DECEMBER 2015 8 Lars Peter Hansen In March 1979, Lars Peter Hansen, a young Ph.D. fresh out of the University of Minnesota, submitted a paper to the prestigious Economet- rica. It described a statistical methodology that, in its final form, would allow economists to draw strong conclusions from models that weren’t completely specified (that is, not all variables, relationships or assump- tions were included or precisely defined). This “generalized method of moments” would give econometricians the ability to appraise alternative theories and investigate important economic phenomena without fully developing each of their elements. Researchers could rely on the most powerful explanatory variables and dispense with unnecessary assumptions. “GMM allows you to ‘do some- thing without having to do everything simultaneously,’” Hansen explains. But the GMM—abstract and mathematically challenging—was not immediately embraced by the field. (Indeed, Hansen’s initial draft was rejected by Econometrica, spurring him to refine and generalize his argument.) Hansen and his colleagues persevered, demonstrating the methodology’s power and range by applying it to exchange rates, as- set pricing models and rational expectations theory. These and other examples gradually convinced economists of its utility and, with time, GMM became the gold standard. In 2013, Hansen received the Nobel Prize in economic sciences for his methodology, specifically in reference to its ability to evaluate asset pricing models. Hansen continues to study asset prices, focusing on linkages be- tween financial markets and the broader macroeconomy. Recent work looks at uncertainty and risk tolerance in asset pricing behavior; he’s also developed methods to analyze and account for the uncertainty of the households and businesses that populate economic models, and also for the uncertainty that econometricians have about the adequacy of their models. Related research examines policymaking under uncertainty. At the top of his field, there are few major awards that he hasn’t received, but he’s especially pleased with his role in developing future generations of gifted economists. He is a major force behind the Becker Friedman Institute at the University of Chicago, a multidisciplinary re- search center that supports young scholars and others in economics, law, public policy and business. And he devotes a full page of his CV to a list of the Ph.D. students he’s advised. “I’m proud of my research accomplishments,” he observes in this Region conversation, “but I am also proud that I am able to associate with so many very good graduate students.” PHOTOS BY PETER TENZER BY PHOTOS

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THE GENERALIZED METHOD OF There’s a long history in formal GMM AND ITS APPLICATION MOMENTS AND ITS APPLICATION econometrics behind this approach. Some of my research had an important Is there a way that you Region: Let’s start, if we could, with as- antecedent, namely, the work of Denis set prices and the generalized method Sargan back in the late 1950s. I was also can study the connections of moments, known as GMM. When very heavily influenced by lectures Chris between asset prices and you were honored with the Nobel award Sims was giving back when I was a grad- macroeconomic outcomes in 2013 for your work on the GMM, the uate student. While developing a formal committee said that the GMM is “par- justification for an econometric method, without necessarily getting ticularly well suited to testing rational what excited me and helped my research all the other details exactly theories of asset prices.” Could you give gain some traction were the empirical correct? My aim was to a brief description of the method and its applications I and others came up with. importance to later work? develop methods that allow Region: What do you think was achieved for initial investigation of Hansen: Sure. I like to think about this by applying these methods, in your own linkages without requiring as the following: Economists can build work and in work by others? a fully fleshed-out model. a full-scale model of a macroeconomy with many different equations, where Hansen: My initial applications included they map out a really rich structure of fi- analyses of forward exchange markets nancial markets and the macroeconomy. with Bob Hodrick and investigation of The question is: Is there a way that you pricing a cross section of asset returns Hansen: Researchers have indeed fo- can study the connections between as- with Ken Singleton. The Hodrick paper cused on the forward-looking nature set prices and macroeconomic outcomes documented empirical challenges that of asset prices. Prices today depend on without necessarily getting all the other have altered how researchers model ex- what people think is going to happen in details exactly correct? For instance, change rate determination. The Single- the future. For instance, I may have ob- an econometrician may wish to avoid ton research exposed gaps in the exist- servations on the market values of some specifying the precise information used ing macroeconomic models in terms of type of underlying dividend or cash flow by investors or detailing all of the ingre- their implications for asset pricing. This process. Or I may make assessments of dients that govern the evolution of the work in turn encouraged Ravi Jaganna- the market value of education, depend- macroeconomy. My aim was to develop than, John Cochrane and me to char- ing in part on guesses as to what the sal- methods that allow for initial investiga- acterize asset-pricing puzzles in more ary will be for different levels of educa- tion of linkages without requiring a fully general terms. Scott Richard and I be- tion going forward. fleshed-out model. gan to explore more abstract economic Asset prices, broadly conceived, reflect formulations of so-called stochastic dis- people’s beliefs about the future, but they Region: Which, of course, is always a count factor models, where such factors also reflect how people respond to uncer- challenge at the initial stages of model simultaneously discount the future and tainty. What makes people cautious and development. adjust for risk. The empirical challenge what makes them bold? From this van- to model builders is to understand why tage point, the challenge of an empirical Hansen: Right. The point is not even to the implied risk prices are large and asset-pricing model is to disentangle the make a pretense of believing that every- fluctuate over time in interesting ways. contributions coming from beliefs versus thing is fully specified. The econome- It’s been rewarding to observe the sub- those coming from concerns about un- trician’s jargon of a “partially specified sequent model extensions and refine- certainty. And I’ve been keenly interested model” applies where one tries to study ments motivated by empirical chal- in methods that allow us to try to disen- linkages without having to spell out all lenges. tangle these two different impacts. the various different details. As you build This aim to extract information from models to use for policy purposes, you ASSET PRICES AND THE forward-looking prices is not just an aca- do have to specify many of those details. MACROECONOMY demic exercise; it’s on the radar screen of But as an initial step, it’s nice to be able to policymakers as well. For instance, those make assessments without all that detail. Region: Asset prices are known to be engaged in monetary policy look to fi- I like to say that the GMM allows you to foward-looking and, as such, they contain nancial markets to try to see where the “do something without having to do ev- information about private sector beliefs. private sector thinks the macroeconomy erything simultaneously.” How does your work bear on this topic? is headed. So it’s very interesting to ask

