Credible School Value-Added with Undersubscribed School Lotteries

2021 ◽  
pp. 1-46
Author(s):  
Joshua Angrist ◽  
Peter Hull ◽  
Parag A. Pathak ◽  
Christopher Walters
Keyword(s):  
New York ◽  
New York City ◽  
Instrumental Variables ◽  
York City ◽  
Empirical Bayes ◽  
Value Added ◽  
Dimensional Models ◽  
Low Dimensional ◽  
School Assignment

Abstract We introduce two empirical strategies harnessing the randomness in school assignment mechanisms to measure school value-added. The first estimator controls for the probability of school assignment, treating take-up as ignorable. We test this assumption using randomness in assignments. The second approach uses assignments as instrumental variables (IVs) for low-dimensional models of value-added and forms empirical Bayes posteriors from these IV estimates. Both strategies solve the underidentification challenge arising from school undersubscription. Models controlling for assignment risk and lagged achievement in Denver and New York City yield reliable value-added estimates. Estimates from models with lower-quality achievement controls are improved by IV.

scholarly journals The Welfare Effects of Coordinated Assignment: Evidence from the New York City High School Match

2017 ◽  
Vol 107 (12) ◽  
pp. 3635-3689 ◽  
Author(s):  
Atila Abdulkadiroğlu ◽  
Nikhil Agarwal ◽  
Parag A. Pathak
Keyword(s):  
High School ◽  
New York ◽  
New York City ◽  
Education Reform ◽  
York City ◽  
Popular Education ◽  
Welfare Effects ◽  
Student Preferences ◽  
Deferred Acceptance ◽  
School Assignment

Coordinated single-offer school assignment systems are a popular education reform. We show that uncoordinated offers in NYC's school assignment mechanism generated mismatches. One-third of applicants were unassigned after the main round and later administratively placed at less desirable schools. We evaluate the effects of the new coordinated mechanism based on deferred acceptance using estimated student preferences. The new mechanism achieves 80 percent of the possible gains from a no-choice neighborhood extreme to a utilitarian benchmark. Coordinating offers dominates the effects of further algorithm modifications. Students most likely to be previously administratively assigned experienced the largest gains in welfare and subsequent achievement. (JEL C78, D82, I21, I28)

scholarly journals Teacher Preparation and Student Achievement

2009 ◽  
Vol 31 (4) ◽  
pp. 416-440 ◽  
Author(s):  
Donald J. Boyd ◽  
Pamela L. Grossman ◽  
Hamilton Lankford ◽  
Susanna Loeb ◽  
James Wyckoff
Keyword(s):  
New York ◽  
New York City ◽  
Teacher Preparation ◽  
York City ◽  
Test Score ◽  
Value Added ◽  
High Quality ◽  
Preparation Programs ◽  
Student Test ◽  
City Schools

There are fierce debates over the best way to prepare teachers. Some argue that easing entry into teaching is necessary to attract strong candidates, whereas others argue that investing in high quality teacher preparation is the most promising approach. Most agree, however, that we lack a strong research basis for understanding how to prepare teachers. This article is one of the first to estimate the effects of features of teachers’ preparation on teachers’ value added to student test score performance. Our results indicate variation across preparation programs in the average effectiveness of the teachers they are supplying to New York City schools. In particular, preparation directly linked to practice appears to benefit teachers in their 1st year.

scholarly journals Separate and Unequal – Title I and Teacher Quality

2019 ◽  
Vol 27 ◽  
pp. 14
Author(s):  
Elizabeth Iris Rivera Rodas
Keyword(s):  
New York ◽  
New York City ◽  
Elementary Schools ◽  
Public Schools ◽  
Title I ◽  
York City ◽  
Negative Relationship ◽  
Value Added ◽  
Quality Teachers ◽  
Title I Elementary Schools

Research has shown that Title I’s “comparability” provision causes gaps in noncategorical per pupil teacher funding. Using a unique dataset that merges 2009-2010 New York City (NYC) Department of Education value-added scores, school finance data, and school demographic data, this study not only confirms that NYC Title I elementary schools received less noncategorical per pupil teacher funding than non-Title I elementary schools, but these schools also had lower quality teachers. This paper provides the first evidence of a negative relationship between noncategorical per pupil teacher funding and the percentage of below average teachers even when controlling for certain school demographics. If Title I elementary public schools in New York City have lower quality teachers, then the students that are served by these schools are not receiving the same quality of education as their peers. Changing the comparability provision in Title I funding would result in more equitable funding.

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