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Finally, in table 8 we analyze the portfolio of college choices among top 10 percent students relative to all other students who apply to colleges. Here, we estimate linear probability models (LPMs) predicting different types of application behavior (application flagships, application to open-enrollment campuses, etc.), conditioned on application to at least one Texas public university. Each cell reported in table 8 comes from a separate LPM regression model estimated by race/ethnicity, and we report the estimated regression coefficients on the indicator of a top 10 percent student relative to a same-race/same-ethnicity student who is not in the top 10 percent but is otherwise similar in observable college readiness (and including high school fixed effects).32 As previously mentioned, students in the top 10 percent of their graduating high school class are automatically admitted to all types of campuses contingent on application. So, in theory, top 10 percent students may choose from a wide array of in-state four-year public colleges.

Table 8.
Ordinary Least Squares Regression Results of the Effects of Automatic Admissions Status on Application Behavior by Race and Ethnicity
Black (1)Hispanic (2)Asian (3)White (4)
Applied to flagship 0.200* 0.214* 0.137* 0.193* 
 (0.012) (0.009) (0.014) (0.007) 
Applied to open enrollment −0.075* −0.018* −0.023* −0.039* 
 (0.011) (0.004) (0.006) (0.004) 
Applied only to flagship 0.159* 0.149* 0.346* 0.283* 
 (0.011) (0.009) (0.015) (0.007) 
Applied only to open enrollment −0.065* −0.012* −0.012* −0.027* 
 (0.010) (0.002) (0.003) (0.003) 
Applied to HBCU −0.055* −0.003* −0.001 −0.001* 
 (0.010) (0.001) (0.002) (0.000) 
Applied to multiple campuses −0.040* 0.015 −0.209* −0.111* 
 (0.014) (0.009) (0.023) (0.006) 
Applied to a high SAT campus 0.150* 0.187* 0.091* 0.158* 
 (0.013) (0.009) (0.014) (0.006) 
Applied to a low SAT campus −0.093* −0.033* −0.031* −0.040* 
 (0.013) (0.007) (0.008) (0.003) 
Number of observations 22,405 48,384 9,945 75,934 
Other controls     
Student characteristics Yes Yes Yes Yes 
High school fixed effects Yes Yes Yes Yes 
Black (1)Hispanic (2)Asian (3)White (4)
Applied to flagship 0.200* 0.214* 0.137* 0.193* 
 (0.012) (0.009) (0.014) (0.007) 
Applied to open enrollment −0.075* −0.018* −0.023* −0.039* 
 (0.011) (0.004) (0.006) (0.004) 
Applied only to flagship 0.159* 0.149* 0.346* 0.283* 
 (0.011) (0.009) (0.015) (0.007) 
Applied only to open enrollment −0.065* −0.012* −0.012* −0.027* 
 (0.010) (0.002) (0.003) (0.003) 
Applied to HBCU −0.055* −0.003* −0.001 −0.001* 
 (0.010) (0.001) (0.002) (0.000) 
Applied to multiple campuses −0.040* 0.015 −0.209* −0.111* 
 (0.014) (0.009) (0.023) (0.006) 
Applied to a high SAT campus 0.150* 0.187* 0.091* 0.158* 
 (0.013) (0.009) (0.014) (0.006) 
Applied to a low SAT campus −0.093* −0.033* −0.031* −0.040* 
 (0.013) (0.007) (0.008) (0.003) 
Number of observations 22,405 48,384 9,945 75,934 
Other controls     
Student characteristics Yes Yes Yes Yes 
High school fixed effects Yes Yes Yes Yes 

Notes: Each cell from table 8 is from a separate regression and only reports on the estimated regression coefficients on the indicator of top 10 percent student by race. Samples include only students who applied to college. Students in the top 10 percent are automatically admitted to all types of campuses contingent on application. All regression specifications control for student demographics (e.g., female; age; free or reduced-price lunch eligible; and limited English proficient status), college readiness measures (e.g., number of Advanced Placement [AP] and International Baccalaureate semesters; took AP English language arts, mathematics, and/or science; total semesters failed; and high school exit exam), and high school fixed effects. HBCU = historically black colleges and universities.

*Statistical significance at p < 0.05 level.

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