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what types of restrictions we impose on ASSET PRICES AND As uncertainty compounds over time, models that allow us to disentangle the THE MACROECONOMY random outcomes that don’t originally contributions of private sector investor look to have big consequences can grow beliefs from adjustments made for the The challenge of an empirical in magnitude as they play out. This re- uncertainties that they perceive. And asset-pricing model is to search provides a way to quantify such this has been a long-standing interest of disentangle the contributions phenomena—to actually measure this mine. compounding uncertainty and see how coming from beliefs versus it might be reflected in the behavior of Region: What methodological approach- those coming from concerns asset prices. es have you recently developed to further about uncertainty. And I’ve Just as growth rate uncertainties com- the understanding of linkages between pound over time, so do the market com- asset pricing and the macroeconomy? been keenly interested in pensations for those uncertainties. Alter- methods that allow us to native economic models have interesting Hansen: The empirical finance literature try to disentangle these two things to say about how compensations has focused on risk-return trade-offs differ across alternative investment ho- over a quarter or a month, or sometimes different impacts. rizons. even shorter horizons. But pricing im- This aim to extract plications extend over much longer ho- information from forward- rizons, and that’s the part that has been UNCERTAINTY AND less well-characterized, although it’s im- looking prices is not just an MARKET RETURNS portant for understanding investment academic exercise; it’s on the radar decisions and has macroeconomic im- screen of policymakers as well. Region: To measure the impact of un- plications. certainty and understand how it com- I’ve been working with collaborators, pounds over time, how do you capture including José Scheinkman and Jarda the link between uncertainty and finan- Borovička, to expand the existing tool cial market returns? kit for analyzing this problem. We take receive as compensation for their expo- our inspiration from two sources: First sure to these macroeconomic shocks. Hansen: Risk premia, which are mea- is from a literature on impulse-response Valuation of the cash flows must account sured compensations in financial mar- functions. This methodology was intro- for their exposure to macroeconomic kets, can be large for one of two reasons. duced to economists by Ragnar Frisch shocks. Much like impulse-response One is that exposures to risk are larger, and has been used extensively in empiri- functions, decompositions of these com- and the other is that the prices of those cal macroeconomics. It aims to quan- pensations by the investment horizon are exposures, the market-based compensa- tify the different sources of economic revealing. Suppose the shock happening tions, are larger. I think about the former fluctuations. Formally, it measures how in the immediate future affects the cash as a quantity effect, the latter as a price important alternative macroeconomic flow the next quarter, two quarters down effect. This dichotomy isolates the mea- shocks are in driving asset prices over the road and subsequent quarters—from surement challenges. different horizons. The shocks them- an asset-pricing perspective, we measure From a quantity perspective, we ask, selves hit the economy the next quar- the implied market-based compensa- how exposed are the economically rel- ter, two quarters down the road, three tions for those exposures. This gives us a evant cash flows to uncertainty? How do quarters down the road and so forth. richer understanding of alternative mod- we measure the amount of uncertainty Then you trace through the dynamic els and a richer perspective from which out there in the underlying economic responses of economic variables to the we can look at linkages between financial environment? How much uncertainty is alternative macroeconomic shocks over markets and the macroeconomy. there about specific economic outcomes, different horizons. These impulses can The resulting quantitative methods or about the macroeconomy in general? build over time and reinforce each other, allow us to measure the impact of un- This is the quantity channel. or they can diminish over time. There’s certainty as it compounds over time. From a price perspective, we ask, how been substantial empirical work that We have a well-known notion of what do decision makers or market partici- characterizes those dynamic patterns. happens when we compound interest; pants react to this uncertainty? What are The second source of inspiration is seemingly small things can grow into our attitudes about uncertainty, and how from an asset-pricing perspective, where very, very big things. Something simi- much aversion do we have to it? These we explore the returns investors must lar occurs in the case of uncertainty. attitudes show up in how markets com-

