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by Andreas Hoffmann David Glasner has posted his paper on “Hayek and equilibrium concepts” on SSRN. An earlier version of this fascinating paper was presented at the History of Economics Society in Toronto in 2017 and the NYU Colloquium. A teaser (taken from the abstract): The now dominant Lucas rational-expectations approach misconceives intertemporal equilibrium and … Continue reading Glasner: “Hayek, Hicks, Radner and Three Equilibrium Concepts”

The Law of One Price One of the core tenets of economic analysis of competitive markets is that, in competitive equilibrium, a particular good or service produced by multiple competing firms should sell for the same price. This "Law of One Price" follows from the assumed property in a competitive market with informed buyers and […]

My first post described a few anecdotes about what a warm person Bob Lucas was, and such a great colleague. Here I describe a little bit of his intellectual influence, in a form that is I hope accessible to average people.The "rational expectations" revolution that brought down Keynesianism in the 1970s was really much larger than that. It was really the "general equilibrium" revolution. Macroeconomics until 1970 was sharply different from regular microeconomics. Economics is all about "models," complete toy economies that we construct via equations and in computer programs. You can't keep track of everything in even the most beautiful prose. Microeconomic models, and "general equilibrium" as that term was used at the time, wrote down how people behave — how they decide what to buy, how hard to work, whether to save, etc.. Then it similarly described how companies behave and how government behaves. Set this in motion and see where it all settles down; what prices and quantities result. But for macroeconomic issues, this approach was sterile. I took a lot of general equilibrium classes as a PhD student — Berkeley, home of Gerard Debreu was strong in the field. But it was devoted to proving the existence of equilibrium with more and more general assumptions, and never got around to calculating that equilibrium and what it might say about recessions and government policies. Macroeconomics, exemplified by the ISLM tradition,  inhabited a different planet. One wrote down equations for quantities rather than people, for example that "consumption" depended on "income," and investment on interest rates. Most importantly, macroeconomics treated each year as a completely separate economy. Today's consumption depended on today's income, having nothing to do with whether people expected the future to look better or worse. Economists recognized this weakness, and a vast and now thankfully forgotten literature tried fruitlessly to find "micro foundations" for Keynesian economics. But building foundations under an existing castle doesn't work. The foundations want a different castle. Bob's "islands" paper is famous, yes, for a complete model of how unexpected money might move output in the short run and not just raise inflation. But you can do that with a half a page of simple math, and Bob's paper is hard to read. It's deeper contribution, and the reason for that difficulty, is that Bob wrote out a complete "general equilibrium" model. People, companies and government each follow described rules of behavior. Those rules are derived as being the optimal thing for people and companies to do given their environment. And they are forward-looking. People think about how to make their whole lives as pleasant as possible, companies to maximize the present value of profits. Prices adjust so supply = demand. Bob said, by example, that we should do macroeconomics by writing down general equilibrium models. General equilibrium had also been abandoned by the presumption that it only studies perfect economies. Macroeconomics is really about studying how things go wrong, how "frictions" in the economy, such as the "sticky" wages underlying Keynesian thinking, can produce undesirable and unnecessary recessions. But here too, Bob requires us to write down the frictions explicitly. In his model, people don't see the aggregate price level right away, and do the best they can with local information. That is the real influence of the paper  and Bob's real influence in the profession. (Current macroeconomic modeling reflects the fact that the Fed sets interest rates, and does not control the money supply.) You can see this influence in Tom Sargent's textbooks. The first textbook has an extensive treatment of Keynesian economics. It's about the most comprehensible treatment there is — but it is no insult to Tom to say that in that book you can see how Keynesian economics really doesn't hang together. Tom describes how, the minute he learned from Bob how to to general equilibrium, everything changed instantly. Rational expectations was, like any other advance, a group effort. But what made Bob the leader was that he showed the rest how to do general equilibrium. This is the heart of my characterization that Bob is the most important macroeconomist of the 20th century. Yes, Keynes and Friedman had more policy impact, and Friedman's advocacy of free markets in microeconomic affairs is the most consequential piece of 20th century economics. But within macroeconomics, there is before Lucas and after Lucas.  Everyone today does economics the Lucas way. Even the most new-Keynesian article follows the Lucas rules of how to do economics. Once you see models founded on complete descriptions of people, businesses, government, and frictions, you can see the gaping holes in standard ISLM models. This is some of his stinging critique, such as "after Keynesian macroeconomics." Sure, if people's income goes up they are likely to consume more, as the Keynesians posited. But interest rates, wages, and expectations of the future also affect consumption, which Keynesians leave out. "Cross equations restrictions" and "budget constraints" are missing. Now, the substantive prediction that monetary policy can only move the real economy via unexpected money supply growth did not bear out, and both subsequent real business cycles and new-Keynesianism brought persistent responses. But the how we do macroeconomics part is the enduring contribution. The paper still had enduring practical lessons. Lucas, together with Friedman and Phelps brought down the Phillips curve. This curve, relating inflation to unemployment, had been (and sadly, remains) at the center of macroeconomics. It is a statistical correlation, but like many correlations people got enthused with it and started reading it as stable relationship, and indeed a causal one. Raise inflation and you can have less unemployment. Raise unemployment in order to lower inflation. The Fed still thinks about it in that causal way. But Lucas, Friedman, and Phelps bring a basic theory to it, and thereby realize it is just a correlation, which will vanish if you push on it. Rich guys wear Rolexes. That doesn't mean that giving everyone a Rolex will have a huge "multiplier" effect and make us all rich. This is the essence of the "Lucas critique" which is a second big contribution that lay readers can easily comprehend. If you push on correlations they will vanish. Macroeconomics was dedicated to the idea that policy makers can fool people. Monetary policy might try to boost output in a recession with a surprise bit of money growth. That will wok once or twice. But like the boy who cried wolf, people will catch on, come to expect higher money growth in recessions and the trick won't work anymore. Bob showed here that all the "behavioral" relations of Keynesian models will fall apart if you exploit them for policy, or push on them, though they may well hold as robust correlations in the data. The "consumption function" is the next great example. Keynesians noticed that when income rises people consume more, so write a consumption function relating consumption to income. But, following Friedman's great work   on consumption, we know that correlation isn't always true in the data. The relation between consumption and income is different across countries (about one for one) than it is over time (less than one for one). And we understand that with Friedman's theory: People, trying to do their best over their whole lives don't follow mechanical rules. If they know income will fall in the future, they consume a lot less today, no matter what today's current income. Lucas showed that people who behave this sensible way will follow a Keynesian consumption function, given the properties of income overt the business cycle. You will see a Keynesian consumption function. Econometric estimates and tests will verify a Keynesian consumption function. Yet if you use the model to change policies, the consumption function will evaporate. This paper is devastating. Large scale Keynesian models had already been constructed, and used for forecasting and policy simulation. It's natural. The model says, given a set of policies (money supply, interest rates, taxes, spending) and other shocks, here is where the economy goes. Well, then, try different policies and find ones that lead to better outcomes. Bob shows the models are totally useless for that effort. If the policy changes, the model will change. Bob also showed that this was happening in real time. Supposedly stable parameters drifted around. (This one is also very simple mathematically. You can see the point instantly. Bob always uses the minimum math necessary. If other papers are harder, that's by necessity not bravado.) This devastation is sad in a way. Economics moved to analyzing policies in much simpler, more theoretically grounded, but less realistic models. Washington policy analysis sort of gave up. The big models lumber on, the Fred's FRBUS for example, but nobody takes the policy predictions that seriously. And they don't even forecast very well. For example, in the 2008 stimulus, the CEA was reduced to assuming a back of the envelope 1.5 multiplier, this 40 years after the first large scale policy models were constructed. Bob always praised the effort of the last generation of Keynesians to write explicit quantitative models, to fit them to data, and to make numerical predictions of various policies. He hoped to improve that effort. It didn't work out that way, but not by intention. This affair explains a lot of why economists flocked to the general equilibrium camp. Behavioral relationships, like what fraction of an extra dollar of income you consume, are not stable over time or as policy changes. But one hopes that preferences, — how impatient you are, how much you are willing to save more to get a better rate of return — and technology — how much a firm can produce with given capital and labor — do not change when policy changes. So, write models for policy evaluation at the level of preferences and technology, with people and companies at the base, not from behavioral relationships that are just correlations. Another deep change: Once you start thinking about macroeconomics as intertemporal economics — the economics that results from people who make decisions about how to consume over time, businesses make decisions about how to produce this year and next — and once you see that their expectations of what will happen next year, and what policies will be in place next year are crucial, you have to think of policy in terms of rules, and regimes, not isolated decisions. The Fed often asks economists for advice, "should we raise the funds rate?" Post Lucas macroeconomists answer that this isn't a well posed question. It's like saying "should we cry wolf?" The right question is, should we start to follow a rule, a regime, should we create an institution, that regularly and reliably raises interest rates in a situation like the current one? Decisions do not live in isolation. They create expectations and reputations. Needless to say, this fundamental reality has not soaked in to policy institutions. And that answer (which I have tried at Fed advisory meetings) leads to glazed eyes. John Taylor's rule has been making progress for 30 years trying to bridge that conceptual gap, with some success.  This was, and remains, extraordinarily contentious. 50 years later, Alan Blinder's book, supposedly about policy, is really one long snark about how terrible Lucas and his followers are, and how we should go back to the Keynesian models of the 1960s. Some of that contention comes back to basic philosophy.  The program applies standard microeconomics: derive people's behaviors as the best thing they can do given their circumstances. If people pick the best combination of apples and bananas when they shop, then also describe consumption today vs. tomorrow as the best they can do given interest rates. But a lot of economics doesn't like this "rational actor" assumption. It's not written in stone, but it has been extraordinarily successful. And it imposes a lot of discipline. There are a thousand arbitrary ways to be irrational.  Somehow though, a large set of economists are happy to write down that people pick fruit baskets optimally, but don't apply the same rationality to decisions over time, or in how they think about the future. But "rational expectations" is really just a humility condition. It says, don't write models in which the predictions of the model are different from the expectations in the model. If you do, if your model is right, people will read the model and catch on, and the model won't work anymore. Don't assume you economist (or Fed chair) are so much less behavioral than the people in your model. Don't base policy on an attempt to fool the little peasants over and over again. It does not say that people are big super rational calculating machines. It just says that they eventually catch on. Some of the contentiousness is also understandable by career concerns. Many people had said "we should do macro seriously like general equilibrium." But it isn't easy to do. Bob had to teach himself, and get the rest of us to learn, a range of new mathematical  and modeling tools to be able to write down interesting general equilibrium models. A 1970 Keynesian can live just knowing how to solve simple systems of linear equations, and run regressions.  To follow Bob and the rational expectations crowd, you had to learn linear time-series statistics, dynamic programming, and general equilibrium math. Bob once described how tough the year was that it took him to learn functional analysis and dynamic programming. The models themselves consisted of a mathematically hard set of constructions. The older generation either needed to completely retool, fade away, or fight the revolution. Some good summary words: Bob's economics uses"rational expectations," or at least forward-looking and model-consistent expectations. Economics becomes "intertemporal," not "static" (one year at a time). Economics is "stochastic" as well as "dynamic," we can treat uncertainty over time, not just economies in which everyone knows the future perfectly. It applies "general equilibrium" to macroeconomics. And I've just gotten to the beginning of the 1970s. When I got to Chicago in the 1980s, there was a feeling of "well, you just missed the party." But it wasn't true. The 1980s as well were a golden age. The early rational expectations work was done, and the following real business cycles were the rage in macro. But Bob's dynamic programming, general equilibrium tool kit was on a rampage all over dynamic economics. The money workshop was one creative use of dynamic programs and interetempboral tools after another one, ranging from taxes to Thai villages (Townsend). I'll mention two. Bob's consumption model is at the foundation of modern asset pricing. Bob parachuted in, made the seminal contribution, and then left finance for other pursuits. The issue at the time was how to generalize the capital asset pricing model. Economists understood that some stocks pay higher returns than others, and that they must do so to compensate for risk. The understood that the risk is, in general terms, that the stock falls in some sense of bad times. But how to measure "bad times?" The CAPM uses the market, other models use somewhat nebulous other portfolios. Bob showed us that at least in the purest theory, that stocks must pay higher average returns if they fall when consumption falls. (Breeden also constructed a consumption model in parallel, but without this "endowment economy" aspect of Bob's) This is the purest most general theory, and all the others are (useful) specializations. My asset pricing book follows. The genius here was to turn it all around. Finance had sensibly built up from portfolio theory, like supply and demand: Given returns, what stocks do you buy, and how much to you save vs. consume? Then, markets have to clear find the stock prices, and thus returns, given which people will buy exactly the amount that's for sale and consume what is produced. That's hard. (Technically, finding the vector of prices that clears markets is hard. Yes, N equations in N unknowns, but they're nonlinear and N is big.)  Bob instead imagined that consumption is fixed at each moment in time, like a desert island  in which so many coconuts fall each day and you can't store them or plant them. Then, you can just read prices from people's preferences. This gives the same answer as if the consumption you assume is fixed had derived from a complex production economy. You don't have to solve for prices that equate supply and demand. Brilliantly, though prices cause consumption to individual people, consumption causes prices in aggregate. This is part of Bob's contribution to the hard business of actually computing quantitative models in the stochastic dynamic general equilibrium tradition. Bob, with Nancy Stokey also took the new tools to the theory of taxation. (Bob Barro also was a founder of this effort in the late 1980s.) You can see the opportunity: we just learned how to handle dynamic (overt time, expectations of tomorrow matter to what you do today) stochastic (but there is uncertainty about what will happen tomorrow) economics (people make explicit optimizing decisions) for macro. How about taking that same approach to taxes? The field of dynamic public finance is born. Bob and Nancy, like Barro, show that it's a good idea for governments to borrow and then repay, so as to spread the pain of taxes evenly over time. But not always. When a big crisis comes, it is useful to execute a "state contingent default." The big tension of Lucas-Stokey (and now, all) dynamic public finance: You don't want any capital taxes for the incentive effects. If you tax capital, people invest less, and you just get less capital. But once people have invested, a capital tax grabs revenue for the government with no economic distortion. Well, that is, if you can persuade them you'll never do it again. (Do you see expectations, reputations, rules, regimes, wolves in how we think of policy?) Lucas and Stoney say, do it only very rarely to balance the disincentive of a bad reputation with the need to raise revenue in once a century calamities. Bob went on, of course, to be one of the founders of modern growth theory. I always felt he deserved a second Nobel for this work. He's absolutely right. Once you look at growth, it's hard to think about anything else. The average Indian lives on $2,000 per year. The average American, $60,000. That was $15,000 in 1950. Nothing else comes close. I only work on money and inflation because that's where I think I have answers. For us mortals, good research proceeds where you think you have an answer, not necessarily from working on Big Questions. Bob brilliantly put together basic facts and theory to arrive at the current breakthrough. Once you get out of the way, growth does not come from more capital, or even more efficiency. It comes from more and better ideas. I remember being awed by his first work for cutting through the morass and assembling the facts that only look salient in retrospect. A key one: Interest rates in poor countries are not much higher than they are in rich countries. Poor countries have lots of workers, but little capital. Why isn't the return on scarce capital enormous, with interest rates in the hundreds of percent, to attract more capital to poor countries? Well, you sort of know the answer, that capital is not productive in those countries.  Productivity is low, meaning those countries don't make use of better ideas on how to organize production.  Ideas too are produced by economics, but, as Paul Romer crystallized, they are fundamentally different from other goods. If I produce an idea, you can use it without hurting my use of it. Yes, you might drive down the monopoly profits I gain from my intellectual property. But if you use my Pizza recipe, that's not like using my car. I can still make Pizza, where if you use my car I can't go anywhere. Thus, the usual free market presumption that we will produce enough ideas is false. (Don't jump too quickly to advocate government subsides for ideas. You have to find the right ideas, and governments aren't necessarily good at subsidizing that search.) And the presumption that intellectual property should be preserved forever is also false. Once produced it is socially optimal for everyone to use it. I won't go on. It's enough to say that Bob was as central to the creation of idea-based growth theory, which dominates today, as he was to general equilibrium macro, which also dominates today.Bob is an underrated empiricist. Bob's work on the size distribution of firms (great tweet summary by Luis Garicano) similarly starts from basic facts of the size distribution of firms and the lack of relationship between size and growth rates. It's interesting how we can go on for years with detailed econometric estimates of models that don't get basic facts right. I loved Bob's paper on money demand for the Carnegie Rochester conference series. An immense literature had tried to estimate money demand functions with dynamics, and was pretty confusing. It made a basic mistake, by looking at first differences rather than levels and thereby isolating the noise and drowning out the signal. Bob made a few plots, basically rediscovered cointegration all on his own, and made sense of it all. And don't forget the classic international comparison of inflation-output relations. Countries with volatile inflation have less Phillips curve tradeoff, just as his islands model featuring confusion between relative prices and the price level predicts. One last note to young scholars. There is a tendency today to value people by the number of papers they produce, and how quickly they rise through the ranks. Read Bob's CV. He wrote about one paper a year, starting quite late in life. But, as Aesop said, they were lions. In his Nobel prize speech, Bob also passed on that he and his Nobel-winning generation at Chicago always felt they were in some backwater, where the high prestige stuff was going on at Harvard and MIT. You never know when it might be a golden age. And the AER rejected his islands paper (as well as Akerlof's lemons). If you know it's good, revise and try again. I will miss his brilliant papers as much as his generous personality. Update: See Ivan Werning's excellent "Lucas Miracles" for an appreciation by a real theorist. 

