Daunting debt limit dynamics

Published on31 MAY 2023
Regional Analysis

In this episode, Stephen Kaplan, associate professor at George Washington University, Alec Phillips, Goldman Sachs Research’s chief political economist, and David Beers, former head of sovereign credit ratings at S&P, who oversaw the rating agency’s U.S. credit rating downgrade in 2011, dig into the history and mechanics of the U.S. debt limit and explore whether the repeated brinkmanship around raising the debt limit could undermine the value of U.S. assets. 


Subscribe to Goldman Sachs Exchanges wherever you get your podcasts.

Spotify | Apple | Stitcher


This podcast was recorded on May 15, 16, 17, and 25, 2023

This podcast should not be copied, distributed, published or reproduced, in whole or in part. The information contained in this recording was obtained from publicly available sources, has not been independently verified by Goldman Sachs, may not be current, and Goldman Sachs has no obligation to provide any updates or changes. All price references and market forecasts are as of the date of recording. This podcast is not a product of Goldman Sachs Global Investment Research and the information contained in this podcast is not financial research. The views and opinions expressed in this podcast are not necessarily those of Goldman Sachs and may differ from the views and opinions of other departments or divisions of Goldman Sachs and its affiliates. Goldman Sachs is not providing any financial, economic, legal, accounting, or tax advice or recommendations in this podcast. The information contained in this podcast does not constitute investment advice or an offer to buy or sell securities from any Goldman Sachs entity to the listener and should not be relied upon to evaluate any potential transaction. In addition, the receipt of this podcast by any listener is not to be taken to constitute such person a client of any Goldman Sachs entity. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this podcast and any liability therefore (including in respect of direct, indirect or consequential loss or damage) is expressly disclaimed.



Explore More Insights