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pensate people when they are exposed UNCERTAINTY AND ble while exploiting this restriction. to different types of uncertainty. All the MARKET RETURNS We originally envisioned the resulting time, we’re talking about financial mar- econometric method as providing a way kets being cautious or bold and risk pre- Risk premia, which are to estimate some key parameters such mia being high or low. Given such obser- measured compensations in as how risk-averse investors are or how vations, the measurement challenges are they view intertemporal substitution in twofold. One is, how much uncertainty financial markets, can be large consumption. It was intended as a for- is there that we’re exposed to? And the for one of two reasons. One is mal way to obtain inputs that we could other is, how do people react or respond that exposures to risk are larger, start plugging into bigger models. to that uncertainty? That wasn’t how the research played and the other is that the prices out. Instead, we and others ended up ex- Region: What are some of the motiva- of those exposures, the market- posing the problems associated with dif- tions behind this research? based compensations, are ferent classes of models. As I mentioned before, my co-authors and I were led to Hansen: I believe that understanding larger. This dichotomy isolates characterize empirical puzzles and chal- the mechanism connecting long-term the measurement challenges. lenges that the next set of models would concerns to short-term consequences have to confront. for financial market compensations is a Empirical puzzles only have meaning very important endeavor. Amir Yaron, relative to a class of models. There is now a former student of mine, in some in- tainty. My aim is to circumvent some of a body of evidence suggesting that there triguing collaborations with Ravi Bansal, the criticisms of the work of Bansal and are periods when financial markets look explored the consequences of what they Yaron, while still getting at similar quan- very cautious or “risk averse,” as reflected referred to as “long-term risk” for as- titative impacts. by the implied market compensations. set pricing. They considered alternative And the types of models we were initial- models of risk preferences for investors THE IMPORTANCE OF ly looking at were just not capturing this suggested in previous research and hit UNCERTAINTY phenomenon. This evidence led econo- upon situations in which investors’ per- mists to think about what would lead to ceptions about long-term uncertainty— Region: Some of your more recent work that type of behavior and how one can in, say, macroeconomic growth—had focuses on the effects of uncertainty, make the model richer to get a much implications for even short-term pric- broadly conceived, on asset prices. What better characterization of these linkages ing of securities. By short-term pricing led you to see uncertainty as an impor- between financial markets and the mac- here, I mean the short-term measures tant question to explore? roeconomy. of the so-called risk-return trade-off— I believe that exposing empirical chal- a common target for empirical work in Hansen: When I was initially doing some lenges encouraged other researchers, finance. Thus, they described interesting of this research jointly with Ken Single- myself included, but also a whole vari- linkages between long-term uncertainty ton, we used “off-the-shelf” macroeco- ety of other people to really think hard and short-term implications. Their work nomic models of the time. They were about other richer models of asset price has been challenged empirically in part so-called rational expectations models, determination and to see to what extent because quantifying long-term uncer- but they had other features as well. Im- they could help us better understand tainty is difficult. Nevertheless, I was position of rational expectations has these various empirical phenomena. I very much intrigued by their finding of been a demonstrably successful way of became intrigued by rethinking how we the potential for this linkage to be im- removing arbitrariness from specifying model investor responses to uncertainty. portant. This is one of the reasons I have beliefs. As a simplifying assumption, it been working on novel characterizations presumes that investors assign probabil- Region: What is your own thinking on of asset-pricing models that look across ities with complete confidence in ways these empirical challenges? different time horizons and what hap- that are consistent with the underlying pens as we change the horizons. economic model. It has been a power- Hansen: There have been a variety of I’ve been very interested in develop- ful modeling tool in a variety of settings. modeling extensions that I find interest- ing tools to think about this problem and We imposed rational expectations on ing related to richer models of investor to explore models in which there can be the part of investors in our use of time preferences and alternative market im- long-term uncertainty, but approached series evidence, and we structured an perfections. Tom Sargent and I became with a more eclectic approach to uncer- econometric approach that was tracta- actively interested in how the impact of