I was recently chatting with someone who teaches introductory macroeconomics (not using my favorite textbook). He does not teach the students about money creation under fractional reserve banking, which he considers an unnecessary technicality, but he does teach them the following two statements about inflation.


If
the Fed lowers the interest rate on reserves, that policy stimulates economic activity in the short run and, via the Phillips curve, increases inflation.
In
the long run, the quantity theory of money explains inflation.


I agree with both of these statements, and I consider them critical for students to understand. But consider: How does one explain the transition from the short run to the long run?

The only way I know to answer this question is that a lower interest rate on
reserves increases bank lending and expands the money supply by increasing the money
multiplier. But if students don't know about how banks create money under fractional
reserve banking, they are not equipped to understand this logic.The bottom line: The traditional pedagogy about how banks influence the money supply remains important if students are to understand the economics of inflation.Update: This post generated more than the usual amount of confusion and misdirection on Twitter. So let me explain my logic more slowly:


It is useful to teach
the quantity theory of money (M and P are parallel) as a long-run
equilibrium condition, regardless of which direction causality runs.
It is useful for
students to know that cutting the interest rate on reserves is
expansionary for aggregate demand and, over time, inflationary. That is,
it raises P.
To complete the story,
you need to explain how cutting the interest rate on reserves raises M.
To be sure, lower
interest rates increase the quantity of money demanded. But you also must
explain the quantity of money supplied.
The money supply M equals m*B, where m is the money multiplier and B is the monetary base
(currency plus reserves).
Cutting the interest on
reserves (unlike open-market operations) does not change B. So if it
changes the money supply M, it must work through the money multiplier m.
One cannot understand
the money multiplier m without understanding fractional reserve banking. (Under 100-percent-reserve banking, m is fixed at 1.)

Loet Leydesdorff on the Triple Helix: How Synergies in University-Industry-Government Relations can Shape Innovation Systems





This is the sixth and last in a series of Talks dedicated to the technopolitics of International Relations, linked to the forthcoming double volume 'The Global Politics of Science and Technology' edited by Maximilian Mayer, Mariana Carpes, and Ruth Knoblich 







The relationship between technological innovation
processes and the nation state remains a challenge for the discipline of
International Relations. Non-linear and multi-directional
characteristics of knowledge production, and the diffusive nature of knowledge
itself, limit the general ability of governments to influence and steer
innovation processes. Loet Leydesdorff advances the framework of the "Triple
Helix" that disaggregates national innovation systems into
evolving university-industry-government eco-systems. In this Talk, amongst others, he shows that these eco-systems can be
expected to generate niches with synergy at all scales, and emphasizes that, though
politics are always involved, synergies develop unintentionally.




Print version of this Talk (pdf)




What is the most relevant aspect
of the dynamics of innovation for the discipline of International Relations?



The
main challenge is to endogenize the notions of technological progress and
technological development into theorizing about political economies and nation states.
The endogenization of technological innovation and technological development
was first placed on the research agenda of economics by evolutionary economists
like Nelson and Winter in the late 1970s and early 1980s. In this context, the
question was how to endogenize the dynamics of knowledge, organized knowledge,
science and technology into economic theorizing. However, one can equally well
formulate the problem of how to reflect on the global (sub)dynamics of
organized knowledge production in political theory and International Relations.



From
a longer-term perspective, one can consider that the nation states – the
national or political economies in Europe – were shaped in the 19th
century, somewhat later for Germany (after 1871), but for most countries it was
during the first half of the 19th century. This was after the French
and American Revolutions and in relation to industrialization. These nation
states were able to develop an institutional framework for organizing the
market as a wealth-generating mechanism, while the institutional framework
permitted them to retain wealth, to regulate market forces, and also to steer
them to a certain extent. However, the market is not only a local dynamics; it
is also a global phenomenon.



Nowadays,
another global dynamics is involved: science and technology add a dynamics different
from that of the market. The market is an equilibrium-seeking mechanism at each
moment of time. The evolutionary dynamics of science and technology nowadays
adds a non-equilibrium-seeking dynamics over time on top of that, and this puts
the nation state in a very different position. Combining an equilibrium-seeking
dynamics at each moment of time with a non-equilibrium seeking one over time
results in a complex adaptive dynamics, or an eco-dynamics, or however you want
to call it – these are different words for approximately the same thing.



For
the nation state, the question arises of how it relates to the global market
dynamics on the one side, and the global dynamics of knowledge and innovation on
the other. Thus, the nation state has to combine two tasks. I illustrated this
model of three subdynamics with a figure in my 2006 book entitled The Knowledge-Based Economy: Modeled,
measured, simulated (see image). The figure shows that first-order interactions
generate a knowledge-based economy as a next-order or global regime on top of
the localized trajectories of nation states and innovative firms. These complex
dynamics have first to be specified and then to be analyzed empirically.



For
example, the knowledge-based dynamics change the relation between government
and the economy; and they consequently change the position of the state in
relation to wealth-retaining mechanisms. How can the nation state be organized
in such a way as to retain wealth from knowledge locally, while knowledge (like
capital) tends to travel beyond boundaries? One can envisage the complex system
dynamics as a kind of cloud – a cloud
that touches the ground at certain places, as Harald Bathelt, for example,
formulated.



How
can national governments shape conditions for the cloud to touch and to remain
on the ground? The Triple Helix of University-Industry-Government Relations can
be considered as an eco-system of bi- and tri-lateral relations. The three
institutions and their interrelations can be expected to form a system carrying
the three functions of (i) novelty production, (ii) wealth generation, and
(iii) normative control. One tends to think of university-industry-government
relations first as neo-corporatist arrangements between these institutional
partners. However, I am interested in the ecosystem shaped through the tri- and
bilateral relationships.



This
ecosystem can be shaped at different levels. It can be a regional ecosystem or
a national ecosystem, for instance. One can ask whether there is a surplus of synergy
between the three (sub-)dynamics of university-industry-government relations
and where that synergy can generate wealth, knowledge, and control; in which
places, and along trajectories for which periods of time – that is, the same
synergy as meant by "a cloud touching the ground".



For
example, when studying Piedmont as a region in Northern Italy, it is
questionable whether the synergy in university-industry-government relations is
optimal at this regional level or should better be examined from a larger perspective
that includes Lombardy. On the one
hand, the administrative borders of nations and regions result from the
construction of political economies in the 19th century; but on the
other hand, the niches of synergy that can be expected in a knowledge-based
economy are bordered also; for example, in terms of metropolitan regions (e.g.,
Milan–Turin–Genoa).



Since
political dynamics are always involved, this has implications for International
Relations as a field of study. But the dynamic analysis is different from
comparative statics (that is, measurement at different moments of time). The
knowledge dynamics can travel and be "footloose" to use the words of Raymond
Vernon, although it leaves footprints behind. Grasping "wealth from knowledge"
(locally or regionally) requires taking a systems perspective. However, the
system is not "given"; the system remains under reconstruction and can thus be
articulated only as a theoretically informed hypothesis.



In
the social sciences, one can use the concept of a hypothesized system
heuristically. For example, when
analyzing the knowledge-based economy in Germany, one can ask whether more synergy
can be explained when looking at the level of the whole country (e.g., in terms
of the East-West or North-South divide) or at the level of Germany's Federal
States? What is the surplus of the nation or at the European level? How can one
provide political decision-making with the required variety to operate as a
control mechanism on the complex dynamics of these eco-systems?



A
complex system can be expected to generate niches with synergy at all scales,
but as unintended consequences. To what extent and for which time span can
these effects be anticipated and then perhaps be facilitated? At this point,
Luhmann's theory comes in because he has this notion of different codifications
of communication, which then, at a next-order level, begin to self-organize
when symbolically generalized.



Codes
are constructed bottom-up, but what is constructed bottom-up may thereafter
begin to control top-down. Thus, one should articulate reflexively the
selection mechanisms that are constructed from the bottom-up variation by
specifying the why as an hypothesis.
What are the selection mechanisms? Observable relations (such as
university-industry relations) are not neutral, but mean different things for
the economy and for the state; and this meaning of the observable relations can
be evaluated in terms of the codes of communication.



Against
Niklas Luhmann's model, I would argue that codes of communication can be
translated into one another since interhuman communications are not
operationally closed, as in the biological model of autopoiesis. One also needs a social-scientific perspective on the
fluidities ("overflows") and translations among functions, as emphasized, for
example, by French scholars such as Michel Callon and Bruno Latour. In
evolutionary economics, one distinguishes between market and non-market
selection environments, but not among selection environments that are
differently codified. Here, Luhmann's theory offers us a heuristic: The complex
system of communications tends to differentiate in terms of the symbolic
generalizations of codes of communication because this differentiation is
functional in allowing the system to process more complexity and thus to be
more innovative. The more orthogonal the codes, the more options for
translations among them. The synergy indicator measures these options as
redundancy. The selection environments, however, have to be specified historically
because these redundancies—other possibilities—are not given but rather constructed
over long periods of time.





How did you arrive where
you currently work on?


I
became interested in the relations between science, technology, and society as
an undergraduate (in biochemistry) which coincided with the time of the student
movement of the late 1960s. We began to study Jürgen Habermas in the framework
of the "critical university," and I decided to continue with a second degree in
philosophy. After the discussions between Luhmann and Habermas (1971), I
recognized the advantages of Luhmann's more empirically oriented systems approach
and I pursued my Ph.D. in the sociology of organization and labour.



In
the meantime, we got the opportunity to organize an interfaculty department for
Science and Technology Dynamics at the University of Amsterdam after a
competition for a large government grant. In the context of this department, I
became interested in methodology: how can one compare across case studies and
make inferences? Actually, my 1995 book The
Challenge of Scientometrics
had a kind of Triple-Helix model on the cover: How do cognitions, texts, and
authors exhibit different dynamics that influence one another?



For
example, when an author publishes a paper in a scholarly journal, this may add
to his reputation as an author, but the knowledge claimed in the text enters a
process of validation which can be much more global and anonymous. These
processes are mediated since they are based on communication. Thus, one can add
to the context of discovery (of authors) and the context of justification (of
knowledge contents) a context of mediation (in texts). The status of a journal,
for example, matters for the communication of the knowledge content in the article.
The contexts operate as selection environments upon one another.



In
evolutionary economics, one is used to distinguishing between market and
non-market selection environments, but not among more selection environments
that are differently codified. At this point, Luhmann's theory offers a new
perspective: The complex system of communications tends to differentiate in
terms of the symbolic generalization of codes of communication because this differentiation
among the codes of communication allows the system to process more complexity
and to be more innovative in terms of possible translations. The different
selection environments for communications, however, are not given but constructed
historically over long periods of time. The modern (standardized) format of the
citation, for example, was constructed at the end of the 19th
century, but it took until the 1950s before the idea of a citation index was
formulated (by Eugene Garfield). The use of citations in evaluative
bibliometrics is even more recent.



In
evolutionary economics, one distinguishes furthermore between (technological)
trajectories and regimes. Trajectories can result from "mutual shaping" between
two selection environments, for example, markets and technologies. Nations and
firms follow trajectories in a landscape. Regimes are global and require the
specification of three (or more) selection environments. When three (or more)
dynamics interact, symmetry can be broken and one can expect feed-forward and
feedback loops. Such a system can begin to flourish auto-catalytically when the
configuration is optimal.



From
such considerations, that is, a confluence of the neo-institutional program of
Henry Etzkowitz and my neo-evolutionary view, our Triple Helix model emerged in
1994: how do institutions and functions interrelate and change one another or,
in other words, provide options for innovation? Under what conditions
can university-industry-government relations lead to wealth generation and
organized knowledge production? The starting point was a workshop about Evolutionary Economics and Chaos Theory: New
directions for technology studies held in Amsterdam in 1993. Henry
suggested thereafter that we could collaborate further on university-industry
relations. I answered that I needed at least three (sub)dynamics from the
perspective of my research program, and then we agreed about "A Triple Helix of
University-Industry-Government Relations". Years later, however, we took our
two lines of research apart again, and in 2002 I began developing a
Triple-Helix indicator of synergy in a series of studies of national systems of
innovation.





What would you give as
advice to students who would like to get into the field of innovation and
global politics?



In
general, I would advise them to be both a specialist and broader than that.
Innovation involves crossing established borders. Learn at least two languages.
If your background is political science, then take a minor in science &
technology studies or in economics. One needs both the specialist profile and
the potential to reach out to other audiences by being aware of the need to
make translations between different frameworks. Learn to be reflexive about the
status of what one can say in one or the other framework.



For
example, I learned to avoid the formulation of grandiose statements such as
"modern economies are knowledge-based economies," and to say instead: "modern
economies can increasingly be considered as knowledge-based economies." The
latter formulation provides room for asking "to what extent," and thus one can
ask for further information, indicators, and results of the measurement.



In
the sociology of science, specialisms and paradigms are sometimes considered as
belief systems. It seems to me that by considering scholarly discourses as
systems of rationalized expectations one can make the distinction between
normative and cognitive learning. Normative learning (that is, in belief
systems) is slower than cognitive learning (in terms of theorized expectations)
because the cognitive mode provides us with more room for experimentation: One
can afford to make mistakes, since one's communication and knowledge claims
remain under discussion, and not one's status as a communicator. The cognitive
mode has advantages; it can be considered as the surplus that is further
developed during higher education. Normative learning is slower; it dominates
in the political sphere.





What
does the "Triple Helix" reveal about the fragmentation of "national innovation
systems"?



