The Wisdom of Laureates

The recent New York Times article on the Minneapolis Fed President, Narayana Kocherlakota is making a moderately big splash on economics blogs because it highlights Kocherlakota’s prominent reversal of his stance on monetary policy.

However, it’s the quote from Ed Prescott that seems to have most people talking.  Prescott is quoted as saying

It is an established scientific fact that monetary policy has had virtually no effect on output and employment in the U.S. since the formation of the Fed.

Paul Krugman says this statement reveals that Prescott is part of “an irrational cult.”  Noah Smith takes this as evidence that the Nobel Prize in economics is screwed-up because, just a few years after Prescott won the Nobel, Chris Sims won and Sims thinks that monetary policy has real effects.  Steve Williamson says that Prescott might simply be trying to be provocative (though he also admits that perhaps there is a case to be made that Prescott is right).

OK, first off – Prescott is wrong.  It is NOT an established fact the monetary policy has no effect on economic activity.  The balance of the evidence suggests the opposite.  Monetary policy seems to have clear measurable effects on the economy.  This isn’t what I want to talk about however.

It struck me as I read the Prescott quote that perhaps we should think a little bit before listening so closely to the opinions of Nobel Laureates.  Nobel Laureates are called upon often to make pronouncements and give policy assessments.  Some of them are asked to be regular contributors to the New York Times.  But should we pay so much attention to their opinions?  Should we grant Ed Prescott, or Paul Krugman, or Robert Lucas, or Peter Diamond much more credence than other smart observers?  It’s really not clear.

All of the Nobel winners are extremely smart.  They are a special group though.  Nobel Prize winners have typically devoted their entire careers to a rather narrow study of a particular area.  I’ll use Paul Krugman as an example.  Paul Krugman’s opinions on trade have to be taken very seriously.  When it comes to the best understanding of international trade, Krugman is the master of the universe.  When he moves on to topics outside of trade however, his assessment loses a lot of its authority.  Krugman is an excellent economist so it’s perfectly reasonable to expect that his opinions on heath policy, tax policy, business cycles, finance, etc. will be reasonable and it’s worth listening to him.  That said, he is not an expert on any of those topics the way he is on trade.

In addition to the fact that Nobel Laureates often have very narrow areas of true expertise, they are also often radical thinkers who are out to overturn established ways of thinking.  Paying attention to a Nobel Prize winner means paying attention to someone who thinks unusual thoughts.  Academics are rewarded not for having good insights on average; they are rewarded for having path-breaking ideas every now and then.   An academic who has one or two ingenious ideas in a career might well be viewed as someone worthy of a Nobel, even if most of their ideas are crazy.  In academia, we can have as many crazy ideas as we want provided that we have a few insightful ideas along the way.  In fact, the price we pay for having unusual insights might be that we often have unorthodox approaches to topics.  I would guess that the Nobel laureates are even more extreme than typical academics.  Prescott’s statement is obviously a bit unorthodox but that is the mode he has been in his whole career.  “Toeing the party line” is just not part of his playbook.  Prescott didn’t win the Nobel Prize for having a balanced assessment of the mainstream consensus of economic expertise.  He won it for putting forth new ways of thinking about economics.  This isn’t limited to Prescott.  Even Paul Krugman has been known to say some rather nutty things at times.

Bobby Fischer was perhaps the greatest chess player ever and was certainly extremely intelligent.  At the same time, Bobby Fischer said many crazy things during his life (he was a Holocaust denier, he thought the U.S. orchestrated the 911 attacks, …).*  Listening to Fischer talk about chess is one thing.  Listening to him talk about foreign policy would be like entering the Twilight Zone.  I certainly don’t want to make a very strong comparison between Bobby Fischer on the one hand, and Paul Krugman and Ed Prescott on the other.  But, when we listen to people like Prescott and Krugman we have to remember that we are drawing on the opinions of a very unusual group.

* Bobby Fischer is a truly tragic figure.  This clip from the ESPN short Finding Bobby Fischer gives a depressing glimpse of Fischer’s life.

Puzzles, Progress and the Scientific Method

In Noah’s reply to my earlier post, he interprets me as saying that purely empirical studies are “worse” than theoretical contributions even if the theories are rejected.  I hope I didn’t give the reader this impression because that certainly wasn’t the point I wanted to make.  If I did, please let me clarify. 

