Economics and Finance Symposium - The Evolution of Economic Science: Individual and Firm Behavior
POTERBA: Good morning. As many of you may guess, I am not, as your program suggests, Dean Deborah Fitzgerald. She will be joining us and welcoming all of you this afternoon as we start into the second half of our program today. But as Jim Poterba and one of the organizers of the events that we will be going through in the next day and a half, I want to thank you all for braving the snow this morning. I want to thank David and the members of the MIT 150 committee for selecting the Economics Department in the Sloan School to sponsor this symposium. And I would like to thank both the dean of the Sloan School and the dean of Humanities, Arts, and Social Sciences for agreeing to support this exciting adventure.
When MIT was founded in 1861, the field of political economy was already taking shape as a well-defined academic discipline. The leading text was John Stuart Mill's Principles of Political Economy, which had been published in 1848. And although in the very early years, economics was not yet on the radar screen of MIT, it arrived soon in the history of the young institution.
In 1880, when Francis Amasa Walker was recruited from Yale to come and serve as the third president of MIT, that was a rather unusual thing for an institution of science and technology because Walker was, actually, one of, along with Irving Fisher at Yale, the most distinguished economists in the United States at that point. And Walker would go on to serve as the first president of the American Economic Association for a period of six years in the 1880s. He'd be the president of the American Statistical Association for a span of 17 years in the 1880s and 1890s. And he introduced the first required undergraduate course in economics, or political economy, here at MIT in the 1880s. So the history of economics and the role of economics in MIT'S fundamental fabric goes way back before the origins of the PhD program that MIT created in the early 1940s.
I thought as one way of getting a perspective to introduce and set the stage for this 150-year perspective on economics at MIT, it might be useful to hear a little bit about some of the questions that emerged in the early Francis Amasa Walker course, so that showed up on the exams that we have from that era, and to give you a sense of how economics has changed or not changed as the case may be. In 1895, the exam included the question how are the debts between nations settled? What determines the value of gold? A question that certainly seems to have relevance today. In 1896, the year when the bimetalism controversy was raging, how and when may mortgage indebtedness press upon the farmer, and compare the effects of such indebtedness in different parts of the United States? The role of mortgages in the US seems to have been an issue again in the more recent past.
And to link to tomorrow's finance symposium, I found this fascinating. The 1896 exam asks illustrate by an example the use of an option by a manufacturer to protect himself against the speculative changes in the price of his raw materials. It actually uses the phrase option in what shows up on the exam.
Walker passed away in 1897. Davis R. Dewey, who served as editor of the American Economic Review for over 30 years and was another key figure in the history of the MIT Economics Department, continued to teach the political economy course. In 1898, he asked, for example, what arguments have been advanced in favor of a tax on inheritances? Again, a question that nearly 110 years later, we don't quite seem to have settled.
Although some issues have changed. In 1899, the question, what are the principal economic advantages of employing children in factories does seem to have [LAUGHTER] moved off the stage. Demonstrating that economists then as now have two hands and have difficulty reaching conclusions, in May of 1901, the exam asked, mention six arguments in favor of the imposition of a protective tariff. In the fall 1901, the next semester, the course asked, what arguments have been advanced against protective tariff duties? We don't have an answer sheet to these exams, unfortunately. We just have the questions.
So the history of MIT, as I said, is intertwined with the role of economics. The course then was called Political Economy and Industrial History. And it was basically trying to offer the students an opportunity to learn about the behavior of firms, the role of firms in the economy, and, of course, the role of consumers who are the demanders of those products. And that will provide a focal point for us as we organize our first session this morning.
The quick thumbnail sketch going forward from the turn of the 20th century, of course, is probably well known. In 1940, MIT introduced a Master's program in economics moving from a service department offering the undergraduates an exposure to economics to a department that was then focused more on research and graduate training. A year later, introduced a PhD program. Lawrence Klein, who taught for many years at the University of Pennsylvania, was the first graduate student went on to win the Nobel Prize-- not a bad start for a fledgling PhD program.
And the rest, in some sense, is history. In the post-war period, MIT, with a band of loyal and dedicated faculty, developed a PhD program which truly transformed the teaching of economics and made MIT a center of research activity in economics that attracted students and faculty from around the world, and has really been a central part of the post-war economics policy theory and educational mission in the broader economics profession. And that in, many ways, is what we are here today to celebrate-- the contributions that MIT as an institution, MIT students, and MIT's faculty have made to the advance of economic science, economic policy, and the design of economic institutions.
Today's program is broken into four components. We will begin this morning with a focus on the evolution of economic theory, both at the micro household level and firm level as well as on the understanding of macroeconomics. This afternoon, we'll switch gears to a somewhat more applied focus on macro policy and on regulatory policy. And we have an all-star cast of speakers who will be sharing their thoughts on a variety of these issues with us as we work our way through the day.
What I would like to do is to basically introduce our speakers for this morning's panel and then simply to allow them to take charge and to handle their presentations. We have, by the way, set up some microphones in the audience. And we will have time for some questions and answers at the end of the presentation today, so that I hope we'll be able to draw some audience participation. Let me just introduce our panelists as my final task this morning
George Akerlof, who will lead off, is the Koshland Professor of Economics at the University of California at Berkeley. He's a 1966 PhD from the Economics Department here at MIT. His work in information economics and more broadly in macroeconomics and behavioral economics has cast an incredibly important influence on the evolution of economic thinking in the last few decades. His paper on the market for lemons has been a perennial favorite both with undergraduates and has had a central role in teaching all of us how to think about the research frontier in information economics. He received the Nobel Prize in 2001, shared the Nobel Prize for his work on the theory of information economics. And he will actually be talking about the role of norms in economics with some illustrations from the field of [INAUDIBLE]
Avinash Dixit from Princeton University, the John J. F. Sherrerd University Professor, Emeritus, will be our second speaker. He received his PhD here at MIT in 1968. He is a past president of both the Econometric Society and the American Economic Association. He is a modeler par none who has an unbelievable capacity to distill a range of economic problems to their essence, to construct models which illustrate them, and to enlighten the broader profession and students about the workings of international trade, of growth theory, of a number of different disciplines. He will actually speak about the role of MIT's small models approach to doing economic theory and the influence that it has had on a number of different fields and on the evolution of our disciplines.
Jerry Housman, the John and Jennie MacDonald Professor of Economics here at MIT, will be our third speaker. Jerry is an applied microeconomist and an econometrician who received the John Bates Clark medal in the early 1980s for his work in bringing microeconometric tools to bear on a roll of different questions, taxes and labor supply, telecommunications, the role of transfer programs in effecting household behavior. Jerry has blazed a trail which has taught a generation or two generations of economists how to use the theory that we learn in our theory courses and the econometrics and statistical methods that we learn in our econometrics courses, to bring them together to enlighten our understanding of household and firm behavior. And he will talk about the question, what is econometrics good for?
Finally, the last speaker this morning is a slightly complicated combination. Oliver Williamson, the Edgar Kaiser Professor of Business Economics and Law at Berkeley is our scheduled speaker, but unfortunately could not join us as a consequence of the snow and travel difficulties. Now he's at University of California at Berkeley. He has sent us his prepared remarks, which focus on the role of economics in organizations. Professor Williamson is a 1955 graduate of the Sloan School as an undergraduate. And he received and shared the Nobel Prize in 2009 for his work on the economics of organizations in understanding what happens within firms and other sorts of organizations.
We have prepared remarks from him, but I am delighted to report that my colleague Paul Joskow, who is the Elizabeth and James Killian Professor of Economics, Emeritus, who was a member of the MIT faculty from 1972 until his moving to emeritus status late last year, and is now the president of the Alfred P. Sloan Foundation in New York City-- Sloan, of course, another MIT graduate from the class of 1895. But Paul, who is an expert on institutional and organizational economics, as well as an industrial organization, and who served as the president of the International Society for New Institutional Economics, has agreed to join us this morning. He will present the prepared remarks that Professor Williamson has sent us. And he will also elaborate on those with his own comments and then participate in the discussion that moves forward.
So without further ado, let me welcome all of you to today's proceedings, our panelists. And I'll turn things over to Georgia Akerlof. George?
AKERLOF: Thank you, Jim. It's tremendously nice to be back at MIT. It's always like coming home to be here. And thank you very much everybody here in the audience for coming, and for everybody else.