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THE IMPORTANCE OF UNCERTAINTY

There’s lots of uncertainty about future macroeconomic growth. … In my view, it is critical to think about both the magnitude of growth rate uncertainty and how this uncertainty affects decision- making.

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uncertainty about the macroeconomy RISK VERSUS UNCERTAINTY make fully probabilistic assessments. So affects both how financial markets work it’s important to go beyond this vision of and design of economic policy. An approach that reflects a game of chance, where we know prob- abilities, into something in which the There’s lots of uncertainty about fu- a struggle, similarly faced by ture macroeconomic growth. For in- decision makers themselves are trying to stance, economists and others debate econometricians in building make guesses about the right way to think whether we’re currently in a period of and analyzing dynamic about the uncertainty. secular stagnation or whether we’re in economic models, will add the process of growing our way out of Region: This relates, I think, to your Nobel it. They debate whether the techno- a richness to how we capture lecture in which you speak at length logical advances of the last couple of the behavior of investors about “inside” and “outside” uncertainty: decades were special in terms of their inside the models we build. the inside uncertainty of actors who pop- potency. Going forward, will techno- ulate economic models—households, logical advances proceed at a much businesses and policymakers—and the slower pace, or will there be new ad- outside-the-model uncertainty of econo- vances that have a major impact on metricians who’ve built the models, but future opportunities? securities market prices, and it shows up do not know all of the parameters or In my view, it is critical to think about in the resulting investment behavior. The aren’t certain they’re right. Could you both the resulting magnitude of growth methods that I’ve been working on are elaborate on the distinction between in- rate uncertainty and how this uncer- designed to turn these kinds of quali- side and outside uncertainty? tainty affects decision-making. From tative descriptions into quantitatively the vantage point of the private sector, meaningful characterizations of the im- Hansen: Let’s go to outside-the-model trying to figure out whether now is a portance of uncertainty. uncertainty first. If we’re given some good time to invest in new projects or dynamic economic model that repre- to fund new enterprises, investors are RISK VERSUS UNCERTAINTY sents our understanding of the economy led to speculate how the future of the (this is the perspective that a statistician macroeconomy is going to evolve. This Region: Could you elaborate on this dis- would take), then the researcher is going challenge in responding to uncertainty tinction between risk and uncertainty? to take that model with unknown pa- is reflected in the behavior of financial How does it differ from the more tra- rameters and use data to figure out what markets. And there have been recently ditional way of understanding risk and those unknown parameters are. There some modeling advances in how deci- uncertainty? may be multiple models, so econome- sion makers respond to uncertainty and, tricians may have to assess whether it’s more specifically, what the consequences Hansen: So I like to draw a distinction a good or bad model, or whether they are for the compensation observed in fi- between them in this way. Imagine that may want to compare alternative mod- nancial markets and the extent to which we’re rolling the dice every period, and els. In assessing economic models, the this uncertainty induces more cautious over time we continually roll the dice. researcher has some uncertainty about behavior. Interestingly, these advances Rolling dice is like a game of chance. how well particular models, or combina- have come from different disciplines, We know the odds of getting different tions of models, represent the economy, including statistics, control theory and numbers, and we can figure out how that or whether those models are even cor- decision theory. compounds as we go, across multiple rectly specified. As I mentioned previously, much eco- rolls of the dice. But in more complicat- But when we’re building econom- nomic analysis targets a particular view ed situations, we don’t know the prob- ic models, we have to take a stand on of risk. This perspective is one in which abilities themselves, and part of what what’s going on inside the models, too. people know probabilities of future we’re doing is using evidence to figure We have to depict the economic actors, events, but they don’t know outcomes. out the probabilities—in our role as stat- the consumers, the enterprises and the I prefer to think of things in broader isticians—but even to do that, we have policymakers—they’re coping with un- uncertainty terms, where they don’t to have some reasonable ways to think certainty. We then deduce consequences know outcomes, but they also struggle about the probabilities. for market outcomes and respect their with probabilities to assign to those The more complex the underlying eco- attempts to cope with uncertainty. outcomes. And when the private sector nomic environment—the macroecono- When we’re thinking about uncer- engages in these struggles, that shows my, for example, or alternative financial tainty, it’s useful to keep both of these up in the behavior of forward-looking markets—the more challenging it is to vantage points in mind. Historically, one