The scientific method goes something like this:

  1. Observation
  2. Formation of hypotheses
  3. Testing/evaluation
  4. Repeat

If you can follow these steps then anything (even economics! even macroeconomics!) can be studied scientifically.  When economics is at its best it truly is a science. 

A purely empirical study is a necessary step in the scientific method (it’s step 1).  Indeed, purely empirical studies, by which I mean simple observational studies, are somewhat undervalued in economics.  However, following the scientific method means that after the observation, we have to move on to forming a hypothesis (building a model or otherwise articulating a theory) and then go on to testing and evaluating the hypothesis (this is the hard part, and the part that is often quite unpleasant for many theories).  Step 1 is not “worse” than step 3.  Both are necessary.  I also didn’t say you should try to hypothesize without looking first at the data and I don’t think macroeconomists are typically modelling without a good grasp of the facts. 

Noah makes some other remarks which I also find interesting. 

First, he makes some surprising remarks about “moment matching.”  It’s true that macroeconomists often evaluate their theories by comparing the statistical moments implied by the model with the analogous moments in the data but it’s hard to see this as a problem.  Moment matching is the underpinning of almost all statistics.  Estimating a mean and a variance is a special case of matching moments.  So is OLS estimation (so is IV and basically every other econometric technique other than maximum likelihood estimation).  I’m a little puzzled as to what Noah would suggest that economists should be doing?  In fact, drop the word “moments” and ask yourself this: should we compare our theories with the data?  I would say we should.  Do we want the theories to match up with the data?  I would say we do. 

Second, he questions whether quantification is valuable when often the theory is rejected.  The way I look at it, the parameters are inputs into the models and will likely have relevance in many settings.  Suppose you have a labor supply / labor demand model and you want to use it to analyze an increase in the minimum wage.  The model makes a prediction and you could use this prediction as a basis for anticipating the effect of the policy.  The predicted change in unemployment will be a function of the labor supply elasticity and the labor demand elasticity.  You can certainly estimate these parameters without testing the model.  Suppose you find that there is no change in employment in the short run and a somewhat larger change in employment as time passes.  This would of course be a rejection of the simple model but it would suggest ways of modifying the model to accommodate the new observations.  Moreover, the parameter estimates retain their usefulness even if the model is rejected. 

Noah’s claim that empirical puzzles are easy to come by is simply wrong.  Noah’s (intentionally) facetious example would only be a puzzle if we had some reason to believe the theory a priori.  None of the puzzles in macroeconomics have trivial explanations.  Here’s an example: inventory accumulation is strongly procyclical (a basic observation).  Is this a puzzle for demand driven business cycle theories?  (No – see Bils and Kahn 2000!).  Here is another example: the real relative price of investment is countercyclical (again a simple observation).  Is this a puzzle?  It might be.  If one thinks that fluctuations in investment demand is an important cause of business cycles then you might think that this real price would be pro-cyclical.  It’s not.  Should we retain this observation?  Is it acceptable to highlight this observation as a puzzle?  I think the answer to both questions is ‘yes’.  Of course, one way to avoid puzzles is to simply avoid trying to explain the data.  You can’t lose a race if you don’t run it. 

There is the famous example of Johannes Kepler who tested the heliocentric theory of the universe (proposed by Copernicus).  His model assumed that planets orbited the sun in perfectly circular orbits.  Unfortunately, the data rejected the model.  He later tried different orbital patterns and discovered that the heliocentric theory worked if the planets followed elliptical orbits.  Was the intermediate stage of rejection (and depression, confusion, …) a sign that his efforts were wasted?  Not at all.  The famous Princeton mathematician Andrew Wiles once compared his work to stumbling around in a darkened room.  This is an excellent analogy and I often have to remind myself that confusion and frustration are the norm. 

Caballero is certainly correct about macro/finance being at the periphery rather than at the core of macro.  It used to be that price rigidity was at the core while financial market imperfections were at the periphery.  I suspect this is slowly changing.  If you are going to try to understand the financial crisis, you will need to have a model that has a central role for financial market failures.  

Is Macro Giving Economics a Bad Rap?

Noah Smith really has it in for macroeconomists.  He has recently written an article in The Week in which he claims that macro is one of the weaker fields in economics and even though there is little good work being done in macro, there is plenty of good work being done in other fields.

