An Improved Version of Bailout Math

The New York Times one ups the Wall Street Journal, taking a more philosophical — and broader — look at the Treasury’s Bailout Math.  

It is still incomplete, but a significant improvement. Recall yesterday we criticized the WSJ’s wide approach  (Light At the End of the Bailout Tunnel) as so much happy talk.

The Time’s Andrew Ross Sorkin followed our advice. In addition to a snarkier tone (Uncle Sam down $89 billion? “It’s enough to make us all feel rich, isn’t it?”) his article included the following bullet points:

• Probable losses from American International Group = $48 billion

• Losses from Fannie Mae and Freddie Mac = about $320 billion

• The Federal Reserve virtually interest-free loans to Wall Street = $1 trillion dollars

• Moral Hazard: Numbers don’t help avoid another financial mess in the future

• Last, its about right and wrong.

Its a more skeptical improvement over other less critical takes on the success of the Bailouts. Still, Sorkin’s piece is also incomplete, leaving out:

• Depleted FDIC reserves;

• FASB 157 suspension allowed banks to hide losses

• Bad loans on bank balance sheets

• General Motors & Chrysler Bailouts

• Ongoing Foreclosures and Housing Problems

• Highly concentrated banking sector/lack of competition

I believe the best we can honestly say about the bailouts (without any spin or bias) is that, so far, the worst case scenarios have not played out, and that the return on investment is in the top quartile of expectations. Further, we still do not know what the final costs will look like, given a variety of factors such as housing, economy, etc. Also, we have no idea what the longstanding repercussions and moral hazard will end up doing in the future. Lastly, we have created a less competitive banking system, and allowed banks to fabricate their balance sheets.

But other than that Mrs, Lincoln . . .

Source:

Imagine the Bailouts Are Working ANDREW ROSS SORKIN NYT, April 12, 2010 http://www.nytimes.com/2010/04/13/business/13sorkin.html


Originally published at The Big Picture and reproduced here with the author’s permission.
 
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