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Panel Discussion Structural Economic Modeling: Is It Useful in the Policy Process? James Bullard President and CEO Federal Reserve Bank of St. Louis International Research Forum on Monetary Policy Washington D.C. 26 March 2010 Any opinions expressed here are my own and do not necessarily reflect those of the Federal Open Market Committee participants. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA Y ES T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS IT IS USEFUL Is calculus useful for engineering? Is knowledge of anatomy useful for surgery? Conclude: Structural modeling is an indispensible tool for macroeconomists. Having a tool is necessary but not sufficient for good policy design. Pretending to not have a structural model in mind is a falsehood—all approaches to macroeconomics have a theory behind them, implicitly or explicitly. Explicit theories have the virtue of laying the assumptions bare for examination and criticism. But ... ... the models we need are big and complicated. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HIS T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS TALK We all know what needs to be done: Organize a more intensive national research effort in macroeconomics. What we have today: Back rooms (academia) and front rooms (policymakers) of macroeconomics. The back room research has been brilliant ... ... but has often been resisted in the front room. As a result, we are nowhere near where we need to be in terms of having a useful, comprehensive macroeconomic model that we can use to get the economy to perform at its peak level. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA B ACK ROOMS T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS AND FRONT ROOMS Sargent’s amusing description of academia—back rooms–versus policymaking—front rooms. My caricature of the back room versus the front room: Back room: States and parameters are known by all, and policy choice is menacingly complicated. Front room: States and parameters are known by none, but policy choice itself is disarmingly simple. Back room: Stationarity assumptions are commonplace, but data are often untrusted. Front room: Stationarity considered unlikely, but thirst for data is unquenchable. Implication: The focus in the policy world is on determining the state of the system by looking at lots of data. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS A COMMENT ON FORECASTING Really, we track the economy. We try to understand the quarters immediately past, the current quarter, and the coming quarter. Beyond that, many forecasts are a near random walk, with only slow reversion to mean. It is possible that the forecastable component of economic activity may never be much greater than it is today. Problem: A credible forecast is itself influencing the actions of forward-looking actors in the economy. Bottom line: Better forecasting is welcome but is not the ultimate objective. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA B ETTER T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS POLICY IS THE PRIMARY GOAL Better policy is the main objective. Improved policy could deliver better outcomes—possibly dramatically better—even in a world in which the forecastable component of real activity is small. Actual policy is like best practice medicine. Actual policy is slow to adapt to suggestions from the research frontier: Stick with policy adjustments which seem to have worked well in the past. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH T HE BACK ROOM I MPROVED M ACROECONOMICS C ONCLUSIONS RESEARCH The academic research in macroeconomics over the past 30 years has been brilliant. The advances in the level of understanding of the intricacies of the economy have been astonishing. The main lesson: The global economy is no simple system governed by a few equations. The fact that the economy is populated by purposeful, forward-looking actors has huge ramifications for policy. Optimal policies may not look like the policies currently in place. To put a satisfactory, comprehensive macroeconomic model together is a Herculean task. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS T HE STICKING POINT The policy community—the front room—continually resisted the developments in macroeconomics for decades. Instead, there was general condemnation from this community of the new approaches as unrealistic and impractical. There was more truth in this early on, and much less truth in it today. The current crisis cannot be blamed on Lucas and Prescott having too much influence in the policy world! I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS I MPROVED MACROECONOMICS We need a more intensive national research effort in macroeconomics. Our current effort is not sophisticated enough to handle the challenges that lie ahead. We are beyond the point where a few professors or a small group of researchers can make a major advance. We need a determined effort to put together a satisfactory, comprehensive model. We should not allow ourselves to be off the research frontier. Daunting? Yes, but we build aircraft carriers and space stations. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS C OMPREHENSIVE ENOUGH Keep very negative outcomes as a possibility inside the model, so that policy choice can be evaluated with the very negative possibilities in mind. Leading example: Financial panic. Be able to understand trade-offs of policy choice on a more global level. With small models, policymakers have to guess what the effects might be on aspects of the economy outside the analysis. Leading example: Low interest rates as a prelude to a bubble. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS F INANCIAL INTERMEDIATION We know from the literature that frictions in the intermediation process can profoundly affect the general equilibrium. Why assume these frictions away? We also have a long line of literature following Diamond and Dybvig (1983) concerning bank runs and related phenomena. This should be integrated into our macro models, so that we can understand how our policies are affecting the probability of a run. Also: global versus local policy analysis— The run is a departure from the neighborhood of the targeted equilibrium. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA M ONEY AND T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS LIQUIDITY There is a large theoretical literature that attempts to be more rigorous about the nature of money demand. This literature should move closer to the data from financial markets. Especially interesting are Gorton’s (2008) ideas about repos as privately-issued money. We cannot make progress on this issue with money-in-the-utility function assumptions. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS I NTERNATIONAL Globalization is upon us. Our understanding of the international linkages between monetary and fiscal policies is tenuous at best. Still, a critical challenge going forward is to understand the impact of rapid development in much of the world on the global equilibrium. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH H ETEROGENEOUS I MPROVED M ACROECONOMICS C ONCLUSIONS HOUSEHOLDS We know that policies have an uneven impact. The last decade has witnessed a burgeoning research agenda on heterogeneous households. With this technology we can better analyze the general equilibrium effects of policies across households. It is hard work, computationally intensive. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH M ULTIPLE EQUILIBRIA AS PHENOMENA I MPROVED M ACROECONOMICS C ONCLUSIONS “ BUBBLE - LIKE ” Two decades, two bubbles. It is time for the policy community to embrace the concept of multiple equilibria from the macroeconomic research world. That would give us policymakers at least one way to coherently address these issues. The typical policy response in the literature: Adopt a policy that kills off the undesirable equilibria. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA L EARNING T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS AND RATIONALITY Much of the criticism of macroeconomics is associated with the idea that there is “too much rationality.” But the rational households in the models can readily be replaced with learning households, and the analysis can proceed from there. This raises new issues, such as learnability of an equilibrium. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA G ROWTH AND T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS HUMAN CAPITAL The pace of long run growth is the most important aspect of economic performance. We should be analyzing stabilization policies in conjunction with growth policies. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA O THER T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS AREAS These are just examples of the types of features a satisfactory model would have. We would like to be able to understand the trade-offs between many policy choices. Above all, we would like to be able to understand where the real dangers are: Big ticket welfare losses are associated with leaving the neighborhood of a targeted equilibrium. This has to be a possibility inside the models. I NTRODUCTION P OLICY C HOICE V ERSUS D ATA T HE BACK ROOM RESEARCH I MPROVED M ACROECONOMICS C ONCLUSIONS C ONCLUSIONS The nation needs a more aggressive and better-funded research effort in macroeconomics. The current level of effort is unlikely to meet the many challenges the U.S. faces going forward. The level of complexity is beyond what individual researchers can handle. Small, shortcut models are going to be wildly wrong on many dimensions. The task is daunting, but the nation will spend a great deal on other large projects arguably of lesser consequence. Federal Reserve Bank of St. Louis stlouisfed.org Federal Reserve Economic Data (FRED) research.stlouisfed.org/fred2/ James Bullard research.stlouisfed.org/econ/bullard/