I think the opposite is true.  Macro is one of the stronger fields, if not the strongest.  At first glance it may appear to be a problematic area in economics but it is not – it is actually much healthier than most fields. [1]

A recurring theme in Noah’s article is that macro has some sort of a problem which other areas don’t have.  I think this is wrong.  Macro is quite productive and overall quite healthy.  There are several distinguishing features of macroeconomics which set it apart from many other areas in economics.  In my assessment, along most of these dimensions, macro comes out looking quite good.

First, macroeconomists are constantly comparing models to data.  Now, it’s true that many of the models used by macroeconomists (that is, the way we try to understand the world) have a really tough time when they are compared to the data.  Of course it is a problem that the theories are so soundly rejected but isn’t it worthwhile to make this comparison and to be candid about the results?  Noah gives his readers the impression that other theories are doing much better but is this really true?  In many other areas in economics the theories aren’t rejected because either the theories are never tested or the theories simply don’t exist.  There are many purely empirical studies in which there is little theory to speak of.  There are other areas in economics which are purely theoretical and the models in this research are rarely tested against actual data.  Holding theories up to the data is a scary and humiliating step but it is a necessary step if economic science is to make progress.  Judged on this basis, macro is to be commended because it so often takes this step and brings the theories close to the facts.  There are other fields that make these comparisons – trade is a notable example.  Modern versions of the Ricardian trade model and the Heckscher-Ohlin model are often compared with data.  Similarly, labor matching models are routinely compared with data though again there are more failures of these theories than successes.  [2]

Second, in macroeconomics, there is a constant push to quantify theories.  That is, there is always an effort to attach meaningful parameter values to the models.  You can have any theory you want but at the end of the day, you are interested not only in idea itself, but also in the magnitude of the effects.  This is again one of the ways in which macro is quite unlike other fields.

Third, when the models fail (and they always fail eventually), the response of macroeconomists isn’t to simply abandon the model, but rather they highlight the nature of the failure.  This is again a good research habit because mistakes and rejections have value – knowing the nature of the mismatch between the model and the data helps you to refine the theory.   There are many “puzzles” in macroeconomics (the excess sensitivity puzzle, the risk-free-rate puzzle, the equity premium puzzle, the international comovement puzzles, and so on, …).  At a superficial level one might be tempted to conclude that the prevalence of such puzzles shows that the field is in a constant state of disarray.  In fact, these mismatches between theory and data serve as an important guide to how to modify the theories.

Lastly, unlike many other fields, macroeconomists need to have a wide array of skills and familiarity with many sub-fields of economics.  As a group, macroeconomists have knowledge of a wide range of analytical techniques, probably better knowledge of history, and greater familiarity and appreciation of economic institutions than the average economist.

In his opening remarks, Noah concedes that macro is “the glamor division of econ”.  He’s right.  What he doesn’t tell you is that the glamour division is actually doing pretty well.

[Note 1]  It is not clear that macro is a field the same way that Public Finance, Labor, Development, Trade, etc., are fields.  I used to think that macro was a field but I’ve since changed my mind.  Instead I think that basically every field has a component of it which is macro.  So, in Public Finance you have people like Martin Feldstein, Alan Auerbach, Larry Kotlikoff, etc.  These researchers work in Public Finance obviously but they also have very strong macro components to their work.  In Labor there are researchers like the late Dale Mortensen, Chris Pissarides, Rob Shimer, Steve Davis, John Haltiwanger, and so forth.  Again, these economists all have very pronounced macro components to their work.  In fact, some of them (Mortensen and Shimer certainly) might be described most often as macroeconomists even though most of his work is on the theory of labor supply and demand.  The macro component of Development, is growth, with researchers like Daron Acemoglu, Chad Jones, Debraj Ray, etc. … In Economic History you have people like Christy Romer who is obviously a very well-known macroeconomist in addition to being a historian.  So, I think the proper way to view macroeconomics is not as its own field, but instead as half of all of the fields.

[Note 2]  There are examples of theories in economics that do exceptionally well.  What Larry Summers derides as “ketchup economics” – the application of no-arbitrage conditions to financial markets – does really well in the real world.  My understanding is that if you take modern option pricing formulas and examine historical option pricing prior to Black-Scholes you find a surprising amount of agreement between the actual market prices and what the Black-Scholes formula implies.  (There are aspects where the model doesn’t do as well as it should but overall it does remarkably well – if there are finance people who want to weigh-in an tell me that I’ve got this all wrong please go right ahead …).  Another area in which there is a strong coherence between predicted and actual behavior, is the study of auctions.  Auction theory and option pricing models are excellent examples of not only comparing theory to data but also examples in which the theory does a remarkably good job.

