2018经济学诺奖得主Paul Romer 芝大物理和数学本科，MIT读两年Econ PHD，萍遇来MIT访学的Queens美女, 为追美转学到Queens。
结果美女转到芝大，Paul 一路追到芝大拿PHD
Interesting story 
http://docentes.fe.unl.pt/~amateus/eco_desenvolvimento/Romer%20interview.htm
Background information
Where and when did you first begin to study economics?
I was a math and physics major at the University of Chicago. I took my first economics course in my senior year because I was planning to go to law school. I did well in the class and the professor encouraged me to go on to graduate school to study economics. Economics offered some of the same intellectual appeal as physics – it uses simple mathematical models to understand how the world works – and in contrast to physics, it was an area of academic study where I could actually get a job.
In some ways staying at the University of Chicago was attractive because it had a very exciting economics department but I had already been there for four years. Even though I had had very little Chicago economics training I did not think it was a good idea to spend my whole career as a student in one place, so I started in the Ph.D. program at MIT. There I met my wife who was just visiting for a year from Queens University in Canada. After two years at MIT we went back to Queens to finish her final year of training in medicine. That was when I started working on growth. At the end of that year I transferred to Chicago, where my wife had a fellowship position, and completed my PhD. I finished my PhD and entered the job market in 1982 — my thesis is actually dated 1983 because it took me a year to polish it up.
As a student did you find any of your teachers to be particularly influential or inspirational?
Well, Sam Peltzman was the professor who encouraged me to switch my career path from law to economics. I shudder to think what my life would have been like if he hadn’t asked to talk with me after the midterm and I had gone on to law school. It is an episode that I try to keep in mind – that professors can be very influential, and a little bit of attention to your students as people can make a big difference in their lives.
Besides having saved me from a life in the law, Sam was also an excellent teacher. He was the first person to show me that you could take very simple tools – demand curves or indifference curves – and derive surprising insights about how the world works. Having mentioned Sam, I should also mention some other very good teachers that I had. Donald McCloskey, now Dierdre McCloskey, was the second person I had for economics. Donald, like Sam, took economics very seriously. Together, they gave me an excellent introduction to the subject. I should also mention that at Chicago, they did not offer what is known as a "principles" course, the watered-down, mind-numbing survey course that most universities offer as a first course in economics. At Chicago, they started right off at the intermediate microeconomics level. So I had the enormous advantage of starting off with challenging, intellectually coherent material and first-rate teachers. I was very fortunate.
Later in graduate school, when I was back at Chicago, Bob Lucas and Jose Sheinkman had a big influence on my style and the way I look at the world. They set a standard for rigor and discipline – zero tolerance for intellectual sloppiness – that I have aspired to ever since. But probably the best year of graduate school was the year I spent at Queens University because I had a lot of interaction with the faculty there. Normally as a graduate student you do not really get that much time to sit and talk with members of the faculty as colleagues. At Queens I had more of that kind of experience. Some of the people I talked with intensively during that year – Russell Davidson and James McKinnon – are terrific economists and had a big effect on my career.
Development of macroeconomics
Are there any particular papers or books that you would identify as having a major influence on the development of macroeconomics?
For me that’s too broad a question. I could list all the usual suspects, people like Keynes, etc. I’d be more comfortable describing the contributions that have influenced my own work.
Tell us about the influences on your own research interests.
Bob Lucas brought a style to macroeconomics that had a big impact on a whole generation of people, including me. There are several papers that exemplify this style. One is his 1972 Journal of Economic Theory paper on ‘Expectations and the Neutrality of Money.’ Another would be his 1978 Econometrica paper ‘Asset Prices in an Exchange Economy’? But his 1971 Econometrica paper, ‘Investment Under Uncertainty,’ written with Edward Prescott, is probably the best example because it really brought to the forefront and crystallised for macroeconomists the connection between what we did in macroeconomics and what the rest of the profession had been doing in general equilibrium theory. In that paper Lucas and Prescott used the connection between solving optimisation problems and equilibria that has become such a powerful tool in modern macroeconomics. That 1971 paper builds on the work of people like Cass (1965) and Koopmans (1965) who had been working in growth theory, and this basic approach for characterising dynamic equilibria can be traced all the way back to Frank Ramsey’s (1928) paper. Still, Lucas and Prescott took this approach much further into the core of macroeconomics. If all you have seen is the theory of investment as developed by the macro modellers and presented by the macro textbook writers, this paper is like a flash of lighting in the night that suddenly shows you where you are in a much bigger landscape.
You mentioned the influence of Bob Lucas’s work. What do you think has been the lasting impact of his work, particularly the work he carried out in the 1970s for which he was awarded the Nobel Prize?
I think the deeper impact of Lucas’s contributions has been on the methodology of the profession. He took general equilibrium theory and operationalised it so that macroeconomists could calculate and characterise the behaviour of the whole economy. Just as Peltzman and McCloskey took intermediate microeconomics seriously, Lucas took general equilibrium theory seriously. Many of the people doing general equilibrium theory for a living did not really seem to believe in what they were doing. They gave the impression that it was a kind of mathematical game. Economists working in trade and growth had shown us how we could use general equilibrium models, but they were not ready to bring dynamics and uncertainty into the analysis. It was economists working first in finance, then in macroeconomics, who took the theory seriously and showed economists that fully specified dynamic models with uncertainty had real implications about the world. A very important result of that methodological shift was a much greater focus on, and a much deeper understanding of the role of expectations. But this is only part of the deeper methodological innovation. You still wouldn’t know it from reading textbooks, but to research professionals, it finally is clear that you can’t think about the aggregate economy using a big supply curve and a big demand curve.
