Common Fallacies Surrounding the 2023 Debt Ceiling Debates
Paul Kupiec (American Enterprise Inst.) and Alex Pollock (Ludwig von Mises Inst.)
May 7, 2023
We investigate the veracity of current and former government officials’ claims made in the context of the 2023 debt ceiling standoff: that it would be unconstitutional for the US to default on its debt; that the US has never before defaulted; and there are no extraordinary measures that could be taken to avoid a government default by mid-summer. We show that all of these claims are demonstrably untrue.
‘Not A Thing’: Seven Legal Reasons the Federal ‘Debt Ceiling’ is Null & Void
Robert C. Hockett (Cornell University – Law School)
May 11, 2023
After twelve years of ‘Debt Ceiling’ nonsense, it is gratifying at last to see many officials and scholars now casting doubt on the Ceiling’s validity. It is somewhat regrettable, however, that attention appears to be focused upon the 14th Amendment alone where these doubts are concerned. The Debt Ceiling as it would be applied by today’s rump Republican faction is indeed an affront to the Debt Clause of the 14th Amendment. But it is also an affront to the 1974 Congressional Budget and Impoundment Control Act of 1974, which made the Federal Budget its own ‘ceiling’ – and ‘floor’ – not to mention additional Constitutional provisions including the ‘Take Care’ and ‘Presentment’ Clauses, along with familiar canons of statutory construction including the Later-in-Time Rule, the Lex Specialis Doctrine, the Constitutional Avoidance Doctrine, and the Absurd Result Principle. This Essay elaborates these seven grounds and concludes with a prudential recommendation that the Senate, the President, and all serious Members of the House or Representatives declare the ‘Debt Ceiling’ null and void, thereafter ignoring it henceforth.
What Does the CDS Market Imply for a U.S. Default?
Luca Benzoni (Federal Reserve Bank of Chicago), et al.
May 17, 2023
As the debt ceiling episode unfolds, we highlight a sharp increase in trading activity and liquidity in the U.S. credit default swaps (CDS) market, as well as a spike in U.S. CDS premiums. Compared with the periods leading up to the 2011 and 2013 debt ceiling episodes, we show that elevated CDS spreads in the current environment are partially explained by the cheapening of deliverable Treasury collateral to CDS contracts. We infer the likelihood of a U.S. default from these CDS premiums, and estimate an increase in the market-implied default probability from about 0.3–0.4% in 2022, to around 4% in April 2023, which is lower than it was in July 2011 and about where it was in October 2013. Finally, we document changes in Treasury bills trading activity as market participant update their expectations for a U.S. default.
The Cost of Political Uncertainty: The Bank-Sovereign Credit Risk nexus During the 2011 U.S. Debt Ceiling Crisis
Filippo Gori (OECD)
April 14, 2023
Political events matter in economics. This paper uses the 2011 politicalstando over increasing the US debt ceiling to estimate the impact of USsovereign credit risk on bank default probabilities. Results show that a 100basis points increase in US sovereign default risk implies a 40 basis pointsincrease in bank credit risk. Calculations also suggest that, as a consequenceof the debt-ceiling crisis, US bank funding costs increased by approximately18 basis points.
The US Debt Crisis 2023 and Money Market Funds
Vaibhav Keshav (U. of Illinois) and Trupti Chaure (U. of Oklahoma)
May 25, 2023
We study the fiscal debt crisis in the US during early 2023 on Money Market Funds (MMFs). We report a spike in yields by approximately 150 basis points for MMFs investing in federal government securities. In addition, due to the debt crisis, investors started withdrawing money from treasury funds due to a “flight to safety.” However, there is no statistically significant asset flow from the government and prime MMFs. Finally, we discuss the implications of our results.
Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno