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An interview by Economic Dynamics with James Bullard, president of the Federal Reserve Bank of St. Louis (source).

EconomicDynamics Interviews James Bullard on policy and the academic world

James Bullard: I have been dissatisfied with the notion that has evolved over the last 25 or 30 years that it was okay to allow a certain group of economists to work on really rigorous models and do the hard work of publishing in journals and then have a separate group that did policymaking and worried about policymaking issues. These two groups often did not talk to each other, and I think that that is a mistake. It is something you would not allow in other fields. If you are going to land a man on Mars, you are going to want the very best engineering. You would not say that the people who are going to do the engineering are not going to talk to the people who are strategizing about how to do the mission. An important part of my agenda is to force discussion between what we know from the research world and the pressing policy problems that we face and try to get the two to interact more. I understand about the benefits of specialization, which is a critical aspect of the world, but still I think it is important that these two groups talk to each other.

ED: Is there a place in policy for the economic models of the "ivory tower"?

JB: I am not one who thinks that the issues discussed in the academic journals are just navel gazing. Those are our core ideas about how the economy works and how to think about the economy. There are no better ideas. That is why they are published in the leading journals. So I do not think you should ignore those. Those ideas should be an integral part of the thinking of any policymaker. I do not think that you should allow policymaking to be based on a sort of second-tier analysis. I think we are too likely to do that in macroeconomics compared to other fields.

ED: Why do you think that is?

JB: I think people have some preconceptions about what they think the best policy is before they ever get down to any analysis about what it might be. I understand people have different opinions, but I see the intellectual market place as the battleground where you hash that out. I do not think the answers are at all obvious. A cursory reading of the literature shows you that there are many, many smart people involved. They have thought hard about the problems that they work on, and they have spent a lot of time even to eke out a little bit of progress on a particular problem. The notion that all those thousands of pages could be summed up in a tweet or something like that is kind of ridiculous. These are difficult issues, and that is why we have a lot of people working on them under some fair amount of pressure to produce results. Sometimes I hear people talking about macroeconomics, and they think it is simple. It is kind of like non-medical researchers saying, "Oh, if I were involved, I would be able to cure cancer." Well fine, you go do that and tell me all about it. But the intellectual challenge is every bit as great in macroeconomics as it is in other fields where you have unsolved problems. The economy is a gigantic system with billions of decisions made every day. How are all these decisions being made? How are all these people reacting to the market forces around them and to the changes in the environment around them? How is policy interacting with all those decisions? That is a hugely difficult problem, and the notion that you could summarize that with a simple wave of the hand is silly.

ED: Do you remember the controversy, the blogosphere discussion, that macroeconomics has been wrong for two decades and all that criticism? Do you have any comments on that?

JB: I think the crisis emboldened people that have been in the wilderness for quite a while. They used the opportunity to come out and say, "All the stuff that we were saying that was not getting published anywhere is all of the sudden right." My characterization of the last 30 years of macroeconomic research is that the Lucas-Prescott-Sargent agenda completely smoked all rivals. They, their co-authors, friends, and students carried the day by insisting on a greatly increased level of rigor, and there was a tremendous amount of just rolling up their sleeves and getting into the hard work of actually writing down more and more difficult problems, solving them, learning from the solution and moving on to the next one. Their victory remade the field and disenfranchised a bunch of people. When the financial crisis came along, some of those people came back into the fray, and that is perfectly okay. But, there is still no substitute for heavy technical analysis to get to the bottom of these issues. There are no simple solutions. You really have to roll up your sleeves and get to work.

ED: What about the criticism?

JB: I think one thing about macroeconomics is that because everyone lives in the economy and they talk to other people who live in the economy, they think that they have really good ideas about how this thing works and what we need to do. I do not begrudge people their opinions, but when you start thinking about it, it is a really complicated problem. I love that about macroeconomics because it provides for an outstanding intellectual challenge and great opportunities for improvement and success. I do not mind working on something that is hard. But everyone does seem to have an opinion. In medicine you do see some of that: People think they know better than the doctors and they think they are going to self-medicate because their theory is the right one, and the doctors do not know what they are doing. Steve Jobs reportedly thought like this when he was sick. But I think you see less of this type of attitude in the medical arena than you do in economics. That is distressing for us macroeconomists, but maybe we can improve that going forward.

ED: What do you think about the criticism of economists not being able to forecast or to see the financial crisis? Do you have any thoughts on that?