One of the ironies in this revolution in thinking is that the two people who did the most to bring it about, Lucas and Robert Solow ended up at swords’ points about the substantive conclusions that this methodology had for macroeconomic policy. Solow’s work has also had a huge impact on the profession, pushing us in the same direction. His work on growth also persuaded economists to take simple general equilibrium models seriously. Many people recognise the differences between Lucas and Solow over macro policy questions, but fail to appreciate the strong complementarity between their work at the methodological level. If Joan Robinson had won the day and banished the concept of a production function from professional discourse, Lucas and Prescott could never have written ‘Investment Under Uncertainty.’
During the 1980s, the real business cycle approach to aggregate fluctuations developed in parallel with new growth theory. How do you view that work, in particular the way it has sought to integrate the analysis of fluctuations and growth?
A lot of the progress in economics still comes from building new tools that help us understand very complicated systems. As a formal or mathematical science, economics is still very young. You might say it is still in early adolescence. Remember, at the same time that Einstein was working out the theory of General Relatively in physics, economists were still talking to each other using ambiguous words and crude diagrams.
To see where real business cycle theory fits in, you have to look not just at its substance and conclusions but also at how it affected the methodological trajectory I was talking about before. You can think of a hierarchy of general equilibrium models – that is models of the whole economy. At the top you have models of perfect competition, which are Pareto optimal so that you can solve a maximisation problem and immediately calculate the behaviour of the economy. Then, at the next level down, you have a variety of models with some kind of imperfection -- external effects, taxes, nominal money, or some kind of non-convexity. In many cases you can find a way to use some of the same maximisation tools to study those dynamic models even though their equilibria are not Pareto optimal. This is what Lucas did in his 1972 paper ‘Expectations and the Neutrality of Money’. Formally it is like an external effect in that model. It is also what I did in my first paper on growth.
The real business cycle guys went one step further than Lucas or I did in trying to simplify the analysis of aggregate economies. They said, "We can go all the way with pure perfect competition and pure Pareto optimality. We can even model business cycles this way. Doing so simplifies the analysis tremendously and we can learn a lot when we do it." My personal view – and increasingly the view of many of the people like Bob King who worked in this area -- is that at a substantive level real business cycle theory simplifies too much. It excludes too many elements that you need to understand business cycles. This doesn’t mean that the initial work was bad. It just means that we are now ready to go on to the next stage and bring back in things like predetermined nominal prices. Methodologically this work helped us refine our tools so we’ll do a better job of understanding predetermined prices when we bring them back into the model.
We frequently make progress in economics by seeming to take a step backwards. We assume away real problems that people have been working on in vague and confused ways, strip things down to their bare essentials, and get a better handle on the essentials using some new tools. Then we bring the complications back in. This is what Solow was doing, and what drove Robinson to distraction, when he modelled the production structure of an economy using an aggregate production function. Later we brought back many of those complications – irreversible investment, limited ex post substitution possibilities, and so on – back into the model. The real business cycle theorists did the same kind of thing, and during the simplification phase, they also made people mad.
Economic growth
In Lucas’s (1988) paper ‘On the Mechanics of Economic Development’ he comments that once you start to think about growth it is hard to think about anything else. In the introduction of their textbook Economic Growth (1995) Robert Barro and Xavier Sala- i- Martin argue that economic growth is the part of macroeconomics that really matters. In the light of these comments by very influential macroeconomists do you think that, on reflection, economists have in the past spent too much time trying to understand business cycles?
That is almost right. Remember that we experienced major macroeconomic calamities in the inter-war period. These depressions were sufficient to wipe out 30 to 40 years’ worth of growth. Economists who grew up during this era certainly didn’t have any trouble thinking about something else besides long-run growth. They naturally focused on avoiding those calamities.
So I don’t think that you can make the statement that focusing on growth is more important in some absolute sense than focusing on stabilisation. What I think is correct is that we now know how to avoid the kind of catastrophic events that we saw in the UK in the 1920s and in the US in the 1930s. Those were both major mistakes in monetary policy and we now know how to avoid them. We also know how to avoid the disruptive hyperinflations of the interwar era. Recently, we have even developed better monetary rules for avoiding the less disruptive but still costly inflation of the 1970s. Once you have learnt to avoid those kinds of problems, growth stands out as the most important remaining issue on the agenda.
I do believe that there was a period in the 1960s and 1970s, when macroeconomists were spending too much time looking at business cycles – the smaller cycles and fluctuations which characterised the post-war period – and too little time on growth. We should have kept working on stabilisation policy, but we should also have worked on the determinants of long-run growth. Adjusting the balance is what my career has been all about.
When I teach students I try very hard to get them to get this balance right. I give them an analogy about a runner who is trying to train for a marathon. Asking whether growth is more important than stabilisation is like asking whether conditioning is more important than putting on a tourniquet when the runner starts bleeding. In a sense the training and the technique of running really are what wins races. But if the runner is bleeding to death, it is pretty silly to lecture her about getting in better shape.
But now, when we look at the allocation of the profession’s intellectual resources today, we are in a situation where we can learn more about how to make minor adjustments in the amplitude of cycles or in the trend rate of growth. Faced with that trade-off, it is very clear that small improvements in the trend rate of growth can have far greater effects on the quality of life and this area has been understudied.
