Federal Reserve

Hsinyu (Samuel) Tseng, Douglas A. WebberWe use the longitudinal component of the Current Population Survey to compare transition rates into and out of disability and employment prior to and after the onset of the pandemic. We find that one-third of the increased employment rate among disabled people is due to the excess incidence of disability seen following the pandemic, while the other two-thirds is attributable to higher participation among people whose disabilities were unrelated to the pandemic.

Jillian Mascelli and Megan RoddenThis paper analyzes the risks posed by future-state quantum computers, specifically the “harvest now decrypt later” (HNDL) risk. We review foundational concepts of quantum computing to address the present and ongoing threat of HNDL to currently protected data. We use the Bitcoin network as an illustrative example to study the implications of HNDL for distributed ledger cryptocurrency networks that rely upon traditional cryptography.

Yesol Huh and Matthew Vanderpool KlingThis paper introduces parallel trends forest, a novel approach to constructing optimal control samples when using difference-in-differences (DiD) in a relatively long panel data with little randomization in treatment assignment. Our method uses machine learning techniques to construct an optimal control sample that best meet the parallel trends assumption. We demonstrate that our approach outperforms existing methods, particularly with noisy, granular data.

Anushka MitraThe unemployment rate remains elevated long after recessions, a persistence that standard search-and-matching models cannot explain. I show that noise shocks—expectational errors due to the noise in received signals about aggregate shocks—account for much of this sluggishness. Using a structural VAR, I find that absent noise shocks unemployment would have recovered to its pre-recession level six quarters earlier over 1968–2019.