In
2003, colleagues from the Department of Economics and Management Studies at the
Erasmus University in Rotterdam offered me firm data from the Netherlands containing
these three dimensions: the economic, the geographical, and the technological dimensions
in data of more than a million Dutch firms. I presented the results at the
Schumpeter Society in Turin in 2004, and asked whether someone in the audience
had similar data for other countries. I expected Swedish or Israeli colleagues
to have this type of statistics, but someone from Germany stepped in, Michael
Fritsch, and so we did the analysis for Germany. These studies were first
published in Research Policy.
Thereafter, we did studies on Hungary, Norway, Sweden, and recently also China
and Russia.



Several
conclusions arise from these studies. Using entropy statistics, the data can be
decomposed along the three different dimensions. One can decompose national
systems geographically into regions, but one can also decompose them in terms
of the technologies involved (e.g., high-tech versus medium-tech). We were
mainly relying on national data. And of course, there are limitations to the
data collections. Actually, we now have international data, but this is
commercial data and therefore more difficult to use reliably than governmental
statistics.



For
the Netherlands, we obtained the picture that would more or less be expected:
Amsterdam, Rotterdam, and Eindhoven are the most knowledge-intensive and
knowledge-based regions. This is not surprising, although there was one surprise:
We know that in terms of knowledge bases, Amsterdam is connected to Utrecht and
then the geography goes a bit to the east in the direction of Wageningen. What
we did not know was that the niche also spreads to the north in the direction
of Zwolle. The highways to Amsterdam Airport (Schiphol) are probably the most
important.



In
the case of Germany, when we first analyzed the data at the level of the
"Laender" (Federal States), we could see the East-West divide still prevailing,
but when we repeated the analysis at the lower level of the "Regierungsbezirke"
we no longer found the East-West divide as dominant (using 2004 data). So, the
environment of Dresden for example was more synergetic in Triple-Helix terms
than that of Saarbruecken. And this was nice to see considering my idea that
the knowledge-based economy increasingly prevails since the fall of the Berlin
Wall and the demise of the Soviet Union. The discussion about two different
models for organizing the political economy—communism or liberal democracy—had
become obsolete after 1990.



After
studying Germany, I worked with Balázs Lengyel on Hungarian data. Originally,
we could not find any regularity in the Hungarian data, but then the idea arose
to analyze the Hungarian data as three different innovation systems: one around
Budapest, which is a metropolitan innovation system; one in the west of the
country, which has been incorporated into Western Europe; and one in the east
of the country, which has remained the old innovation system that is state-led
and dependent on subsidies. For the western part, one could say that Hungary
has been "europeanized" by Austria and Germany; it has become part of a
European system.



When
Hungary came into the position to create a national
innovation system, free from Russia and the Comecon, it was too late, as
Europeanization had already stepped in and national boundaries were no longer
as dominant. Accordingly, and this was a very nice result, assessing this
synergy indicator on Hungary as a nation, we did not find additional synergy at
the national (that is, above-regional) level. While we clearly found synergy at
the national level for the Netherlands and also found it in Germany, but at the
level of the Federal States, we could not find synergy at a national level for
Hungary. Hungary has probably developed too late to develop a nationally
controlled system of innovations.



A
similar phenomenon appeared when we studied Norway: my Norwegian colleague
(Øivind Strand) did most of our analysis there. To our surprise, the
knowledge-based economy was not generated where the universities are located (Oslo
and Trondheim), but on the West Coast, where the off-shore, marine and maritime
industries are most dominant. FDI (foreign direct investment) in the marine and
maritime industries leads to knowledge-based synergy in the regions on the West
Shore of Norway. Norway is still a national system, but the Norwegian
universities like Trondheim or Oslo are not so much involved in entrepreneurial
networks. These are traditional universities, which tend to keep their hands
off the economy.



Actually,
when we had discussions about these two cases, Norway and Hungary, which both
show that internationalization had become a major factor, either in the form of
Europeanization in the Hungarian case, or in the form of foreign-driven
investments (off-shore industry and oil companies) in the Norwegian case, I
became uncertain and asked myself whether we did not believe too much in our
indicators? Therefore, I proposed to Øivind to study Sweden, given the availability
of well-organized data of this national system.



We
expected to find synergy concentrated in the three regional systems of
Stockholm, Gothenburg, and Malmö/Lund. Indeed, 48.5 percent of the Swedish
synergy is created in these three regions. This is more than one would expect
on the basis of the literature. Some colleagues were upset, because they had
already started trying to work on new developments of the Triple Helix, for
example, in Linköping. But the Swedish economy is organized and centralized in
this geographical dimension. Perhaps that is why one talks so much about
"regionalization" in policy documents. Sweden is very much a national
innovation system, with additional synergy between the regions.





Can governments alter
historical trajectories of national, regional or local innovation systems?



Let
me mention the empirical results for China in order to illustrate the
implications of empirical conclusions for policy options. We had no Chinese
data set, but we obtained access to the database Orbis of the Bureau van Dijk
(an international company, which is Wall Street oriented, assembling data about
companies) that contains industry indicators such as names, addresses,
NACE-codes, types of technology, the sizes of each enterprise, etc. However,
this data can be very incomplete. Using this incomplete data for China, we said
that we were just going to show how one could do the analysis  if one had full data. We guess that the
National Bureau of Statistics of China has complete data.
I did the analysis with Ping Zhou, Professor at Zhejiang University.



We
analyzed China first at the provincial level, and as expected, the East Coast
emerged as much more knowledge intense than the rest of the country. After
that, we also looked at the next-lower level of the 339 prefectures of China.
From this analysis, four of them popped up as far more synergetic than the
others. These four municipalities were: Beijing, Shanghai, Tianjin, and
Chongqing.



These
four municipalities became clearly visible as an order of magnitude more
synergetic than other regions. The special characteristic about them is that –as
against the others – these four municipalities are administered by the central
government. Actually, it came out of my data and I did not understand it; but
my Chinese colleague said that this result was very nice and specified this
relationship.



The
Chinese case thus illustrates that government control can make a difference. It
shows – and that is not surprising, as China runs on a different model – that
the government is able to organize the four municipalities in such a way as to
increase synergy. Of course, I do not know what is happening on the ground. We
know that the Chinese system is more complex than these three dimensions
suggest. I guess the government agencies may wish to consider the option of
extending the success of this development model, to Guangdong for example or to
other parts of China. Isn't it worrisome that all the other and less controlled
districts have not been as successful in generating synergy?



Referring
more generally to innovation policies, I would advise as a heuristics that
political discourse is able to signal a problem, but policy questions do not
enable us to analyze the issues. Regional development, for example, is an issue
in Sweden because the system is very centralized, more than in Norway, for
example. But there is nothing in our data that supports the claim that the
Swedish government is successful in decentralizing the knowledge-based economy
beyond the three metropolitan regions. We may be able to reach conclusions like
these serving as policy advice. One develops policies on the basis of intuitive
assumptions which a researcher is sometimes able to test.



As
noted, one can expect a complex system continuously to produce unintended
consequences, and thus it needs monitoring. The dynamics of the system are
different from the sum of the sub-dynamics because of the interaction effects
and feedback loops. Metaphors such as a Triple Helix, Mode-2, or the Risk
Society can be stimulating for the discourse, but these metaphors tend to develop
their own dynamics of proliferating discourses.



The
Triple Helix, for example, can first be considered as a call for collaboration
in networks of institutions. However, in an ecosystem of bi-lateral and
tri-lateral relations, one has a trade-off between local integration
(collaboration) and global differentiation (competition). The markets and the
sciences develop at the global level, above the level of specific relations. A
principal agent such as government may be locked into a suboptimum. Institutional
reform that frees the other two dynamics (markets and sciences) requires
translation of political legitimation into other codes of communication. Translations
among codes of communication provide the innovation engine.





Is there a connection
between infrastructures and the success of innovation processes?



One
of the conclusions, which pervades throughout all advanced economies, is that
knowledge intensive services (KIS) are
not synergetic locally because they can be disconnected – uncoupled – from the
location. For example, if one offers a knowledge-intensive service in Munich
and receives a phone call from Hamburg, the next step is to take a plane to
Hamburg, or to catch a train inside Germany perhaps. Thus, it does not matter
whether one is located in Munich or Hamburg as knowledge-intensive services
uncouple from the local economy. The main point is proximity to an airport or
train station.



This
is also the case for high-tech knowledge-based manufacturing. But it is
different for medium-tech manufacturing, because in this case the dynamics are
more embedded in the other parts of the economy. If one looks at Russia, the
knowledge-intensive services operate differently from the Western European
model, where the phenomenon of uncoupling takes place. In Russia, KIS
contribute to coupling, as knowledge-intensive services are related to state
apparatuses.



In
the Russian case, the knowledge-based economy is heavily concentrated in Moscow
and St. Petersburg. So, if one aims –as the Russian government proclaims – to create
not "wealth from knowledge" but "knowledge from wealth" – that is, oil revenues
–it might be wise to uncouple the knowledge-intensive services from the state
apparatuses. Of course, this is not easy to do in the Russian model because
traditionally, the center (Moscow) has never done this. Uncoupling
knowledge-intensive services, however, might give them a degree of freedom to
move around, from Tomsk to Minsk or vice
versa, steered by economic forces more than they currently are (via institutions
in Moscow).





Final question. What does path-dependency mean in the context of
innovation dynamics?



In
The Challenge of Scientometrics. The development, measurement, and
self-organization of scientific communications (1995), I used Shannon-type information theory to study
scientometric problems, as this methodology combines both static and dynamic
analyses. Connected to this theory I developed a measurement method for
path-dependency and critical transitions.



In
the case of a radio transmission, for example, you have a sender and a
receiver, and in between you may have an auxiliary station. For instance, the
sender is in New York and the receiver is in Bonn and the auxiliary station is
in Iceland. The signal emerges in New York and travels to Bonn, but it may be possible
to improve the reception by assuming the signal is from Iceland instead of
listening to New York. When Iceland provides a better signal, it is possible to
forget the history of the signal before it arrived in Island. It no longer
matters whether Iceland obtained the signal originally from New York or Boston.
One takes the signal from Iceland and the pre-history of the signal does not
matter anymore for a receiver.



Such
a configuration provides a path-dependency (on Iceland) in
information-theoretical terms, measurable in terms of bits of information. In a
certain sense you get negative bits of information, since the shortest path in
the normal triangle would be from New York to Bonn, and in this case the
shortest path is from New York via Iceland to Bonn. I called this at the time a
critical transition. In a scientific text for instance, a new terminology can
come up and if it overwrites the old terminology to the extent that one does
not have to listen to the old terminology anymore, one has a critical
transition that frees one from the path-dependencies at a previous moment of
time.



Thus,
my example is about radical and knowledge-based changes. As long as one has to
listen to the past, one does not make a critical transition. The knowledge-based
approach is always about creative destruction and about moving ahead,
incorporating possible new options in the future. The hypothesized future
states become more important than the past. The challenge, in my opinion, is to
make the notion of options operational and to bring these ideas into
measurement. The Triple-Helix indicator measures the number of possible options
as additional redundancy. This measurement has the additional advantage that one
becomes sensitive to uncertainty in the prediction.





Loet Leydesdorff is Professor Emeritus at the Amsterdam School of Communications Research (ASCoR) of the University of Amsterdam. He is Honorary Professor of the Science and Technology Policy Research Unit (SPRU) of the University of Sussex, Visiting Professor at the School of Management, Birkbeck, University of London, Visiting Professor of the Institute of Scientific and Technical Information of China (ISTIC) in Beijing, and Guest Professor at Zhejiang University in Hangzhou. He has published extensively in systems theory, social network analysis, scientometrics, and the sociology of innovation (see at http://www.leydesdorff.net/list.htm). With Henry Etzkowitz, he initiated a series of workshops, conferences, and special issues about the Triple Helix of University-Industry-Government Relations. He received the Derek de Solla Price Award for Scientometrics and Informetrics in 2003 and held "The City of Lausanne" Honor Chair at the School of Economics, Université de Lausanne, in 2005. In 2007, he was Vice-President of the 8th International Conference on Computing Anticipatory Systems (CASYS'07, Liège). In 2014, he was listed as a highly-cited author by Thomson Reuters. 





Literature and Related
links:



Science & Technology Dynamics,
University of Amsterdam / Amsterdam School of Communications
Research (ASCoR) 


Leydesdorff,
L. (2006). The Knowledge-Based Economy: Modeled, Measured, Simulated. Universal Publishers, Boca Raton, FL.


Leydesdorff, L. (2001). A Sociological Theory of Communication: The Self-Organization of the
Knowledge-Based Society. Universal Publishers, Boca Raton, FL.


Leydesdorff,
L. (1995). The Challenge of Scientometrics . The development, measurement, and
self-organization of scientific communications. Leiden, DSWO Press, Leiden University.


http://www.leydesdorff.net/





Print version of this Talk (pdf)



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So, who from Louisiana's political left is right
about the morass of the state's Democrats? The veteran political analyst who
foresees the light at the end of the tunnel as very distant? Or the academician
who thinks the party's political fortunes can improve dramatically?

As
part of his television gig, longtime editor of the shopper New Orleans
Gambit – no longer a shopper since The Advocate chain gulped it up a few
years ago – Clancy DuBos doesn't see much hope for the party that ruled the
state uncontested starting over a century ago for six decades, and still was in
the majority until about 15 years. He declared the party on "life support" and,
boldly asserting perhaps the surest thing in state political history, foresaw a
major shakeup in state party leadership within the next few months.

That's axiomatic for a state party with a single
out of eight members of Congress, without a single statewide executive, standing
on the wrong sides of supermajorities in each legislative chamber, soon to be
down 9-2 on the Board of Elementary and Secondary Education, and in three years
likely to lose ground on the one elected body where it isn't in a steep minority,
the Public Service Commission. Having no candidate come within 25 points of
Republican winners in any statewide race and ceding even more supermajority
ground to the GOP in the Legislature as a result of this year's election makes leadership
change a question not of if, but of when.

Possibly the party's state central committee will
act sooner, at its next quarterly meeting, to dump current Chairwoman Katie Bernhardt
and others. Being that they are the ones that put her there originally, they
may not and concentrate instead on winning reelection next spring and then have
the new group make the change.

Regardless of when, expect its happening to eject
from leadership the final vestiges of the rent-seeking/trail lawyer/courthouse
liberal populist gang of whites lording over the party. The facts are that of all
the 48 state office elected Democrats – two on the PSC, two on BESE, 11 in the
Senate, and 33 in the House – all but seven are black, and blacks comprise 61
percent of the party registrants. Black political elites must take primary
control of the party to help shape candidacies that will attract a majority black
base that will inspire a turnout that among that base which likely was below 20
percent in the general election runoff.

On the point that new, if unspecified other than
it needs to raise more money, leadership is needed, Dillard University
professor Robert Collins agrees.
Yet he thinks, with that in hand, there's a way forward for Democrats, based
upon observations of other odd-year state election results. Specifically, he
views the success of an amendment to Ohio's constitution to make abortion less
restricted, of Virginia Democrats' ability to stave off further Republican
gains there in legislative elections, and Kentucky Democrat Gov. Andy Beshear to
win narrowly reelection as object lessons towards reinvigorating Louisiana
Democrats.

However, there's much less to the eye here than he
argues. First, Louisiana is not a swing state like Ohio – slightly red – or
Viriginia – slightly blue. It's a solidly center-right state slowly becoming less
of the former and more of the latter. So, among the three states, only Kentucky
is comparable.