So I'm going to speak about the evolution of macroeconomics. And the analysis is going to be based on a book with Rachel Kranton whose title is Identity Economics. So that book is about the role of norms in economics. Now, actually, economists don't talk about norms very much. What is a norm? And norm is things that people think they should or should not do.
And, actually, if you just think about norms, they're tremendously powerful. I think everybody in this room, what we're doing at this very moment, I think a lot of what we're doing is we're here because we think this is something we should do for some reason or other and depending upon what our role is and who we are.
So the book describes a general procedure for bringing norms into economic thinking by including them in the utility function. And then it gives four examples where norms make a very big difference, a very big difference to economics. So those examples are the economics of education, the economics of organizations, the economics of minority poverty, and of gender discrimination.
But then there's another chapter to the book. This is one that we sort of sneaked in where we talk about the role of norms in the economics profession itself. And there we see the norms of how an economist should behave as playing a key role in determining the economics we have. In turn of course, then, this is important for the whole world, for everybody, because our economics plays a key role in the economic system itself.
So let me go back to an old article, which is important. With this preface, let me characterize the norms for how economics should be done. This is how economists think we should do economics. The source for this is Milton Friedman's article on economic methodology. It was written some 50 years ago. And now 50 years later, this article-- which I think was a little bit radical. I think people didn't believe it at this time. This article remarkably well describes how most economists think that economics should be done.
So Friedman says that we should start with a model, a mathematical model, with a null hypothesis, he said, of perfect competition. Now 50 years later, that norm, I think, for the null hypothesis has been broadened. And I think most economists would now say that one should begin with a model where people have only economic motivations.
And then there's been a little bit of an addition to that because we have behavioral economics. And I think behavioral economists say that they'll also allow people to make some kind of cognitive error. Beginning with such an all hypothesis, then, is the first norm for how an economist should proceed in the analysis of any problem. So that's the first norm. And that's in Friedman.
The next norm concerns the use of statistics. This is in Friedman, definitely. Starting with such a rational economic model, the analysis should continue to be the null unless rejected by statistical methods. That means that non-economic motivation is inappropriate. It's inappropriate unless one has statistically rejected all variants of explanation with purely economic motivation.
So what happens, it affects the economics we have. And then it's going to affect, actually, the world we have in so far as economics plays a role. And I think it does play a role. Because such norms privilege economic motivation and therefore they play a major role in the economics we have.
But then further, the institutions of the economics profession itself, especially for acceptance and rejection of economic articles, play a further role. So I'm going to talk a little bit about those institutions of economics.
So those institutions and economics are centered around our journals. Now articles at the journals are refereed by those who have previously published in the same area. So this means that those who accept or those who reject articles have a bias. And this then creates a feedback loop, a feedback loop between those who get their articles published in one generation and the output of the next generation.
So this then poses two questions. First, the norms of economics may be a bit broader than the norms proposed by Milton Friedman 50 years ago, but they're not that much broader. So the question is, do these norms cause economics to evolve toward descriptions of reality? Or do they prevent it from such an evolution? Second, does the system for acceptance or rejection through journal articles lead to evolution toward the truth? Or does it prevent the system from correcting its errors?
So the feedback loop suggests that norms of good economics could potentially get into a stable equilibrium even if much better descriptions of economic reality were possible. It's not only the journal system that determines whether this will happen. It also depends on the interaction. It depends on the interaction with the subject matter itself.
So if, as in physics, models make very specific predictions and empirical tests are powerful in rejecting wrong hypotheses, then these biases will make no difference. But in economics, I don't see that as being the case. In economics, the models make only very general predictions and therefore the power of our tests is extremely low.
So let me just give you one example. So Larry Summers gave us an example of an auto regressive system for stock prices where prices would deviate from the efficient market hypothesis by 30% more than 2/3 of the time. So he gave some kind of hypothesis as a mathematical formula, and the system behaves that way.
Then he asks, how much data would it take for you to refute that system? Stocks are quite a bit away from what the efficient markets hypothesis would suggest. And what he found was it took more than 5,000 years worth of monthly data to reject it with probability one-half. Unfortunately, we don't have 5,000 years worth of monthly data for stock prices. As far as I know, we have no more than 150 years or so.
Now, furthermore, the remarkable thing is this is a case where the model's very precise. The efficient markets hypothesis gives us one of the most strongest possible predictions as to what the model should look like. Usually, it's harder still to reject statistically the rational economics because there are many different models with only economic motivation. Because there are so many models out there, it's a little bit like the trials of Jason and the Argonauts. As soon as you've killed one of those warriors which has come up with their sword who's about to kill you, then that guy dies and you have to kill somebody else. It's really terrible. So as soon as you've rejected one rational model, and new one arises that you have to fight as well.
So then the question is, should we care? We should because without the right economics, we're going to get the wrong economic policy. So I'm going to give you some examples.
Three times in the United States in the last 125 years, we've had major, major downturns. The first was in the vast recession of the 1890s. The second was the worldwide depression of the 1930s. And now, as I speak, we're facing a very deep and a very robust downturn.
And economics gave us the wrong model here because it failed to predict it. So I see this as a tell-tale, a tell-tale that the system's not generating the right economics. And there's a reason to believe this. We can go look at what happened in detail. And we can see why we should believe this.
In 1936, after recession and depression had hit England for more than a decade, John Maynard Keynes wrote the General Theory. It's a long, well-written book, even if here and there it's slightly hard to read. But then John Hicks boiled it down to three easy equations in a journal article.
To remind you what those equations are, they're first the IS and LM equation, which together are the equations for aggregate demand. And then there's a separate equation for aggregate supply.
So you have these three equations. And they are the basis for all macroeconomic models today. But the reduction of the general theory to a journal article spawned a major tragedy, a major tragedy for which today we're paying a great price.
The General Theory did describe Hicks's three equations, but it did much more. The General Theory also described how asset markets worked. And there's a whole chapter, there's a whole chapter there, a wonderful chapter, on stock market irrational exuberance. And it describes in words the origins of this irrational exuberance and also its consequences.
That irrational exuberance explains why we get booms and busts and especially the major sorts of booms and busts that lead to economic calamities such as we had in the 1930s and such as we are experiencing today. This part of the General Theory was not based on standard economic motivation, and so it got lost in translation.
Thus the current crisis and the failure of economists to predict it serves as a potential tell-tale. It's a tell-tale that economics is not systematically getting right answers. If that tell-tale is informative, then we should see answers to other questions that are also wrong.
So now I'm going to give you two other examples. All you need to do to see that is to go to the macroeconomic textbooks, the standard macroeconomics textbooks. So here's an example from the very best of them. It's a wonderful book and very, very well-written and also very convincing.
So it introduces the consumption function with a line from Keynes that says, as a psychological rule-- law-- as a rule, and on the average, as people's income goes up their consumption goes up but by not as much. So if you get an extra dollar's worth of income, you tend to spend some fraction of it.
So we can imagine the sophomores reading this, nodding their heads silently as they read it. And they're saying something like this to themselves. Yeah, when I was 13, my mother got $1,000 bonus. And we went off to Martha's Vineyard. And we stayed at the Fisherman's Lodge. And I stepped on a jellyfish. at the beach. And it's wonderful Keynes understood that even though he didn't know my mother. And he didn't know about that $1,000. He's a really cool guy, that Keynes.
But then that chapter explains that people have other motivations. Yeah, it's not just that. They tend to smooth out consumption as they save for their retirement. And so we can imagine the sophomores still nodding their heads. Yeah, that's right, too.
And then that chapter explains that formal economic reasoning would have predicted that in the beginning. And if we'd use that formal economic reasoning, we would have had a more sophisticated view. And that's how we should proceed.
What we would have done is we would have applied the Friedman-Fischer graph and seen the consumption depends only on lifetime wealth given the rate of interest. And then that's the end of the chapter. So the sophomore says, yeah, I should've used that form of reasoning. And that's what I would have gotten. And I would have been much wiser for it.
But the sophomore is never told-- he's never told-- that this presumed right way of doing economics produces a truly surprising result. This is the result. Given his level of wealth, a consumer's purchases will not change by a single dime as the time path of that income changes. Will not change by a single dime as income goes up and his income goes down given that the total wealth is constant. Says that the rational consumer does not consume more at the time she receives a large bonus check.
