Seven Faces of "The Peril"...

Besides being one of the better titled economics papers that I have come across in awhile, St. Louis Fed President James Bullard's Seven Faces of "The Peril" is an excellent discussion of current U.S. Monetary policy and the likelihood of the U.S. experiencing a Japanese style extended period of deflation. 

Bullard's analysis, which is largely based on a Benhabib et al paper entitled "The Perils of Taylor Rules," concludes that current Fed policy of an "extended period of low nominal interest rates" is likely increasing the likelihood of the U.S. experiencing a Japanese style deflation!  The best tool that the Fed has to flight the deflation scenario is aggressive quantitative easing.

Hospice Care...

I am not very knowledgable when it comes to the economics of healthcare, but having watched two grandparents die of cancer this excellent article in the New Yorker by Atul Gawande struck close to home.

If you find the New Yorker piece interesting, then check out his books:

Niall Ferguson '03 versus Niall Ferguson '10...

Matthew Yglesias puts together a hilarious and also very sad mock debate between Niall Ferguson circa 2003 and Niall Ferguson circa 2010.  I really enjoyed Empire and Colossus...but for a historian he makes a piss-poor economist.

Favorite snippet (bold is Niall circa 2003 and italics is Niall earlier this month in the FT):

The only imminent danger is that the dollar could slide sharply against Asian currencies, as it has against the euro. But the chief losers then would be the Asians. And those who panicked about the debt under President Reagan failed to see how manageable it was. It’s even more manageable today.

Hogwash. It was said of the Bourbons that they forgot nothing and learned nothing. The same could easily be said of some of today’s latter-day Keynesians!

The Economy: A Closed or Open System...

The first law of thermodynamics (aka the conservation of energy principle) says that energy is neither created nor destroyed.  This central principle of physics featured prominently in the texts used by Leon Walras and William Jevons when they were developing the mathematical economics that underlie general equilibrium.  There is also a second law of thermodynamics that states that entropy (a measure of disorder/randomness) is always increasing.  Coincidentally the second law of thermodynamics was not well understood at the time that Walras and Jevons were developing their ideas on general equilibrium.

Thermodynamics also recognizes two types of systems: closed systems and open systems.  Closed systems are those systems that do not react, interact, or communicate with any other system (i.e., there is no energy, matter, information, etc flowing out of a closed system).   Within a closed system energy may be converted from one form to another, but it is neither created nor destroyed (via the first law of thermodynamics) and (via the second law of thermodynamics) the system will tend to a state of maximum disorder or entropy where it will come to a rest.  Open systems, on the other hand, are different.  Energy, matter, and information flow into and out of an open system.  Open systems can harness the energy flowing in to create structure and order temporarily, but over time via the second law of thermodynamics disorder reigns supreme.  In open systems there is a constant tension between energy fed order creation, and entropy driven order destruction.

Closed systems always have a predicable maximum entropy equilibrium (although the dynamics by which the system reaches this equilibrium can be quite complicated).  Open systems on the other hand may display equilibrium behavior...or they may display sustained disequilibrium behavior, wild oscillations, exponential growth, punctuated equilibrium dynamics, chaotic behavior, etc.  Closed systems will tend toward an equilibrium state of maximum disorder and do not have the ability to self-organize the way open disequilibrium systems do...

So...is the economy best characterized as a closed equilibrium system or an open disequilibrium system?  I urge you to answer this question for yourself, as it has fairly profound implications as to the type of economics (particularly macroeconomics) that you should spend time studying.  But before you spend a great deal of time pondering...take 30 seconds and look out the nearest window.

Complex Adaptive Systems...

Wendell Jones has published an excellent introductory essay on complex adaptive systems on Beyond Tractability.  Although his specific focus is conflict resolution, he does a good job of explaining the key differences between adaptive versus determined systems, and complex versus complicated systems.  Jones also makes an interesting observation on western approaches to knowledge and science and how these approaches might actually be impediments to our understanding of complex systems: 

"Those of us embedded in European or North American cultures face a significant challenge in understanding and describing complex social systems such as complex intractable conflicts. There are epistemological assumptions so deeply embedded in these cultures' education and worldview, that one is not even generally aware of them. However, these assumptions make it difficult to understand and/or deal with complexity. These assumptions include:

• Every observed effect has an observable cause.
• Even very complicated phenomena can be understood through analysis. That is, the whole can be understood by taking it apart and studying the pieces.
• Sufficient analysis of past events can create the capacity to predict future events.

These assumptions have proven marvelously potent in developing our understanding of the physical world. They have served less well, however, in illuminating how communities of humans interact and behave. It is not for lack of intense effort that these assumptions have fallen short; the social sciences, in the second half of the 20th century, were dedicated to applying these principles to human phenomena."

Jones also has an excellent graphic on the on the differences between complex and complicated systems which I reproduce below:

Ezra Klein Channels Krugman (of March 2009!)...

Read Ezra Klein's blog post from yesterday...and then follow that up with Krugman vintage March, 2009.

Love him or hate him (and many of my conservative friends loathe him), his analysis of the unfolding economic crisis has been consistently superior, more prescient, and more data driven than that of his peers.

Overfitted Models and Overly Complicated Regulation...

Governments are always legislating the last crisis (whether economic or security related).  I would argue that one of the reasons that they persist in doing this is that they always seem to craft overly complicated and excessively precise legislation.  This legislation seems to focus on patching specific "holes" in the existing regulation regime that were identified ex post as that the "causes" of the crisis.