That doesn't mean the issue of state regulations
on abortion can't be used as a wedge to pry some voters away from Republicans. Except
that Collins misreads the inherent power of that issue not just in Louisiana,
but nationally. Ever since the U.S. Supreme Court (rightfully through one of
the most
erudite decisions in its history) disabused the notion that the Constitution
contained a right to snuff the unborn, the degree to which only constrained by
state action within the bounds of an incoherent Court decision made a
half-century ago, now with states empowered to decide abortion's boundaries they
have engaged in an equilibrium exercise to align their laws with their people's
prevailing moral beliefs as enunciated through their elected representatives or
through instruments of direct democracy.

Since the decision, states have wandered their ways
towards their individual median preferences. Soon, that will resolve and the
issue will cease to grant either political party more than a miniscule
advantage or disadvantage, which will include Louisiana because it pretty much
rested at equilibrium from the moment the decision came down.

Collins mistakenly doesn't think so, citing a
recent poll (and he could have gone with another
a bit older) showing slightly more Louisianans oppose the current law that
allows for abortions only in the case of a threat to the mother's physical health
or is unviable than support it, using this factoid to argue that a Democrat running
hard on the issue to loosen restrictions could gain major traction.

The problem with this is abortion for decades
among Louisianans (and nationally) has been far down the list of voter concerns.
Most recently, issues towards the top (from the poll Collins cited) swing very
much against Democrats, and in Louisiana in particular because the negative
outcomes the state experiences on these come precisely from decades of governance
by liberal Democrat populists – and voters increasingly are acknowledging that
role in the state's economic destruction.

Running hard on liberalizing abortion in Louisiana
– often described as the most
pro-life state in America and with the oldest and deepest Catholic roots of
any – is a fool's errand. It will hardly move the needle in a state suffering depopulation,
economic development running behind almost all others, and educational quality
still lagging just about any other. (As shown in the Senate District 12 race last
month where an avowedly
pro-abortion candidate lost 78-13 percent.)

Nor can the lesson in the one state Collins mentioned
with a similar political environment to Louisiana, Kentucky and the Democrat Beshear
win, translate to Louisiana Democrats. What Collins doesn't know or
disregards is Beshear won only because his last name is Beshear. His father
having been governor from 2007-15 and the last name on state ballots 15 times
in the last 44 years, the dynastic familiarity with the name made him an
extreme outlier in a system that in every other way mirrors Louisiana –
supermajorities in the state legislature and Republicans controlling every
other statewide office.

There's no such Democrat in Louisiana now or for the
foreseeable future. And almost certainly in Kentucky in 2027, when Beshear is
term-limited, we'll see a Jeff Landry-like
Republican seize the office to give the Kentucky GOP a clean sweep. In essence –
in one of the few instances where Louisiana isn't behind the times now –
Kentucky is four years behind Louisiana.

DuBos, running against type over the past couple
of decades, is right: Louisiana Democrats have no immediate hope of becoming a
relevant party again. But he does miss the caveat: unless they make a concerted
effort to move closer to the median voter. Since the election of Democrat Pres.
Barack
Obama, the party has emulated its national level, becoming shriller as its
leadership sprinted to the far left, embracing tighter identity politics and conspiratorial
economics.

The ensuing trickle down to its candidates gushes
precisely against the prescriptions of its waning Great Society base who argue
any platform that doesn't put first and foremost, beyond any other issue such
as climate alarmism, defunding police, gender affirmation, etc., economic policy
to address working class concerns will not win elections. That goes triple in
Louisiana, where the irony is the population already is sensitized to the folly
of the economic policies these liberals have stumped for since the Great
Society.

Moving towards the Louisiana median voter will be
a hard thing for the party to do with all the pressure coming from the national
party that predicates its issue preferences on what New York, Illinois, and
California Democrats want. But pulling rabbit candidates out of hats, pinning
hopes on insignificant single issues, or pining for leadership that is just old
wine in new bottles won't make it; shedding radicalism is the only hope for
Louisiana Democrats to gain anything but episodic and rarely consequential
influence over policy-making in the state.