That, curiously, is also a result that's contradicted by the data. It also is contrary to what got the freshman to nod his or her head at the very beginning of the chapter. So the freshman got sucked into this, was pulled through this line of reasoning, and now believe something that's truly radical-- not knowing it, either.
I can tell a very similar tale regarding the treatment of the acceleration of the Phillips curve that gets the student to accept the view not just that people try to adjust for inflation in so far as they can, but much more radically that nominal variables corrected for expectations have no effect-- literally no effect-- on how the system works at all. And so that's, I think, seen in almost all macro textbooks. And it is, I think, something that almost every economist believes. It has very important consequences. But yet, when you actually put it the other way, do people have any effect-- do nominal variables have any effect? No. Most people would say no, I think, if most people don't have formal economics training. So that takes us to our conclusion.
So let's go back to the beginning and the question about the evolution of economics. We have institutions of economics and also norms for what's good economics and what is bad economics. But curiously, no one has ever done the analysis for our own institutions and our own norms that we say we should follow as good economists everywhere else. We've never done, for economics, what we've done, what we do for everybody else. No one has ever done an empirical check to see that these are the right norms and the right institutions for an economics that really serves the public. But I've given here at least three examples where we've gotten wrong answers.
In one case, regarding the causes for economic fluctuations, we could have prevented the current world recession. We also saw that the institutions of economics systematically weed out the parts of the analysis that rely on what's called non-economic motivation. For example, it weeded out totally Keynes' explanation for how irrational markets produce boom and bust. And as it did so, we got an economics that gave no appropriate place for macro prudential regulation of asset markets, which we should have had.
So let me conclude. In conclusion, there is an evolution of economics. And there are biases. And it's not clear that it evolves into an economics that systematically gives us the right answers. We should be questioning our journal system for acceptance and rejection of articles. In physics and chemistry, that journal system is really very different. Assistant professors do not have to wait in those fields years to get their article rejected simply because the referees have decided that they do not like it. It's much more easier in these fields to get your article published. And furthermore, it's not going to take you years.
And we should also be questioning-- furthermore, we should be questioning our methodology. We should be questioning our methodology of that dis-privileges non-economic motivations. And it also just dis-privileges careful detailed observation in the place of statistical work, in the place of statistical work that usually has very low power and therefore has a very hard time rejecting a null, even if that null might happen not to be true. Okay, that's all. Thank you.
DIXIT: It's a real pleasure and privilege to help celebrate MIT's 150th anniversary. Thank you so much, Jim and all the other organizers, for involving me in it. The Economics Department is where I learned my craft of economics. I learned it not just from a galaxy of stellar teachers, but from many fellow students, many of whom went on to join that galaxy. And you will see George is, of course, a prime example. You'll see many others today and tomorrow.
These people were not just brilliant. They're also very collegial. I remember the hospitality of professors at their homes and Friday lunchtime bridge games in the student lounge just as much as I remember classes and workshops. And I'm sure we learned just as much from these social settings as we did in the more formal ones.
I want to do something unusual. Rather than talk about frontiers of research, I want to look back and talk about one specific way in which the MIT department has been instrumental in many of these frontier research developments. I want to talk about what I learned, basically. And it was not any kind of doctrine or ideology. The MIT economics department was never a school of thought in the sense that, let's say, Chicago or the London School of Economics was. It was more a school of research style. Many of its members learned, developed, refined an art of economic modeling that's come to influence a very large proportion of economists the world over in the way they think, write, and do research.
Economic models come in many varieties. Just to contrast two, the very, very general, overarching models of economic systems, general equilibrium where in principle you allow zillions or maybe even an infinite number of goods and services, and try and characterize properties of equilibrium involving demands and supplies for all of these. The problems of devising good social mechanisms for collective decision making, possibility or impossibility of them. These kind of models are very general, very abstract. And the art of doing them is to find the right mathematical framework in which to pause and analyze the question.
Then there are models that are tailored to analyzing very specific issues. For example, what's the relative importance of capital accumulation and technological progress in economic growth, which was a key theme of Bob Solow's researches. The art of these kind of models is to distill the central question that's being asked into small number of special assumptions, setting aside everything else to focus in on that one. And MIT largely, I believe, specialized in the second kind.
That's an art. One can learn science systematically. Art is best acquired by demonstration, by practice. And so let me explain what I mean by giving just a few examples that are my favorites among MIT style of modeling.
Of course, very appropriately, my first choice is a model from Paul Samuelson. It's his exact consumption loan model of interest. The question he asked was, when each person wants to work and save when young, and retire and consume the principle and interest accumulated on the savings when old, how will the interaction between all the people of this kind work out?
So he constructed a model in which there is an overlapping set of generations. Each person lives for two periods, works and saves in the first period of life, retires and consumes the principal and interest on the previous savings in the second period. There is no way of storing goods across time. So you can just store your own output. And there is no durable capital machinery or things of that kind. So you can't, when you're young, build a machine and then consume the output of that when you are old.
Soon as you hear this, all the non-economists, I'm sure, and perhaps many economists as well, say, oh, but that's totally unrealistic. What about childhood? Isn't the working life much longer than retirement? That certainly was so in 1958 when Paul wrote the paper and may become so again as retirement age gets longer and longer.
Of course, there's durable capital. There's uncertainty. There's technological progress. There are business cycles-- all kinds of things.
But, I hold, that it was precisely by ignoring all of these other aspects that Samuelson could zero in on the essential new thing that market for borrowing and lending over the life cycles brings, namely, if a young worker today gives some goods to an old retiree who is not working and not producing any goods, there's nothing the retiree can give to the young person by way of goods and services in exchange. And you can't resolve this problem by using any kind of a longer cycle where a gives to b, b gives to c, et cetera. And z gives back to a, even with a longer, but finite lifetimes.
And this difficulty of organizing exchange creates a new kind of market failure. Samuelson then went on to analyze how that kind of a market failure could be overcome by using social contracts so there is an ongoing understanding where the young person who gives up goods getting nothing directly in exchange is then promised goods when he is retired from the then young, and so on, and so on, and so on. It can also be resolved by creating longer-lived assets, what Samuelson called the social contrivance of money.
So the grossly simplified, stripped-down model gave us conceptual understanding of key aspects of asset markets, of money, and of the possibility of market failures. And all of these deep key issues of the question what has been very hard to spot in a complicated model that tried to bring in all the details of the reality of life cycle saving.
The converse is easier. Once you have the conceptual understanding, you can add all kinds of questions, complexities, bells and whistles; take the model to the data; calculate numerical solutions, simulations; and so on, and so on. And, in fact, that has been done with the result that Samuelson's paper counts well over 2,000 citations on Google Scholar.
The model also proved useful in giving a number of other insights. Building on that, new conceptual questions could be posed, answered, and key insights obtained. The one I want to focus on, again, very appropriately talking at MIT, is Peter Diamond's model of national debt, which combined Samuelson's model of saving across generations with Solow's growth model. So the savings of each period's young could go on to finance the physical capital that would combine then with labor of the future young to produce output, some of which the then-retired could get as returned to their previous saving.
Again, this was an absurdly simple model of a complex reality. But the very simplicity allowed us to understand key economic mechanisms that will work, develop new intuitions. It showed how saving decisions of individuals, each of whom has a finite life, can depart from calculations of socially optimal capital investment, and, again, clarifies how inherent inefficiencies in the operation of markets through time can arise.
Then, when government debt was introduced into the model, it highlighted the effect of saving interest rates and long run capital accumulation, which was how Diamond was able to resolve the conflicting views on national debt, which are still being voiced, one that held that we are mortgaging the future generations, the second that says, oh, we owe the debt to ourselves. So it just cancels out on the balance sheet and doesn't matter at all. Diamond showed that both of these were wrong. And, actually, perhaps particularly interestingly and completely contrary to what raw intuition might have led to suggest, turned out that debt owed to our own nationals has a worse effect on capital accumulation than debt owed to foreigners.
Again, this model has also been the source of a large number of extensions, generalizations, numerical calculations, et cetera, et cetera. Peter built this model soon after he left MIT. And that says how the MIT style kind of spreads to other places. And my third example is a good example of that. That comes from Ronald Jones who got his MIT PhD, went on to be on the faculty at Rochester, and many years later produced a model of international trade that I think is an excellent exemplar of the MIT style of modeling that he must have learned from Samuelson, Solow, and others at MIT.