Looking back, one of the reasons why economists avoided questions about growth was that our tools were not sufficiently well developed. Purely technical or mathematical issues about the existence of a solution to an infinite horizon maximisation problem, transversality conditions, knife-edge behaviour and explosive growth deterred economists from asking the right kind of substantive questions about long-run growth. Now that our tools are better, we have been able to set those issues aside and make progress on the substantive questions.
The classical economists were very concerned with long-run issues such as growth. Did you find any inspiration for your work by going back and looking at the contributions of the classical economists and other early work on growth?
I did spend some time thinking about that, reading Adam Smith and Alfred Marshall. For example, I read the 1928 paper by Allyn Young, which builds on Marshall’s work. I think it is in the same issue of the Economic Journalas Ramsey’s paper. So there was a period where I spent a couple of years trying to sort out the connections between what Young and Smith were saying and what I was trying to say. I did that for a while and enjoyed it, then I stopped doing it. I am not sure I would recommend it as a research strategy for a young person but it can be interesting and instructive.
When I started working on growth I had read almost none of the previous literature. I started very much from a clean sheet of paper and only later went back to try and figure out what other people had said. I think that in a lot of cases that is the right way to do it. If you devote too much attention to ancestor worship, you can get trapped and lose the chance to see things from a new perspective. Of course, in economics, your ancestors are still around, occupying positions of power in the profession, and they are not always happy when someone comes along and tries to take a fresh look at things.
During the whole period from the marginalist revolution in the 1870s through to the mid 1950s economists were mainly concerned with microeconomic developments and managing the birth of macroeconomics during the Great Depression. Then the issue of economic growth came back onto the scene during the 1950s. One of the puzzles is that during the period when growth theory made great advances, with the contributions of Solow in 1956 and 1957, the field of development economics seemed to evolve as an almost separate area of interest. Why did that dichotomy happen?
I am probably going to sound like a broken record here, repeating my message over and over, but the divide was methodological. The growth guys talked math; the development guys still talked words. They diverged further and further apart because they could not understand each other. It was less the differences in the substantive questions they were asking, than the tools they were selecting to try and address them.
Wasn’t it more the case that development economists actually wanted and needed to say something about policy issues?
There was an element of that. As I said about the real business cycle theorists, sometimes you have to take a step back and simplify to make progress developing new formal tools. This is hard to do when you are in the thick of the process of trying to offer policy advice.
If you go back and read Smith, Marshall or Young, you have to be struck by what an incredibly wrenching transformation the economics profession has gone through, from operating as a purely verbal science to becoming a purely mathematical one. Remember that Allyn Young's paper came out at the same time, even in the same issue, as Frank Ramsey’s. Ramsey was using tools like the calculus of variations that physicists had been using for decades. But economists were still having trouble with basic calculus. Jacob Viner needed help from his draftsman to get the connection right between long-run and short-run average cost curves. Nowadays economists use math that is as sophisticated and as formal as the math that physicists use. So we went through a very sharp transition in a relatively short period of time. As we learned how to use mathematics we made some trade-offs. You could think of a kind of production possibility frontier, where one axis is tools and the other axis is results. When you shift effort towards the direction of building tools you are going to produce less in the way of results. So the development guys would look at Solow and say, ‘What you are producing has no useful content for policymakers in the development world, you guys are just off in mathematical space wasting time while we are out here in the real world making a difference.’ The tool builders should have responded by explaining the intertemporal trade-off between results and tool building and that as a result of this work we can give better policy advice in the future. Overall the right stance for the profession as a whole is one where we approve of the division of labour, where the people who specialise in those different activities can each contribute and where we do not try and force the whole profession into one branch or the other. Ideally we should keep the lines of communication open between the two branches.
Let us turn to Robert Solow’s contributions. What do you see as being the main strengths and weaknesses of the Solow growth model? Some economists like Greg Mankiw (1995) would prefer to modify the Solow model rather than follow the endogenous growth path.
When it was introduced, the Solow model made several very important contributions to economics and progress in this tool building direction. It was a very important demonstration of how you could take general equilibrium theory and apply it and say things about the real world. As I suggested before, Solow helped persuade us that there are ways to think about the equilibrium for the whole economy, using simple functional forms and simplifying assumptions, and get some important conclusions out of that. It is a very different style of general equilibrium theory from that of Arrow and Debreu and their more abstract work that was going on at the same time. Remember that Solow and Samuelson had to engage in vicious trench warfare about this time with Cambridge, England, to make the world safe for those of us who wanted to use the concept of a production function.
At the substantive level -- which I think is where your question was directed -- the strength of Solow’s model was that he brought technology explicitly into the analysis in both his empirical paper and his theoretical paper. He had an explicit representation for technology, capital and labour. Those are the three elements that you have to think about if you want to think about growth. That was the good part. The downside was that because of the constraints imposed on him by the existing toolkit, the only way for him to talk about technology was to make it a public good. That is the real weakness of the Solow model. What endogenous growth theory is all about is that it took technology and reclassified it, not as a public good, but as a good which is subject to private control. It has at least some degree of appropriability or excludability associated with it, so that incentives matter for its production and use. But endogenous growth theory also retains the notion of nonrivalry that Solow captured. As he suggested, technology is a very different kind of good from capital and labour because it can be used over and over again, at zero marginal cost. The Solow theory was a very important first step. The natural next step beyond was to break down the public good characterisation of technology into this richer characterisation – a partially excludable nonrival good. To do that you have to move away from perfect competition and that is what the recent round of growth theory has done. We needed all of the tools that were developed between the late 1950s and the 1980s to make that step.
