NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

NBER Publications by Rebecca Diamond

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April 2016Who Wants Affordable Housing in their Backyard? An Equilibrium Analysis of Low Income Property Development
with Timothy McQuade: w22204
We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5%, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher income areas causes house price declines of 2.5% and attracts lower income households. Linking these price effects to a hedonic model of preferences, LIHTC developments in low-income areas cause aggregate welfare benefits of $116 million. Affordable housing development acts like a place-based policy and can revitalize low-income communities.
The Long-term Consequences of Teacher Discretion in Grading of High-stakes Tests
with Petra Persson: w22207
This paper analyzes the long-term consequences of teacher discretion in grading of high-stakes tests. Evidence is currently lacking, both on which students receive test score manipulation and on whether such manipulation has any real, long-term consequences. We document extensive test score manipulation of Swedish nationwide math tests taken in the last year before high school, by showing significant bunching in the distribution of test scores above discrete grade cutoffs. We find that teachers use their discretion to adjust the test scores of students who have "a bad test day," but that they do not discriminate based on gender or immigration status. We then develop a Wald estimator that allows us to harness quasi-experimental variation in whether a student receives test score manipulation...
February 2010Clustering, Spatial Correlations and Randomization Inference
with Thomas Barrios, Guido W. Imbens, Michal Kolesar: w15760
It is standard practice in empirical work to allow for clustering in the error covariance matrix if the explanatory variables of interest vary at a more aggregate level than the units of observation. Often, however, the structure of the error covariance matrix is more complex, with correlations varying in magnitude within clusters, and not vanishing between clusters. Here we explore the implications of such correlations for the actual and estimated precision of least squares estimators. We show that with equal sized clusters, if the covariate of interest is randomly assigned at the cluster level, only accounting for non-zero covariances at the cluster level, and ignoring correlations between clusters, leads to valid standard errors and confidence intervals. However, in many cases this m...

Published: Thomas Barrios & Rebecca Diamond & Guido W. Imbens & Michal Koles�r, 2012. "Clustering, Spatial Correlations, and Randomization Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 578-591, June. citation courtesy of

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