Again, his economy has two words, but a very natural way to distinguish exports from imports, so very fitting for international trade. He compares it, one, when the economy is close to the rest of the world, and second, when it's freely trading with the rest of the world. And in a very elegant system of just four equations, he captures what before that was a long and complicated series of diagrams and verbal arguments.
I could never understand those. I read the one paper by Ron Jones. And it became crystal clear. He clarified the basics of comparative advantage; effects of labor force, growth, and capital accumulation on the pattern of trade; and the effects of changes in world prices on the returns to a country's factor of production, for example, wages.
Recently, Jones was elected as a distinguished fellow of the American Economic Association. And Gene Grossman, yet another MIT PhD, wrote the citation for that that's worth reading. Said Ronald Jones makes the few equations of small-scale general equilibrium models deliver profound insights. He has applied this talent to the [INAUDIBLE] transfer problem, the effect of tariffs, international factor flaws, and the incidence of technological progress. Jones always had just the right set of equations to capture the sense of a resource allocation problem without unnecessary clutter.
Given enough time, I could produce many, many other examples, a few more of Samuelson's own papers, for example, on the stock market and a couple of models of international trade-- Bob Solo's growth model, of course; Paul Krugman's models of international trade and economic geography; George Akerlof's model of market failures with asymmetric information; and many, many more.
Now, some economists who come from other research styles dismissed these as toy models. But we practitioners of the MIT style wear that label "toy models" proudly. The clarity and intuition that these models convey is absolutely invaluable. And I could cite support from other authorities. For example, Einstein said everything should be made as simple as possible, but no simpler. But I'm going to offer two rather unusual sources of outside support.
One is Hannibal Lecter. [LAUGHTER] Remember what he told Clarice Starling. He said, read Marcus Aurelius. The emperor advises simplicity. Of each particular thing, ask, what is it in itself? What is its nature? And once you understand the innate nature of the problem, the rest is detail.
Detail is important. It needs a lot more painstaking research to bring it to fruition. But it's detail.
And my second outside source, if you don't like Hannibal Lecter being held up as an exemplar, is Mozart. Remember what he told the emperor. I use just the notes I need-- neither too many, nor too few. And to me, that's exactly the sense of the MIT style of economic modeling. Thank you very much.
HAUSMAN: So since Jim Poterba gave a little history, I'll give a little bit, too. I had a grandmother-in-law who lived to be 108 and probably, apart from vacation, never got more than 10 miles out of downtown Boston, or 15 miles. And I was interested, when I came back from graduate school and started teaching here, she always called MIT the Tech. And so, it turned out that was the old name for MIT.
And she and her husband were always curious because she was actually born just about the time that MIT started. She lived to be 108. And she and her husband always regarded MIT as a school that produced engineers. And those engineers went to work for corporations that her class ran in Boston. And she was always curious that we had economics at MIT.
The other thing which I think she actually got right, which I always found funny, she said that she just didn't believe that all these skyscrapers were ever going to make it because she remembered when MIT was in the Back Bay. And she actually remembered when they filled in the Back Bay with mainly dirt from Needham, which they brought in by train.
And when I first came back, she said, you know, they're building this John Hancock Building. It's just never going to work. I can remember when that was all under water.
And I said, no, no. There are all these MIT engineers. And they dig down to the bedrock. And they float the building. And it's all going to work.
Well, of course, for those of you who live around here, you remember all the windows fell out of the John Hancock. And so I never heard the end of that. That's what grandmothers-in-law are good for, I guess. So that was one thing that, to the extent that engineers were involved, they didn't get quite right.
So I'm going to talk today about econometrics. But I'm going to talk about a particular type of econometrics, which is microeconometrics, which as Jim Poterba said, is sort of what I specialized in. So these are models of how firms behave and how people behave, not about how large economies behave.
And I would say the great advance in econometrics of post World War II-- although it happened during World War II, but the advance happened after World War II-- was the notion of bringing equilibrium into econometrics. So I'll explain that.
So I think the most powerful notion in economics, or certainly one of the most powerful notions, is the idea of equilibrium. So I think most people have an intuitive understanding, which, of course, was discussed by philosophers for years, about cause and effect. Something happens. That's a cause. And because of that cause, there's an effect.
But the idea of equilibrium in economics, which is perhaps not as intuitive to people-- one of the reasons you probably want to study economics-- is you don't have a cause and effect because in equilibrium, something changes, you might think that's a cause. That has an effect. But then that effect has a feedback, which changes the cause.
So prices go up some for a commodity. So the government in its infinite wisdom decides to subsidize ethanol. So the price of corn goes up. When the price of corn goes up, people buy less commodities with corn. And that then has a feedback through getting farmers to plant more corn. And then it subsequently affects the price of corn.
So this notion of equilibrium is an extremely powerful notion. And, of course, Avinash Dixit just talked about that Ron Jones model. I should say that Avinash taught me my first course in economics when I was a graduate student at Oxford. And he said at that time that Ron Jones, that was a great paper. And I'm pleased to see that he hasn't changed his mind in the meantime, since I read the paper very carefully. So that's almost 40 years ago. And it's still a great paper.
So how did econometrics take this into account? Well, econometrics, to a large extent, uses what are called regression models. A regression model is you have a variable you'd like to explain. So the example I'm going to use for a second are house prices. So you want to explain house prices in some suburb of Boston like Lexington, or maybe across suburbs. And you use a regression model to try to figure out how to explain the price.
So what would you take into account? Well, you'd take into account the lot size of the house, the square feet of the house, the number of bathrooms. If you were looking across suburbs, you'd probably look at tax rates and how good the schools are and various things like that.
So that type of regression model was known probably and used from 1910 or 1920 in England. So those models were known. And, actually, regression was known by Gauss, which goes back to probably the 17th century. And that just says, we want to explain some variable like the housing prices. And we're going to use the characteristics of the houses to do it.
That was well known. And, in fact, it was done in England even before computers. So one of the great lines in economics-- this was done at Cambridge University-- and I don't know whether any of you ever seen in the science museum here, but they had these calculators in which you would program in the numbers because you had to invert matrices pretty much by hand. And these old Smith's Marchant calculators would go thunk, thunk, thunk, thunk, thunk as they were doing it.
But anyway, the guy that ran that who did win the Nobel Prize was Sir Richard Stone. And that's always called the Stone age of econometrics in Cambridge because you had all these people who had run these. And then it had to be double and triple checked to make sure it was right because it was quite easy to make a mistake. But, of course, in the '50s, computers came in. And that really gave econometrics a big boost.
So why am I going to talk about microeconomics and econometrics and not macroeconometrics? Well, I'm going to argue that microeconometrics works pretty well. And I'll give you a couple examples where it's led to stuff, which I think has had a big effect on economic policy in people's lives.
Macroeconometrics, a lot was done here at MIT before I came and about the time I came. That's had a much more difficult road. I'm not saying that we haven't learned anything, but the main problem with macroeconomics or econometrics is, I tell my students, is we essentially have only one economy to study. And so things tend to move together. You can look, of course, internationally, other economies, but then that raises other difficulties. But it's very difficult to take quarterly data. George Akerlof mentioned that that's what we often use. And the economy is not all that stable. And you can't use 150 years of data. In fact, you might not want to use more than 10 or 15 years of data. And that makes progress very difficult.
Well, what about microeconometrics? I talked about firms and individuals. Well, starting in the 1970s or 1980s, very large surveys started to be collected. And oftentimes these surveys follow people over time.
So one of the first ones was done at the University of Wisconsin. And when you go into microeconometrics, it's not out of the question-- I mean, the minimum number of observations you'll typically have is about 1,000. But it's not out of the question that you'll have 10,000 or 15,000 observations. And these individuals are often acting in pretty much independent ways. So that's really a lot of data that you can piece things out. And you compare that to 40 observations, if you had 10 years of quarterly data on the macro economy.
And in terms of firms what happened are companies like AC Nielsen and IR-- IRI, in a sense, was partly started at MIT-- but they go and collect scanner data from stores so we know what they're selling, or even better, they now give people wands and so we know everything that a given household will buy. They pass a wand over the UPC codes, which I think were invented at MIT. And anyway, by cellular telephone, it then goes to a database. So we'll have an observation of how 5,000 American households-- they're followed for two years, not only watching TV, but this is everything they essentially buy. So we can do a lot of research on that. And that's led to a lot of advances.