Let me place the other strand of growth in context, the so-called AK versions of endogenous growth. In these models, technology is just like any other good -- we might put another label on it and call it human capital or we can call it generalised capital -- but technology is treated as being completely analogous with physical capital. I think that approach actually represented a substantive step backwards compared to the Solow model. The AK models are actually less sophisticated than the Solow model because those models do not recognise that technology is a very different kind of input. As I suggested above, I also disagree with the real business cycle methodology that says "Let us do everything with perfect competition." Before, you could argue that there was no alternative, but that’s no longer true. We have perfectly serviceable dynamic general equilibrium models with monopolistic competition and there is no reason not to use them if they capture important features of the world.
There is still a group that says "Let’s just treat technology as pure private good and preserve perfect competition." Then there is another group of economists who, like Mankiw, say that technology is different, but we can treat it as a pure public good just as Solow did. I think that both of these positions are mistaken. There are incredibly important policy issues where the pure private good characterisation and the pure public good characterisation of technology are just completely off the mark.
Wasn’t your earlier work, as exemplified in your 1986 paper, more concerned with increasing returns than the determinants of technology change?
You have to look between the lines of that paper at what was going on at the methodological level, because remember, methodological and formal issues had been holding everything up. The logical sequence in my 1986 paper was to say that as soon as you think about growth, you have to think about technology. As soon as you think about technology, you have to confront the fact that there is a built-in form of increasing returns – technically, a nonconvexity. Notice that is all there in Solow’s model. If you look at AF (K, L) you have got increasing returns in all the relevant inputs A, K and L. So up to this point, Solow and I are on the same track. You have to think of technology as a key input and one that is fundamentally different from traditional inputs. As soon as you think about that, you face increasing returns or nonconvexities. Then you have to decide how to model this from a methodological point of view. Solow said treat it as a public good. There are two variants of that. One is that it comes from the sky and is just a function of time. The other is that the government could publicly provide it. I think Solow had both of those in mind and it does not really matter which you specify. What I wanted was a way to have something where there are some increasing returns but also some private provision. I wanted to capture the fact that private individuals and firms made intentional investments in the production of new technologies. So in this sense, the paper was very much about technological change. To allow for private provision, I used the concept of Marshallian external increasing returns. This lets you describe an equilibrium with price-taking but still allows you to have nonconvexities present in the model. That was a first provisional step. It was a way to capture the facts: there is some private control over technology, there are incentives that matter, and there are increasing returns in the background. What happened between 1986 and 1990 was that I worked hard at the mathematics of this and persuaded myself that the external increasing returns characterisation was not right either -- just as the public goods assumption of Solow was not right.
Whenever you write down theories you make approximations, you take short cuts. You are always trading off the gains from simplicity against the losses in our ability to describe the world. The public good approximation was a reasonable first step, but we needed to keep working and improve on it. The external increasing returns approximation was something of an improvement but the later monopolistic competition version (Romer, 1990) was the one which really gets about the right trade-off between simplicity and relevance.
Since Solow’s (1957) paper there has been a huge literature on growth accounting. What do you think have been the main substantive findings from this research?
The general progression in that area has been to attribute a smaller fraction of observed growth to the residual and a higher fraction to the accumulation of inputs. The way that literature started out was a statement that technology is extremely important because it explains the bulk of growth. Where we are now is that technology does not explain, all by itself, the majority of growth. Initially, we overstated its importance when we claimed that technological change explained 70 per cent of growth all by itself. But there are some people who would like to push this further and say there is really no need to understand technology, because it is such a small part of the contribution to growth. They argue that we can just ignore it. That is a non sequitur. It does not follow logically. We know from Solow, and this observation has withstood the test of time, that even if investment in capital contributes directly to growth, it is technology that causes the investment in the capital and indirectly causes all the growth. Without technological change, growth would come to a stop.
When we spoke to Bob Solow yesterday he explained why he made technology exogenous in his model. It was simply due to his lack of understanding of the causes of technological change.
That is a reasonable provisional strategy when you are dealing with a complicated world.
A great deal of attention during the past decade or so has been focused on the so-called convergence issue. At the same time your first important endogenous growth paper was published in 1986, Moses Abramovitz and William Baumol also had papers published that drew attention to this catch-up and convergence debate. This controversy continues to draw research interest, for example, in a recent issue of the Journal of Economic Perspectives Lant Pritchett (Summer, 1997) has a paper entitled ‘Divergence Big Time’. When we talked to Edward Prescott two days ago he was reasonably confident that convergence would eventually occur. Did this important debate influence your own thinking about growth and what are your views on this area of research?
It is very important to keep clear what the facts are. The facts are that over the time horizon that people have looked at the data, say from 1950 to the present, there is very little evidence of overall convergence. Everybody agrees about this, even if it is not always stated up front. People who describe this tendency for countries to converge are saying that if everything else were the same -- if you hold all the right variables constant -- then there would be a tendency for countries to converge. For example, this is one of the key results in Robert Barro’s work. This is really just a refined statement of the convergence club interpretation articulated by Baumol. If you look at countries that have the same values for these variables, then they tend to converge. But it is also true that in the background, the overall progress towards reduced dispersion in per capita incomes has been very modest. Pritchett was making a useful background point. If you go back before 1950, it must be the case that there was a period where incomes diverged quite a bit -- some countries moved very rapidly ahead as others were left behind. At that time, the overall distribution of income widened for a period of time. More recently, in the post-war years, the overall distribution has been roughly constant.
