in Education: Evidence From Engineering College Admissions in India. NBER Working Paper No. 13926. (2008, unknown): “action in higher education using detailed micro-admissions data similar to our own and Arcidiacono (2005) , who has used a structural model to estimate the impact of”
University Differences in the Graduation of Minorities in Stem Fields: Evidence from California (2013, unknown): “Students with relatively low levels of academic preparation will find majoring in a STEM field relatively less attractive at the most selective schools.(7) Our estimates suggest that the vast majority of minority students who begin in the sciences at UC Berkeley would be more likely to graduate with”
The Demand for Effective Charter Schools (2018, unknown): “Other related studies look at selection in higher education (Arcidiacono 2005; Brand and Xie 2010; Howell 2010; Arcidiacono, Aucejo, and Hotz 2016; Dillon and Smith 2017) and in education programs outside the United States (Ajayi 2013; Kirkebøen, Leuven, and Mogstad 2016).”
Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models (2008, background): “x for type m defined as the fixed point of the mapping defined by ( 11 ).”
Beyond Signaling and Human Capital: Education and the Revelation of Ability (2008, unknown): “Model (1) (2) (3) (4) (5) (6) Standard.”
An Empirical Investigation of the Option Value of College Enrollment (2012, background): “Columns (1) and (2) provide estimates from a base model with no learning about academic aptitude while columns (3) and (4) provide estimates from the full model described above.”
The Structural Estimation of Behavioral Models: Discrete Choice Dynamic Programming Methods and Applications (2011, methodology): “With regard to a¢ rmative action, Arcidiacono (2005) simulates how African American educational choices would change if they faced white admission and nancial aid rules.”
Practical Methods for Estimation of Dynamic Discrete Choice Models (2011, methodology): “pt(dt|xt) = ∫ I {δt(xt, ǫt) = dt} g(ǫt)dǫt = ∫ I { arg max dt∈Dt [vt(xt, dt) + ǫt(dt)] = dt } g(ǫt)dǫt (7) Therefore, conditional on being able to form vt(xt), estimation is no different than the approach taken for static discrete choice models.”
Affirmative Action and the Quality-Fit Tradeoff (2016, unknown): “Structural models of how students sort into schools by Arcidiacono (2005) and Howell (2010) have been used to predict how the removal of affirmative action affects both the extensive margin (whether students enroll at all) and the intensive margin (where they enroll).”