The yield curve as a recession indicator...

According to a couple of recent papers from the N.Y. Federal Reserve, the magnitude of the yield curve at the end of monetary policy tightening cycles is an excellent predictor of whether or not the economy will end up in recession within 24 months following the end of the tightening cycle. 

The earlier paper (Adrian and Estrella, 2009) documents the empirical result, while the later paper (Adrian, Estrella, and Shin, 2010) provides a plausible causal mechanism that has its roots in balance sheet management by financial intermediaries.  The idea in (Adrian, Estrella, and Shin, 2010) is that when monetary tightening is associated with a flattening of the term spread (i.e., the gap between yields on 10 year U.S. government bonds and short-term Treasury bills becomes sufficiently small), it reduces net interest margins (NIM) for financial intermediaries.  This reduction in NIM makes lending less profitable, which leads to a contraction in the supply of credit. 

The plot above is slightly different than the one reproduced in both of the above papers.  The difference is that I used the difference between GS10, 10-year U.S. government bonds (constant maturity), and TB3MS, 3-month T-bills (secondary market rate), to construct my yield curve. 

The authors above use a constant maturity 3-month T-bill rate.  I choose the secondary market rate because the data series went back further.  It is possible (likely) that the secondary market rates are systematically higher than the corresponding constant maturity rates.  So compared with the authors measure,  my measure of the term spread is likely to be narrower.

I don't know which method of constructing the term spread is preferable...but Greg Mankiw uses the same method!   I will post my R-code (and data) for constructing the above plots soon...

Asset Price Cycles and Collateral...

Some intuition on how borrowing constraints can lead to cycles in asset prices.  My explanation below is heavily influenced by Geanakoplos (1997), and Kiyotaki and Moore (1997).  First I will explain why asset prices will be more volatile in a world where investors can buy on margin, and then I will provide some intuition as to why this process can lead to cycles in assets prices.

Suppose that you are an investor, and that you have the ability to buy assets on margin (i.e., you are allowed to use the asset that you wish to purchase as collateral to borrow the funds necessary to make the purchase).  Note, in passing, that because the borrower keeps position of the collateral during the period of repayment, a fairly sophisticated courts system is a prerequisite for buying on margin.

Buying on margin will allow those agents with the most optimistic view of the future value of those assets (in the Geanakoplos (1997) framework optimistic agents are those agents whose marginal utility of holding the asset is the highest) can hold a larger fraction of those assets in their portfolio than would have been possible absent the ability to buy on margin.  This will lead (initially) to an increase in asset prices because:

1. Asset prices will be higher because every agent can now afford to buy more assets (because of the ability to buy on margin)
2. The marginal buyer of the assets will be an agent with strictly higher marginal utility (compared to a world without the ability to buy on margin).

The ability to buy on margin leads the optimistic agents to have high levels of leverage.  It is the leverage that creates the volatility in asset prices.  To see the leverage effect consider the effects of "bad news" on the price of an asset:

1. Every agent now values the asset less than before the arrival of the "bad news"
2. The lower valuation redistributes wealth from optimistic agents to the pessimistic agents (who did not purchase the asset on margin).  This redistribution of wealth can be very large depending on the leverage of the optimistic agents.  

Now if we are willing to assume that enough optimistic agents survived the fire sale (i.e., that at least some of the optimistic agents were not so levered up that they completely defaulted on their debts following the revaluation of asset prices), then these agents will find the assets that they value highly available for purchase at extremely low prices.  Now is an excellent time for then to buy.  The optimistic agents will begin to bid up the price, and voila we have the makings of a cycle!

Thoughts?

At some point I would like to know (with high probability at least) whether or not the following statement is true:

By spreading risk to those most able to bear it, creating new markets for financial assets (i.e, market completion) increases the productive capacity of the economy.

I came across the statement in a very nice paper by John Geanakoplos.  To provide a bit of context, the quote was lifted from a section of the paper where Geanakoplos was discussing ways in which splitting mortgage promises (i.e., tranching) into collateralized mortgage obligations (CMOs) increase the number of buyers.  The first way is the effectively the above quote.

The second way is that tranching allows investor to speculate on the movements of things like interest rates.  The utility of CMOs as a speculative hedge, raises the value of the CMO to the bank because the bank knows that it will be easier to sell the mortgage on after it has been tranched.  This encourages banks to lower interest rates (or credit standards! or both!) in order to create the CMOs to sell to speculators.  Not surprisingly, Geanakoplos points out that this whole process is not necessarily welfare enhancing. 

Complexity Economics

I embed the videos of the Complexity Economics Panel from the recent INET conference in Bretton Woods for those interested. On a related note, I am wondering what (if any) connections exist between the complex systems notion of the economy as a disequilibrium system, and the existing economic literature on disequilibrium dynamics...

Introduction by Eric Beinhocker:


Brian Arthur:


Ian Goldin:


Thomas Homer Dixon:


Moderated Q/A:

The Use of Knowledge in Society...

I first came across this paper while doing a bit of outside reading during the MSc.  It is one of my all-time favorites, and has strongly influenced my interests in the complex systems approach to economics in general, and networks in particular. 

I quote my favorite passage:

"The problem is in no way solved if we can show that all the facts, if they were known to a single mind (as we hypothetically assume them to be given to the observing economist), would uniquely determine the solution; instead we must show how a solution is produced by the interactions of people each of whom possess only partial knowledge.  To assume that all the knowledge to be given to us as the explaining economists is to assume the problem away and to disregard everything that is important and significant in the real world."

What I take from the above passage is that it is not enough to show that an equilibrium exists, what is needed is to show a process of dynamic adjustment that describes how such an equilibrium can be reached given that agents have only partial knowledge of the world.  I remember as an MSc student being deeply skeptical of the utility of the Arrow-Debreu general equilibrium framework because it showed only that an equilibrium existed and did not specify a dynamic process of through which that equilibrium was obtained.  Needless to say, I was very excited when I came across this paper as it indicated to me that I was not alone in my concern. 

On a related note, for those interested in a another way of modeling the price system, I highly recommend Growing Artificial Societies.  The book is slightly dated now (most of the work was done in the late 1980's early 1990's).  The authors use a computational model/simulation to show how (and under what conditions) market prices in an economy consisting of heterogeneous agents, operating under only limited knowledge of their environment, can converge to something resembling an equilibrium prices.  Perhaps even more interestingly they delve into when prices should not be expected to converge.  NetLogo has a version of the model that replicates most (all?) of the results from the book.

Upon reflection, I think the economics of Keynes and Hayek are in many respects closer than people think.  This is particularly true if one's knowledge of the differences between Keynes and Hayek comes from the following two rap videos from YouTube.