So why do we care about this issue? First you might care about it from a human welfare point of view, or an income distribution point of view. On those grounds there is some reason for pessimism — we really have not made that much progress in the last thirty or forty years. You might also care about it because you think it might help you discriminate between different theories of growth -- which ones are right and which are wrong. Many people have asserted that this process of conditional convergence -- everything else equal, incomes converge -- is consistent with a pure Solow style model, i.e., one where knowledge is a public good, all technology is a public good. So they say the evidence is consistent with the public good model of technology. That statement is correct but the evidence is also completely consistent with a model where technology is not a public good. In this interpretation, the technology gap model, flows of technology between countries is what drives the convergence process. In this explanation, the convergence you see is catching up with technology, not just catching up in the stock of capital per worker. Under the Solow model as interpreted by Mankiw and others, technology is already the same everywhere in the world. It is a public good that is in the air like a short-wave radio broadcast, so under this model there is no room for technological catch-up. It still mystifies me that people try to justify this model in the face of direct evidence about the importance of technology flows. But they certainly use the conditional convergence evidence to back up their position.
So I do not think that the convergence controversy has helped us discriminate between the different models. As a result, I think a great deal of the attention that the convergence controversy has generated has been misplaced. Prescott’s assertion is that he does not think that we are going to see continued divergence. I think he is probably right about that. I personally think that these flows of technology between countries are very important forces in the big convergence episodes that we have seen. If you look at a country like Japan and ask what lies behind its very rapid convergence with the leading nations of the world, then the transfer of technology was a critical part of the process. There are grounds for optimism, looking ahead. If we can get the right institutions in place in these developing countries, the same process of flows of technologies could be unleashed and we really could see some narrowing of world-wide income inequality. If you weight it by countries the situation looks worse than if you weight it by people, at least during the last ten years. This is because the process of catching up in China will make a huge difference to the overall picture. And China is a good illustration of what is wrong with the public good model. China had a high savings rate before the reform era. What’s most different now in the sectors of manufacturing where China has been so successful, has been the flow of technology into China via direct foreign investment. Reforms that changed the incentives that for foreign firms faced to bring technology and put it to work in China.
Did you ever look at the work of economists such as Gunnar Myrdal (1957) and Nicholas Kaldor (1970) who tended to reject the equilibrating properties of the neo- classical model in favour of the forces of cumulative causation? In their models a lack of convergence is no surprise.
It interested me in the same way that Allyn Young interested me. I wanted to see how much there was in common between what I and what they were thinking. But it is very hard to tell, quite frankly, when you go back and read economics that is stated in purely verbal terms. There is always the danger that you read between the lines and say, oh, they had it exactly right -- here is this mathematical model which shows what they were thinking. But that is usually based on a charitable reading and one that ignores some of the ambiguities and confusions. I wrote a paper like that at one point interpreting Allyn Young’s paper, so one could probably do that for some of the other economists in this area. For example the big push paper by Murphy, Shleifer and Vishny (1989) did this for some of this literature. So the right conclusion to make is that these were very smart people and they did have some good ideas, but they were working with very crude tools. I guess I would describe ancestor worship as a research strategy as probably an unproductive one (laughter). But as a consumption activity it is something that can be fun.
Well we want to keep you on the topic of ancestors for a moment. Given that your research has concentrated heavily on the influence and determinants of technological change and the importance of R and D, has the work of Joseph Schumpeter ever influenced your ideas?
No, I can honestly say that it has not. Schumpeter coined some wonderful phrases like "creative destruction" but I did not read any of Schumpeter’s work when I was creating my model. As I said, I really worked that model out from a clean sheet of paper. To be honest, the times when I have gone to try and read Schumpeter I have found it tough going. It is really hard to tell what guys like Schumpeter are talking about (laughter).
Too many words and no enough math?
Yes, and words are often ambiguous.
That problem has also been the source of confusion and the various conflicting interpretations of Keynes’s General Theory.
Yes, right. Paul Krugman (199?) has a nice article talking about the big push idea in development economics. When you state it now in mathematical terms, the way Murphy, Shleifer and Vishny did, you see how clearly the idea can be expressed and you wonder why someone had not done it before. I think that what it shows is that economists now are the beneficiaries of a lot of development of mathematical modes of thinking and analysis and it seems very easy to us now because we have those tools to work with. Before these techniques were available it was really very tough.
Let us go back to the issue of nonrivalry and excludability with reference to the growth of knowledge and technological change. How do you get the balance right between encouraging technological change by using incentives and yet making the new ideas and discoveries available to the rest of society? There is a trade-off problem here with respect to patent rights.
Sure. What’s interesting about this question is that it is not resolved. If you take traditional private goods that are excludable and rival, we know what the best institutional arrangement is: strong property rights and anonymous markets. That’s all you need. This is a remarkably important insight that economists must still communicate to the rest of the world. If people understood it, there would not be so much resistance to pricing roads, pollution or water in agriculture. Non-economists are still slow to understand how powerful the price mechanism is for allocating and producing rival goods.