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approach is to assume that inside actors LONG-TERM UNCERTAINTY AND the aim is to still get interesting and fas- know what the risks that affected them SHORT-TERM BEHAVIOR cinating models whereby this becomes a were as captured formally by a probabil- reason for why financial market prices ity model. But realistically, they may not There are all sorts of are high sometimes and not other times. know how to model the risk, and they possible sources of long-term may react differently to alternative forms ROBUST CONTROL THEORY of uncertainty. This suggests that an ap- uncertainty. It’s fascinating proach that reflects a struggle, similarly to explore what happens when Region: Let me turn to a related topic, faced by econometricians in building we endow investors robust control theory. You and Tom and analyzing dynamic economic mod- with less confidence in their Sargent pioneered its application in eco- els, will add a richness to how we capture nomics, and in your 2007 book with the behavior of investors inside the mod- abilities to make precise Tom, you wrote that there’s been a long els we build. assessments of the nature of tradition in economics of framing macro these long-term uncertainties. policy rules “in light of doubts about LONG-TERM UNCERTAINTY AND model specification.” SHORT-TERM BEHAVIOR Robust control theory, as I under- stand it, is about designing rules that Region: How does this work of yours ap- will work under a range of alternately proach the challenge of understanding Region: Do you think that the average in- specified models because policymak- when long-term uncertainty affects in- vestor thinks in terms of long-term and ers, or econometricians themselves, are vestors in the short term? How do you short-term behavior of the economy? uncertain about those models. Is robust understand that connection? control theory an effort to address those Hansen: Once we came out of the fi- doubts about model specification? Hansen: Investors who are in the finan- nancial crisis, I think there was lots cial markets may well not know what’s of uncertainty about how quickly the Hansen: The term “robust control theo- going to happen to the macroeconomy economy was going to recover. Some ry” comes out of control theory in en- four, five, 10 years down the road. That people thought it might recover fast; gineering. In my work with Tom and can affect their current period decision- some thought it might recover slowly, in work by other economists, we find making and how they allocate financial and that thinking impacts what type of it very handy to build on insights that resources in both the short term and the new investment projects people engage have come out of the control theory en- long term. Thus, the struggle with what’s in. Should we hold back and be cautious gineering literature. This work has been going to happen over longer time peri- now, or is now a good time to invest in targeted toward solving practical prob- ods affects what goes on in even short- new business and new enterprises, when lems, where you have to develop meth- term behavior inside financial markets— we’re not really sure where the economy ods that are numerically attractive as how financial market compensations for is going to be in the future, long term? well as revealing—that is, that we can at- uncertainty fluctuate over time. There are all sorts of possible sourc- tach meaningful interpretations to them. Asset markets may behave cautiously es of long-term uncertainty, from fiscal We’ve also found guidance coming out today in part because the participants challenges to what’s going to happen to of decision theory within economics and are concerned about where the macro- technological growth over long hori- out of statistical decision theory. Robust economy is going to be in five and 10 zons or, for that matter, the economic Bayesian methods, for instance, have a years. So what does it take for the future impact of climate change and, converse- very similar flavor to them. to matter a lot for decisions I make today ly, the impact of climate change on the I find it interesting to draw insights about short-term investments? In finan- economy long term. Of course, measur- from all these different literatures and cial markets, you always have this pos- ing these with any degree of accuracy is try to make connections and then build sibility that you can make an investment enormously challenging. What has been on them. Economic models are different today, but if things are liquid enough, fascinating to me is both having the from standard engineering models, so you can undo it tomorrow. So you can methods to think about this problem in a it’s not as if we can just take their models, afford to take a short-term perspective as very systematic way and exploring what put in economic data and turn the crank, well. But it can still be the case that peo- happens when we endow investors with but they’ve had some very insightful ple’s concerns about long-term behavior less confidence in their abilities to make ways to look at problems. of the overall macroeconomy can affect precise assessments of the nature of Robustness becomes relevant when even that short-term decision-making. these long-term uncertainties. And then we put multiple models on the table.