So I'd like to give two examples where this idea of equilibrium comes into play, or the cause and effect is not straightforward, the contrast that to the regression example that I gave before. So I think-- economists, of course, disagree about a lot of things. But I think that one thing that most economists agree on-- and it was also in the President's State of the Union address-- is that the returns to education are quite high.
Now how do we know that? Well, I'll tell you in a second how we know that. But that has immense policy implications because it is generally agreed that we have to improve the educational system. But also we need to get people to have more education. Because for people with only a high school degree, it's very difficult to have a good job anymore.
And this has been known, really, since the late 19790s. It was interesting that a Harvard professor-- I won't mention his name, although his sister did go to MIT-- I taught her-- published a book in the late 1970s called The Overeducated American in which he claimed people were getting too much education. So if anybody ever got anything wrong and really wrong, that was it because the gap between high school and college education has just grown ever since that time. And it's probably now 35% or 40% if not larger.
But anyway, how did we figure out, or how do we know what the returns to education are? So what you might say, OK, I'm going to fit a simple regression model. I'm going to put people's earnings on the left-hand side, or actually we use a log of their earnings. And on the right-hand side, we're going to put the number of years of education.
And if you run that, not at all surprisingly you find a positive coefficient. And you'll say, well, people get more education, they're going to have higher earnings. So that's a good idea.
And if you look at the coefficient on that, back in the '70s, it was about 8% or 9%. But, as I said, it's really grown a lot since then. So in terms of investments either privately that people could make or the government might want to subsidize, you get a very high return to education.
OK, but what's the objection to that? Well, I used to call this a Jewish mother problem. But now I guess it would be more accurate to call it the Asian mother problem.
So what happens is your mother causes you to study a lot and do well in school. So you get more education holding every everything else equal. But these good work habits you get also rewarded when you go to work at a job. And the unexplained personal habits you have when you work hard on your job enter what is called the stochastic term. And that's correlated with education. And so you would think that there is an upward bias. So if you just run a regression-- a lot of people said this-- we're just getting an upward biased estimate.
So that's sort of the problem, that you can't just use a regular regression model to do this. But as I said, around World War II and surely thereafter, there were new techniques developed called instrumental variables. And these basically solved the problem, although, I mean, this is still a large area of research about exactly how to do it right. I think people pretty much agree that we have solved the problem, and being able to figure out what the effect of education is alone, apart from personal habits.
And interestingly enough in terms of this research, when it was done, everybody thought that the returns to education would fall once you got rid of the Jewish mothers of the world. But, in fact, the estimated return to education rose. And I wrote a paper in about 1981 saying if you do this right, you actually get about a 25% higher estimate than otherwise. And this was shown time and time again in people's papers.
And David Card, who's a professor at Berkeley, published a paper in about 2000 just demonstrating this happen time and time again. And this happened for another econometric reason. And it was that the years of education are not the best variable because, of course, once you get on the job, it's not necessarily the years of education. It's what you've learned and how you can apply it. And there's what was called an errors in variables problem. And when that's solved, that tends to bias downward the effect. And when that's solved, the effect actually goes up.
And the way that you can see that is that if you look at data from before World War II, the schools in the South, of course, were much worse than the schools in the cities in the North. And you can see that the returns to education from people who went to schools in the North who were given the same number of years of education on average is higher.
So the next example I want to give how this might affect your life is cell phones. So I'm sure everybody in the room has a cell phone. And I'm pretty sure that everybody in the room has a cell phone on a subsidized plan. So when you go in and buy an iPhone, the retail price of an iPhone is about $500 or $600. But you get it for $200. And if you want to get a less expensive phone, you can get it for free.
So how did this come about? I mean, why don't people just go into a store, pay the $500 or $600, and get service? You know, you would think that was how it was going to work.
Well, it turned out that I wrote a paper in which I published in the late 1970s looking at people buying air conditioners because, of course, cell phones didn't get started till 1984 in Los Angeles and Chicago. But, anyway, when I looked at people buying air conditioners, there's this trade-off. You can buy a more expensive air conditioner and pay more and get a more efficient one. And, of course, it's going to use less electricity.
So depending on where you live, how hot it gets in the summer, and what the electricity price is, you can sort of figure out what the best solution is for people with an econometric model. And what I found was that people had very high discount rates of about 30%. So, in other words, they'd much rather buy a less efficient air conditioner and pay more for electricity later than buy a more efficient air conditioner pay more now.
And so in the late 1980s, I was working with PacTel Cellular, which is the biggest cellular company in the country. And most of you probably don't remember this, or were not interested, but cellular telephone was very slow to take off in the United States. In the late 1980s, there as very low penetration.
So we were sitting around a meeting. And I said, you know, I have this academic paper. And what it shows is blah, blah, blah.
And I said, so what you guys should do is subsidize the price of your phones, give people contracts, and then get the money by charging a higher contract price, which they did. And then in California, holding other things constant, you could fit a model and see that cellular really took off.
The only problem with my plan, which these guys never let me forget, was they said, oh, we-- you said all we had to do was subsidize it. At that time, there were only car phones. And they cost $1,500. So I said, why don't you subsidize it down to about $1,000?
They said, but you never predicted that competition was going to drive the subsidies so large that the price would be zero. Because what happened was, as more and more competition subsidies grew ever larger and it became zero. So I would say, I don't know what you guys are complaining about. Your stock price has gone through the roof and you all have your own private jets.
You know, I got the direction right at least. You can't expect everything to be right. But it's interesting because if you think about satellite TV, they originally came out, and you had to buy the dish, et cetera, et cetera. But now you get the dish for free. So this comes out.
So the last thing I want to talk about, which I'm going to disagree with George Akerloff about, is can you reject null hypotheses with econometrics. So I actually invented something called the Houseman specification test. And it's used a lot. And I just want to make two points.
Number one, it's quite straightforward to reject null hypotheses, especially with microeconomic data. Some people claim it rejects too much. But, secondly, it's very easy to reject the efficient markets model. So [INAUDIBLE] had one idea. But, you know, I think Andrew Lo is probably in the room somewhere. He's published at least three papers showing that it's quite straightforward. Andrew is a student of mine, so I'm going to give him some advertising. It's quite straightforward to reject it. So it is true that maybe one model won't do it, but we are advancing because if you think it all hard about it, you'll come up with a better way to do things and it's quite straightforward to reject.
OK, thank you.
JOSKOW: Thank you. It's a pleasure to be here. I'm really very sorry that Oliver Williamson couldn't join us this morning because of the snow. But I'm also pleased that Jim Poterba's asked me to present Ollie's remarks. I've known Ollie for almost 40 years. And Ollie's research has had a significant effect on my own research.
For those of you who know Ollie, he has a particular lecturing style, which I will not try to reproduce. But he did send along his remarks.
I think perhaps to make the remarks a little bit more understandable for some of you, I'd very briefly just talk about what it is that Ollie's research is best known for. It's generally referred to as transaction cost economics. And transaction cost economics focuses on a variety of frictions, transaction costs, that can occur in both markets and inside organizations.
And Ollie's research has focused on using the attributes of transactions and the associated transaction costs to better understand the boundaries between firms and markets, the structure of contractual relationships between buyers and sellers, the internal organization of firms, and a wide variety of other institutional arrangements that either don't appear in traditional economic models or were difficult to understand. And much of this work has influenced other social sciences including political science and organizational behavior.
So let me turn now to Ollie's remarks. The title of Ollie's paper is "The Microanalytics of Micro (and Macro?) Economics." So I'm going now refer to Ollie.
My remarks are in three parts. First, I briefly discuss my experience as a student at MIT. And I was actually interested to read this because I had never heard much about his experience here. This is followed by a discussion of my experience as a PhD student at Carnegie and how this led me into the microanalytics of microeconomics, especially with reference to transaction cost economics. Finally, but very tentatively, I raise the possibility that there are microanalytic commonalities between transaction cost economics and what Ricardo Caballero refers to as the periphery of macroeconomics.
And Ricardo is here. And I haven't actually read the paper Ollie's going to refer to. But he can he can rebut whatever Ollie says later.