But when you come to nonrival goods, we do not know what the right institutions are. It is an area that I think is very exciting because there is a lot of room for institutional innovation. One strategy is to work out a rough trade-off where you allow patent rights but you make them be narrow and have a finite duration. You would allow partial excludability -- less than full but stronger than zero excludability. We often talk as if that is the general solution. But in fact, this is not the general solution. You have to break the question down by type of nonrival good. There are some nonrival goods like the quadratic formula or pure mathematical algorithms that traditionally have been given no property rights whatsoever. There are other forms of nonrival goods like books. You will get a copy right for this book of interviews, which is a very strong form of protection. The text that you write and my words – you can take them and put a copyright on them so that nobody else can re-use them. I can not even re-use my own words without getting permission from you (laughter). So that is a very strong form of intellectual property protection. What we need is a much more careful differentiation of different types of nonrival goods and an analysis of why different institutional structures and degrees of property protection are appropriate for different kinds of goods.
Patent rights or legal property rights are only a part of the story. We create other mechanisms, like subsidies for R and D. We create whole institutions like universities which are generally nonprofit and government supported, that are designed to try and encourage the production of ideas. The analysis of institutions for nonrival goods is more subtle than many people realise.
For example, I have argued that it is very important to distinguish human capital from ideas -- they are very different types of economic goods. Human capital is just like capital or land. It is an ordinary private good. I agree with Gary Becker on this. I think a lot of claims about human capital externalities are wrong. Nevertheless, when people conclude that we should not have any government subsidies for the production of human capital, I disagree. Why is that? It is because human capital is the crucial input into producing ideas. If you want to encourage the production of ideas, one way is to subsidise the ideas themselves. But another way is to subsidise the inputs that go into the production of ideas. In a typical form of second-best analysis, you may want to introduce an additional distortion – subsidies for scientists and engineers – to offset another – the fact that the social returns from new ideas are higher than the private returns. You create a much larger pool of scientists and engineers. This lowers the price of scientists and engineers to anybody who wants to hire their services to produce new ideas.
So in general, the optimal design of institutions is an unresolved problem. We have seen a lot of experimentation during the last 100 years. I have made the claim that the economies that will really do well in the next 100 years will be the ones that come up with the best institutions for simultaneously achieving the production of new ideas and their widespread use. I am quite confident that we will see new societal or institutional mechanisms that will get put in place for encouraging new ideas.
Research into economic growth has extended into a large number of other interesting areas in recent years. For example Alberto Alesina and Dani Rodik (1994) have explored the relationship between inequality and growth, Robert Barro (1996) Alesina and others (1996) have explored the relationships between democracy, political stability and growth. How do you view this work? Can we help poor countries more by exporting our economic systems than our political systems as Barro has suggested?
Let me back up a little here. One of the disciplines that formal economic theory forces on you is that you must start with an explicit conceptual framework. For example, Marshallian analysis makes us think about supply vs. demand when we look at the world. General equilibrium theory forces us to split the world into preferences and the physical opportunities available to us. That split is really important and I always try to get my students to think about it when they approach a question. What do people in your model want? What are the production possibilities that are available to them?
All of growth theory has been operating under the physical opportunities question side of the model. We describe the physical opportunities as physical objects like raw materials and then you start to think about ideas as recipes for rearranging these objects. When you start to think about democracy and politics, you have to start addressing the other side of the model. What is it that people want? What drives their behaviour? If you expand the concept of preferences and say that it is everything that is inside of peoples’ heads, it includes all kinds of things that sociologists and psychologists talk about: tastes, values and norms, etc. When you start to talk about the connections between economic growth and democracy you really have to start inquiring into these issues. Barro’s assertions are based on some empirical generalisations and they are fine as far as they go, but what is missing there is any kind of theoretical understanding of the connection between economic development and political structures. This is not just a problem in economics. It is also a deep problem in political science. There are many fundamental issues that have not been addressed in political science. To begin with, why does anybody bother to vote? The standard theory that political scientists have is that people go and vote because they have a stake in the outcome and they want to influence the outcome so it goes their way -- less taxes and more transfers, etc. That theory contradicts itself as soon as you state it because the probability that any one voter will be decisive in an election is so trivial that the cost of going to the polls just dwarfs any possible expected gain that anyone could get from going to the poll.
So I would just assert a cautionary note here. There is a little bit of empirical evidence that suggests a connection between the level of income and democracy, but we really face an almost total theoretical vacuum in studying this question. We are unlikely to make much progress until we have some theoretical foundations that force us to think clearly about the issues involved.
Another controversial area that has received much attention in the economic development literature is the relationship between foreign trade and growth. This is especially topical given the current crisis, which has spread throughout the ‘Asian Tiger’ economies that are often held up as prime examples of export-driven growth. As economists we can easily envisage an effect on the level of GDP coming from trade, but can trade influence the rate of growth?
There are two mechanisms here. From a development point of view the main thing you want to think about is this process of catching up. The key role for trade is that it lets developing countries get access to ideas that exist in the rest of the world. I tell my students that in the advanced countries of the world, we already know everything that we need to know to provide a very high standard of living for everybody in the world. It is not that we lack physical resources, it is not a lack of mass or matter that makes people in India and China poor. What makes them poor is that they do not have access to the knowledge and ideas that we have already worked out in North America, Europe and Japan for doing all the things that we do in the modern economy. The trick to make them better off is just to get that knowledge flowing into those countries. Much of it is very basic knowledge -- like how do you operate a distribution system so that clothes get from a factory to a store shelf so that someone can buy a shirt when they want one. How do you make sure that food does not spoil and is distributed to the right locations at the right times? How do you implement quality control systems in a manufacturing process? This is all basic knowledge but it is the stuff that raises living standards. A lot of that knowledge can be put to work in poor countries if they allow the right kinds of trade. Direct foreign investment from multinationals, in particular, is important for getting quick access to these kinds of ideas.