As a result of the high levels of complexity and precision, such legislation is likely to be brittle/fragile and will likely result in unintended consequences.  In a sense, such legislation suffers from problems similar to those of an over-fitted statistical model.  A good model will capture key drivers of the underlying process while allowing for some (perhaps even significant variation) between the estimated and observed values.   Because it has captured key drivers of the underlying process, a good model will be very robust when used to predict future values.  An over-fitted model, on the other hand, will be crafted to fit the historical data with very high precision, but because of this high level of historical precision the model can be very brittle when used to predict future values.  Instead of capturing key drivers of the underlying process, an over-fitted model simply reproduces the historical data with high accuracy...who knows what it might produce when used to predict future values.

How does this relate to government legislation/regulation? Good legislation/regulation should capture in broad strokes the key factors associated with a crisis or socio-economic process that the government legislation is designed to target.  Now clearly this is easier said than done as what actually constitutes a "key factor" in the real world of politics is just as debatable as what constitutes a "key driver" in the real world of economic modeling. 

Nonetheless, I think it would be useful if more people new the difference between an over-fitted model and a good model...      

Free-form Thought of the Day...

Not quite Faulkner-esque stream of conciousness, but...

While walking the dog this morning, I began thinking about the evolution of economic networks over the business cycle.  I think there may be a way to take Hyman Minsky's financial instability hypothesis and embed it into a dynamic network context.  The idea would be to take a model that links business cycles in the real economy with network evolution in the financial sector.  Two possible features of network evolution over the business cycle that I think would map nicely into Minsky's instability hypothesis:

1. During the growth phase of the business cycle links are added to the financial network as more lending takes place, and
2. If one thinks of the links between any two financial institutions in the network as being weighted in proportion to the amount of credit/debt between the two firms, then if leverage levels increase with the business cycle these links will be "strengthened."

Do business cycles incentivize the development of certain network structures in financial markets that are locally robust, but globally fragile?  If so how does this robust, yet fragile network relate to Minsky's instability hypothesis?  Alternatively does the evolution of certain network structures in the financial markets drive business cycles?  Do incentive structures in the financial markets encourage the development of robust yet fragile networks that invariably breakdown causing recessions?  Maybe a little bit of both?  To be continued...

Links for Today...

• MSN: Jubak on the bubble in the Chineses housing market
• WSJ: "Liberal Tax Revolt"
• FT: Trichet says "Stimulate no more!"
• WSJ: Less Than Stressful EU Stress Tests?
• BW: Interview with Nassim Taleb on Government Debt and Deficits
• FT: A tongue-in-cheek Martin Wolf on the 'Politcal Genius of Supply-Side Economics'
• Time: "With Stocks its not the Economy"

Asking About Prices, Again...

Due to popular demand, I thought that I would take some time to expound upon some of the interesting results from Alan Blinder's Asking About Prices: A New Approach to Understanding Price Stickiness.

First of all, why should we care about price stickiness?  Chiefly because sluggish price adjustment (price stickiness) provides a mechanism through which monetary policy can affect the real economy.

The following theories of prices stickiness emerged from the results of Blinder's survey as winners: coordination failure, non-price competition, implicit contracts and cost-based pricing (it is worth noting that all of the theories that did well in the survey have a distinctly Keynesian flavor):

1. Coordination Failure: Firms hold back on price changes waiting for other firms to go first.
2. Cost-Based Pricing: Price rises are delayed until costs rise, and these delays accumulate through  multi-stage production process.
3. Non-Price Competition: Firms vary non-price elements such as delivery lags, service, or quality.
4. Implicit Contracts: Firms tacitly agree to stabilize prices, perhaps out of "fairness" to customers.

Coordination Failure: First it is worth noting that this theory implies a priori that price increases should be "stickier" than price decreases.  This implication was borne out in the survey data.  As Blinder points out, the theory also implies that increases in the nominal money supply should be more effective at ending recessions than decreases in the nominal money supply are at causing them.  

Non-Price Competition: This one is a bit more difficult to summarize...as such I will try to address it in a later blog post.

Implicit Contracts and Cost-Based Pricing: Though it did well in the survey, Okun's implicit contract theory is difficult to test. Okun's original idea was that firms would form these implicit contracts as a result of their desire to attract repeat customers and thus economize on search costs.  Interestingly, firms in the survey with larger numbers of repeat customers did not rate this theory highly.  Firms who rated this theory highly focused on the need to establish a general reputation for "fairness" or "fair-dealing."  Now cost-based pricing only works as a theory of price stickiness if firms fail to react to anticipated increases in input prices (i.e., costs).  Why would a firm not raise nominal prices if it sees nominal cost rises coming?  Coordination failure and an unwillingness to antagonize customers perhaps (i.e., implicit contract theory)?  But what about money illusion?  Any implicit contracts that are optimal/rational would have to apply to relative prices (i.e. real prices).  Thus there should be no money illusion...but Blinder's survey results clearly demonstrate that firms rarely pay attention to national inflation forecasts.  Most real-world contracts are nominal.  How to reconcile these two facts...perhaps if firms believe that customers suffer from money illusion, then frequently tinkering with nominal prices as part of an effort to stabilize real/relative prices might drive them off!

I really enjoyed reading this book.  I think Blinder's contribution is significant and worthy of more notoriety than it seems to have attained.  In fact I wonder if you could use the book to teach a graduate course (or part of one) in macro...  