JB: One of the main things about becoming a policymaker is the juxtaposition between the role of forecasting and the role of modeling to try to understand how better policy can be made. In the policy world, there is a very strong notion that if we only knew the state of the economy today, it would be a simple matter to decide what the policy should be. The notion is that we do not know the state of the system today, and it is all very uncertain and very hazy whether the economy is improving or getting worse or what is happening. Because of that, the notion goes, we are not sure what the policy setting should be today. So, the idea is that the state of the system is very hard to discern, but the policy problem itself is often disarmingly simple. What is making the policy problem hard is discerning the state of the system. That kind of thinking is one important focus in the policy world. In the research world, it is just the opposite. The typical presumption is that one knows the state of the system at a point in time. There is nothing hazy or difficult about inferring the state of the system in most models. However, the policy problem itself is often viewed as really difficult. It might be the solution to a fairly sophisticated optimization problem that carefully weighs the effects of the policy choice on the incentives of households and firms in a general equilibrium context. That kind of attitude is just the opposite of the way the policy world approaches problems. I have been impressed by this juxtaposition since I have been in this job. Now, forecasting itself I think is overemphasized in the policy world because there probably is an irreducible amount of ambient noise in macroeconomic systems which means that one cannot really forecast all that well even in the best of circumstances. We could imagine two different economies, the first of which has a very good policy and second of which has a very poor policy. In both of these economies it may be equally difficult to forecast. Nevertheless, the first economy by virtue of its much better policy would enjoy much better outcomes for its citizens than the economy that had the worse policy. Ability to forecast does not really have much to do with the process of adopting and maintaining a good policy. The idea that the success of macroeconomics should be based on forecasting is a holdover from an earlier era in macroeconomics, which Lucas crushed. He said the goal of our theorizing about the economy is to understand better what the effects of our policy interventions are, not necessarily to improve our ability to forecast the economy on a quarter-to-quarter or year-to-year basis. What we do want to be able to forecast is the effect of the policy intervention, but in most interesting cases that would be a counterfactual. We cannot just average over past behavior in the economy, which has been based on a previous policy, and then make a coherent prediction about what the new policy is going to bring in terms of consumption and investment and other variables that we care about. It is a different game altogether than the sort of day-to-day forecasting game that goes on in policy circles and financial markets. Of course it is important to try to have as good a forecast as you can have for the economy. It is just that I would not judge success on, say, the mean square error of the forecast. That may be an irreducible number given the ambient noise in the system. One very good reason why we may not be able to reduce the amount of forecast variance is that if we did have a good forecast, that good forecast would itself change the behavior of households, businesses, and investors in the economy. Because of that, we may never see as much improvement as you might hope for on the forecasting side. The bottom line is that better forecasting would be welcome but it is not the ultimate objective. We [central banks] do not really forecast anyway. What we do is we track the economy. Most actual forecasting day to day is really just saying: What is the value of GDP last period or last quarter? What is it this quarter? And what is it going to be next quarter? Beyond that we predict that it will go back to some mean level which is tied down by longer-run expectations. There is not really much in the way of meaningful forecasting about where things are going to go. Not that I would cease to track the economy--I think you should track the economy--but it is not really forecasting in the conventional sense. The bottom line is that improved policy could deliver better outcomes and possibly dramatically better outcomes even in a world in which the forecastable component of real activity is small.

ED: Can the current crisis be blamed on economic modeling?

