In a recent article, Nobel Prize winning economist George Akerlof explained why the modern Economics Profession is incapable of embracing the Information Matrix. It doesn’t have any fancy math.

Since the publication of his famous Lemon Problem paper, Professor Akerlof notes the profession has shifted towards the use of mathematical models. No place is this truer than in the academic journals where the use of mathematical models is virtually a requirement for a paper to get through the peer review process.

However, this emphasis on mathematical models has come at a significant cost to the Economics profession. PhD Economists have become specialists with only a single tool in their tool kit. This has made the profession far less relevant for advising on real world problems which frequently take multiple tools to address.

The classic example of the Economic profession’s descent into irrelevance is its failure to predict the Great Financial Crisis. As Professor Akerlof observes:

In the aftermath of the financial crisis of 2008, economists asked the question why no one had predicted it, at least exactly as it happened. Rajan (2011) said that such a prediction had not been made since it would have required detailed knowledge of theory and institutions in the disparate specialties of finance, real estate and macroeconomics*….

There were incentives to present the key pieces of the puzzle, but none to put them together. Following Caballero (2010), regarding theory, a model with all the pieces could not have been published; it would have been considered too far from precise, simple ideas (such as those that motivate simple new Keynesian or DSGE models); and, in this way, too Soft to merit publication.

Interestingly, the Economics profession also shunned individuals who did put the key pieces together and predicted the crisis in papers published by the BIS. The lack of a mathematical model made it easy to dismiss these papers too.

Professor Akerlof goes on to explain how the preoccupation with math effectively blocks the Economics profession from understanding financial crises.

Suppose the paradigm not only describes the subject matter of the field; suppose it also describes the field’s appropriate methodology. In this case, observations that contradict the existing paradigm will be dismissed if they violate the prescribed methodology. The Hardness police will rule them out, as inadmissible evidence.

Shorter, if you cannot express it with a mathematical equation, Economists aren’t interested.  And this is why they are not interested in the Information Matrix.

Understanding financial crises isn’t possible using mathematical equations.  While you can express a bank run mathematically, you cannot understand the circumstances that trigger the run and hence the crisis.

The Information Matrix allows you to understand the circumstances that trigger a bank run or why a crisis occurred.

The Information Matrix is so easy to understand it can be used to explain financial crises to a 6-year old. As regular readers know, the Information Matrix makes predicting when a financial crisis is likely to occur easy (after all, I used it to predict the Great Financial Crisis based solely on looking at the level of opacity in the global financial system).  The Matrix highlights how Wall Street uses narratives to sell opaque securities.  The Matrix explains what regulations are necessary to prevent a financial crisis (disclosure regulations so buyers and sellers can know what they own and therefore Trust, but Verify the valuation narratives Wall Street tells).  The Matrix also sheds light on how to end a financial crisis (restore transparency).

Information Matrix

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

By introducing the Blind Betting quadrant, the Information Matrix forces members of the economics profession to answer the question of what assumption about information are they making in their models.

When that question is asked, one quickly finds all the finance models and most economic models assume Perfect Information.  This includes models relying on the Efficient Market Hypothesis as EMH assumes the existence of someone with access to perfect information who buys and sells a security.  It also includes models based on information asymmetry as they too assume one party to the transaction has access to perfect information.  

It is not surprising these models assume Perfect Information.  There is no reason to think blindly betting yields the same outcome as informed decision making.

The Information Matrix shows opacity is the ultimate market imperfection.  A market imperfection that Professor Akerlof identified in his Lemon Problem paper.  A market imperfection the financial regulations that emerged in the 1930s focused on correcting.

The Blind Betting quadrant in the Information Matrix is the critical element in integrating behavioral and classic economics.  Behavioral economics has shown everyone likes a good story.  The fact we like a good story isn’t lost on Wall Street.  It deliberately creates opaque securities it can sell based on a valuation story it tells.  The difference between the Perfect Information and Blind Betting quadrant is in the Perfect Information quadrant buyers and sellers can Trust, but Verify the story.  In the Perfect Information quadrant they act as the rational economic man.  In the Blind Betting quadrant, buyers and sellers can only Trust the story as opacity prevents their verifying if it is true or not. When doubts arise about an investment story that cannot be verified, investors run to get their money back (the classic “financial panic” we see during financial crises).

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*During the course of my career, I acquired the detailed knowledge of theory and institutions Professor Rajan asserts and Professor Akerlof agrees is necessary.