Quote of the Day...

"Economic theory is always and inevitably too simple; that can not be helped. But it is all the more important to keep pointing out foolishness wherever it appears. Especially when it comes to matters as important as macroeconomics, a mainstream economist like me insists that every proposition must pass the smell test: does this really make sense? I do not think that the currently popular DSGE models pass the smell test. They take it for granted that the whole economy can be thought about as if it were a single, consistent person or dynasty carrying out a rationally designed, long-term plan, occasionally disturbed by unexpected shocks, but adapting to them in a rational, consistent way. I do not think that this picture passes the smell test. The protagonists of this idea make a claim to respectability by asserting that it is founded on what we know about microeconomic behavior, but I think that this claim is generally phony. The advocates no doubt believe what they say, but they seem to have stopped sniffing or to have lost their sense of smell altogether."

-Robert Solow

Links for Today...

• Bloomberg: "Bond Default Means Too Much Debt, Too Little Time"
• Salon: "Restore the Estate Tax"  (Personally, I would like to see a 100% estate tax above some inflation indexed threshold with 100% of the tax liability forgiven if the money is donated to charity).
• Bloomberg: "Bernanke Swings Both Ways!"
• Matthew Yglesias: "Why are we Democratizing Investing?"
• Chaospet: Zombie Karl Popper!
• Krugman: "Notes on Rogoff"
• Robert Solow to U.S. Congress: DSGE Models fail the "Smell Test"
• FT: "America's sensible stance on recovery"
• A profile of Harvard economist Al Roth

Chinese Housing Bubble...

Read this interesting post on the Chinese housing market from Econbrowser.  A guest at a dinner party I attended a couple of weeks back who manages a luxury hotel in Shanghai had an interesting anecdote about the housing market in China at the moment.  His story went something like this...

"There are a lot of recently completed but mostly empty luxury high-rise apartments in Shanghai and other major Chinese cities.  The reason that they are mostly empty is not because people aren't buying them, but because people are buying them on spec and then re-selling them.  Individuals are borrowing the money, buying these apartments and them re-selling them after 3-4 months without ever living in them.  It is the pace of the turnover that I found to be astounding: 3-4 months!  It certainly says something about the amount of liquidity that must be flowing through the Chinese economy (despite the Chinese gov'ts apparent recent attempts to rein in lending)." 

Asking About Prices...

I have finished reading Alan Blinder's "Asking About Prices." I would highly recommend it. Among the many survey results he reports I will mention several that stuck out for me in particular:

1. The majority of firms surveyed reported that they had globally declining MC curves (as opposed to the textbook increasing marginal costs). Blinder does point out that marginal costs is not a concept that makes much sense to real world businessmen and posits that they may be confounding MC with AC.
2. Hardly any firms used freely available data on inflation as part of their price setting decisions...hard to justify unless you allow for the possibility that people suffer from money illusion.
3. The theory of sticky prices that tested the best (by far) amongst real world businessmen was a theory of coordination failure amongst firms (2nd best was a theory of NON-price adjustment where markets clear in dimensions other than price). Without going into the bowels of the coordination failure theory it is worth noting that this theory predicts a priori that prices should be more sticky when prices are increasing. This is counter to the conventional Keynesian idea that prices are sticky when they are decreasing. This is particularly noteworthy in light of another major survey finding...
4. Survey finds evidence that prices are more sticky when prices are increasing than when prices are decreasing! One key reason for this that crept up again and again in the free form answers from real world businessmen was that they were afraid to increase prices because they did not want to "antagonize their customers." This idea has a very Keynesian "Animal Spirits" flavor to it...

I could go on with additional nuggets...but really anyone interested in macro should read the book.

Quote of the Day...

"It is rare for anyone but an economist to suppose that price is predominately governed by marginal cost"

-John Maynard Keynes

Links for Today...

• Interesting critique from the Weekly Standard of a recent Alan Blinder WSJ op-ed.  Once you have read the Weekly Standard piece, re-read my post yesterday concerningHyman Minsky and see if you can construct a critique of both the Weekly Standard and the WSJ articles.
• More on Okun's Law...
• More from Niall Ferguson...
• Brad Delong: "Rogoff is wrong on debt worries"
• Ken Rogoff: "No need for a panicked fiscal surge"
• The Chinese are Coming! 
• And the Germans are defying us!

On Privatizing the Education System...

For some reason, and I have no idea why, I spent some time today thinking about the implications of privatizing the education system (by privatizing the education system, I mean totally eliminating the role of the federal, state, and local governments in K-12 and university level education and leaving education to be sorted out by the "market forces"). This is not something that I have given much thought to before, so I apologize if my thoughts seem a bit simplistic.  I assume based on no metric (other than intuition) that the current status quo has government (at all levels) more involved in K-12 education than in unversity level education (in the U.S.)  My initial thoughts...

Clearly the average quality of education at the K-12 level in the U.S. leaves much to be desired.  Ardent supporters of privitization would argue that if education was left up to the "market," then the quality of education would improve (perhaps dramatically).  Implicitly I suppose they mean that, if left up to the market, the quality of education would improve on average.  I wonder though what would happen to the variance (i.e., the spread) of education quality?  What would happen to the gap between the average quality of education and the median quality of education?

At this point I would be willing to concede that the average quality of education might increase, but I am almost certain that the variance/spread of education quality would increase substantially if the education system were privatized.  I would also be willing to bet that the gap between the average quality of education and the median quality of education would increase substantially. 