JB: No. I think that this is being said by people who did not spend a lot of time reading the literature. If you were involved in the literature as I was during the 1990s and 2000s, what I saw was lots of papers about financial frictions, about how financial markets work and how financial markets interact with the economy. It is not an easy matter to study, but I think we did learn a lot from that literature. It is true that that literature was probably not the favorite during this era, but there was certainly plenty going on. Plenty of people did important work during this period, which I think helped us and informed us during the financial crisis on how to think about these matters and where the most important effects might come from. I think there was and continues to be a good body of work on this. If it is not as satisfactory as one might like it to be, that is because these are tough problems and you can only make so much progress at one time. Now, we could think about where the tradeoffs might have been. I do think that there was, in the 1990s in particular, a focus on economic growth as maybe the key phenomenon that we wanted to understand in macroeconomics. There was a lot of theorizing about what drives economic growth via the endogenous growth literature. You could argue that something like that stole resources away from people who might have otherwise been studying financial crises or the interaction of financial systems with the real economy, but I would not give up on those researchers who worked on economic growth. I think that was also a great area to work on, and they were right in some sense that in the long run what you really care about is what is driving long-run economic growth in large developed economies and also in developing economies, where tens of millions of people can be pulled out of poverty if the right policies can be put in place. So to come back later, after the financial crisis, and say, in effect, "Well those guys should not have been working on long-run growth; they should have been working on models of financial crisis," does not make that much sense to me and I do not think it is a valid or even a coherent criticism of the profession as a whole. In most areas where researchers are working, they have definitely thought it through and they have very good ideas about what they are working on and why it may be important in some big macro sense. They are working on that particular area because they think they can make their best marginal contribution on that particular question. That brings me to another related point about research on the interaction between financial markets and the real economy. One might feel it is a very important problem and something that really needs to be worked on, but you also might feel as a researcher, "I am not sure how I can make a contribution here." Maybe some of this occurred during the two decades prior to the financial crisis. On the whole, at least from my vantage point (monetary theory and related literature) I saw many people working on the intersection between financial markets and the real economy. I thought they did make lots of interesting progress during this period. I do think that the financial crisis itself took people by surprise with its magnitude and ferocity. But I do not think it makes sense to then turn around and say that people were working on the wrong things in the macroeconomic research world.

ED: There is a tension between structural models that are built to understand policy and statistical models that focus on forecasting. Do you see irrevocable differences between these two classes of models?

JB: I do not see irrevocable differences because there is no alternative to structural models. We are trying to get policy advice out of the models; at the end of the day, we are going to have to have a structural model. We have learned a lot about how to handle data and how to use statistical techniques for many purposes in the field, and I think those are great advances. These days you see a lot of estimation of DSGE models, so that is a combination of theorizing with notions of fit to the data. I think those are interesting exercises. I do not really see this as being two branches of the literature. There is just one branch of the literature. There may be some different techniques that are used in different circumstances. Used properly, you can learn a lot from purely empirical studies because you can simply characterize the data in various ways and then think about how that characterization of the data would match up with different types of models. I see that process as being one that is helpful. But it has to be viewed in the context that ultimately we want to have a full model that will give you clear and sharp policy advice about how to handle the key decisions that have to be made.

ED: What are policy makers now looking for from the academic modelers?

JB: I have argued that the research effort in the U.S. and around the world in economics needs to be upgraded and needs to be taken more seriously in the aftermath of the crisis. I think we are beyond the point where you can ask one person or a couple of smart people to collaborate on a paper and write something down in 30 pages and make a lot of progress that way. At some point the profession is going to have to get a lot more serious about what needs to be done. You need to have bigger, more elaborate models that have many important features in them, and you need to see how those features interact and understand how policy would affect the entire picture. A lot of what we do in the published literature and in policy analysis is sketch ingenious but small arguments that might be relevant for the big elephant that we cannot really talk about because we do not have a model of the big elephant. So we only talk about aspects of the situation, one aspect at a time. Certainly, being very familiar with research myself and having done it myself, I think that approach makes a great deal of sense. As researchers, we want to focus our attention on problems that can be handled and that one can say something about. That drives a lot of the research. But in the big picture, that is not going to be enough in the medium run or the long run for the nation to get a really clear understanding of how the economy works and how the various policies are affecting the macroeconomic outcomes. We should think more seriously about building larger, better, more encompassing types of models that put a lot of features together so that we can understand the relative magnitudes of various effects that we might think are going on all at the same time. We should also do this within the DSGE context, in which preferences are well specified and the equilibrium is well defined. Therein lies the conflict: to get to big models that are still going to be consistent with micro foundations is a difficult task. In other sciences you would ask for a billion dollars to get something done and to move the needle on a problem like this. We have not done that in economics. We are way too content with our small sketches that we put in our individual research papers. I do not want to denigrate that approach too much because I grew up with that and I love that in some sense, but at some point we should get more serious about this. One reason why this has not happened is that there were attempts in the past (circa 1970) to try to put together big models, and they failed miserably because they did not have the right conceptual foundations about how you would even go about doing this. Because they failed, I think that has made many feel like, "Well, we are not going to try that again." But just because it failed in the past does not mean it is always going to fail. We could do much better than we do in putting larger models together that would be more informative about the effects of various policy actions without compromising on our insistence that our models be consistent with microeconomic behavior and the objects that we study are equilibrium outcomes under the assumptions that we want to make about how the world works.

ED: Can you perhaps talk about some cutting edge research? You have made some points on policy based on cutting edge research.