There is also a second issue. If you take the rich economies, OECD countries for example, the larger the market the bigger the incentives are to develop new ideas. So free trade in very large market areas creates greater incentives for innovation and therefore leads to more technological progress. If you don’t think that this is true, just ask yourself how much innovation would be taking place in Silicon Valley if products made there had to be sold just in the US, or just in California, or just in Santa Clara County? Some, to be sure, but a lot less than we see right now.
So trade matters for catching up. It also matters for sustaining growth in the leading countries.
Since growth is so important to the improvement of living standards it is inevitable that governments will try and influence the growth rate. What should the role of government be with respect to growth, in particular what role do you see for monetary and fiscal policy here?
On monetary policy it is a bit like the distinction I talked about before -- stopping the bleeding vs. getting in shape. There is a certain amount of emergency medicine that governments have to be prepared to engage in. A lot of that amounts to an injunction to do no harm. It helps enormously if policy makers just keep from screwing up the way they did in the inter-war period. But a sensible monetary policy only creates the opportunity for growth to happen; it does not make it happen. On the fiscal side, a government has to be able to pay its bills and it must keep from taxing income at such high rates that it severely distorts incentives.
There are other policies that also matter. Some of those involve creating a legal framework. What kind of institutions matter if you are in the United States? Venture capital, fluid capital markets -- think of all the things that help a company like Intel come into existence and grow into a huge force. The government did not have to do anything very active but it did have to put in place structures that permitted venture capital, a new-issue stock market and so forth. Beyond that there are measures related to human capital. There is a role for government there. The modern university, as it emerged in the United States in the last century, is one that is very focused on training and practical problem-solving. It is subsidised by the government. As I said before, subsidising human capital is a very important way to indirectly subsidise technological change. So the modern university is an example of the kind of institution that the government can support.
I should add the caveat that many of the direct roles that people articulate for the government are not justified. A lot of people see endogenous growth theory as a blanket seal of approval for all of their favourite government interventions, many of which are very wrong-headed. For example, a lot of the discussion about infrastructure is just wrong. Infrastructure is to a very large extent a traditional physical good and should be provided in the same way that we provide other physical goods, with market incentives and strong property rights. A move towards privatisation of infrastructure provision is exactly the right way to go. The government should be much less involved in infrastructure provision. So that is one area where I disagree with some of the wild-eyed interventionists. Another is the notion that the government should directly subsidise particular research programmes to produce particular kinds of ideas. If you compare that mechanism with the mechanism of subsidising human capital and letting the market mechanism allocate where the human capital goes and what ideas get developed, the human capital-based approach works better. Selecting a few firms and giving them money has obvious problems. How do bureaucrats get access to all the decentralised information they need if they are to decide which projects should be supported? How do you keep rent seeking and pork barrel politics from dominating the allocation process?
A great deal of thought has been given to the design of institutions to avoid non-trivial rates of inflation. However the relationship between inflation performance and growth performance is far from clear, especially at low rates of inflation. How do you read the evidence on this issue?
Inflation is somewhat damaging and it is probably a non-linear relationship, so the higher the rate of inflation gets the more damaging it is likely to be.
Is this due to the greater variability of inflation at higher rates?
At least partly. The variability and the higher rates both make the damage grow more than linearly. There is no trade-off, fundamentally, between growth and inflation and therefore no reason not to aim at very low levels of inflation from a growth perspective. The best place to be is at a very low level of inflation and there is no reason to accept say, 10 per cent inflation because we think we can get some benefit in terms of long-run growth. So if you are trying to do the best job you can on growth you basically want to aim for whatever the consensus is on minimal inflation. That will vary between zero and two or three percent at the moment. It may not be too harmful to be up at six percent instead of two or three, but if it is harmful at all, why accept even that.
During the early 1970s a great deal of interest was stirred up by the book Limits To Growth ( Meadows et al., 1972). Since then the environmental movement has become increasingly influential. Do you ever think or worry about the environmental impact of growth or the possibility of resource limitations on growth? Can the rest of the world expect to enjoy the same living standards currently enjoyed in the OECD economics without generating an environmental catastrophe?
Environmental problems are real problems. They are cases where our current institutional structures do not put prices on physical objects that should have prices on them. When you do not have prices on fish in the sea, market incentives cause fishermen to overfish. We know that we either need to institute a price mechanism or some regulatory system that has the same effect as a price mechanism. We will face a big challenge if, for example, human sources of carbon dioxide prove to be too much for the carrying capacity of the atmosphere. We are going to have trouble implementing a world-wide price or a regulatory system to deal with this, but we will need to do it.