For a more concrete example, think of the wealth distribution in the U.S.  The average income is very high, but the disribution is also highly skewed (i.e. unequal, average income is higher than median income, etc).  The distribution of income is a particular stark example of a skewed disribution.  But it is also an example of a distribution whose shape is determined by "market forces" and if we are going to ration education by ability to pay (i.e., by the market...and note that I did not say willingness to pay...in the real world willingness to pay and ability to pay are NOT the same thing) then the shape of the income distribution would seem to be relevant.

I haven't yet touched on issues related to market competition.  Advocates of privitization frequently argue that privitizing the education system would allow "market forces" to bid the price of education down.  The problem is that in no way, shape, or form would there exist anything approach perfect competition in the market for education.  At a minimum, options for K-12 education would still be significantly constrained by the physical residence of the parents.  I will try to elaborate on competition related issues in a follow-up post...      

Links for Today...

It was another light day...

• Colander et al: "Mathematics, Methods, and Modern Economics"
• Tamny: "Worry Over the Wealth Gap is Wasted"
• Pesek: "America's AAA Rating is Cut in the Land of Bubbles"
• Wolfers: "Is Okun's Law Really Broken"

Quote of the Day...

"Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world. It is compelled to be this, because, unlike the typical natural science, the material to which it is applied is, in too many respects, not homogeneous through time. The object of a model is to segregate the semi-permanent or relatively constant factors from those which are transitory or fluctuating so as to develop a logical way of thinking about the latter, and of understanding the time sequences to which they give rise in particular cases. Good economists are scarce because the gift for using "vigilant observation" to choose good models, although it does not require a highly specialized intellectual technique, appears to be a very rare one."

-John Maynard Keynes

DeLong vs. Ferguson...

This post was prompted by two dueling op-ed pieces by Brad Delong and Niall Ferguson in today's Financial Times.  The two sides can be best summarised by their respective titles:

• "It is far too soon tom end expansion," and
• "Today's Keynesians have learnt nothing"

I am a big fan of the work of Hyman Minsky which figures prominently in DeLong's piece and I would highly recommend Minsky's "Stabilizing an Unstable Economy" to anyone interested in macroeconomics and financial crises.  Minsky's argument, which is aptly summarised by DeLong, is that in a recession (or depression) brought about by a financial crisis there is an excess demand for safe, risk-free financial assets.  This excess demand is then balanced by excess supply in the labor market (i.e., high levels of unemployment).  Given his diagnosis, Minsky's remedy is to have the government expand the supply of safe, risk-free financial assets by acting as the "lender of last resort." From a practical standpoint, this can be done in three ways:

1) Expand the money supply.  This is the monetarist's cure...
2) Create reserve deposits...
3) Further expand the supply of safe, risk-free government bonds by selling them and using the proceeds to buy risky private sector securities...

All of this rests on the implicit assumption that people view government issued and backed securities as safe and risk-free.  What happens if this is not the case? or perhaps more importantly, how can we tell if people are starting to alter their risk-free expectations concerning government securities?  DeLong argues that financial markets will send a strong signal (in the form of rising interest rates on government securities) when people have had enough expansionary policy, and that currently these markets are sending strong signals (in the form of falling interest rates) that additional expansionary policy is needed.

Ferguson's argument has a predictably more historical flavor, and compares today's economic environment with the economic environment leading up to the second World War.  See here, and here for substantive critiques of his argument.  In the end he arrives at the conclusion that the real debate is not between austerity policies and expansion policies, but between those policies that increase private-sector confidence and those that do not.

Now...if you believe that Minsky's diagnosis is correct, then policies whose sole purpose is aimed at boosting private sector confidence will not help very much (and could very well be counterproductive).  Increased private sector confidence is typically interpreted to mean increased private sector investment.  As such policies aimed at increasing private sector confidence are typically designed to induce private sector investment.  The reason that such policies will be ineffective is that a la Minsky, the excess demand is for safe, risk free assets and NOT for private sector securities (which are inherently risky).         

The Limits of Behavioral Economics...

An interesting op-ed by George Loewenstein in the NYT today on the limits of behavioral economics.  The timing is interesting as I have been thinking about this issue ever since I read Rajiv Sethi's post on the topic a couple of days ago (incidentally, he has now written a follow-up piece).

When I finished my MSc I had a very poor opinion of the rational actor model.  I had just read the reading material for Xavier Gabaix's behavioral economics course at MIT, and was enthralled with the work being done in the area...it seemed so much more advanced and relevant than what I had been taught in graduate school.

Now, however, I am starting to appreciate the rational actor model a bit more.  Don't get me wrong, I think that the rational actor model abstracts from the well documented cognitive biases that human beings exhibit when making decisions.  But I do not think that every economic puzzle can be explained by "irrational" behavior on the part of decision makers.

I am starting to think that the major flaw with the neoclassical (as well as the new-Keynesian) paradigm is that it relies on general equilibrium.  Many aggregate/macro economic behaviors that behavioral economists tend to explain using some model that relies on some type of agent irrationality might also be explained by locally rational agents interacting directly with one another...   

This is a really poorly written post...apologies...it is however a post that I think is on the right track...I just need to figure out a better way to formulate the argument...actually on second thought don't read this post! Read the new post by Rajiv Sethi that I linked to above.  He does a much better job... 

Complex Systems Paper(s) of the Day...