A further thought:  It’s true that most of the theories that we have run into trouble.  Noah has another recent post in which he points out that the consumption Euler equation does not fare very well in macroeconomic models.  That’s true though there are more in-depth, detailed analyses in which the model does much better.  For instance, there is a well-known paper by Gourinchas and Parker who use extremely detailed individual-level data together with a structural model and they show that most household’s exhibit behavior that suggests that they are liquidity constrained up to roughly age 40 – age 45 at which point they switch over and start exhibiting behavior that is more consistent with the PIH and what the Euler equation would predict.  In contrast to what Noah would have you believe, this is an excellent example of a theory being refined and sharpened as a result of being compared to detailed data.

Inequality in Adam Smith’s World

Inequality is a fact of economic life and it is becoming more and more pronounced over time.  It’s not exactly clear why this is happening but it is clear that it is happening.  Inequality is certainly rising for pre-tax income measures and I’m virtually certain that it is rising for after-tax measures of income as well. 

There are many forces in our economy that create income inequality.  The most basic of these forces however, is tied to the nature of trade itself and can be traced all the way back to Adam Smith and the division of labor.  If you read the Wealth of Nations (something I told you not to do a few blog posts back …) you will find that Smith begins by marveling at the incredible increases in productivity that can be obtained by exploiting the division of labor, that is, by specializing.  The way Adam Smith envisioned it, a market system would be populated by specialists.  Each person would have a single craft that they would focus on.  This is a world with doctors, lawyers, carpenters, teachers, chefs, and so on.  A jack-of-all-trades is simply not valued in a market system.  (Renaissance men are dinosaurs in Adam Smith’s world.) 

The way you get the division of labor to work is by combining it with trade.  Once you get to the point where you conclude that the division of labor is something you want to take advantage of, trade is a necessary next step.  A physician cannot consume only her own medical advice – she must draw on the productivity of the many other specialists in society.  If you are willing to do trade, you can, by specializing, reach incredible levels of productivity.  As populations grow, and as the ability to trade grows, you should see more and more specialization and higher and higher productivity.  (Obviously the division of labor is not the only source of increases in productivity.) 

However, there is a downside to this plan.  Adam Smith’s plan exposes people to incredible variations in income and thus a market system possesses and important force which causes inequality.  Specialization ties your entire wellbeing to a single industry.  If you decide that you are going to become a web designer, your fate is very closely tied to the market for web designers.  As a result, while Smith’s plan dramatically increases overall productivity, it also exposes us to incredible risk. 

Of course, markets do have responses to risk.  The typical response is for the market to provide insurance contracts to reduce risk.  In this case however, the type of insurance needed is actually income or job insurance.  These types of insurance contracts are not typically available.  It is possible that you might be able to use the stock market to insure yourself against job risk.  For instance you might be able to short-sell claims on the company you work for.  I suppose I could short-sell stock based on the profitability of the University of Michigan Economics Department.  In the event that the U of M Econ department gets in serious trouble, my short position in these assets would have a huge payoff and I would be insured.  In reality, few people have asset portfolios like this.  Moreover, it doesn’t seem like insurance companies are able to provide “career” insurance.  (In part, this post is related to work in the so-called “New Dynamic Public Finance.”)

I don’t mean to imply that all or even most of the alarming increase in inequality is due to the division of labor and trade.  I would guess that modern technology (which allows people to leverage luck to extreme degrees by cheaply reproducing and transmitting ideas and information) and inheritance, both play a significant role in creating inequality.  However, living with income inequality is an implicit part of the deal we made with Adam Smith and it will be with us in some form for a long time.  

The Robin Hood Principle and the Minimum Wage

Robin Hood stole from the rich and gave to the poor. However you feel about the ethical and efficiency implications of active income redistribution, I think most people would agree that Robin Hood was at least making transfers in the right direction. That is to say, even if you are strongly opposed to redistribution, once we have decided that we are going to redistribute, we had better be shifting income from the rich to the poor. I am open to reasonable variations on the ‘Robin Hood’ principle: from the fortunate to the unfortunate, from the privileged to the oppressed … you get the idea. If you are transferring income, at least make sure it’s going to and from the correct people.