However, all this is very different from saying that there are long-run limits to growth. The way to think about limits is to ask, "What does it mean to say that our standards of living are higher now or that we have more income now than we had one hundred years ago?" It does not mean that we have more mass, more pounds or kilos of material. What it means is that we took the finite resources that are available here on earth and just rearranged them in ways that made them more valuable. For example, we now take abundant silicon and we rearrange it into microchips that are much more valuable. So the question is: how much scope is there for us to take the finite amount of mass here on earth and rearrange it in ways that people will find more valuable? Here, you can make a strong case that the potential is virtually unlimited. There is absolutely no reason why we cannot have persistent growth as far into the future as you can imagine. If you implement the right institutions, the type of growth might take a slightly different form than what we anticipated. If carbon dioxide turns out to be a really big problem and we implement institutions which raise the price of carbon emissions, then cars will get smaller. Or we might drive cars somewhat less frequently, or we might rely on video conferencing, instead of driving automobiles, to meet with family and so on. We could shift to much greater reliance on renewable biomass or photovoltaics as a primary source of energy. We have the technology to do this right now. It’s a more expensive way to generate electricity than burning oil and coal, but if income per capita is 5 to 10 times higher 100 years from now, paying a bit more for energy will be a minor issue.
The bottom line is that there are pollution and other environmental problems that we will need to address. But these problems will not stop microchips from getting faster, hard disc storage densities from continuing to get higher, new pharmaceuticals from being introduced, new communications technologies from emerging, new methods for distributing goods like overnight delivery and discount retailing from emerging. All those processes will continue in the rich counties and will spread to the poor countries. In the process, the standards of living will go up for everyone.
In looking at the post-war economic growth performances of Germany and Japan compared to the UK do you think there is anything in Mancur Olsen’s (1982) argument, developed in his book The Rise and Decline of Nations, that societies which have been stable for a long time such as the UK develop organisations for collective action which are harmful to economic efficiency and dynamism?
His conjecture is interesting, but to evaluate it, we have to come back to the discussion we had earlier about production possibilities versus preferences. What Mancur tried to do was bring back into the discussion some theory about what is going on inside someone's head. He wanted to do this so he could understand the political dynamics that influence policy decisions about universities, regulations, rent-seeking and so on. Those are important questions both from a development perspective and from a long-run growth perspective for advanced countries like the UK. These are important issues but when we think about them, it is important to distinguish between assertions about the physical world and assertions about what goes on inside someone’s head. Anytime you bring politics into the discussion you are crossing that divide. At that point it is always important to remind oneself that we know very little about this area. Mancur is relying on a few empirical generalisations. He looks at historical episodes where something like a revolution or a war frees things up and then you see rapid growth. He has also looked at the general process of the growth slowdown. History is never a completely reliable guide for these kind of questions because we do not have very many observations and the current circumstances are always different from the past. I always caution someone like Mancur to be honest about the extent of our ignorance in this area, although I encourage economists to think about these questions. Just saying that the physical world presents us with enormous opportunities for growth does not mean that we will necessarily organise ourselves and take advantage of them as rapidly as we could.
Moses Abramovitz (1986), your colleague at Stanford University, has stressed the importance of what he calls ‘social capability’ in the catch-up process. Differences among countries productivity levels create a potential for catch-up providing the follower countries have the appropriate institutions and technical competence. Can we operationalise a concept like social capability?
Social capability is one of those vague terms like social capital that I think would benefit from the kind of clarification that you are forced to engage in when you write down a mathematical model. It could be something that you understand in this physical opportunity side of the theoretical framework. For example, you can think of human capital as a key complementary input for technology. So just as physical capital by itself cannot explain much -- neither land nor labour can themselves produce corn, but the two of them together can -- it could be that human capital is the key complement for ideas or knowledge just as land is complementary to labour. Just bringing in physical capital from the rest of the world will not work if you do not have the human capital there to work with it.
You could also interpret social capability in a broader sense. You could ask whether a country has a political or social ethic or a set of norms that lets markets operate, that encourages risk taking, that supports the rule of law as opposed to either corruption or purely discretionary negotiations. You can interpret social capability in that broader sense and there are some important issues there. But when you do this, you have to recognise that you are theorising about what goes on in someone’s head.
A great deal of research and effort has been put into investigating the existence, causes and consequences of the productivity slowdown in the US and other advanced industrial countries. What is your personal interpretation of the findings from this research?
When I talk to students and with people from the outside the university, I try to be honest about our ignorance. It is always very tempting for economists to claim more than they know. We do not know what happened with the productivity slowdown in two senses. First, I don’t think we know for sure what the basic facts are. The quality of the data is such that we cannot speak with authority and answer the question about what has happened over time to the rate of growth of productivity. Second, even if there was a slowdown we do not know the reasons with any confidence. In a recent paper with Kevin Murphy and Craig Riddell, I have started looking at the labour market evidence which suggests to me that technological change has proceeded at a pretty rapid but steady pace for the last three or four decades, neither slowing down nor speeding up. This calls into question some of the interpretation of the output data that we have, which does suggest that there has been a big slowdown. But all of the inferences here have to be quite tentative. You have to be realistic about what you can expect. It could be that when we get the hard numbers we will conclude that there was a productivity slowdown and we may never completely understand why it happened. I have never claimed that endogenous growth theory is necessarily going to be able to predict or explain precisely all the things that we observe. The economy is a very complicated beast and the goal for us should not be to predict within a few tenths of a percentage point the rate of growth, prospectively or retrospectively. The real test is, does the theory give us some guidance in constructing institutions that will encourage growth? Does it help us understand what kinds of things led to difference between the growth performance of the UK and the US in the last one hundred years? If the theory gives us that kind of guidance then it has been successful and can help us design policies to improve the quality of peoples lives and that is an extremely important contribution.
Where do you think the direction of research into economic growth is likely to go next or where should it go next?
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