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ROBUST CONTROL THEORY

The simple fact that there are uncertain- ties—about the exact magnitude, the timing, how a problem might unfold— doesn’t mean it isn’t prudent to act now. It just influences what things are sensible to do now. ... I think a lot of the fear of acknowledging uncertainty is fear that it will lead to inaction, and I don’t think that’s a correct assumption.

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We may not trust any of the given mod- “SYSTEMIC RISK” mission mechanism through which els that we have, but they are our best changes in monetary policy influence guesses. So how do we use models with- I’m not very optimistic that the macroeconomy. I would interpret that as saying, “We out taking them too literally or too seri- we will be able to say, “Here’s ously and still make them serve as use- don’t really understand the details of the ful guides? Many policymakers, once the one measure of systemic transmission mechanism, and maybe they’re outside the public realm, actually risk; let’s go with it.” But I do there are dangers in pretending we know too much. Instead, maybe we ought to be go through informal exercises similar to think that we’ve made some the following: “This is one view or mod- doing something simple, to avoid taking el of the world. Or it might be another limited progress in thinking too literally the complexities that a given model. Suppose we consider a course of about where regulatory model might have.” Once I start looking across models and recognizing potential action; how might it work under the dif- oversight of financial markets ferent models? Does one course of action differences or similarities across models, seem to work pretty well across different is crucial and where it can I might well be led to do something rela- economic models?” be counterproductive. tively simple that works across the mod- This, I believe, is a reasonable alterna- els rather than embracing some particu- tive approach to presuming, “This is the lar, more complicated approach based on model, I know it to be right and I’m going taking this one model literally. to go with the answer from this model.” just influences what things are sensible to So my statement was meant to get at Of course, we may wish to weight the al- do now. One could say, “Well, we should that type of idea, but I do not have a for- ternative models as suggested by Bayes- wait until we get more knowledge.” But if mal statement or proof of such a propo- ian decision theory, but there is still a we wait until we get more knowledge, it sition. Let me also add that there are challenge as to what weights to use and may be very, very costly or impossible to simple rules that are good, and simple how sensitive the policy prescription is intervene at that point in time. So I think ones that are bad, so simplicity is only to this weighting. a lot of the fear of acknowledging uncer- part of the story. In the statement that I worry about the pressures that poli- tainty is fear that it will lead to inaction, you quote, the reference is to simplicity cymakers face to project a lot of confi- and I don’t think that’s a correct assump- being a possible outcome that I think we dence in a precise rationale when they tion. Maybe it will lead to doing some ought to seriously consider. It is not a communicate with the public. Moreover, simple things now until we understand statement that, in all sets of circumstanc- some economists who want to influence mechanisms more clearly, but it doesn’t es, one should necessarily do something policymakers are led to project their own necessarily lead to the conclusion that we simple. viewpoints with incredible certitude, so shouldn’t do anything. There are fascinating links between that the policymakers can then turn complex environments and how much around and present these same view- Region: Related to this point about the uncertainty you have. The more com- points to the public. This outcome often projection of certainty, your closing plex the environment, the harder it is for overstates the certainty of our underly- observation in your Nobel lecture was, us to understand all those complexities, ing knowledge base in ways that can be “Uncertainty generally conceived is not and the more we have to deal with some socially unproductive. often embraced in public discussions of form of uncertainty as we think about There’s a lot of concern about ac- economic policy. When complexity is the environment. It can be problematic knowledging uncertainty. For instance, I not fully understood by policymakers, when policy complexity itself adds to the see this in some of the discussions of cli- perhaps it is the simpler policies that are underlying uncertainty in the economic mate change. People are concerned that, more prudent.” Can you elaborate on environment and opens the door further once we acknowledge the scientific un- that? I found it a little provocative. to regulatory discretion. certainty, the conclusion the public will reach is, “Well, therefore, we shouldn’t Hansen: [Laughs.] Well, this builds on “SYSTEMIC RISK” do anything because we’re uncertain of long-standing discussions that econo- the exact human influence on the envi- mists have had in other contexts. A long Region: During development of the ronment going forward.” time ago in a rather different monetary Dodd-Frank Act, a policy effort to pre- The simple fact that there are uncer- policy environment than we have today, vent future financial crises, there was tainties—about the exact magnitude, the Milton Friedman argued that we need to much discussion of “systemic risk.” In timing, how a problem might unfold— have simple policy rules because there a 2013 paper, you wrote about the chal- doesn’t mean it isn’t prudent to act now. It are long and variable lags in the trans- lenge of identifying what that is and then