First, MIT. Unlike most of the people who are speakers at this symposium, I neither received my PhD from MIT, nor have I been a member of the MIT economics or Sloan School faculties. Rather, I received my bachelor's degree from MIT in 1955 in Course 15, the Sloan School, Chemical Option. I didn't know there was a Chemical Option in the Sloan school. [LAUGHTER] Maybe that's what smells in E52. I'm not sure. [LAUGHTER]
I was largely without contact with the powerhouse economics faculty then in progress. Although to be sure, I was aware that it was a special event when riding the elevator with Paul Samuelson or with Norbert Wiener. I did, however, have the privilege of taking an undergraduate course in statistics from Bob Solow, who spiced up his lectures with amusing observations. For example, that kurtosis is not merely the fourth moment, but also describes lower back pain.
And I've known and often worked with MIT faculty members for years. Peter Diamond and I were appointed to the faculty of economics at Berkeley at the same time in 1963. And it was my pleasure in my capacity as editor of the Bell Journal of Economics from 1975 to 1981 to work with Paul Joskow-- me-- and Jerry Hausamn, who you just heard from.
And, of course, with others on miscellaneous committees of the NSF and the American Economic Association and the Sloan Foundation over the years. Since I'm now president of the Sloan Foundation, I introduce an editorial note. Largely thanks to Bob Solow, a long-time Sloan Foundation advisor and trustee, the Sloan Foundation embarked on a program to support faculty and student research to encourage advances in microeconomics in the late 1970s. This was motivated in part by the assumption that macroeconomics was well understood, while microeconomics had received inadequate creative attention in the post World War II period.
Ollie was on the economics faculty at the University of Pennsylvania from 1965 until 1983. He received one of the first grants from the Sloan Foundation for work on transaction costs economics. And the Sloan Foundation supported his research, his workshop, and many of his PhD students in the early stages of that work. I return now to Ollie's remarks.
I'm naturally pleased to be here and to report that although I took no courses in economics while at MIT, I did take away what I think served me well when later I was a PhD student in economics at Carnegie Mellon. That lesson was this. Engineering and economics differ as they move from theory to applications. Specifically, although both relied on simplifying assumptions for theory development, and often took the form of assuming the absence of frictions, the two frequently differed when it came to applications. Thus whereas the absence of friction, perfect gas laws, perfect vacuums, frictionless planes, and so on was prominent in many of the theories upon which engineering models relied, this practice was not carried over into engineering applications where instead provisions for friction was expressly made-- a very good thing.
By contrast, the absence of friction in both theory and practice was common in economics, the assumption of zero transaction cost being an example. Even worse, the assumption of zero transaction cost was often invoked asymmetrically. Markets failed, but there was no corresponding literature on government failure. Instead, as Avinash Dixit has observed of the public finance literature, assumptions of omniscience, omnipotence, and benevolence precluded such failures. And Avinash, you've also heard from on this panel.
It's my belief that my engineering training provided grounding that made it easy for me as an applied micro economist to recognize that all feasible forms of organization are flawed in relation to a hypothetical idea. And accordingly, the expressed provision for frictions of positive transaction costs should frequently be made to better understand real-world organizations and institutional relationships.
Carnegie Mellon. transaction cost issues were not expressly featured when I was a PhD student at Carnegie, but interdisciplinary social science definitely was. Of special importance to me is that economics and organization theory both played important roles in the curriculum. And these two are frequently in tension.
An abiding curiosity about all things organizational pre-eminated the place. Jacques Dreze, a French economist, summarized his experience as a visitor as follows. Never since then have I experienced such intellectual excitement. Parts of this are captured by the Carnegie tripple, which is this. Be disciplined. Be interdisciplinary. Have an active mind.
I will spare you the details of the succession of events whereby my interest moved from applied microeconomics with an emphasis on industrial organization and applied welfare economics to a focus on transactions cost. But I will describe the crucial move which was this. Rather than examine nonstandard and unfamiliar modes of contract and organization entirely through the neoclassical lens of choice, I began also to bring the lens of contract to bear, especially with reference to the ex-post governance of contractual relations.
Specifically the allocation of economic activity as between firms and markets is not taken as given, but is to be derived where firms and markets are described as alternative modes of governance, or institutions, where governance is the means by which to infuse order thereby to mitigate conflict and realize mutual gains. That, in effect, is what I did when I reformulated the vertical integration problem in incomplete contract terms in my 1971 paper and soon thereafter began applying this approach to economic organization more generally.
Another editorial note-- Ollie does not mention it in his remarks, but in 1966 and 1967, he served as special economic assistant to the Assistant Attorney General for antitrust in the US Department of Justice. That position eventually became the deputy assistant attorney general for antitrust, or the chief economist of the antitrust division, a post held by several MIT PhDs-- Dennis Carlton is here and Carl Shapiro is now the chief economist of the antitrust division for, I think, a record second time.
From personal conversations, I know that Ollie was profoundly affected by this experience in Washington. In particular, he was troubled by the prevailing view of antitrust lawyers that vertical integration, long-term contracts, and other deviations from simple spot market transactions, as well as large hierarchical firms, were viewed as being inherently suspect on antitrust grounds. He was horrified by the incomprehensible antitrust cases and the absence of meaningful economic theory or empirical work relevant to issues of organization of firms, both internal organization and the boundaries between firms and markets.
He also could not understand why merger efficiencies played no role in merger analysis at that time. And for any of you who took an antitrust course in the 1960s, early 1970s, reading those cases, just so you sort of scratched your head wondering what they were talking about. And I think this had a big motivation on the directions Ollie took a little bit later in his career.
Returning to his remarks. As it turns out any issue that arises can be reformulated as a contracting problem and can be examined to advantage in transaction costs economic terms. Once reformulated, the action is in the details.
Now Ollie to a section to discuss, or at least to propose, that there may be commonalities between the kind of work he does in microeconomics and Ricardo's recent paper in the Journal of Economic Perspectives in macroeconomics. I cautiously advance the proposition that there are many commonalities between the core and periphery-- I'll come back to core and periphery at the end-- of macroeconomics to which he refers and the core resource allocation paradigm and periphery comparative contractual analysis in microeconomics where the periphery in both cases is concerned with microanalytical mechanisms that had long been ignored or pushed aside. But there are also differences, I suspect, for example, that the links between the core and the periphery and macro are closer than in microeconomics, where problems in the latter fall into one bucket or another, but that is merely a conjecture.
And then Ollie goes on to discuss various observations that Ricardo makes in his paper. And I'll just mention a few. First, mechanisms. The periphery macroeconomics focuses on, quote, "the details of sub problems and mechanisms," unquote. The corresponding focus in transaction cost economics is with the mechanisms of alternative modes of governance, with emphasis on mechanisms that are responsive to differing coordination needs as opposed by different transactions.
A second commonality. Frameworks in public policy. Macro, quote, "the inside building mode of the periphery of macroeconomics gave us frameworks to understand phenomena, such as speculative bubbles, leverage cycles, fire sales, flight to quality, and so on," unquote, that would thereafter be instructive for public policy purposes in restraining the recent crisis Ollie then turns to micro. Transaction cost economics gave us a framework to understand phenomena, such as vertical integration, vertical market restrictions, long-term contracts, regulation, deregulation, the use of debt and equity, exchange agreements, and so on that thereafter provided a basis for reshaping public policy towards business. And Ollie goes on to hypothesize a number of other similarities between Ricardo's observations about the periphery and core of macro and Ollie's observations about the periphery and core of transaction cost economics.
And here I'll conclude with a final note. Ollie's comments about the core and the periphery may give you the impression that Ollie's been on the extreme periphery of my microeconomics. This is not so. He did win a Nobel Prize, so he can't be too far on the periphery. But he's also perhaps the most cited living economist.
Markets and Hierarchies, his famous first book describing transaction cost considerations and how they affect the internal organization of firms and contractual relations between firms has over 14,000 Google Scholar citations. His paper "Transaction Cost Economics" in The Handbook on New Institutional Economics has 1,600 Google citations. And his "Markets and Hierarchies" paper in the American Economic Review in 1973 has 5,800 Google Scholar citations. Ollie's work has had an impact on all fields of social science. His research is widely recognized. And I would say that the core is moving closer to the periphery in many areas of social science as we study things like contractual arrangements, organizations, and the institutions of government and governance more generally. Thank you.