This post takes up from two previous posts (part 1;  part 2), asking just what do we (we economists) really know about how interest rates affect inflation. Today, what does contemporary economic theory say? As you may recall, the standard story says that the Fed raises interest rates; inflation (and expected inflation) don't immediately jump up, so real interest rates rise; with some lag, higher real interest rates push down employment and output (IS); with some more lag, the softer economy leads to lower prices and wages (Phillips curve). So higher interest rates lower future inflation, albeit with "long and variable lags." Higher interest rates -> (lag) lower output, employment -> (lag) lower inflation. In part 1, we saw that it's not easy to see that story in the data. In part 2, we saw that half a century of formal empirical work also leaves that conclusion on very shaky ground. As they say at the University of Chicago, "Well, so much for the real world, how does it work in theory?" That is an important question. We never really believe things we don't have a theory for, and for good reason. So, today, let's look at what modern theory has to say about this question. And they are not unrelated questions. Theory has been trying to replicate this story for decades. The answer: Modern (anything post 1972) theory really does not support this idea. The standard new-Keynesian model does not produce anything like the standard story.  Models that modify that simple model to achieve something like result of the standard story do so with a long list of complex ingredients. The new ingredients are not just sufficient, they are (apparently) necessary to produce the desired dynamic pattern. Even these models do not  implement the verbal logic above. If the pattern that high interest rates lower inflation over a few years is true, it is by a completely different mechanism than the story tells. I conclude that we don't have a simple economic model that produces the standard belief. ("Simple" and "economic" are important qualifiers.) The simple new-Keynesian model The central problem comes from the Phillips curve. The modern Phillips curve asserts that price-setters are forward-looking. If they know inflation will be high next year, they raise prices now. So Inflation today = expected inflation next year + (coefficient) x output gap.  \[\pi_t = E_t\pi_{t+1} + \kappa x_t\](If you know enough to complain about \(\beta\approx0.99\) in front of \(E_t\pi_{t+1}\) you know enough that it doesn't matter for the issues here.)Now, if the Fed raises interest rates, and if (if) that lowers output or raises unemployment, inflation today goes down. The trouble is, that's not what we're looking for. Inflation goes down today, (\(\pi_t\))relative to expected inflation next year (\(E_t\pi_{t+1}\)). So a higher interest rate and lower output correlate with inflation that is rising over time.    Here is a concrete example: The plot is the response of the standard three equation new-Keynesian model to an \(\varepsilon_1\) shock at time 1:\[\begin{align} x_t &= E_t x_{t+1} - \sigma(i_t - E_t\pi_{t+1}) \\ \pi_t & = \beta E_t \pi_{t+1} + \kappa x_t \\ i_t &= \phi \pi_t + u_t \\ u_t &= \eta u_{t-1} + \varepsilon_t. \end{align}\] Here \(x\) is output, \(i\) is the interest rate, \(\pi\) is inflation, \(\eta=0.6\), \(\sigma=1\), \(\kappa=0.25\), \(\beta=0.95\), \(\phi=1.2\). In this plot, higher interest rates are said to lower inflation. But they lower inflation immediately, on the day of the interest rate shock. Then, as explained above, inflation rises over time. In the standard view, and the empirical estimates from the last post, a higher interest rate has no immediate effect, and then future inflation is lower. See plots in the last post, or this one from Romer and Romer's 2023 summary:Inflation jumping down and then rising in the future is quite different from inflation that does nothing immediately, might even rise for a few months, and then starts gently going down. You might even wonder about the downward jump in inflation. The Phillips curve makes it clear why current inflation is lower than expected future inflation, but why doesn't current inflation stay the same, or even rise, and expected future inflation rise more? That's the "equilibrium selection" issue. All those paths are possible, and you need extra rules to pick a particular one. Fiscal theory points out that the downward jump needs a fiscal tightening, so represents a joint monetary-fiscal policy. But we don't argue about that today. Take the standard new Keynesian model exactly as is, with passive fiscal policy and standard equilibrium selection rules. It predicts that inflation jumps down immediately and then rises over time. It does not predict that inflation slowly declines over time.  This is not a new issue. Larry Ball (1994) first  pointed out that the standard new Keynesian Phillips curve says that output is high when inflation is high relative to expected future inflation, that is when inflation is declining. Standard beliefs  go the other way: output is high when inflation is rising.  The IS curve is a key part of the overall prediction, and output faces a similar problem. I just assumed above that output falls when interest rates rise. In the model it does; output follows a path with the same shape as inflation in my little plot. Output also jumps down and then rises over time. Here too, the (much stronger) empirical evidence says that an interest rate rise does not change output immediately, and output then falls rather than rises over time. The intuition has even clearer economics behind it: Higher real interest rates induce people to consume less today and more tomorrow. Higher real interest rates should go with higher, not lower, future consumption growth. Again, the model only apparently reverses the sign by having output jump down before rising. Key issuesHow can we be here, 40 years later, and the benchmark textbook model so utterly does not replicate standard beliefs about monetary policy? One answer, I believe, is confusing adjustment to equilibrium with equilibrium dynamics. The model generates inflation lower than yesterday (time 0 to time 1) and lower than it otherwise would be (time 1 without shock vs time 1 with shock). Now, all economic models are a bit stylized. It's easy to say that when we add various frictions, "lower than yesterday" or "lower than it would have been" is a good parable for "goes down over time."  If in a simple supply and demand graph we say that an increase in demand raises prices instantly, we naturally understand that as a parable for a drawn out period of price increases once we add appropriate frictions. But dynamic macroeconomics doesn't work that way. We have already added what was supposed to be the central friction, sticky prices. Dynamic economics is supposed to describe the time-path of variables already, with no extra parables. If adjustment to equilibrium takes time, then model that.  The IS and Phillips curve are forward looking, like stock prices. It would make little sense to say "news comes out that the company will never make money, so the stock price should decline gradually over a few years." It should jump down now. Inflation and output behave that way in the standard model. A second confusion, I think, is between sticky prices and sticky inflation. The new-Keynesian model posits, and a huge empirical literature examines, sticky prices. But that is not the same thing as sticky inflation. Prices can be arbitrarily sticky and inflation, the first derivative of prices, can still jump. In the Calvo model, imagine that only a tiny fraction of firms can change prices at each instant. But when they do, they will change prices a lot, and the overall price level will start increasing right away. In the continuous-time version of the model, prices are continuous (sticky), but inflation jumps at the moment of the shock.  The standard story wants sticky inflation. Many authors explain the new-Keynesian model with sentences like "the Fed raises interest rates. Prices are sticky, so inflation can't go up right away and real interest rates are higher." This is wrong. Inflation can rise right away. In the standard new-Keynesian model it does so with \(\eta=1\), for any amount of price stickiness. Inflation rises immediately with a persistent monetary policy shock. Just get it out of your heads. The standard model does not produce the standard story. The obvious response is, let's add ingredients to the standard model and see if we can modify the response function to look something like the common beliefs and VAR estimates. Let's go. Adaptive expectations We can reproduce standard beliefs about monetary policy with thoroughly adaptive expectations, in the 1970s ISLM form. I think this is a large part of what  most policy makers and commenters have in mind.  Modify the above model to leave out the dynamic part of the intertemporal substitution equation, to just say in rather ad hoc way that higher real interest rates lower output, and specify that the expected inflation that drives the real rate and that drives pricing decisions is mechanically equal to previous inflation, \(E_t \pi_{t+1} = \pi_{t-1}\). We get \[ \begin{align} x_t &= -\sigma (i_t - \pi_{t-1}) \\ \pi_t & = \pi_{t-1} + \kappa x_t .\end{align}\] We can solve this sytsem analytically to \[\pi_t = (1+\sigma\kappa)\pi_{t-1} - \sigma\kappa i_t.\]Here's what happens if the Fed permanently raises the interest rate. Higher interest rates send future inflation down. (\(\kappa=0.25,\ \sigma=1.\)) Inflation eventually spirals away, but central banks don't leave interest rates alone forever. If we add a Taylor rule response \(i_t = \phi \pi_t + u_t\),  so the central bank reacts to the emerging spiral, we get this response to a permanent monetary policy disturbance \(u_t\): The higher interest rate sets off a deflation spiral. But the Fed quickly follows inflation down to stabilize the situation. This is, I think, the conventional story of the 1980s. In terms of ingredients, an apparently minor change of index from \(E_t \pi_{t+1}\) to \(\pi_{t-1}\) is in fact a big change. It means directly that higher output comes with increasing inflation, not decreasing inflation, solving Ball's puzzle.  The change basically changes the sign of output in the Phillips curve. Again, it's not really all in the Phillips curve. This model with rational expectations in the IS equation and adaptive in the Phillips curve produces junk. To get the result you need adaptive expectations everywhere. The adaptive expectations model gets the desired result by changing the basic sign and stability properties of the model. Under rational expectations the model is stable; inflation goes away all on its own under an interest rate peg. With adaptive expectations, the model is unstable. Inflation or deflation spiral away under an interest rate peg or at the zero bound. The Fed's job is like balancing a broom upside down. If you move the bottom (interest rates) one way, the broom zooms off the other way. With rational expectations, the model is stable, like a pendulum.  This is not a small wrinkle designed to modify dynamics. This is major surgery. It is also a robust property: small changes in parameters do not change the dominant eigenvalue of a model from over one to less than one.  A more refined way to capture how Fed officials and pundits think and talk might be called "temporarily fixed expectations." Policy people do talk about the modern Phillips curve; they say inflation depends on inflation expectations and employment. Expectations are not mechanically adaptive. Expectations are a third force, sometimes "anchored," and amenable to manipulation by speeches and dot plots. Crucially, in this analysis, expected inflation does not move when the Fed changes interest rates.  Expectations are then  very slowly adaptive, if inflation is persistent, or if there is a more general loss of faith in "anchoring." In the above new-Keynesian model graph, at the minute the Fed raises the interest rate, expected inflation jumps up to follow the graph's plot of the model's forecast of inflation. As a simple way to capture these beliefs, suppose expectations are fixed or "anchored" at \(\pi^e\). Then my simple model is \[\begin{align}x_t & = -\sigma(i_t - \pi^e) \\ \pi_t & = \pi^e + \kappa x_t\end{align}\]so \[\pi_t = \pi^e - \sigma \kappa (i_t - \pi^e).\] Inflation is expected inflation, and lowered by higher interest rates (last - sign). But those rates need only be higher than the fixed expectations; they do not need to be higher than past rates as they do in the adaptive expectations model. That's why the Fed thinks 3% interest rates with 5% inflation is still "contractionary"--expected inflation remains at 2%, not the 5% of recent adaptive experience.  Also by fixing expectations, I remove the instability of the adaptive expectations model... so long as those expectations stay anchored. The Fed recognizes that eventually higher inflation moves the expectations, and with a belief that is adaptive, they fear that an inflation spiral can still break out.Even this view does not give us any lags, however. The Fed and commenters clearly believe that higher real interest rates today lower output next year, not immediately; and they believe that lower output and employment today drive inflation down in the future, not immediately. They believe something like \[\begin{align}x_{t+1} &= - \sigma(i_t - \pi^e) \\ \pi_{t+1} &= \pi^e + \kappa x_t.\end{align}\] But now we're at the kind of non-economic ad-hockery that the whole 1970s revolution abandoned. And for a reason: Ad hoc models are unstable, regimes are always changing. Moreover, let me remind you of our quest: Is there a simple economic model of monetary policy that generates something like the standard view? At this level of ad-hockery you might as well just write down the coefficients of Romer and Romer's response function and call that the model of how interest rates affect inflation.  Academic economics gave up on mechanical expectations and ad-hoc models in the 1970s. You can't publish a paper with this sort of model. So when I mean a "modern" model, I mean  rational expectations, or at least the consistency condition that the expectations in the model are not fundamentally different from forecasts of the model. (Models with explicit learning or other expectation-formation frictions count too.) It's easy to puff about people aren't rational, and looking out the window lots of people do dumb things. But if we take that view, then the whole project of monetary policy on the proposition that people are fundamentally unable to learn patterns in the economy, that a benevolent Federal Reserve can trick the poor little souls into a better outcome.  And somehow the Fed is the lone super-rational actor who can avoid all those pesky behavioral biases. We are looking for the minimum necessary ingredients to describe the basic signs and function of monetary policy. A bit of irrational or complex expectation formation as icing on the cake, a possible sufficient ingredient to produce quantitatively realistic dynamics, isn't awful. But it would be sad if irrational expectations or other behavior is a necessary ingredient to get the most basic sign and story of monetary policy right. If persistent irrationality is a central necessary ingredient for the basic sign and operation of monetary policy -- if higher interest rates will raise inflation the minute people smarten up; if there is no simple supply and demand, MV=PY sensible economics underlying the basic operation of monetary policy; if it's all a conjuring trick  -- that should really weaken our faith in the whole monetary policy project.  Facts help, and we don't have to get religious about it. During the long zero bound, the same commentators and central bankers kept warning about a deflation spiral, clearly predicted by this model. It never happened. Interest rates below inflation from 2021 to 2023 should have led to an upward inflation spiral. It never happened -- inflation eased all on its own with interest rates below inflation.Getting the desired response to interest rates by making the model unstable isn't tenable whether or not you like the ingredient.  Inflation also surged in the 1970s faster than adaptive expectations came close to predicting, and fell faster in the 1980s.  The ends of many inflations come with credible changes in regime. There is a lot of work now desperately trying to fix new-Keynesian models by making them more old-Keynesian, putting lagged inflation in the Phillips curve, current income in the IS equation, and so forth. Complex learning and expectation formation stories replace the simplistic adaptive expectations here. As far as I can tell, to the extent they work they largely do so in the same way, by reversing the basic stability of the model. Modifying the new-Keynesian modelThe alternative is to add ingredients to the basic new-Keynesian model, maintaining its insistence on real "micro-founded" economics and forward-looking behavior, and describing explicit dynamics as the evolution of equilibrium quantities.  Christiano Eichenbaum and Evans (2005) is one of the most famous examples. Recall these same authors  created the first most influential VAR that gave the "right" answer to the effects of monetary policy shocks. This paper modifies the standard new-Keynesian model with a specific eye to matching impulse response functions. The want to match all impulse-responses, with a special focus on output. When I started asking my young macro colleagues for a standard model which produces the desired response shape, they still cite CEE first, though it's 20 years later. That's quite an accomplishment. I'll look at it in detail, as the general picture is the same as many other models that achieve the desired result. Here's their bottom line response to a monetary policy shock: (Figure from the 2018 Christiano Eichenbaum and Trabandt Journal of Economic Perspectives summary paper.)  The solid line is the VAR point estimate and gray shading is the 95% confidence band. The solid blue line is the main model. The dashed line is the model with only price stickiness, to emphasize the importance of wage stickiness. The shock happens at time 0. Notice the funds rate line that jumps down at that date. That the other lines do not move at time 0 is a result. I graphed the response to a time 1 shock above. That's the answer, now what's the question? What ingredients did they add above the textbook model to reverse the basic sign and jump problem and to produce  these pretty pictures? Here is a partial list: Habit formation. The utility function is  \(log(c_t - bc_{t-1})\). A capital stock with adjustment costs in investment.  Adjustment costs are proportional to investment growth, \([1-S(i_t/i_{t-1})]i_t\), rather than the usual formulation in which adjustment costs are proportional to the investment to capital ratio \(S(i_t/k_t)i_t\). Variable capital utilization. Capital services \(k_t\) are related to the capital stock \(\bar{k}t\) by \(k_t = u_t \bar{k}_t\). The utilization rate \(u_t\) is set by households facing an upward sloping cost \(a(u_t)\bar{k}_t\).Calvo pricing with indexation: Firms randomly get to reset prices, but firms that aren't allowed to reset prices do automatically raise prices at the rate of inflation.Prices are also fixed for a quarter. Technically, firms must post prices before they see the period's shocks.Sticky wages, also with indexation. Households are monopoly suppliers of labor, and set wages Calvo-style like firms. (Later papers put all households into a union which does the wage setting.) Wages are also indexed; Households that don't get to reoptimize their wage still raise wages following inflation. Firms must borrow working capital to finance their wage bill a quarter in advance, and thus pay a interest on the wage bill. Money in the utility function, and money supply control. Monetary policy is a change in the money growth rate, not a pure interest rate target. Whew! But which of these ingredients are necessary, and which are just sufficient? Knowing the authors, I  strongly suspect that they are all necessary to get the suite of results. They don't add ingredients for show. But they want to match all of the impulse response functions, not just the inflation response. Perhaps a simpler set of ingredients could generate the inflation response while missing some of the others. Let's understand what each of these ingredients is doing, which will help us to see (if) they are necessary and essential to getting the desired result. I see a common theme in habit formation, adjustment costs that scale by investment growth, and indexation. These ingredients each add a derivative; they take a standard relationship between levels of economic variables and change it to one in growth rates. Each of consumption, investment, and inflation is a "jump variable" in standard economics, like stock prices. Consumption (roughly) jumps to the present value of future income. The level of investment is proportional to the stock price in the standard q theory, and jumps when there is new information. Iterating forward the new-Keynesian Phillips curve \(\pi_t = \beta E_t \pi_{t+1} + \kappa x_t\), inflation jumps to the discounted sum of future output gaps, \(\pi_t = E_t \sum_{j=0}^\infty \beta^jx_{t+j}.\)  To produce responses in which output, consumption and investment as well as inflation rise slowly after a shock, we don't want levels of consumption, investment, and inflation to jump this way. Instead we want growth rates to do so. With standard utility, the consumer's linearized first order condition equates expected consumption growth to the interest rate, \( E_t (c_{t+1}/c_t) = \delta + r_t \) Habit, with \(b=1\) gives  \( E_t [(c_{t+1}-c_t)/(c_t-c_{t-1})] = \delta + r_t \). (I left out the strategic terms.) Mixing logs and levels a bit, you can see we put a growth rate in place of a level. (The paper has \(b=0.65\) .) An investment adjustment cost function with \(S(i_t/i_{t-1})\) rather than the standard \(S(i_t/k_t)\) puts a derivative in place of a level. Normally we tell a story that if you want a house painted, doubling the number of painters doesn't get the job done twice as fast because they get in each other's way. But you can double the number of painters overnight if you want to do so. Here the cost is on the increase in number of painters each day.   Indexation results in a Phillips curve with a lagged inflation term, and that gives "sticky inflation."  The Phillips curve of the model (32) and (33) is \[\pi_t = \frac{1}{1+\beta}\pi_{t-1} + \frac{\beta}{1+\beta}E_{t-1}\pi_{t+1} + (\text{constants}) E_{t-1}s_t\]where \(s_t\) are marginal costs (more later). The \(E_{t-1}\) come from the assumption that prices can't react to time \(t\) information. Iterate that forward to (33)\[\pi_t - \pi_{t-1} = (\text{constants}) E_{t-1}\sum_{j=0}^\infty \beta^j s_{t+j}.\] We have successfully put the change in inflation in place of the level of inflation. The Phillips curve is anchored by real marginal costs, and they are not proportional to output in this model as they are in the textbook model above. That's important too. Instead,\[s_t = (\text{constants}) (r^k_t)^\alpha \left(\frac{W_t}{P_t}R_t\right)^{1-\alpha}\] where \(r^k\) is the return to capital \(W/P\) is the real wage and \(R\) is the nominal interest rate. The latter term crops up from the assumption that firms must borrow the wage bill one period in advance. This is an interesting ingredient. There is a lot of talk that higher interest rates raise costs for firms, and they are reducing output as a result. That might get us around some of the IS curve problems. But that's not how it works here. Here's how I think it works. Higher interest rates raise marginal costs, and thus push up current inflation relative to expected future inflation. The equilibrium-selection rules and the rule against instant price changes (coming up next) tie down current inflation, so the higher interest rates have to push down expected future inflation. CEE disagree (p. 28). Writing of an interest rate decline, so all the signs are opposite of my stories,  ... the interest rate appears in firms' marginal cost. Since the interest rate drops after an expansionary monetary policy shock, the model embeds a force that pushes marginal costs down for a period of time. Indeed, in the estimated benchmark model the effect is strong enough to induce a transient fall in inflation.But pushing marginal costs down lowers current inflation relative to future inflation -- they're looking at the same Phillips curve just above. It looks to me like they're confusing current with expected future inflation. Intuition is hard. There are plenty of Fisherian forces in this model that want lower interest rates to lower inflation. More deeply,  we see here a foundational trouble of the Phillips curve. It was originally a statistical relation between wage inflation and unemployment. It became a (weaker) statistical relation between price inflation and unemployment or the output gap. The new-Keynesian theory wants naturally to describe a relation between marginal costs and price changes, and it takes contortions to make output equal to marginal costs. Phillips curves fit the data terribly. So authors estimating Phillips curves (An early favorite by Tim Cogley and Argia Sbordone) go back, and separate marginal cost from output or employment. As CET write later, they "build features into the model which ensure that firms' marginal costs are nearly acyclical." That helps the fit, but it divorces the Phillips curve shifter variable from the business cycle! Standard doctrine says that for the Fed to lower inflation it must soften the economy and risk unemployment. Doves say don't do it, live with inflation to avoid that cost. Well, if the Phillips curve shifter is "acyclical" you have to throw all that out the window.  This shift also points to the central conundrum of the Phillips curve. Here it describes the adjustment of prices to wages or "costs" more generally. It fundamentally describes a relative price, not a price level. OK, but the phenomenon we want to explain is the common component, how all prices and wage tie together or equivalently the decline in the value of the currency, stripped of relative price movements. The central puzzle of macroeconomics is why the common component, a rise or fall of all prices and wages together, has anything to do with output, and for us how it is controlled by the Fed. Christiano Eichenbaum and Evans write (p.3) that "it is crucial to allow for variable capital utilization." I'll try explain  why in my own words. Without capital adjustment costs, any change in the real return leads to a big investment jump. \(r=f'(k)\) must jump and that takes a lot of extra \(k\). We add adjustment costs to tamp down the investment response. But now when there is any shock, capital can't adjust enough and there is a big rate of return response. So we need something that acts like a big jump in the capital stock to tamp down \(r=f'(k)\) variability, but not a big investment jump. Variable capital utilization acts like the big investment jump without us seeing a big investment jump. And all this is going to be important for inflation too. Remember the Phillips curve; if output jumps then inflation jumps too. Sticky wages are crucial, and indeed CEE report that they can dispense with sticky prices. One reason is that otherwise profits are countercyclical. In a boom, prices go up faster than wages so profits go up. With sticky prices and flexible wages you get the opposite sign. It's interesting that the "textbook" model has not moved this way. Again, we don't often enough write textbooks. Fixing prices and wages during the period of the shock by assuming price setters can't see the shock for a quarter has a direct effect: It stops any price or wage jumps during the quarter of the shock, as in my first graph. That's almost cheating. Note the VAR also has absolutely zero instantaneous inflation response. This too is by assumption. They "orthogonalize" the variables so that all the contemporaneous correlation between monetary policy shocks and inflation or output is considered part of the Fed's "rule" and none of it reflects within-quarter reaction of prices or quantities to the Fed's actions. Step back and admire. Given the project "find elaborations of the standard new-Keynesian model to match VAR impulse response functions" could you have come up with any of this? But back to our task. That's a lot of apparently necessary ingredients. And reading here or CEE's verbal intuition, the logic of this model is nothing like the standard simple intuition, which includes none of the necessary ingredients. Do we really need all of this to produce the basic pattern of monetary policy? As far as we know, we do. And hence, that pattern may not be as robust as it seems. For all of these ingredients are pretty, ... imaginative. Really, we are a long way from the Lucas/Prescott vision that macroeconomic models should be based on well tried and measured microeconomic ingredients that are believably invariant to changes in the policy regime. CEE argue hard for the plausibility of these microeconomic specifications (see especially the later CET Journal of Economic Perspectives article), but they have to try so hard precisely because the standard literature doesn't have any of these ingredients. The "level" rather than "growth rate" foundations of consumption, investment, and pricing decisions pervade microeconomics. Microeconomists worry about labor monopsony, not labor monopoly; firms set wages, households don't. (Christiano Eichenbam and Trabandt (2016) get wage stickiness from a more realistic search and matching model. Curiously, the one big labor union fiction is still the most common, though few private sector workers are unionized.) Firms don't borrow the wage bill a quarter ahead of time.  Very few prices and wages are indexed in the US. Like habits, perhaps these ingredients are simple stand ins for something else, but at some point we need to know what that something else is. That is especially true if one wants to do optimal policy or welfare analysis. Just how much economics must we reinvent to match this one response function? How far are we really from the ad-hoc ISLM equations that Sims (1980) destroyed? Sadly, subsequent literature doesn't help much (more below). Subsequent literature has mostly added ingredients, including heterogeneous agents (big these days), borrowing constraints, additional financial frictions (especially after 2008), zero bound constraints, QE, learning and complex expectations dynamics. (See CET 2018 JEP  for a good verbal survey.) The rewards in our profession go to those who add a new ingredient. It's very hard to publish papers that strip a model down to its basics. Editors don't count that as "new research," but just "exposition" below the prestige of their journals. Though boiling a model down to essentials is maybe more important in the end than adding more bells and whistles. This is about where we are. Despite the pretty response functions, I still score that we don't have a reliable, simple, economic model that produces the standard view of monetary policy. Mankiw and Reis, sticky expectations Mankiw and Reis (2002) expressed the challenge clearly over 20 years ago. In reference to the "standard" New-Keynesian Phillips curve \(\pi_t = \beta E_t \pi_{t+1} + \kappa x_t\) they write a beautiful and succinct paragraph: Ball [1994a] shows that the model yields the surprising result that announced, credible disinflations cause booms rather than recessions. Fuhrer and Moore [1995] argue that it cannot explain why inflation is so persistent. Mankiw [2001] notes that it has trouble explaining why shocks to monetary policy have a delayed and gradual effect on inflation. These problems appear to arise from the same source: although the price level is sticky in this model, the inflation rate can change quickly. By contrast, empirical analyses of the inflation process (e.g., Gordon [1997]) typically give a large role to "inflation inertia."At the cost of repetition, I emphasize the last sentence because it is so overlooked. Sticky prices are not sticky inflation. Ball already said this in 1994: Taylor (1979, 198) and Blanchard (1983, 1986) show that staggering produces inertia in the price level: prices just slowly to a fall in th money supply. ...Disinflation, however, is a change in the growth rate of money not a one-time shock to the level. In informal discussions, analysts often assume that the inertia result carries over from levels to growth rates -- that inflation adjusts slowly to a fall in money growth. As I see it, Mankiw and Reis generalize the Lucas (1972) Phillips curve. For Lucas, roughly, output is related to unexpected inflation\[\pi_t = E_{t-1}\pi_t + \kappa x_t.\] Firms don't see everyone else's prices in the period. Thus, when a firm sees an unexpected rise in prices, it doesn't know if it is a higher relative price or a higher general price level; the firm expands output based on how much it thinks the event might be a relative price increase.  I love this model for many reasons, but one, which seems to have fallen by the wayside, is that it explicitly founds the Phillips curve in firms' confusion about relative  prices vs. the price level, and thus faces up to the problem why should a rise in the price level have any real effects. Mankiw and Reis basically suppose that firms find out the general price level with lags, so output depends on inflation relative to a distributed lag of its expectations. It's clearest for the price level (p. 1300)\[p_t = \lambda\sum_{j=0}^\infty (1-\lambda)^j E_{t-j}(p_t + \alpha x_t).\] The inflation expression is \[\pi_t = \frac{\alpha \lambda}{1-\lambda}x_t + \lambda \sum_{j=0}^\infty (1-\lambda)^j E_{t-1-j}(\pi_t + \alpha \Delta x_t).\](Some of the complication is that you want it to be \(\pi_t = \sum_{j=0}^\infty E_{t-1-j}\pi_t + \kappa x_t\), but output doesn't enter that way.) This seems totally natural and sensible to me. What is a "period" anyway? It makes sense that firms learn heterogeneously whether a price increase is relative or price level. And it obviously solves the central persistence problem with the Lucas (1972) model, that it only produces a one-period output movement. Well, what's a period anyway? (Mankiw and Reis don't sell it this way, and actually don't cite Lucas at all. Curious.)  It's not immediately obvious that this curve solves the Ball puzzle and the declining inflation puzzle, and indeed one must put it in a full model to do so. Mankiw and Reis (2002) mix it with \(m_t + v = p_t + x_t\) and make some stylized analysis, but don't show how to put the idea in models such as I started with or make a plot.  Their less well known follow on paper  Sticky Information in General Equilibrium (2007) is much better for this purpose because they do show you how to put the idea in an explicit new-Keynesian model, like the one I started with.  They also add a Taylor rule, and an interest rate rather than money supply instrument, along with wage stickiness and a few other ingredients,. They show how to solve the model overcoming the problem that there are many lagged expectations as state variables. But here is the response to the monetary policy shock: Response to a Monetary Policy Shock, Mankiw and Reis (2007). Sadly they don't report how interest rates respond to the shock. I presume interest rates went down temporarily. Look: the inflation and output gap plots are about the same. Except for the slight delay going up, these are exactly the responses of the standard NK model. When output is high, inflation is high and declining.  The whole point was to produce a model in which high output level would correspond to rising inflation. Relative to the first graph, the main improvement is just a slight hump shape in both inflation and output responses. Describing the same model in "Pervasive Stickiness" (2006), Mankiw and Reis describe the desideratum well: The Acceleration Phenomenon....inflation tends to rise when the economy is booming and falls when economic activity is depressed. This is the central insight of the empirical literature on the Phillips curve. One simple way to illustrate this fact is to correlate the change in inflation, \(\pi_{t+2}-\pi_{t-2}\) with [the level of] output, \(y_t\), detrended with the HP filter. In U.S. quarterly data from 1954-Q3 to 2005-Q3, the correlation is 0.47. That is, the change in inflation is procyclical.Now look again at the graph. As far as I  can see, it's not there. Is this version of sticky inflation a bust, for this purpose? I still think it's a neat idea worth more exploration. But I thought so 20 years ago too.  Mankiw and Reis have a lot of citations but nobody followed them. Why not?  I suspect it's part of a general pattern that lots of great micro sticky price papers are not used because they don't produce an easy aggregate Phillips curve. If you want cites, make sure people can plug it in to Dynare. Mankiw and Reis' curve is pretty simple, but you still have to keep all past expectations around as a state variable. There may be alternative ways of doing that with modern computational technology, putting it in a Markov environment or cutting off the lags, everyone learns the price level after 5 years. Hank models have even bigger state spaces! Some more modelsWhat about within the Fed?  Chung,  Kiley, and  Laforte 2010, "Documentation of the Estimated, Dynamic, Optimization-based (EDO) Model of the U.S. Economy: 2010 Version" is one such model.  (Thanks to Ben Moll, in a lecture slide titled "Effects of interest rate hike in U.S. Fed's own New Keynesian model") They describe it as This paper provides documentation for a large-scale estimated DSGE model of the U.S. economy – the Federal Reserve Board's Estimated, Dynamic, Optimization- based (FRB/EDO) model project. The model can be used to address a wide range of practical policy questions on a routine basis.Here are the central plots for our purpose: The response of interest rates and inflation to a monetary policy shock.  No long and variable lags here. Just as in the simple model, inflation jumps down on the day of the shock and then reverts. As with Mankiw and Reis, there is a tiny hump shape, but that's it. This is nothing like the Romer and Romer plot. Smets and Wouters (2007) "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach" is about as famous as Christiano Eichenbaum and Evans as a standard new-Keynesian model that supposedly matches data well. It "contains many shocks and frictions. It features sticky nominal price and wage settings that allow for backward inflation indexation, habit formation in consumption, and investment adjustment costs that create hump-shaped responses... and variable capital utilization and fixed costs in production"Here is their central graph of the response to a monetary policy shockAgain, there is a little hump-shape, but the overall picture is just like the one we started with. Inflation mostly jumps down immediately and then recovers; the interest rate shock leads to future inflation that is higher, not lower than current inflation. There are no lags from higher interest rates to future inflation declines. The major difference, I think, is that Smets and Wouters do not impose the restriction that inflation cannot jump immediately on either their theory or empirical work, and Christiano, Eichenbaum and Evans impose that restriction in both places. This is important. In a new-Keynesian model some combination of state variables must jump on the day of the shock, as it is only saddle-path stable. If inflation can't move right away, that means something else does. Therefore, I think, CEE also preclude inflation jumping the next period. Comparing otherwise similar ingredients, it looks like this is the key ingredient for producing Romer-Romer like responses consistent with the belief in sticky inflation. But perhaps the original model and Smets-Wouters are right! I do not know what happens if you remove the CEE orthogonalization restriction and allow inflation to jump on the day of the shock in the date. That would rescue the new-Keynesian model, but it would destroy the belief in sticky inflation and long and variable lags. Closing thoughtsI'll reiterate the main point. As far as I can tell, there is no simple economic model that produces the standard belief. Now, maybe belief is right and models just have to catch up. It is interesting that there is so little effort going on to do this. As above, the vast outpouring of new-Keynesian modeling has been to add even more ingredients. In part, again, that's the natural pressures of journal publication. But I think it's also an honest feeling that after Christiano Eichenbaun and Evans, this is a solved problem and adding other ingredients is all there is to do. So part of the point of this post (and "Expectations and the neutrality of interest rates") is to argue that this is not a solved problem, and that removing ingredients to find the simplest economic model that can produce standard beliefs is a really important task.  Then, does the model incorporate anything at all of the standard intuition, or is it based on some different mechanism al together? These are first order important and unresolved questions!But for my lay readers, here is as far as I know where we are. If you, like the Fed, hold to standard beliefs that higher interest rates lower future output and inflation with long and variable lags, know there is no simple economic theory behind that belief, and certainly the standard story is not how economic models of the last four decades work. Update:I repeat a response to a comment below, because it is so important. I probably wasn't clear enough that the "problem" of high output with inflation falling rather than rising is a problem of models vs. traditional beliefs, rather than of models vs. facts. The point of the sequence of posts, really, is that the traditional beliefs are likely wrong. Inflation does not fall, following interest rate increases, with dependable, long, and perhaps variable lags. That belief is strong, but neither facts, empirical evidence, or theory supports it. ("Variable" is a great way to scrounge data to make it fit priors.) Indeed many successful disinflations like ends of hyperinflations feature a sigh of relief and output surge on the real side. 