In addition to my academic research, I am highly interested in developing practical applications of network and complex adaptive systems theory.  Here are a series of papers from Peter Mucha at UNC that outline some techniques that I think have significant practical applications in finance and business process optimization (i.e.,  supply chain optimization, currency portfolio optimization, etc):

• Dynamic Clustering of Exchange Rates 
• Communities in Networks 
• Community structure in time-dependent, multiscale, and multiplex networks
• Community Structure in Congressional Co-Sponsorship Networks

Many of the above papers focus on the time evolution of network community structure.  While much of the early network literature focuses on static networks, real world networks are dynamic and evolve over time.  Thus practical applications of networks would be most useful if they could capture this dynamic time evolution in a meaningful way.  Following this line of thinking...

If one was interested in the time evolution of community structure in inter-bank networks with an eye towards creating indicators of systemic risk...then there are a couple of issues that would need to be addressed:

1. Develop a robust network data set!  This type of analysis is incredibly data intensive.  You need enough of a network data so that you can take cross-section slices at various time intervals (quarterly, monthly, weekly, etc).  Ideally you would need to take daily slices in order to develop systemic risk indicators that would be useful...
2. Develop a MEANINGFUL algorithm to identify community structure in bank networks.  There are a number of algorithms that have been developed to id community structure.  However, as discussed in Matthew Jackson's book on social networks, it is often difficult to identify exactly these algorithms are capturing (i.e., do the identified communities have any economic justification? Or are they simply a statistical artifact of the data?)
3. What network analysis techniques are must appropriate to use as measures of systemic risk?
4. Last but not least, how do you get buy-in from clients that this type of analysis would be useful?

Someone who could solve the above problems would make quite a bit of money...

Links for Today

• Felix Salmon: "Moving Out of Equities"
• Tim Duy: "A Deepening Divide?"
• Wall Street Journal: "The Bush Tax Cuts and the Deficit Myth"
• Roubini and Bremmer: "Sagging Global Growth Requires Us to Act" (Incidentally, I wonder who wrote the article Roubini or Bremmer...or neither...methinks neither as it could easily have been written by an advanced undergraduate.)
• NYT: "Moody's Cut Portugal's Credit Rating"
• Skeptical Market Observer: "Two Fat-Tails: Inflation and Deflation"

Complex Systems Paper of the Day...

I have not had the chance to browse this PhD dissertation entitled "Agent-Based Keynesian Macroeconomics".  The intro, however, contains an excellent literature review of applications (both existing and potential) for agent-based modeling in macroeconomics.

I will continue to post my comments on the thesis once I get a chance to read through it in greater detail.  I have high hopes...

The Things That Make Me Laugh...

From the archives of the Three-Toed Sloth...

Major takeaway:

"Sir, you can't work out the answer to that question in any statistically reliable manner, sir, because economic processes are nonergodic, sir, because the economy is subject to positive destabilising feedback sir!"

Very well done that pupil. The rest of you, go back to the books and revise.

CBS News: "On Economy: White House Message Not Sticking"...

CBS News: "On Economy: White House Message Not Sticking"
I am NOT at all surprised that the administration is having difficulty getting their message to stick when their message is at odds with the day-to-day experiences of the millions of Americans who can't find a job, or who have simply stopped looking for a job altogether.

Quote of the Day...

"The role of the economist in discussions of public policy seems to me to be to prescribe what should be done in light of what can be done, politics aside, and not to predict what is ‘politically feasible' and then to recommend it."

Milton Friedman

Links for Today...

• Raghuram Rajan: "How Inequality Fueled the Crisis"
• N. Gregory Mankiw: "The Trilemma of International Finance"
• Two posts and a column by Paul Krugman: "One Size Fits One", "What Have we Learned", and "The Feckless Fed"
• Rajiv Sethi: "Rationality and Fragility in Financial Markets"

It was a light reading day for me, I actually had a couple of meetings to attend at the office...

Complex Systems Paper of the Day...

And today's winner is...

"The Emergence of Firms in a Population of Agents: Local Increasing Returns, Unstable Nash Equilibria, And Power Law Size Distributions"

The paper is long and demanding, but lays out an early (circa 1999) complex systems theory of the firm.  The author relates the complex systems approach to the classical literature on the theory of the firm, outlines his agent-based computational model in detail, and then discusses whether or not the model's predictions concerning various aggregate distributions of firm size, firm growth rates, etc are born out empirically (they are!)

A nice summary paragraph taken from the intro:

"Firms form in the model due to the increasing returns [to agent cooperation at the local level], but, since agents are constantly adjusting their effort levels, large firms are not stable. This is because once a firm becomes large each agent's share is only weakly related to its effort level, and so free-riding sets in. Agents eventually move out of firms "infected" with free riders. Exit decisions are, therefore, also endogenous. It is demonstrated analytically that there do not exist stable equilibria in this environment. Furthermore, it is argued that the nonequilibrium regime provides greater welfare for the agents than would equilibrium even if it were stable. An agent-based computational model is used to study the non-equilibrium dynamics, in which firms are perpetually born, growing and perishing. After an initial transient period there results stationary distributions of firm size (by both number of employees and output) and growth rate. Firm size follows a scaling (power law) distribution, in accord with empirical data.  In fact, for certain parameterizations the power law exponent estimated from the model data is similar to that for U.S. firms. In contrast to increasing returns at the firm level constant returns obtain at the macro-level. The computational model generates empirically testable patterns and regularities, about which there seem to be very little data, such as the distribution of firm lifetimes. Finally, there is a sense in which the model supports the idea that intra-firm cooperation between agents is a by-product of inter-firm competition for agents."