The President supports an increase in the Federal Minimum wage from its current value of $7.25 to roughly $10.00 per hour. Now, you might think a policy like this might be a bad idea for an economy that is still pretty weak. Going from 7 dollars an hour to 10 seems like a pretty steep increase in labor costs and I wouldn’t be surprised if it ultimately cost quite a few jobs at the low end of the pay scale. Nevertheless, the bulk of the empirical evidence on the minimum wage seems to point to only modest job losses for minimum wage workers (where am I getting this “bulk of the evidence” thing you ask? – I asked the labor economists in Lorch Hall of course …). That said, I don’t support an increase in the minimum wage and I don’t think any economist should endorse the idea.

The minimum wage is simply bad policy. The main reason that it is poor policy is that (in addition to the fact that it distorts the labor market a bit) it violates the Robin Hood principle. Here are the best reasons to support an increase in the minimum wage:

1. It will probably transfer some income to low-wage workers and there are some wealthy people who will implicitly pay for this transfer.
2. It probably won’t have huge effects on employment for low-wage workers or a huge effect on business profits for firms that hire low-wage workers.
3. It is politically popular.

This last point, that the minimum wage is politically popular, might be the best reason to support it. Minimum wage laws are easy to understand. They can be sold by people who claim (truthfully I believe) to care about the poor. Also, the costs of the policy are hidden – the policy is discussed without candidly disclosing who actually pays for the policy. Among all policies that actually help low-income families, the minimum wage might be the one most likely to be passed into law.

It’s still bad policy though.

Let’s assume, in the best case scenario, that there will be no effect on the employment of low-wage workers. Minimum wage workers will simply get more money. Where is this money coming from? There are several possible sources.

The most obvious answer is that the transfer will come from the profits of businesses that hire lots of low wage workers. This might already strike you as a bit odd – Goldman Sachs doesn’t employ many (any?) workers at the minimum wage and as a result it doesn’t have to make any transfers to minimum wage workers. In contrast, businesses like McDonalds employ thousands of low wage workers and their reward for doing so will be that they get to pay a penalty called the minimum wage. OK, who has a claim on these profits? It depends on the business of course. If we are talking about profits of some huge publicly traded firm then the people who pay for the minimum wage will be shareholders so think of the typical owner of a mutual fund – perhaps a retiree or an upper income saver. If the business is a small family owned grocery then it will be the family members who own the business. These people are probably members of the middle class or perhaps upper middle class.

There are of course other people who will pay to fund the minimum wage. To the extent that businesses raise prices in response, the minimum wage will be financed by customers of these firms. OK, who buys goods from Walmart? From McDonalds? If you think these customers are particularly affluent, think again.

What about the people who get the transfer? While there are many people earning the minimum wage who are truly low-income, there are many who are not. A single mother who works a minimum wage job to make ends meet is very different from a teenager who works for minimum wage to get cash for the weekend. Unfortunately, the minimum wage is a blunt instrument – it can’t distinguish between these two people.

The truth is that, the reason that the minimum wage is politically popular is exactly the same reason that we should be opposed to it. In the best case scenario, while there are no jobs lost, it is not clear that we are transferring from the rich to the poor. It is certain that some low-income households will lose money because of the minimum wage. It is equally certain that some upper-income people will benefit.

This is not to say that we should not push for more aggressive income redistribution. The disparity in income inequality has been rising for quite some time and it is completely correct for people to desire a more equitable distribution of income. There are better policies that could be considered however. Expansion of the EITC is often offered as an example of an effective redistributive tool where we have control over who pays and who receives. A negative income tax bracket could transfer income to families in need, and encourage employment of low income workers.

Dwight Eisenhower’s farewell speech (Jan 17, 1961) still rings true … .

The most often quoted segment: 

This conjunction of an immense military establishment and a large arms industry is new in the American experience. The total influence – economic, political, even spiritual – is felt in every city, every state house, every office of the federal government. We recognize the imperative need for this development. Yet we must not fail to comprehend its grave implications. Our toil, resources and livelihood are all involved; so is the very structure of our society.

“In the councils of government, we must guard against the acquisition of unwarranted influence, whether sought or unsought, by the military-industrial complex. The potential for the disastrous rise of misplaced power exists and will persist.

We must never let the weight of this combination endanger our liberties or democratic processes. We should take nothing for granted. Only an alert and knowledgeable citizenry can compel the proper meshing of the huge industrial and military machinery of defense with our peaceful methods and goals, so that security and liberty may prosper together.

(Does it seem to anyone else that the quality of U.S. leadership has been steadily falling for the past 50 years?)