Nouriel Roubini On The 10 Megathreats That Could Destroy Our Economy
The Julia La Roche Show The Julia La Roche Show
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 Published On Jan 30, 2024

Nouriel Roubini, Professor Emeritus of Economics at New York University's Stern School of Business, returns to The Julia La Roche Show.

Roubini, known as "Dr. Doom" due to his tendency to make pessimistic predictions, shared his near-term macro outlook for 2024, pointing out that a hard or no landing scenario look unlikely, and a soft or softish landing is the most likely probability.

Elsewhere, Roubini gave an update on the medium-to-longer-term outlook, which includes ten interconnected Megathreats that are a slow moving trainwreck.

Roubini is the Chief Economist at Atlas Capital Team, CEO of Roubini Macro Associates, and Co-Founder of TheBoomBust.com. He is a former senior economist for international affairs in the White House's Council of Economic Advisers during the Clinton Administration. He has worked for the International Monetary Fund, the US Federal Reserve, and the World Bank. His website is NourielRoubini.com, and he is the host of NourielToday.com.

Links:
Megathreats book: https://www.amazon.com/MegaThreats-Da...
Twitter/X:   / nouriel  
Website: https://nourielroubini.com/

0:00 Intro and welcome
1:00 Macro view — soft landing, no landing, or hard landing scenario
3:54 No landing and hard landing scenario don’t look as likely today
6:00 The downside scenario
9:03 Why we avoided a recession in 2023
12:49 Update on Megathreats, worrisome risks in the longer-term, stagflation
20:00 Impact of AI, positive deflation
23:00 Deaths of despair
28:38 Debt situation, mother of all debt crises
31:00 Inflation in the medium-term, 5 or 6%
34:00 Fiscal dominance
36:00 Addressing the debt situation in the U.S.
41:00 Inflation rate likely 6% rather than 2%, impact on 10-year treasury, mortgage rates
46:00 Take on the markets, are they pricing in a soft landing?
49:30 Bitcoin, Bitcoin Spot ETF, and crypto
55:25 World Economic Forum in Davos, conventional wisdom of WEF is always wrong

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