Excellent and insightful paper that outlines a different approach to the theory of the firm.  Those who are interested in leanring more about applying techniques to analyze disequilibrium economic behavior (or those who are just interested in disequilibrium economics generally) will want to read this paper... 

Leverage Causes Fat Tails and Clustered Volatility...

A short, excellent paper by Stefan Thurner, J. Doyne Farmer and John Geanakoplos entiteled: "Leverage Causes Fat Tails and Clustered Volatility."

As noted by the authors, previous literature on endogenous processes that lead to fat tails and clustered volatility in distributions of asset price fluctuations have focused on various forms of "irrational trading behavior" as the root cause.  This paper demonstrates how the ability of traders to buy more assets than there weath would allow by borrowing money from banks (i.e., leverage) causes asset price flucatuations to exhibit fat tails and clustered volatility. 

In their model one of the causes of systemic risk is perversely the risk control policies of the banks themselves.  A prudent bank will seek to insure itself against by placing limits on the amount of leverage that a trader can maintain.  When a trader exceeds his leverage limit he is forced to repay some of his loan by selling the underlying asset.  Crashes can arise when a large number of traders find themselves in excess of their leverage limits (and thus having to repay) when the price of the underlying asset is already falling.  The resulting non-linear positive feedback reinforces the negative price movement causing it to fall even further, etc.  Now in the real world banks often seek to adjust leverage limits based on recent market conditions (i.e., banks will raise leverage limits when the market has been relatively stable, and will lower leverage limits when markets have been highly volatile).  Based on the linkages shown in the model, this would only make matters worse as traders would be deprived of funds at the moment they need them the most.

Major takeaways for me:

1. The linkage between leverage, fat-tails, and clustered volatility in the distribution of asset price fluctuations.
2. Sensible risk management policy at the individual bank level, can easily lead to increasing levels of risk exposure for the banking system as a whole. Sensible regulatory policy aimed at mitigating systemic risk should not rely soley on mitigating risk at the level of the individual bank.
3. This does not imply that leverage limits are a bad thing!

Perhaps what is needed is substantial diversity of leverage limits in the banking system, as opposed to a set of rules that apply to all banks?  I am reading "The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies" by Scott Page at the moment, and thus the potential benefits of diversity are fresh in my mind...

David's Rules of Consulting Work, Cont'd...

• Maintain a professional and organized HR staff that is able to respond quickly and efficiently to both employees and prospective employees queries...

Competent HR is a BIG deal, particularly with prospective employees.  HR personnel are typically the first to have substantial interaction with potential hires, and a disorganized and unprofessional HR staff is a big turn-off and reflects poorly on the whole company...

Links for Today...

• Robert Vienneau: Manifestations of Sraffa Effects in General Equilibrium Models?
• Multiple posts by Rajiv Sethi:
• An Outsider's View of Modern Macroeconomics
• On the Consequences of Nominal Wage Flexibility
• On Buiter, Goodwin, and Nonlinear Dynamics
• On Rational Expectations and Equilibrium Paths
• Michael Spence: America Needs a Growth Strategy
• American Enterprise Institute: The Rising Threat of Deflation
• David Colander: Telling Better Stories in Introductory Macro
• Andy Grove: How to Make an American Job Before Its Too Late

Greatest Hits, Intro...

A good friend of mine (who happens to also be studying for his PhD in economics) recently posed the following question to me via email:

"What do you think have been the 5 or 10 greatest substantive contributions (i.e. not just discussions of methodology) of complex systems theory to economics so far?"

An excellent question!  For those readers of this blog (if there are any at this point) who are not familiar with/sceptical of the complex systems approach to economics, these 5-10 greatest hits will serve as a nice anchor/point of departure. 

This post will be a work in progress...to get things started, I would like to direct your attention to a nice slide deck on Agent-Based Computational Economics (ACE) by Leigh Tesfatsion at Iowa State.  I am going to try to avoid commenting further on methodological issues, but the majority of the results that I will discuss will likely use some form of agent-based modelling, so it is worthwhile to have some knowledge of these methods.  For those interested in a deeper discussion of ACE, I would refer you here. 

To Extend, or Not to Extend...

If you are interested in the debate on whether or not to extend unemployment benefits I would recommend the following:

• "Unemployment Benefits Aren't Stimulus" Read this Wall Street Journal Op-ed by Arthur Laffer before moving on to read/ look through Raj Chetty's slide deck below on the same topic...
• "Should Unemployment Benefits be Extended" 

Needless to say, I found Chetty's argument for extending unemployment benefits to be much more compelling.

Interview with Rob Hall...

A nice interview with Rob Hall.  Pertinent excerpt:

Region: Your recent paper on gaps, or “wedges,” between the cost of and returns to borrowing and lending in business credit markets and homeowner loan markets argues that such frictions are a major force in business cycles.

Would you elaborate on what you mean by that and tell us what the policy implications might be?

Hall: There’s a picture that would help tell the story. It’s completely compelling. This graph shows what’s happened during the crisis to the interest rates faced by private decision makers: households and businesses. There’s been no systematic decline in those interest rates, especially those that control home building, purchases of cars and other consumer durables, and business investment. So although government interest rates for claims like Treasury notes fell quite a bit during the crisis, the same is not true for private interest rates.