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quantifying it as a first step in addressing THE MACRO FINANCIAL regulatory agencies had to provide quick it. Do you believe we have a better sense MODELING PROJECT responses. We hope to accomplish a few of “systemic risk” than we did previously? things. First is to bring together people Economists in both macro- from the fields of finance and macroeco- nomics and engage in more conversa- Hansen: The term “systemic risk” has economics and finance an interesting history. If you go back 10 tion. Another is to nurture a new cohort years and do some Google searches for collectively asked, “Isn’t now of researchers just coming into this area it, you won’t find out that much. Post- a good time to think more with quantitative and empirical ambi- tions. financial crisis, it’s become kind of the systematically about quantita- buzzword or grab bag, so to speak, that As we first got started, we received lots people use to rationalize a variety of in- tive and empirical methods of sympathetic responses from the lead- terventions in financial markets. As we that will provide guidance not ers in research departments, the public sector and central banks who participat- sort through the various empirical evi- only for monetary policy, but dence connected to this financial crisis ed in some of our conferences. That was and as we revisit other financial crises, for financial market oversight very important because it helped expose we will get a better idea of a variety of in the future?” academics to the types of challenges that constructs connected to so-called sys- public sector economists were facing. temic risk. But most likely, it’s going to be The resulting exchanges have helped to the case that there isn’t some single way guide the research questions. This aim is to measure systemic risk. government agencies and in academia to encourage the next step of construct- To really support measurement, we’re to take some of the existing modeling ing models that are richer along some going to have to add more specificity and efforts in macroeconomics and make dimensions, to build on the successes of think about it in different ways and then some modifications. A lot of these initial the previous modeling ventures and also do the quantitative assessment of which modifications were more like quick fixes. to expose some of their failures. of these different channels really turns Model builders connected to govern- out to be the most important one. I think mental agencies were under pressure to PASSING ALONG LESSONS that’s where some of the quantitative am- get answers quickly, because they had to AND FUTURE GOALS bition going forward can be really very provide immediate guidance for policy powerful. choices. As a short-run response, that Region: Your research career obviously So I’m not very optimistic that we will seemed perfectly reasonable and per- comprises a wide range of interests and be able to say, “Here’s the one measure fectly natural. discoveries. How do you try to pass on the of systemic risk; let’s go with it.” But I Andy and I, along with many distin- lessons you’ve learned to your students? do think that we’ve made some limited guished economists in both macroeco- progress in thinking about where regu- nomics and finance, collectively asked, Hansen: I feel very lucky to have had latory oversight of financial markets is “Isn’t now a good time to think more just an incredibly rich array of graduate crucial and where it can be counterpro- systematically about quantitative and students. Right after the Nobel Prize an- ductive. Better and more meaningful empirical methods that will provide nouncement, before we went to Stock- quantitative measurement is a fruitful guidance not only for monetary policy, holm, a bunch of my former graduate future endeavor. but for financial market oversight in the students put on a conference here. It was future?” There was a variety of ways to extremely exciting to see the breadth of THE MACRO FINANCIAL rethink macroeconomic modeling and what they were doing. They weren’t like MODELING PROJECT linkages to credit and other financial Lars Hansen clones; they were off doing markets, including focusing on alterna- their own thing. Region: Systemic risk is one of the top- tive mechanisms that hadn’t previously I suspect my influence was not always ics examined in the Macro Financial received much attention. Also, add- direct because often I wasn’t telling them Modeling project that you co-direct with ing quantitative ambition to qualitative what to work on. Maybe I was giving them Andrew Lo of MIT. What are some of its modeling insights seemed critical in an interesting perspective on important goals? What kind of progress has it made? pushing such research forward. problems to work on, and maybe I was We have the luxury of taking a longer- trying to convince them to take modeling Hansen: After the financial crisis, there term perspective on this research problem; seriously. Perhaps I pushed them in some was a very big push among research whereas, some of the research depart- ways, but the exciting thing was just to see departments at central banks, various ments in the various central banks and the breadth of their range of accomplish-

