b'FACULTYSPOTLIGHTJONATHAN PAYNEBCF faculty member Jonathan Payne has developed a new global solution algorithm forsolving continuous time heterogeneous agent economies with aggregate shocks. Thisapproach approximates the key functional relationships using neural networks and then usesdeep learning tools to train the model. The main advantage of this technique is that it relaxesthe curse of dimensionality and allows us to find global solutions to non-linear problemswith a large number of agents. This means that researchers can understand how large shocksand major policy changes impact inequality.Payne has two upcoming papers that deploy this toolkit. One paper, Institutional AssetPricing, Segmentation, and Inequality, investigates how restrictions on the financial sectorimpact inequality. Another paper, Deep Learning for Search and Matching Models, studieshow recessions and expansions impact different types of workers. This reflects the USrecovery following the 2007-09 financial crisis during which it took much longer for low-education workers to see a wage recovery than high-education workers.BACKGROUNDJonathan Payneis an Assistant Professor at the Bendheim Center for Finance in theDepartment of Economics at Princeton University. His research studies questions in finance,banking, macroeconomics, economic history, computational economics and econometrics.Prior to joining Princeton in 2019, he held research and teaching positions at NYU and theUniversity of Melbourne. He earned a Ph.D. in economics from NYU in 2019 and an B.C. ineconomics from the University of Melbourne in 2008.4'