Between those rates is some kind of friction, and what this means is that even though the Fed has driven the interest rate that it controls to zero, it hasn’t had that much effect on reducing borrowing costs to individuals and businesses. The result is it hasn’t transmitted the stimulus to where stimulus is needed, namely, private spending.

The government sector—federal, state and local—has been completely unable to crank up its own purchases of goods; the federal government has stimulated [spending] slightly but not enough to offset the decline that’s occurred at state and local governments.

Region: Yes, I’d like to ask you about that later.

Hall: So to get spending stimulated you need to provide incentive for private decision makers to reverse the adverse effects that the crisis has had by delivering lower interest rates. So far, that’s just not happened. The only interest rate that has declined by a meaningful amount is the conventional mortgage rate. But if you look at BAA bonds or auto loans or just across the board—there are half a dozen rates in this picture—they just haven’t declined. So there hasn’t been a stimulus to spending.

The mechanism we describe in our textbooks about how expansionary policy can take over by lowering interest rates and cure the recession is just not operating, and that seems to be very central to the reason that the crisis has resulted in an extended period of slack.

Can Hall's financial frictions be explained by network effects?  I don't know I will think on it...I have in mind a model where agents are connected via some underlying network where the network topology would serve to exacerbate a contagion of negative beliefs regarding the probability that private lenders would be repayed.  This dynamic would be exacerbated further in the presence of some type of information asymmetry in which lenders were uncertain which agents would default.  In short by helping to spread contagion of beliefs, the network undermines trust (which is crucial in any lending/credit network).

Labor Hoarding...

From Stumbling and Mumbling:

The OBR reckons (pdf) that private sector employment will grow by a net 1.95 million between 2010-11 and 2015-16, more than enough to offset public sector job cuts. I agree with Anthony and Sunny that this is unlikely, for three reasons.

1. It’s a lot by historic standards. The OBR’s forecast is for an 8.3% increase. Although this is less than the 9.7% rise we had in 1993-98 - after the last recession - it is above the 5.6% rise we saw in the five years to the peak in 2008Q1.

2. And there’s a big difference between those five years and the next. Companies could borrow freely then. But unless things change a lot, they’ll not be able to in the next five years.

3. This recession has differed in one respect (at least!) from the early 90s’ one. Back then, firms were quick to shed staff, and so had to re-hire quickly as the economy picked up. This time, though, employment has held up well relative to output: since Q1 2008, private sector GDP has fallen by around 6.6%, whilst employment has dropped just 4.1%.

This suggests many firms have been hoarding labour and under-employing people. Perhaps they’ve been loath to sack skilled workers for fear of not being able to re-hire in the upturn. But this in turn suggests that if the economy recovers, firms will react by using existing labour more intensively, rather than by hiring new staff.

Of course, it could be instead that employment has held up not because of labour hoarding, but because of an adverse productivity shock. But if this is the case, how can employment rise quickly without generating inflation?

These suspicions make me wonder about the OBR. Their forecasts look very much like they are heeding Montagu Norman's advice to a Bank of England economist: “Your job is not to tell us what we should do, but to explain to us why we’ve done what we have.”

Quote of the Day...

"A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it."

-Max Planck, A Scientific Autobiography (1949).

Ramblings on Micro-foundations, Part II...

Here I attach an interesting technical discussion of problems with microfoundations (or perhaps more appropraitely "Lucas-style" microfoundations).  Ever since I took my first graduate-level course in macroeconomics at the University of Edinburgh I have been interested in the issues raised by the Lucas-style microfoundations paradigm.  These issues are important as I believe they cut to the core of macroeconomics, and now that I have decided to pursue a PhD I will have some time (hopefully!) to explore these issues a bit more formally.

In my mind the following are closely linked (but as of yet I have only inklings of how the pieces fit together):

1. Mantel-Sonnenschein-Debreu (MSD)'s "anything goes" theorm concerning the form of aggregate excess demand functions...
2. Disequilibrium dynamics/issues with General Equilibrium
3. The aggregation problem
4. Issues with the Lucas Critique
5. The economy as a complex adaptive system

There is already a well-defined (although perhaps not that well-known?) link between 1, 2 and a version of 3.  What Arrow et al. proved was that IF aggregate excess demand functions 'looked like' individual demand functions (i.e. satisfied the Weak Axiom of Revealed Preference (WARP)), THEN the dynamics of the economy would converge.  What the MSD theorem states is that given the assumptions made on individual behavior and the corresponding individual demand functions within the General Equilibrium (GE) (i.e., Arrow-Debreu) framework, the IF statement above does not hold in general (i.e. aggregate excess demand functions will not necessarily satisfy WARP).  The MSD theorem implies that tatonnement dynamics will not converge (in general).  The reason for this (i.e. that aggregate excess demand functions do not look like individual demand functions) is a version of the aggregation problem.

For me the issues related to 1, 2, and 3 outlined above reinforced my intuition that the economy is best described as a complex adaptive system.  In a complex system, by definition, efficient descriptions of the system depend on the level of aggregation and as such one would not expect that properties of microeconomic excess demand functions would necessarily hold true for an aggregate excess demand function.  Within the complex adaptive systems framework that emphasizes decentralized, local interactions between economic agents, aggregate excess demand is an emergent property. 