POTERBA: We thank all of the panelists for their remarks. Does anyone want to respond to anyone else on the panel at this stage? Or should we open for questions? OK, hearing nothing, we have a microphone set up here and here. If there are questions from the audience, we are now open for comments or reactions or questions for any of the panelists. OK, we have someone who's brave enough to come to the microphone here.
AUDIENCE: Hello. Sam Siddiqui, MIT class of '99 undergrad. Thanks a lot for the presentations. My question is based on what Professor Akerlof said about the challenge of economics being focused really on modeling and, let's say, extend it with a Professor Hasuman's comments that macroeconometrics don't work.
Let's say a grad student came to you. I'd like maybe just two or three sentences as a response saying, hey, I want to do a qualitative thesis for my PhD. What would you tell them?
POTERBA: George, I think you get to start.
POTERBA: You can speak there from your microphone.
AKERLOF: Yeah, OK.
POTERBA: You can stay. They can turn you on from there.
AKERLOF: OK. Good. OK. Turn me on. OK, I think that there's a lot of good work yet to be done in macro. That somehow-- I think actually listening to what Ollie was saying is very important, that the core to, I think, a good macro is having the organizations and how people behave in organizations to be properly represented. And I think that there's a bias in how we do macro which has left out a good share of the motivations for how people work in organizations and what they do, and that we get a very different macro once we've done that.
Furthermore, I mean, I had this example. The example was Keynes on speculative markets. If one just took a description of how speculative markets work, a realistic description, and embedded that in a macro system, I think we would have predicted, we would have known, and we should have known just how bad the bubble was. In fact, going back to an MIT graduate, Ken Rogoff has this wonderful book of This Time is Different. So MIT graduates were, in fact, thinking along those lines. And actually Charles Kindleberger, one of the greats of the MIT faculty, has this long book, which is the predecessor book to This Time is Different.
So I think that once you get away from having a very strong view as to exactly how economics should be done, and it should be doing done, one, two, three, you actually open up the field. And I think we would have predicted it if we'd had it. I think if we'd had-- I think furthermore, I think if we'd-- well, I'll just say I know that Paul Samuelson, for example, I know that he, in fact, was very worried about what was happening before, in fact, the breakdown and that he predicted it. I think probably there are other members of the economics faculty who were also similarly prescient.
But somehow, we didn't-- we might have been prescient, but the way that the journal system works, we didn't know how to put this into articles that would come out and give us an economics which systematically would tell us that we were going to have these problems.
AKERLOF: Well, I actually took economics first from Sir John Hicks. And I've heard many a story about Keynes. But in terms of predicting bubbles, I'll just give the following true story that Keynes was a well-known speculator. And he speculated in commodities. And at one point, he didn't predict a bubble. And he did so badly that he was going to have to store grain in the King's Chapel.
Now many of you have been to Cambridge. And he perhaps was shocked when the fellows told him that he wasn't going to be able to use the King's Chapel to store his grain. And so when you actually look at Keynes' record, he was not the world's best speculator.
And in terms of what was predicted and was wasn't predicted, there were a lot of people out there who are saying this is going to come to a bad end. So you can always find people who can say that. I think an interesting question-- I'm not necessarily disagreeing here-- but an interesting question is, in terms of policy-- policy is, as I understand it, a question of using models and good judgment. And I should point out that Ben Bernanke, who runs the world and saved the world, is my former teaching assistant. So, of course, he has an [LAUGHTER] MIT PhD as well.
But I think there are many interesting questions of how economics gets translated into policy which are very complicated. But, I mean, one thing is that I think that most economists-- again, I mean, you can find people who don't agree-- thought that we should have a stimulus program once recession hit. But, again, Christine Romer's, an MIT PhD, and Larry Summers was an MIT undergraduate, et cetera, et cetera.
But I think the stimulus program wasn't a Keynesian stimulus program. Not much money got out there. It was very badly done. And so the question is-- most economists said this is what we should be doing. Why did that happen?
Well, that's a question of politics, which I'm not an expert on. And I'll let political scientists do that. So I think that is a very interesting question, is you have people out there who can see things. There will be people disagreeing. But even when people agree, it somehow seems to be very difficult to translate into policy.
And so if one goes back and looks at the recent recession, a bad recession, and seen what's happened, apart from the Fed, who I actually-- and Mervyn King in England, both of whom I think have done a very good job-- I think the political response, both here with the Obama administration and Gordon King-- I mean, Gordon Brown-- in the UK, where there are zillions of Keynesian economists, was really quite poor. And I don't understand that. But that's for someone to write a book about, about why we can't translate good economic advice into good policy outcomes.
AKERLOF: [INAUDIBLE] I think that my major point here was not necessarily that we could have predicted the booms, but, in fact, that we would have had a prudential system which would have not allowed it in the first place. Why don't we go onto a-- I just wanted to clarify.
AUDIENCE: Kind of building on this discussion right now, as you come at economics from different perspectives, and I was wondering in the context we have here of the Fed printing a lot of money, debt layered throughout the society, the unemployment, and what people are being incentivized to do or not do, what observations or solutions do each of the panelists have that we haven't heard in the main press?
POTERBA: Before any of the panelists have to respond, I should just say that we do a whole session this afternoon which will focus on exactly these kinds of macro policy questions. We will have a set of panelists who also are more focused on that set of issues. So if the current panelists would choose to defer on some of those issues, they're welcome to. But I'll open the [LAUGHTER] opportunity. I would give the out if you'd like to take it.
AUDIENCE: There's a lot of micro stuff going on as well.
AKERLOF: OK, I can give one very short answer. And that is that there's a balanced budget multiplier. It's possible by raising taxes and by spending to increase the level of GDP having no effect on the level of the debt. And it seems that what's currently restricting US policy is that we don't want to run more debt. This is actually a result that Paul Samuelson especially liked, the balanced budget multiplier.
So that especially at the beginning of the recession where states and local governments had to do a lot of cutting, that was unnecessary. So I think that there actually-- if we look around, we can find creative policies which will help.
AUDIENCE: My name is Nicholas [INAUDIBLE] from Beirut, Lebanon. Dr. Hausman, I think that the examples that you gave are very interesting concerning the trade-off between the high upstream fee or the high consumption fee in the air conditioning business and in the cellular phone business. But there is one difference. In the former, in the AC business, the profits don't accrue to the same party. They accrue partly to the AC hardware manufacturer and then to the utility company. Whereas in the other one, you have other considerations with the competition, as you mentioned, and the roaming and so on.
Another outrageous business model is the razor and blade model, where the company, which has almost a monopoly, is almost minting money. So did you run a regression of that sort? And in the razor business, you cannot roam from one razor to the other. You have to use the same razor with the blades. Did you run the regression to find out about the discount rate in that business?
HAUSMAN: Well, my view is the cellular business, I mean, in most countries is not the razor and blade business because by and large you have three or four competitors. And the competition is usually pretty strong. But the one notion that is somewhat the same here is that-- at least in the US [INAUDIBLE] other countries I'm aware of-- you have to sign a two-year contract to get the subsidies. So in a senses-- I mean, the razor and blade model of Gillette is a monopolist or near monopolist. It's going to get the blades anyway. But in cellular, you have to use a phone on that system for two years. So that it works out. It's not really quite the same model because this is playing off discount rates. But the effect is, to some extent, similar because, as I said, you use it for two years.
And, in fact, when you do research, you find out that after two years, most people stay on the system for about another year. So on average, they're on between three and four, or maybe even as much as five years.
But the idea that-- I mean, now everybody has cellular. So the idea now is that you want them to get new phones. And the other empirical finding is very interesting. You can offer people a really good deal and say, well, we'll give you half-price cellular service if you don't get a new phone. Everybody wants a new phone. In Japan, it's crazy. Everybody wants a new phone every six months. But in the US, people have tried to offer deals, and everybody wants a new phone when their contract ends. And that's how the market works. So the market is giving consumers what they want.
It's sort of interesting in terms of the economics of this. Some government agencies-- the Netherlands, in particular-- think people get too many new cellular phones. So who's to decide? But it's sort of what Oliver Williams said, and what Avinash has said, it's never clear to me that the government knows what you want better than what you know what you want. [LAUGHTER] But that's an interesting thing to debate.
POTERBA: We'll take one more question.
AUDIENCE: Hi. Hello? Is it coming through?
