The Economics profession’s obsession with mathematical models makes it incapable of addressing economic topics that are too difficult to model.  The classic example of this type of topic are financial crises.  Ironically, the adoption of a soft model, would ultimately lead to the creation of the data necessary to mathematically model financial crises.

The soft model that needs to be adopted is the Information Matrix.

Information Matrix

	Does Seller Know What They Are Selling?
Does Buyer Know What They are Buying?		Yes	No
	Yes	Perfect Information	Antique Dealer Problem
	No	Lemon Problem	Blind Betting

The Economics profession is already very familiar with and embraces three out of the four quadrants of this matrix.  The notion of Perfect Information underlies much of its standard economic models.  Information asymmetry was introduced to explain deviations from these standard models.

However, the Economics profession and, in particular, the information economists completely missed and still miss the fact these three quadrants define the existence of the Blind Betting quadrant.

It is the Blind Betting quadrant of the Information Matrix that explains financial crises.

Our financial markets are built on the idea investors are suppose to Trust, but Verify.

Behavioral economics explains why Verify doesn’t always happen.  It recognizes people like a good story.  Wall Street understands this too.  Behind every investment product Wall Street sells is a narrative designed to make the product sound appealing.

In the run up to the Great Depression, it was thought making investors responsible for all losses on their investments would be enough to prevent investors falling prey to Wall Street’s story telling prowess.  The assumption was investors would demand the information they needed to Verify the story.

The stock market crash of 1929 and bank runs throughout the early 1930s showed this wasn’t true.  Why wasn’t it true?  In order to sell an investment, Wall Street doesn’t need every investor.  It only needs the investors who are willing to Trust without Verifying.  Akerlof and Shiller referred to this as Phishing for Phools.

In response to the stock market crash and bank runs, the financial system was redesigned in the early 1930s.  Specifically, transparency was introduced.  The government was given the responsibility for ensuring the disclosure for all publicly traded securities was sufficient so investors could know what they owned.

The Information Matrix shows the intent of the redesigned financial system was to move the vast majority of investments from Wall Street’s preferred Blind Betting quadrant into the Perfect Information quadrant.

Moving investments into the Perfect Information quadrant made sense on a number of levels.  First, the Perfect Information quadrant is where all the theories developed under classical economics about how the market optimally allocates resources work.  Second, it allowed investors to Trust, but Verify the story Wall Street told.  And investors had the incentive to Verify as under the redesigned financial system they were responsible for 100% of the losses on their investment exposures.

Keep in mind, behavioral economic’s observation people like a good story operates in both the Perfect Information and Blind Betting quadrant.  The key difference between the two quadrants is in the Perfect Information quadrant the story can be verified and in the Blind Betting quadrant the absence of the necessary information means the story cannot be verified.

Whether the story can be verified or not results in a vastly different response when Wall Street’s valuation story is called into doubt.  In the Perfect Information quadrant, the story can be verified and the doubt dismissed.  In the Blind Betting quadrant, the story cannot be verified.  Not only is the doubt not dismissed, but the logical follow-up question arises:  is the investment worth anything?  This too cannot be verified.  Investors recognize this and, as behavioral economics suggests, naturally panic.  The result is a “run” to get their money back.

So now we have a “soft” model for financial crises.  How can embracing this model create the data so a financial crises can be mathematically modeled?

The “soft” model suggests the need for the Transparency Label Initiative.  This Initiative awards a label for those investments that provide sufficient disclosure so an investor can know what they own.

This label allows us to measure how much opacity there is the financial system.  Naturally, there is a tipping point where an earthquake along the opacity fault line like we experienced in 2007/2008 triggers a financial crisis.

So the question becomes how much of the global financial system has to be opaque so a financial crisis is possible.  This is a question that can actually be studied and modeled.