Approaches within the complex adaptive systems framework have also been more successful in proving convergence results using models that involve decentralized, local interactions.  The use of decentralized, local interactions in complex systems models contrasts sharply with tatonnement dynamics and the GE framework which are very centralized.  In my opinion the decentralized, local interaction approach is a more intuitive description of reality.

Issues with Modern Macro, Part I...

A very readable paper by Alan Kirman on his issues with certain strains of modern macroeconomics...nothing new if you are already familiar with his work, but will provide an excellent summary of his major issues with the current state of macroeconomics that is tied to the recent/ongoing economic crisis.

Although I agree wholeheartedly with the criticisms outlined in this paper, I should mention that Kirman does not directly address some of the more recent advances in macroeconomics (such as the use of DSGE-style models with heterogeneous agents).  Many of Kirman's critiques will translate to these newer classes of models, but some may not (I am still trying to work out for myself which of his criticisms will carry over...).

David's Rules of Consulting Work...

I have been thinking about the possibility of starting my own consulting firm for a while now.  What follows are some business heuristics that I have developed based on my own experiences doing consulting work:

• The two most important initial hires in a consultancy are your accountant and your Chief Technology Officer/Head of IT.  These should be long term hires, and you must be willing to trust them with your livelihood.
• Whatever expectations and analytic standards you might set for yourself initially, over time the pressures of business will drive your expectations and standards to an equilibrium that is just a little bit ahead of those of your clients.  Therefore, take on a small number of clients that satisfy three requirements:
• Interesting/challenging but tractable problems
• High expectations for both themselves and for your work
• High analytic standards/integrity 
• Be wary of contracting for the government!  Government clients tend to be subject to political considerations.  Oftentimes these political considerations will lead them to throw analytic integrity under the bus.  If you must contract for the government, seek out those agencies/departments whose analytic integrity is closely tied to their institutional reputation (i.e., central banks, etc).  Avoid at all costs working for highly politicized agencies/departments. 
• Leverage the power of cognitive diversity!  Hire a group of cognitively diverse, smart people and then pay them enough to eliminate money as the primary motivator...
• Foster a positive business culture that encourages collaboration both within and across teams...
• Have your employees invest 20% of their time on R&D and professional development...
• Grow Slow! Fast growth is unsustainable growth...

More to follow...

Two Interesting Video Links...

The first video is a lecture by Prof. Herb Gintis on his "Five Principles for the Unification of the Behavioral Sciences"  This is an excellent lecture that serves as a point of departure for key social science theories outside of economics that every economist should be familiar with...

The second video is an excellent exposition on motivation with application to the business world...

Ramblings on Micro-foundations, Part I...

This is the first of many future posts on the topic of proper micro-foundations of macroeconomic models...

A major critique of the complex systems approach that I hear repeatedly from economists is that the models lack micro foundations.  This is patently FALSE.  What they lack, typically, but not always is what I term Lucas-style micro-foundations.  This type of micro-foundations can be very useful (particularly as a normative base-line in certain circumstances), but the idea that all macro models MUST have this style of micro-foundation has more to do with the model preferences of economists and is not (in my opinion) grounded in theory.  I would argue there are two types of macro behaviors:

Type I: Macro behaviors that are well described as simple aggregates of the behavior of micro-automata.  Here interaction effects between the agents might not be important.  Thus modeling interactions as impersonal exchanges that happen only through prices is likely quite reasonable.  In a sense if you correctly specify your model of micro behavior, then you can simply "scale" it up and you will have a description of the macro system behavior.

Type II (Emergent): Macro behaviors that are not well described as simple aggregates of the behavior of micro-automata.  In this case the macro behavior of the system is highly dependent on the interactions between agents (i.e. strategic interactions effects, network effects that might engender positive/negative feedback loops, cycles, etc).  If you were able to correctly specify a model of the micro behavior, you can't simply "scale" it up and achieve an accurate description of the macro system behavior.

Now most Lucas style micro-founded macro models (in my opinion) implicitly assume type I behavior (this would include DSGE models as a high profile case).  When I mention behaviors that are irreducibly macro, I meant that they are Type II (Emergent).  If your goal is to describe the properties/dynamics of the macro system, then in this case you can not achieve it by reducing your model to the micro level and then simply "scaling" it back up (a la Lucas style DSGE models). 

Another related criticism of the complex systems approach is that the micro level behavior heuristics assumed in these models are ad hoc.  This is sometimes true and sometimes false.  If a scientist chooses to model micro behavior by assuming that agents follow some decision rule that is well documented in the sociology or social psychology litereature (such as a decision rule documented by Kahneman and Tversky, etc) then is this ad hoc?  I would say no, but I imagine others might disagree.  Clearly a scientist who has documented some type of emergent macro property would want to check to see if this property is simply an artifact of the assumed micro behavior.  If this is the case, then this model is clearly less useful from both a scientific and policy perspective than one in which the emergent behavior is robust to different assumptions on micro behavior. 

The Visa Process...

So, I filled out my UK student Visa application and submitted it online this past week.  The visa process has changed somewhat since I applied two years ago for my MSc.  It seems to have been streamlined significantly, which is a good thing! There is still a biometrics (digital fingerprints and photograph) requirement, and the application fee seems to have gone up a bit.

Now I am awaiting the CAS email and official letter detailing my Principal's Career Development Scholarship funding.  Both of these documents need to be sent in hard copy along with my passport to the UK Consular Office in New York before I can receive my Visa.  Fingers crossed that I will receive the documents soon so that I can finish processing my Visa.  More to follow...