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Working Paper
The Hidden Effects of Algorithmic Recommendations
Algorithms are intended to improve human decisions with data-driven predictions. However, algorithms provide more than just predictions to decision-makers—they often provide explicit recommendations. In this paper, I demonstrate these algorithmic recommendations have significant independent effects on human decisions. I leverage a natural experiment in which algorithmic recommendations were given to bail judges in some cases but not others. Lenient recommendations increased lenient bail decisions by 40% for marginal cases. The results are consistent with algorithmic recommendations making ...
Report
Identifying term interbank loans from Fedwire payments data
Interbank markets for term maturities experienced great stress during the 2007-09 financial crisis, as illustrated by the behavior of the one- and three-month Libor. Despite widespread interest in these markets, little data is available on dollar interbank lending for maturities beyond overnight. We develop a methodology to infer information about individual term dollar interbank loans settled through the Fedwire Funds Service, the large-value bank payment system operated by the Federal Reserve Banks. We find a sharp increase in the dispersion of inferred term interbank interest rates, a ...