DECEMBER 2015 18 The Region

PASSING ALONG LESSONS AND FUTURE GOALS More About Lars Peter Hansen It’s just fun to see people that I had the opportunity Current Positions

to teach who are doing so David Rockefeller Distinguished Service Professor, University of Chicago, since 2010; well, enriching a field that, Professor in Statistics, since 2007; on faculty since 1981 in many respects, barely Director and Chair of Research Council, Becker Friedman Institute for Research in Economics

existed back in the early ’80s. Previous Positions

Associate Professor, GSIA, Carnegie-Mellon University, 1980-81; Assistant Professor, 1978-80

Professional Affiliations ments. I’m proud of my research accom- plishments, but I am also proud that I am Co-Editor, Econometrica, since 2012; 1986-90 able to associate with so many very good Vice President, American Economic Association, 2011 graduate students. Honors and Awards Region: I know you have a long list of Honorary Academician of Academia Sinica, 2014 them in your CV. Bank of Sweden Prize in Economic Sciences in Honor of the Memory of Alfred Nobel, 2013 Hansen: There’s a Macro Finance Society that was created a few years ago, trying to Distinguished Fellow, Macro Finance Society, since 2013 nurture research in this area, especially Frontiers of Knowledge Award in Economics, Finance and Management, BBVA Foundation, 2010 that from younger scholars. And a fair number of the founding members of this MSRI Prize in Innovative Quantitative Applications, CME Group, 2008 group are my former students. These days, Fellow, American Finance Association, since 2007 I have both students and “grandstudents”: students of students. It’s very hard for me Erwin Plein Nemmers Prize in Economics, Northwestern University, 2006 to acknowledge my age in all this, but it’s Fellow, National Academy of Sciences, since 1999 just fun to see people that I had the op- portunity to teach who are doing so well, Member, American Academy of Arts and Sciences, since 1993 enriching a field that, in many respects, barely existed back in the early ’80s. Fellow, Econometric Society, since 1985; President, 2007; First Vice President, 2006; Second Vice President, 2005

Region: So, in closing, what should we Frisch Medal, Econometric Society, Co-winner with Kenneth J. Singleton, 1984 expect to hear from Lars Peter Hansen Publications in the next five to 10 years? Author and co-author of numerous papers on econometric methods, asset pricing and financial Hansen: This answer should be obvious. markets, uncertainty and risk aversion, robust control theory, and macroeconomic risk, growth It is UNCERTAIN! I look to work on a and fluctuation variety of exciting projects, but I con- Education tinue to find research in economic dy- namics with quantitative ambitions to be University of Minnesota, Ph.D., economics, 1978 fascinating. I hope to push further along Utah State University, B.S., mathematics and political science, 1974 some of the topics covered here related to the impact of uncertainty on econom- ic analysis and on the shaping of prudent For further background, visit economic policies. larspeterhansen.org —Douglas Clement Nov. 4, 2015

19 DECEMBER 2015