JB: One of the things that struck me in the research agenda of the last decade or more is the work by Jess Benhabib, Stephanie Schmitt-Grohe and Martin Uribe on what you might think of as a liquidity trap steady state equilibrium which is routinely ignored in most macroeconomic models. But they argue it would be a ubiquitous feature of monetary economies in which policymakers are committed to using Taylor-type rules and in which there is a zero bound on nominal interest rates and a Fisher relation. Those three features are basically in every model. I thought that their analysis could be interpreted as being very general plus you have a really large economy, the Japanese economy, which seems to have been stuck in this steady state for quite a while. That is an example of a piece of research that influenced my thinking about how we should attack policy issues in the aftermath of the crisis. I remain disappointed to this day that we have not seen a larger share of the analysis in monetary policy with this steady state as an integral part of the picture. It seems to me that this steady state is very, very real as far as the industrialized nations are concerned. Much of the thinking in the monetary policy world is that "the U.S. should not become Japan." Yet in actual policy papers it is a rarity to see the steady state included. That brings up another question about policy generally. Benhabib et al. are all about global analysis. A lot of models that we have are essentially localized models that are studying fluctuations in the neighborhood of a particular steady state. There is a fairly rigorous attempt to characterize the particular dynamics around that particular steady state as the economy is hit by shocks and the policymaker reacts in a particular way. There are also discussions of whether the model so constructed provides an appropriate characterization of the data or not, and so on. However, whether the local dynamics observed in the data are exactly the way a particular model is describing them or not is probably not such a critical question compared to the possibility that the system may leave the neighborhood altogether. The economy could diverge to some other part of the outcome space which we are not accustomed to exploring because we have not been thinking about it. Departures of this type may be associated with considerably worse outcomes from a welfare perspective. I have come to feel fairly strongly that a lot of policy advice could be designed and should be designed to prevent that type of an outcome. If the economy is going to stay in a small neighborhood of a given steady state forever, do we really care exactly what the dynamics are within that small neighborhood? The possibility of a major departure from the neighborhood of the steady state equilibrium that one is used to observing gives a different perspective on the nature of 'good policy.' We need to know much more about the question: Are we at risk of leaving the neighborhood of the steady state equilibrium that we are familiar with and going to a much worse outcome, and if we are, what can be done to prevent that sort of global dynamic from taking hold in the economy? I know there has been a lot of good work on robustness issues. Tom Sargent and Lars Hansen have a book on it. There are many others who have also worked on these issues. I think, more than anything, we need perspectives on policy other than just what is exactly the right response to a particular small shock on a particular small neighborhood of the outcome space.

ED: Do you have an example?

JB: I have also been influenced by some recent theoretical studies by Federico Ravenna and Carl Walsh, in part because the New Keynesian literature has had such an important influence on monetary policymakers. A lot of the policy advice has been absorbed from that literature into the policymaking process. I would not say that policymakers follow it exactly, but they certainly are well informed on what the advice would be coming out of that literature. I thought the Ravenna-Walsh study did a good job of trying to get at the question of unemployment and inflation within this framework that so many people like to refer to, including myself on many occasions. They put a rigorous and state-of-the-art version of unemployment search theory into the New Keynesian framework with an eye toward describing optimal policy in terms of both unemployment and inflation. The answer that they got was possibly surprising. The core policy advice that comes out of the model is still price stability--that you really want to maintain inflation close to target, even when you have households in the model that go through spells of unemployment and even though the policymaker is trying to think about how to get the best welfare that you can for the entire population that lives inside the model. The instinct that many might have--that including search-theoretic unemployment in the model explicitly would have to mean that the policymaker would want to "put equal weight" on trying to keep prices stable and trying to mitigate the unemployment friction--turns out to be wrong. Optimal monetary policy is still all about price stability. I think that is important. We are in an era when unemployment has been much higher than what we have been used to in the U.S. It has been coming down, but it is still quite high compared to historical experience in the last few decades. For that reason many are saying that possibly we should put more weight on unemployment when we are thinking about monetary policy. But this is an example of a very carefully done and rigorous piece of theoretical research which can inform the debate, and the message that it leaves is that putting too much weight on unemployment might be actually counterproductive from the point of view of those that live inside the economy because they are going to have to suffer with more price variability than they would prefer, unemployment spells notwithstanding. I thought it was an interesting perspective on the unemployment/inflation question, which is kind of a timeless issue in the macro literature.