We conduct meta-analysis on a comprehensive set of studies of the impacts of US K-12
public school spending on student outcomes–estimating average marginal impacts and …

Many personal and policy decisions turn on perceptions of school effectiveness, defined
here as the causal effect of attendance at a particular school or set of schools on student test …

As the scope of machine learning broadens, we observe a recurring theme of algorithmic
monoculture: the same systems, or systems that share components (eg datasets, models) …

Disparities by race, gender, and other protected characteristics have been widely
documented in many important settings—such as employment, housing, criminal justice …

Notwithstanding the improved integration of various minority groups in the workforce,
unequal treatment in hiring still hinders many individuals' access to the labour market. To …

Algorithms (in some form) are already widely used in the criminal justice system. We draw
lessons from this experience for what is to come for the rest of society as machine learning …

This paper surveys the literature on theories of discrimination, focusing mainly on new
contributions. Recent theories expand on the traditional taste-based and statistical …

Macroeconomics in Context lays out the principles of macroeconomics in a manner that is
thorough, up to date, and relevant to students. Like its counterpart, Microeconomics in …

We assess racial discrimination in mortgage approvals using new data on mortgage
applications. Minority applicants tend to have significantly lower credit scores, higher …

We document the existence of a racial gap in realized housing returns that is an order of
magnitude larger than disparities arising from housing costs alone, and is driven almost …