AUDIENCE: My name's Laurel Grassin-Drake. I'm actually in the PhD program here at the Sloan School. And I wanted to just extend to what Professor Akerlof was saying earlier, the idea that the norms actually originate even earlier in the programs. I have my first area of work, my first career, was in finance and securities. And when I started looking into doing PhD, finance, economics was an obvious route for me. But the more I looked into it, exactly some of the concerns you're voicing were concerns that I had in seeing it. And I've chosen to do economics sociology instead within the Sloan School for those reasons.
But my point is that those norms actually start with the universities from the beginning in the students that are allowed to come into the program, that there is a heavy focus at this point now coming into economics on young people who can only do a high-level mathematics. And therefore, their focus and their desire is going to be to continue to do mathematics. And I just kind of throw out the idea of might it be worthwhile over time for economics to reconsider other viewpoints that aren't just mathematical, quantitative viewpoints. And that was just what I wanted to say.
AKERLOF: OK, so, actually, I think a lot of what I was talking about is actually based upon a very nice book by Marion Fourcade in sociology who did a study of the American, the British, and the French systems of economics. And interestingly, they have different economic systems. And then they get different economics that comes out of it. And she thinks that this is a significant reason why, for example, France has a very different economic system, for example, from the United States.
DIXIT: I think your question and one earlier that came up poses qualitative and quantitative mathematical work as if they're alternatives. And I think that's the wrong way of looking at it. Both are necessary. They should be complimentary [INAUDIBLE]. Lot of quantitative modeling or econometric work should take its inspiration from facts that have been generally observed, questions that have generally been posed.
But, on the other hand, I think the quantitative work of modeling, estimation, et cetera remains important. There's a wonderful paper by Paul Krugman who develops the idea of the progress of thought in economics and many other subjects as an analogy to Europe's discovery of Africa, how at one time just kind of vague things, half of which were total rumors about people whose heads do grow beneath their shoulders and so on, were around. Then people discovered the boundaries of Africa, and all knowledge of the interior was completely lost until finally exploration brought all that to light and completed Europe's knowledge of Africa.
All stages are important. And the fact that the quantitative exploration of the coast line and near interior lost some of the kind of half-knowledge of the interior, it's just a phase that has to be gone through. You still need to keep a proper exploration, which in all sciences works through quantitative modeling, fitting to data, those kinds of things. You mustn't dismiss that, either.
POTERBA: Let me just--
HAUSMAN: I was going to make one quick--
POTERBA: Yeah, go ahead.
HAUSMAN: So I think one thing that economists and people in business schools know very well is the importance of differentiated products. So if you walk into a modern supermarket, I think there are about five times as many products as there were 20 years ago. You have improved logistics and improved computer systems and all. So the benefits to firms from differentiated products have been well studied and I think are well understood.
So I think an interesting question here is-- I mean, I agree with both George and Avinash that you want both types-- but there's nothing stopping economic programs from differentiating themselves. So you had the New School for years. And now you could say that there is an institutional bias. And we could have a discussion about that. But it is interesting that, especially with the fall of the Berlin Wall, a lot of the places like the New School and all that did qualitative-- I don't want to use Marxian in a bad sense because it's actually sort of interesting to study-- those have really faded from view. And so the question is why isn't there more demand out there for this differentiated product?
And I think that's a very complicated question. But my point is that I don't think there's any institutional things from stopping it. If some university wants to have a sociology-based economics department, or part of it, they can. I mean, places like the University of Sydney still has that after all these years. So I just don't think it's succeeded in the market test.
Now I'm sure a lot of people would say, well, the market's never given it a, quote, "fair test," whatever that means. But it is interesting that since I've been an economist for the last 40 years, that style of research has actually decreased quite markedly rather than increased for whatever reason.
JOSKOW: Could I just add something? I mean, Oliver Williamson, if you read his papers, I don't think there's one equation in any of his papers or books. There are no numbers. But he's widely cited in economics. He's stimulated a lot of research on contracts and organizations, both theoretical and empirical.
So I think Jerry's right. If you actually come up with something that catches people's attention, there is a market test. And I agree, it's unfortunate that it takes so long in economics to get papers published. And the refereeing process is sometimes obscure. Ollie has papers published in the best journals. And he got them accepted because the ideas were new and interesting and challenging. So I don't think there's a tremendous barrier.
Now that's not to say that-- Ollie was an engineering student here. If you read his thesis, he actually did real theoretical modeling at Carnegie and simulations. So he had those tools. But he was attracted by interesting problems that others had not really been able to crack.
And I think that's really the task. Can you find a problem that has really been difficult to crack? And if it has been, and you can find some insights into it, whether it's theoretical or it's qualitative or it's empirical or a combination of all three, I think there's a real market for that.
POTERBA: Let me just add a closing comment on this broad issue. Because I think without feeling that there needs to be a tension between a technical, mathematical approach to economic issues and one which might be more narrative or draw from other disciplines and less technical things, as a historical matter, one of the incredibly important contributions of the MIT economics department in the last 150, and particularly the last 75 years, has been its playing a critical role in advancing the development of analytical and more mathematical economics.
Paul Samuelson came to MIT in 1940. The publication of Paul's thesis-- that's "Foundations of Economic Analysis"-- was a transformative event in terms of bringing the mathematical tools of optimization and analysis to a whole range of economic problems and adding structure and adding formalism which made it possible to sweep away, as Avinash was alluding to, lots of misconceptions about how many problems worked or what key economic findings were, and introducing a whole new possibility for what economics could do. And then in the immediate post-war period, a group of MIT faculty-- and I think we should actually acknowledge people like Morris Adelman, Bob Bishop, Cary Brown, Charlie Kindleberger, Bob Solow, Harold Freeman, others who basically sort of embraced this approach to trying to do technical analysis and pushing it out in a variety of different ways.
Paul Samuelson used to say that MIT was the natural place for that kind of economics to flourish. Because given that it was a place with a tremendous commitment to technical and rigorous analysis, that if you were asking where might a group of economists find a comfortable home to pursue this kind of an intellectual mission, that MIT was exactly the right sort of a place. And I think that's very important to call attention to and thinking about the history of the Institute and the role it's played in economic analysis.
If one looks back at the history of that period and just asks, what were some of the key contributions that emerged? It's an incredibly long list. And many of the people who worked on these questions and extended these questions are here with us today. But the theory of public goods, the notion of the full employment deficit, the balanced budget surplus, overlapping generations models that you've heard about today, growth theory, optimal tax theory, the option pricing model, Bob Merton's work on an optimal [INAUDIBLE] temporal consumption, specification testing, overshooting in models of exchange rates, the differences in differences approach to thinking about econometric work, aggregate demand/aggregate supply analysis, Dornbusch and Fischer in terms of their work in macro, empirical development economics, the current revival in political economy-- these are all things that have emerged from the melting pot of analytical tools, mathematical methods, mixed with a healthy interest in the real-world questions that were important to address and that were well-grounded in practical real-world problems. And that has been the recipe, in some sense, which has made MIT economics such an incredibly influential place, as a place for research, as a place for training students, and then, as our title for the symposium suggests, as a way of building out and having an enormous influence on the world of economic policy.
President Hockfield has an illustration of the role in the policy world which we'll hear more about this afternoon. President Hockfield sent me an e-mail several years ago when Jose de Gregorio, one of our PhD graduates, was named the new head of the Central Bank of Chile. There are actually five sitting Central Bank presidents in the world who have MIT PhDs, which speaks as a clear record for any department. She sent a message saying I see that MIT has captured a new central bank with an MIT PhD in Chile. And I had to send back a message and say no, I'm afraid he replaced the old MIT PhD. [LAUGHTER]
The good news is, as Susan's interest in questions about central bankers and economics suggests, is that not only is the research and educational environment in economics here at MIT incredibly healthy today, as I look out at this audience I hope that there are some who are here as students, as faculty who will be back when MIT celebrates its 200th anniversary to help tell the story of MIT economics in the next 50 years. But it is a commentary on the central role of economics just in the world today, but also on our campus that Susan Hockfield sends us her greetings. She unfortunately can't be with us today to participate in this symposium. She is in Davos, Switzerland, at the World Economic Forum.
So thank you all. On that note, we will adjourn for this moment. We will take a 15-minute break and come back for a second session.