I haven't had time to do much blogging lately. But I have been studying the recent burst of inflation and thinking of how to interpret what we're experiencing. As is my way, I decided to write down a little model (a dynamic general equilibrium model) to help organize my thinking on this question. Below, I summarize the interpretation stemming from the model (available on request). Because it's a model, it does not capture everything that one might think isimportant. But I think it certainly captures some of the main forces operating on the U.S. economy over the 2020-2022 time period. And if so, then it offers a different take on how to interpret the recent episode of (relatively) high and (hopefully) transitory inflation. I look forward to any feedback. DAIntroduction In February 2020, the month before the full effects of the pandemic were felt in the United States, PCE and CPI measures of inflation were running between 1.7% and 2.4%, consistent with the Federal Reserve's official 2% target inflation rate. From March 2020 to February 2021, these measures of inflation declined significantly, with most measures falling below 1% in May 2020, before recovering to somewhere near 1.5% by February 2021. In March 2021, measures of inflation began to rise sharply and significantly. By February 2020, the month prior to the Russian invasion of Ukraine, PCE and CPI inflation rates rose to between 5.4% to 8.0%, with core PCE peaking in that month. Other measures of inflation peaked in the summer of 2022. Inflation has been declining slowly and steadily since then. Most outlooks have inflation declining to between 2% and 3% by the end of 2024.    If inflation continues along its projected path to settle in at or even somewhat above 2%, then the recent inflation dynamic will be hump-shaped, beginning in 2021, peaking in 2022, and falling significantly in 2023; see Figure 1.Figure 1   How should we interpret the hump-shaped inflation dynamic in Figure 1? The answer to this question is critically important because an evaluation of monetary and fiscal policy over this episode requires a proper interpretation of the phenomenon being studied. More than one interpretation is possible, of course. But any useful interpretation will have to rely on theory at some level. The goal of this paper is to develop a dynamic general equilibrium model that can explain the qualitative properties of data in an empirically plausible manner and be used to assess the monetary and fiscal policies employed since March 2020.An overview of the argument     Views on the causes and nature of the "COVID-19 inflation" vary considerably. There is no doubt an element of truth to many of these views and my interpretation below relies on more than one causal factor.     Beginning in March 2020, there were the supply disruptions induced by the pandemic. Some sectors of the economy, like leisure and hospitality, were virtually shut down in an attempt to "flatten the curve." Individuals stopped patronizing establishments delivering in-person services. The prime-age employment-to-population ratio fell from 80% to 70% from February to April in 2020 and did not recover its initial level for another two years. Severe disruptions in the global supply chain led to shortages of goods at final destinations. At the time these COVID-19 related shocks had more or less dissipated, additional disruptions emerged with the Russian invasion of Ukraine in late February 2022 along with growing Sino-American tensions.          These "supply side" shocks were real and significant. It is not entirely clear, however, how they might be used to understand the inflation dynamic in Figure 1. The intensity of the "supply side" shock likely peaked in 2020, a year in which inflation declined. And the Russia-Ukraine war shock appeared in 2022, after the sharp rise in inflation in 2021. Of course, these observations do not mean that supply disruptions had no effect on the inflation dynamic. But they do suggest that other forces were likely at work.          Other important forces were surely at work on the "demand side" of the economy. Exactly what these forces were and how they should be modeled remains an open question. Guerrieri, Lorenzoni, Straub, and Werning (2022) demonstrate how a negative sectoral supply shock in an incomplete markets setting can endogenously result in "deficient demand" (a decline in actual output in excess of the decline in potential output). Although their paper does not focus on inflation dynamics, the mechanism they identify is presumably disinflationary; at least, on impact.          Another way in which demand can be affected is through expectations. Developed economies devote significant amounts of time and resources to activities broadly classified as investments, including business fixed investment, residential investment, human capital accumulation, and job recruiting. The contemporaneous demand for goods and services devoted to investment (broadly-defined) surely depends on its expected rate of return. Indeed, there is considerable evidence suggesting that this is the case; see Liao and Chen (2023) and the references cited within. Whether these expectations are driven by news over economic fundamentals (e.g., Beaudry and Portier, 2006) or by purely psychological factors (e.g., Keynesian "animal spirits") matters little for positive analysis. Depressed expectations over the return to investment will depress investment demand whether expectations are formed rationally or not. The manner in which expectations are formed does, however, have implications for monetary and fiscal policy.          The analysis below assumes a large "negative sentiment shock" in 2020, consistent with the fear and uncertainty associated with the unfolding pandemic and the dramatic measures taken to shut down parts of the economy. When the outlook on investment returns darkens, investors typically seek safe havens. During the financial crisis of 2008-09, U.S. Treasury securities served as a "flight to safety" asset. The result was plummting bond yields. To the extent that interest rates do not (or cannot) move lower, the demand for safety expresses itself as a decline in capital spending and the price-level. That is, a negative sentiment shock is disinflationary; at least, on impact. Below, I assume that this negative sentiment shock largely reversed itself in 2021, consistent with the appearance and widespread use of COVID-19 vaccines in that year.          Now, imagine for the moment, that monetary and fiscal policy remained roughly unchanged from 2019 to today. That is, imagine that the Fed did not lower its policy rate in March 2020 and that the large discretionary fiscal programs (primarily the CARES Act of 2020 and the American Rescue Plan of 2021) had not been implemented. Assume that the negative sentiment shock was significantly more powerful than the negative supply shock in 2020, in line with Guerrieri, Lorenzoni, Straub, and Werning (2022). Assume that these two shocks are largely reversed in 2021. Then the supply-demand framework sketched above suggests a large disinflationary impulse and recession in 2020, followed by an equally large inflationary impulse and economic recovery in 2021. Depending on the nature of adjustment costs, employment and inflation should have more or less returned to their pre-pandemic levels by 2022 or shortly thereafter. To a first approximation, this is essentially what happened. However, actual inflation turned out to be much higher and more persistent than can be rationalized by these shocks alone. What is missing?         What is missing, of course, are the monetary and fiscal policy responses implemented at the start of the crisis. In March 2020, the Fed lowered its policy rate from 150bp to essentially zero where it remained until March 2022. The anticipated monetary tightening began in late 2021 (see the 2-year rate in Figure 2). From March to December of 2022, the federal funds rate rose by over four hundred basis points.Figure 2         From 2020 to 2021, the U.S. Congress passed a number of bills described as delivering "stimulus and relief." The two largest bills were the CARES Act, passed in March of 2020, and the American Rescue Plan (ARP), passed in March 2021. In broad terms, these spending packages had the following properties. First, the consisted largely of monetary transfers targeting the bottom half of the income distribution as well as distressed businesses. Second, the spending packages were large--around $2 trillion each--over ten percent of GDP in both 2020 and 2021. Third, the spending packages were not offset by spending reductions in other areas. Nor were surtaxes levied to finance the programs. The programs were financed with net new issuances of nominal securities purchased by the banking sector. That is, the transfers essentially took the form of "helicopter drops" of money; see Figure 3.Figure 3    The ultra loose monetary and fiscal policies over 2020-21 exerted strong inflationary pressures. In 2022, the Russian-Ukraine war contributed to headline inflation. The output loss in 2020 contributed to inflationary pressure. The reversal in business sentiment in 2021 contributed to inflationary pressure.     The inflationary pressures cited above were offset by strong deflationary pressures in 2020 and 2022. In 2020, there was a strong negative demand shock, resulting in a strong decline in investment with an accompanying movement in the demand for money (the inverse of money velocity); see Figure 4.Figure 4     As business sentiment reversed in 2021, the demand for money (safe assets, in general) declined. This turn of events occurred just as the ARP kicked in. Together, these two events generated a strong inflationary impulse in 2021. This impulse was counteracted in 2022 by strongly contractionary monetary and fiscal policies (a sharp rise in the policy interest rate in 2022 and the expiration of the ARP by the end of 2021).          The account given above is based on a model that I formalize below. Note that the account is purely qualitative in nature. This is because my model is designed only to flesh out the qualitative effects of a variety of economic forces that seem plausibly important (I am working on a quantitative version of the model with a coauthor). Formalizing the argument above through a simple dynamic general equilibrium model has two benefits. First, it will force me to be explicit about the assumptions I am making to render the verbal interpretation above logically coherent. Second, it will allow me to evaluate monetary and fiscal policies employed in the 2020-22 period. The model can also be used to perform counterf actuals. Policy assessmentThe model suggests the following assessment.1. Cutting the policy rate in March 2020 was appropriate only to the extent that there were forces driving a declining output below potential. A strong deflationary pressure is not sufficient to identify an "output gap," because rationally-pessimistic forecasts are deflationary. One would have to make the case that investors became overly-pessimistic. Or that sectoral shocks somehow led to deficient demand (Guerrieri, et. al., 2022). These are difficult arguments to make because "potential" is unobservable and prior to the arrival of the vaccines, a gloomy sentiment did not seem irrational. 2. The fiscal transfers associated with the 2020 CARES Act were desirable. The policy mostly redistributed purchasing power (at a time when total output was declining) from high to low-income persons (the latter group being disproportionately affected by the shutdowns). Without the CARES Act, the economy would have likely experienced a significant deflation (benefiting those with wealth in the form of money/bonds). Hence, the desired redistribution was financed through an inflation tax. A temporary income or consumption tax might have been used instead. In this sense, inflation was at least in part an efficient tax (or constrained efficient, better ways of financing the desired transfers were available).3. A case could be made that the 2021 ARP was desirable ex ante. A case could be made that it was undesirable ex post. Either way, the model suggests that the ARP was implemented at precisely the time investor sentiment had returned to normal. Essentially, 2021 saw a large increase in the supply of money and a large decrease in the demand for real money balances. Both effects served to drive inflation higher. 4. Strong disinflationary policies were enacted at the beginning of 2022. First, fiscal policy became highly contractionary (by ceasing the ARP). Second, the Fed began to raise its policy rate aggressively. These disinflationary policies were partially offset by the inflationary consequences of growing geopolitical tensions.          My own assessment of monetary and fiscal policy over this period of time (based in part on my model) is as follows. First, the Fed should not have lowered its policy rate in March 2020 (its emergency lending programs worked as needed). Conditional on having lowered the policy rate (forgivable, in light of the weak inflation numbers), the Fed should have begun tightening sometime in 2021 (consistent with the recommendations of those economists who favor NGDP targeting). Second, despite all its warts, the CARES Act was essential and did what it needed to do. Third, desirability of the ARP is better weighed in political, rather than economic, terms. It was a redistribution policy. It was financed through an inflation tax. It might have been financed in some less-inflationary way. But a tax in some form would have been unavoidable.          The policies and programs put in place by our elected representatives to meet the economic challenges inflicted on us by the pandemic were designed to redistribute purchasing power. If those policies were widely viewed as desirable, then it seems strange to blame inflation (or some other tax) for inflicting economic hardship. Inflation was mainly a symptom of the solution to a problem inflicted on humanity by nature. This is the sense in which one can describe the recent inflationary episode as "constrained efficient inflation." PS. If the hump-shaped inflation pattern continues to play out, it will be judged by economic historians as a "transitory" inflation. There is nothing in the model which suggests that a recession is necessary for the transitory part. A helicopter drop of money creates a transitory inflation. This is textbook economics. 

The Supreme Court is hearing a case with profound implications for the income tax. WSJ editorial here and good commentary from Ilya Shapiro here. This issue is naturally contorted into legalisms:  What the heck does "apportioned" mean? How is "income"  defined legally? I won't wade into that. What are the economic issues? What's the right thing to do here, leaving aside legalisms?Three general principles underlie taxation. The most important is: The government taxes what it can get its hands on. The economists' analysis of incentives comes much later: The government tries to tax in such a way that does not set off a rush to avoidance, either legal (complex structures to avoid taxes) or economic (don't do the thing that gets taxed, like earn income). So why does the government tax income? Because, circa 1913, income was easier to measure than sales, value added, consumption, or other economically better concepts. When money changes hands, it's relatively for the government to see what's there and take a share.  Tariffs really start from the same concept. It's relatively easy to see what's going through the port and demand a share, Adam Smith, David Ricardo and free trade be damned.  But the government wanted more money than tariffs could provide. So, even if it were a good idea to tax wealth, the problem is that there is not neceassarily any cash around where there is wealth or unrealized capital gains. When you sell an asset, you get some cash, and it's easy for the government to demand it. When you do not sell an asset, you have no extra cash. It's a "paper profit." What are you going to pay the government with? This comes up in practical terms with estate taxes. Yes, we have a 40% top marginal rate wealth tax right now. (If wealth taxes are unconstitutional, why isn't the estate tax number one on the chopping block? OK, I promised not to delve in to law, but I wish someone would answer it.)  But private businesses, family farms, and the like don't have 40% of their value sitting around in cash. Unless you carve out a Swiss cheese of loopholes, and complex legal structures, you have to break up or sell the business to get the cash. That's why the estate tax has said Swiss cheese. It also has happened in the news lately with internet titans who got big stock grants at the top of the market. The market crashes. They still owe tax on the value of stock when granted. Property taxes are another case. Yes, we have wealth taxes, in the form of property taxes. (They are state and local, not federal, and the issue is federal wealth taxes.) People sometimes can own a house but not have the money to pay the tax. Wealth and unrealized capital gains are also troublesome because in many cases it's hard to know exactly how much there is. Just what is the value of a house, a building, or a privately held business? Accountants can differ, especially if taxes are at stake. The minute you tax it,  accountants also can get creative about corporate structure to game valuation rules -- voting vs. non voting shares, debt with embedded options, options to buy that are never exercised, interlocking trusts, and so forth. See above estate tax Swiss cheese.Moreover, market values change. If I pay tax on unrealized appreciation this year, do I get my money back when the value goes down next year?So you can see it makes sense: If one wants to include "investment income" as "income." then tax it when there is a definite value -- the market sale price -- and  tax it when there is some cash around to grab; when it is realized. But now trouble perks up. It's reasonably easy to turn actual income into an unrealized gain. Suppose you have some income stream, and you don't plan to spend it right away. You want to reinvest it. Rather than pay income tax on the income, then additional income tax on the interest or dividends over time, and then more income tax on the appreciation of the final sale, create a corporation or other entity; let the income flow into the corporation which reinvests it. The "corporation" could just be a shell to receive income and put it in a mutual fund. Yes, you'll still pay capital gains tax when you sell, but that's a lot less. And delay is always great. Now you know why we have a corporate income tax at all. There is no economic point to corporate taxes, and "corporations pay their fair share" is nonsense. Every cent of corporate income tax comes from higher prices, lower wages, or lower payouts to stock and bondholders. We should tax those people. And if you want redistribution, taxing the "right" people, that's a lot easier to do when you tax people. But if there is no corporate tax, lots of people will incorporate to avoid income taxes. So, we tax corporate income and then your payout. Thousands of pages of tax law and regulation follow to plug one hole after another.  After 100 years of patchwork, including some taxing of unrealized gains, it sort of kept a balance, but people keep inventing new ideas. The case before the court involves domestic owners of a foreign corporation and the treatment of the income received into that corporation abroad. So, as revealed by the pro-tax arguments before the court, we have already stepped over the grab-it-while-it's-hot line and taxed a good deal of unrealized income. There was some sort of equilibrium of not overdoing it. But not overdoing it, obeying norms and gentlepersons's agreements, is going out of style these days. From WSJ:The Ninth Circuit's opinion opened up a freeway to tax wealth and property. And wouldn't you know, President Biden's budget this year includes a 25% tax on the appreciation of assets of Americans with more than $100 million in wealth....Justice Samuel Alito asked: "What about the appreciation of holdings in securities by millions and millions of Americans, holdings in mutual funds over a period of time without selling the shares in those mutual funds?" Ms. Prelogar replied: "I think if Congress actually enacted a tax like that, and it never has, that we would likely defend it as an income tax."Well, it's also called an estate tax, and we have it now!  There you have it. The Biden Administration believes the Sixteenth Amendment lets Congress tax the unrealized appreciation of assets. As Justice Neil Gorsuch noted, when the Supreme Court opens a door, "Congress tends to walk through it." The Justices should close the wealth-tax door. But it is also true that would upset the delicate balance above that allows the government to collect a lot of taxes. Someone has to pay taxes, so other rates would have to go up a lot. When one side overdoes it, the gentleperson's agreement explodes. Like corporate income, taxing investment income also makes no sense. You earn money, pay taxes on it, and invest it. If you choose to consume later rather than now, why pay additional tax on it? One of the main don't-distort-the-economy propositions is that we should give people the full incentive to save, by refraining from taxing investment income.So why take investment income? Again, because once you tax income, many people can shift labor income to investment income. If you run a business, don't take a salary, but pay yourself a dividend. If you're a consultant, incorporate yourself and call it all business income. In the 1980s even cab drivers incorporated to get lower corporate tax rates. The income tax is the original sin. Taxing income made no sense on an economic basis. The government only did it because it was easy to measure and grab, at least before people started inventing a century's worth of clever schemes to redefine "income."  It leads inescapably to more sins, the corporate tax and the tax on investment income. And now the repatriation tax on accumulated foreign earnings. What's the solution? Well, duh. Tax consumption, not income or wealth. Get the rich down at the Porsche dealer. Leave alone any money reinvested in a company that is employing people and producing products. Now we can do it. And we can then throw out the income tax, corporate tax, and estate tax. Income is really meaningless. You earn a lot of income in your middle years, but little early and late. The year you sell a house, you're a millionaire, but then back to low income the rest of the time. Yet our government hands out more and more benefits based on income as if it were an immutable characteristic. It is not. Consumption is a lot more meaningful! The case brings up another uncomfortable question. The couple invested their money, and then the IRS changed the rules and told them to pay taxes now on decades worth of past earnings. While we're playing lawyer, laws generally cannot penalize past behavior. Surely if they knew this rule, the couple would have arranged their business differently. Here there is an uncomfortable principle of taxation. Unexpected, just this once and we'll never do it again wealth taxes are economically efficient. The problem of taxation is disincentives. If you announce a wealth tax in the future, people respond by not accumulating wealth. Go on round the world private jet tours instead. (I hear UAE is nice this time of year, and all the smart people are there.) But if you tax existing wealth, and nobody knew it was coming, there is no disincentive. This is, however, one of the most misused propositions in economics. That promise never to do it again isn't credible. If the government did it once, why not again? And it feels horribly unfair, doesn't it? Grabbing wealth willy nilly unpredictably is not something responsive rule-of-law democracies can or should do. (This  issue came up with the corporate tax cut. There was a lot of effort not to reward past investment. That's the same principle as trying to tax that past investment now that it is made. I prefer stable rules.) Thus, I actually hope that the Supreme Court does blow up the tax system. It's a bloated crony-capitalist mess. Most people suspect that others with clever lawyers are getting away with murder, which is corrosive to democracy.  If the friends of the court are right that the tax system will not survive a narrow definition of income, that  might force a fundamental reckoning. We need a ground up reform. Not every decision taken in 1913 has to last forever. Let the income tax implode, and bring on a consumption tax. (Instead, not as well as!) I doubt it will happen though. The court is really good at constitutional law, but not at first-principles economics. With the continued political assault on their legitimacy, they will surely find a way to decide this narrowly, and wait to strike down the wealth tax when and if it is enacted.  But who knows, it's interesting that they took it in the first place. 

By the standards of mainstream media coverage of technical economics, Peter Coy's coverage of HANK (Heterogeneous Agent New Keynesian) models in the New York Times was actually pretty good. 1) Representative agents and distributions. Yes, it starts with the usual misunderstanding about "representative agents," that models assume we are all the same. Some of this is the standard journalist's response to all economic models: we have simplified the assumptions, we need more general assumptions. They don't understand that the genius of economic theory lies precisely in finding simplified but tractable assumptions that tell the main story. Progress never comes from putting more ingredients and stirring the pot to see what comes out. (I mean you, third year graduate students looking for a thesis topic.) But in this case many economists are also confused on this issue. I've been to quite a few HANK seminars in which prominent academics waste 10 minutes or so dumping on the "assumption that everyone is identical." There is a beautiful old theorem, called the "social welfare function." (I learned this in graduate school in fall 1979, from Hal Varian's excellent textbook.) People can have almost arbitrarily different preferences (utility functions), incomes and shocks, companies can have almost arbitrarily different characteristics (production functions),  yet the aggregate economy behaves as if there is a single representative consumer and representative firm. The equilibrium path of aggregate consumption, output,  investment, employment, and the prices and interest rates of that equilibrium are the same as those of an economy where everyone and every firm is the same, with a "representative agent" consumption function and "representative firm" production function.  Moreover, the representative agent utility function and representative firm production function need not look anything like those of any particular individual person and firm. If I have power utility and you have quadratic utility, the economy behaves as if there is a single consumer with something in between. Defining the job of macroeconomics to understand the movement over time of aggregates -- how do GDP, consumption, investment, employment, price level, interest rates, stock prices etc. move over time, and how do policies affect those movements -- macroeconomics can ignore microeconomics. (We'll get back to that definition in a moment.) Now uniting macro and micro is important. Macro estimation being what it is, it would be awfully nice to use micro evidence. The program kicked off by Kydland and Prescott to "calibrate" macro models from micro evidence would be very useful. Kydland and Prescott may have had a bit of grass-is-greener optimism about just how much precise evidence macroeconomists have on firms and people, but it's a good idea. Adding up micro evidence to macro is hard, however. Here "aggregation theory," often confused with the "social welfare function" theorem comes up, more as a nightmare from graduate school. The conditions under which the representative agent preferences look like individual people are much more restricted. Like all good theorems, this one rests on assumptions, and the assumptions are false. The crucial assumption is complete markets, and in particular complete risk sharing: There is an insurance market in which you can be compensated for every risk, in particular losing your job.  A generalized form still works, however. There is still a representative agent, but it cares about distributions. The representative agent utility function depends on aggregate consumption, aggregate labor supply but now also statistics about the distribution of consumption across people. In asset pricing, the Constantinides-Duffie model is a great example: the cross-sectional variance of consumption becomes a crucial state variable for the value of the stock market, not just aggregate consumption. All economic theorems are false of course, in that the assumptions are not literally true. The question is, how false? Conventional macroeconomics comes down to a description of how aggregates evolve over time, based on past aggregates: [aggregate income, consumption, employment, inflation... next year ] = function of [aggregate income, consumption, employment, inflation, policy variables... this year ]  + unforecastable shocks. That's it. That's what macroeconomics is. Theory, estimation and calibration to figure out the function. [Update. I added policy variables, e.g. interest rates, to the function. And, the point of macro is to figure out how policies affect the economy, and furthermore with an objective in hand to derive optimal policies. Thanks François Velde for pointing out the omissions in comments.] If HANK is useful to macroeconomics, then, it must be that adding distributional statistics helps to describe aggregate dynamics. Reality must be [aggregate income, consumption, employment, inflation... next year ] = function of [aggregate income, consumption, employment, inflation, distribution of consumption, employment, etc.,  policy variables,... this year ]  + unforecastable shocks. So here is a central question I have for HANK modelers: Is that true? Do statistics on the distribution across people of economic variables really help us to forecast or understand aggregate dynamics? So far, my impression is, not much. The social welfare function theorem can be wrong in its assumptions, yet still a pretty good approximation. And "heterogeneity" has been around macro for a long time, but never has seemed to matter much in the end. (The investment literature of the early 1990s is a great example.) But I would be happy to be proved wrong. This post is as much a suggestion for HANK modelers as a critique. Another possibility: Maybe HANK is about aggregation after all. Can we actually use micro evidence, and add it up constructively, to learn what the representative agent - social welfare function is? Even before HANK, there were good examples. For example, the literature on labor supply: Macro models want people to work more in response to temporarily higher wages. Most individual people work 8 hours a day or zero, so micro evidence finds a small response. But a small number of people move from non-work to work as wages rise. So the representative agent can have a much larger elasticity than individual people. And, you have to understand labor market structure, and the distribution of who is available to work to add up from micro to macro evidence.  Here, I would like to know the basic functional form -- how much does the SWF care about today vs. tomorrow, risk, work vs leisure, as well as any distributional effect? 2) Income effectsCoy also goes on with the usual New York Times schtick about how dumb and irrational all the little hoi polloi are. (Of course we of the elite and the federal government handing out nudges would never be behavioral.) But you don't need HANK to assume that the representative investor is dumb either. He goes on to describe pretty well where the current literature is. Behind this is, however, one of the major features of HANK models so far. One of its most important uses has been to put current income in the IS equation. (Economists talk amongst yourselves for a bit while I explain this to regular people. So far, the central description of demand in new Keynesian models is based on "intertemporal substitution:" When the real interest rate is higher, you consume a bit less today, save a bit more, so that you can consume a lot more tomorrow. That is the crucial mechanism by which higher real interest rates (say, induced by the Fed) lower demand today. Old Keynesian models didn't have people in them at all, but hypothesized that consumption simply follows income. That adds a more powerful mechanism, the "multiplier:" an initial income drop lowers consumption, which lowers income and around we go. )HANK models often add some "hand to mouth" consumers. Some people think about today vs. the future, but others just eat what income they make today. You can get this out of "rational, liquidity constrained" people, but that's typically not enough. To get significant effects, you need people who just behave that way. So,  there is this little bit of behaviorism in many HANK models. But it's a little spice in the otherwise Lucas soup. In equations, the standard model says consumption today = expected consumption tomorrow - (number) x real interest rateAfter an immense amount of algebra and computer time, HANK models allow you to writeconsumption today = (number) x income today + (number) x expected consumption tomorrow - (number) x real interest rate New Keynesian models were invented on the hope they would turn out to be holy water sprinkled on old-Keynesian thinking, for example justifying big spending multipliers and strong monetary policy. They turned out to be nothing at the sort once you read the equations. A movement is underway to modify (torture?) new-Keynesian models to look like old-Keynesian models, to bring macro back to roughly the 1976 edition of Dornbush and Fisher's textbook. Complex expectation formation theories and this aspect of HANK can be digested that way. So here is my second question for HANK modelers: Is this it? When we boil it all down to the linearized equations of the model you take to data, to explain aggregates and monetary and fiscal policy, is there a big bottom line beyond an excuse to revive bits of the Keynesian consumption function? That too is an honest question, and perhaps a suggestion--show us the textbook back of the envelope bottom line model. (It would be awfully nice if distributions mattered here too, theoretically, empirically, and quantitatively.) 3) Micro implications of macro Maybe you disagreed a few paragraphs ago with my definition of macroeconomics, as only concerned with the movement of aggregates over time. Talking with some of my HANK colleagues, a different purpose is at work -- figuring out the effects of macroeconomics on different people. Recessions fall harder on those who lose jobs, and certain income and other groups; harder on some industries and areas than others. Here HANK dovetails with concerns over income diversity and "equity." That's a perfectly good reason to study it, but let's then be clear. If that's the case, HANK really doesn't change our understanding of how policies and events move aggregates around, it is really just about understanding how those aggregates affect different people differently. That may change calculations of optimal monetary policy. If the objective function cares negatively about income diversity, then adding HANK may produce a model that makes no difference at all for the effect of monetary policy on aggregates, but gives a greater weight to employment vs. inflation. ("May!" Inflation also falls harder on people experiencing low incomes, so concerns for equity could go the other way too. Thanks to a correspondent for pointing that out.)  Many models have observationally equivalent predictions for aggregates but different welfare implications, and the same model can have different welfare implications if you put in different preferences for distributions across people. But surely HANK has more to offer than a long-winded excuse for dovishness towards tolerating inflation in place of unemployment. Also, in the big picture this seems like a classic answer in search of a question. If you care about the less fortunate, you start with the big issues: crime, awful schools, family breakdown, opportunity. The additional benefit for the less fortunate from the level of the overnight federal funds rate might be fun to isolate in a model, but we are really staring at a caterpillar on a leaf of a tree and missing the forest of economic misfortune. 4) Last thoughtsI hesitate to write, as I am a consumer not a producer of HANK research, and thus will probably get things wrong or show my limited knowledge of the literature. Please fill the comments with corrections, amplifications, pointers to good papers, etc. There is a tendency in economics to pursue a new technical possibility without really knowing where it's going or why. That's not unhealthy; figure out what you can do first, and what to do later. The why always does come later.  This was true of rational expectations, real business cycles, new-Keynesian models and more. Now that HANK is pretty well developed and is coming out in public, with admiring New York Times articles, it is worth assessing the why, the bottom line, what it does. I'm also hesitant to write and especially too critically. I vividly recall being in grad school, and some speaker (I mercifully forgot who) went on a tirade about all these young whippersnappers using too much math and not enough intuition and just being in love with building models. I vowed if I ever thought that I would retire. What do we say to the angel of old age? Not today. Bring it on, and let's all figure out what it means.Update:  Alessandro Davis comments below, reminding me of their recent QJE paper "Imperfect Risk Sharing and the Business Cycle." This paper evaluates directly the question, how much does heterogeneity matter for aggregate dynamics? The headline answer is "not much, though maybe more at the zero bound." deviations from perfect risk sharing implied by this class of models account for only 7% of output volatility on average but can have sizable output effects when nominal interest rates reach their lower bound. Now, 7% might actually be a lot. A little secret of contemporary macro models is that none of them explain a lot of output volatility. In my above characterization aggregates next year = function of aggregates today + shocks, the shocks are big and account for most variation in aggregates. Most inflation comes from inflation shocks, not movements in other variables like employment, especially as fed through a model. This isn't necessarily a failing of models. New Keynesian models are designed to understand how monetary policy affects output, not to explain why output varies. Milton Friedman thought that most business cycles were due to monetary policy mistakes, so understanding the former is the same as the latter, but he seems to have been wrong about that, at least since 1982.  Or maybe not. The paper's computation takes heterogene in the data, and asks how much does that affect the new-Keynesian model's predictions for output, employment, etc. I have in mind a slightly different question: Even without much theory, how much can data on heterogeneity actually improve forecasts of output, employment, etc. Do distributional variables improve VAR forecasts? Let me know if you have an answer to that one. The paper has a crystal clear summary of the representative agent theorem, and its important extension. They show how distributional variables enter in to a representative agent representation as simple "wedges." Using a representative agent does not mean you assume all people are identical! There is also a great literature review on the general understanding that distributional variables don't matter much for aggregates, starting with Krussell and Smith.  A parallel literature in finance qualitatively examined the beautiful Constantinides-Duffie mechanism, finding that uninsured idiosyncratic risk isn't large enough or variable enough to account for asset pricing puzzles. So far -- that's all from the 1990s and a lot of the point of HANK is to reverse that impression. UpdateSee Matthew Rognlie's superb answer below.  I ask a lot of questions but seldom get such clear and detailed answers!  Thanks for the short course on Hank model big picture! Update 2 Ben Moll writes Hi John, thanks a lot for the very thoughtful post. Lots of great food for thought. In case you hadn't seen it, Tom Sargent posted a new paper a few days ago that has a really great discussion of the main takeaways from HANK. See in particular sections 5 and 7. For example, see the point that HANK "challenges the neoclassical synthesis and a widely-believed prescription for separating macro policy design from policies to redistribute income and wealth." But plenty of other great points there too. Finally, yes, Matt Rognlie's response is really fantastic.Sargent's paper is here. It's fantastic. I'm going to save a review for a separate blog post. 

Today, I'll add an entry to my occasional reviews of interesting academic papers. The paper: "Price Level and Inflation Dynamics in Heterogeneous Agent Economies," by Greg Kaplan, Georgios Nikolakoudis and Gianluca Violante. One of the many reasons I am excited about this paper is that it unites fiscal theory of the price level with heterogeneous agent economics. And it shows how heterogeneity matters. There has been a lot of work on "heterogeneous agent new-Keynesian" models (HANK). This paper inaugurates heterogeneous agent fiscal theory models. Let's call them HAFT. The paper has a beautifully stripped down model. Prices are flexible, and the price level is set by fiscal theory. People face uninsurable income shocks, however, and a borrowing limit. So they save an extra amount in order to self-insure against bad times. Government bonds are the only asset in the model, so this extra saving pushes down the interest rate, discount rate, and government service debt cost. The model has a time-zero shock and then no aggregate uncertainty. This is exactly the right place to start. In the end, of course, we want fiscal theory, heterogeneous agents, and sticky prices to add inflation dynamics. And on top of that, whatever DSGE smorgasbord is important to the issues at hand; production side, international trade, multiple real assets, financial fractions, and more. But the genius of a great paper is to start with the minimal model. Part II effects of fiscal shocks. I am most excited by part II, the effects of fiscal shocks. This goes straight to important policy questions. Note: This figure plots impulse responses to a targeted and untargeted helicopter drop, aggregated at the quarterly frequency. The helicopter drop is a one-time issuance of 16% of total government nominal debt outstanding at t = 0. Only households in the bottom 60% of the wealth distribution receive the issuance in the targeted experiment (dashed red line). The orange line plots dynamics in the representative agent (RA) model. The dashed black line plots the initial steady state. Source: Kaplan et al. Figure 7At time 0, the government drops $5 trillion of extra debt on people, with no plans to pay it back. The interest rate does not change. What happens? In the representative agent economy, the price level jumps,  just enough to inflate away outstanding debt by $5 trillion. (In this simulation, inflation subsequent to the price level jump is just set by the central bank, via an interest rate target. So the rising price level line of the representative agent (orange) benchmark is not that interesting. It's not a conventional impulse response showing the change after the shock; it's the actual path after the shock. The difference between colored heterogeneous agent lines and the orange representative agent line is the important part.) Punchline: In the heterogeneous agent economies, the price level jumps a good deal more. And if transfers are targeted to the bottom of the wealth distribution, the price level jumps more still. It matters who gets the money. This is the first step on an important policy question. Why was the 2020-2021 stimulus so much more inflationary than, say 2008? I have a lot of stories ("fiscal histories," FTPL), one of which is a vague sense that printing money and sending people checks has more effect than borrowing in treasury markets and spending the results. This graph makes that sense precise. Sending people checks, especially people who are on the edge, does generate more inflation. In the end, whether government debt is inflationary or not comes down to whether people treat the asset as a good savings vehicle, and hang on to it, or try to spend it, thereby driving up prices. Sending checks to people likely to spend it gives more inflation. As you can see, the model also introduces some dynamics, where in this simple setup (flexible prices) the RA model just gives a price level jump. To understand those dynamics, and more intuition of the model, look at the response of real debt and the real interest rate The greater inflation means that the same increase in nominal debt is a lesser increase in real debt. Now, the crucial feature of the model steps in: due to self-insurance, there is essentially a liquidity value of debt. If you have less debt, the marginal value of higher; people bid down the real interest rate in an attempt to get more debt. But the higher real rate means the real value of debt rises, and as the debt rises, the real interest rate falls. To understand why this is the equilibrium, it's worth looking at the debt accumulation equation, \[ \frac{db}{dt} = r_t (b_t; g_t) b_t - s_t. \]\(b_t\) is the real value of nominal debt, \(r_t=i_t-\pi_t\) is the real interest rate, and \(s_t\) is the real primary surplus. Higher real rates (debt service costs) raise debt. Higher primary surpluses pay down debt. Crucially -- the whole point of the paper -- the interest rate depends on how much debt is outstanding and on the distribution of wealth \(g_t\). (\(g_t\) is a whole distribution.)  More debt means a higher interest rate. More debt does a better job of satisfying self-insurance motives. Then the marginal value of debt is lower, so people don't try to save as much, and the interest rate rises. It works a lot like money demand,Now, if the transfer were proportional to current wealth, nothing would change, the price level would jump just like the RA (orange) line.  But it isn't; in both cases more-constrained people get more money. The liquidity constraints are less binding, they're willing to save more. For given aggregate debt the real interest rate will rise. So the orange line with no change in real debt is no longer a steady state. We must have, initially \(db/dt>0.\) Once debt rises and the distribution of wealth mixes, we go back to the old steady state, so real debt rises less initially, so it can continue to rise. And to do that, we need a larger price level jump. Whew. (I hope I got that right. Intuition is hard!)  In a previous post on heterogeneous agent models, I asked whether HA matters for aggregates, or whether it is just about distributional consequences of unchanged aggregate dynamics. Here is a great example in which HA matters for aggregates, both for the size and for the dynamics of the effects. Here's a second cool simulation. What if, rather than a lump-sum helicopter drop with no change in surpluses, the government just starts running permanent primary deficits? 
Note: Impulse response to a permanent expansion in primary deficits. The dotted orange line shows the effects of a reduction in surplus in the Representative Agent model. The blue line labelled "Lump Sum" illustrates the dynamics following an expansion of lump sum transfers. The dashed red line labelled "Tax Rate" plots dynamics following a tax cut. The orange line plots dynamics in the representative agent (RA) model. The dashed black line plots the initial steady state. Source: Kaplan et. al. Figure 8.

In the RA model, a decline in surpluses is exactly the same thing as a rise in debt. You get the initial price jump, and then the same inflation following the interest rate target. Not so the HA models! Perpetual deficits are different from a jump in debt with no change in deficit. 
Again, real debt and the real rate help to understand the intuition. The real amount of debt is permanently lower. That means people are more starved for buffer stock assets, and bid down the real interest rate. The nominal rate is fixed, by assumption in this simulation, so a lower real rate means more inflation. For policy, this is an important result. With flexible prices, RA fiscal theory only gives a one-time price level jump in response  to unexpected fiscal shocks. It does not give steady inflation in response to steady deficits. Here we do have steady inflation in response to steady deficits! It also shows an instance of the general "discount rates matter" theorem. Granted, here, the central bank could lower inflation by just lowering the nominal rate target but we know that's not so easy when we add realisms to the model. 
To see just why this is the equilibrium, and why surpluses are different than debt, again go back to the debt accumulation equation, \[ \frac{db}{dt} = r_t (b_t, g_t) b_t - s_t. \] In the RA model, the price level jumps so that \(b_t\) jumps down, and then with smaller \(s_t\), \(r b_t - s_t\) is unchanged with a constant \(r\). But in the HA model, the lower value of \(b\) means less liquidity value of debt, and people try to save, bidding down the interest rate. We need to work down the debt demand curve, driving down the real interest costs \(r\) until they partially pay for some of the deficits. There is a sense in which "financial repression" (artificially low interest rates) via perpetual inflation help to pay for perpetual deficits. Wow!
Part I r<gThe first theory part of the paper is also interesting. (Though these are really two papers stapled together, since as I see it the theory in the first part is not at all necessary for the simulations.) Here, Kaplan, Nikolakoudis and Violante take on the r<g question clearly. No, r<g does not doom fiscal theory! I was so enthused by this that I wrote up a little note "fiscal theory with negative interest rates" here. Detailed algebra of my points below are in that note,  (An essay r<g and also a r<g chapter in FTPL explains the related issue, why it's a mistake to use averages from our real economy to calibrate perfect foresight models. Yes, we can observe \(E(r)<E(g)\) yet present values converge.) I'll give the basic idea here. To keep it simple, think about the question what happens with a negative real interest rate \(r<0\), a constant surplus \(s\) in an economy with no growth, and perfect foresight. You might think we're in trouble: \[b_t = \frac{B_t}{P_t} = \int e^{-r\tau} s d\tau = \frac{s}{r}.\]A negative interest rate makes present values blow up, no? Well, what about a permanently negative surplus \(s<0\) financed by a permanently negative interest cost \(r<0\)? That sounds fine in flow terms, but it's really weird as a present value, no? Yes, it is weird. Debt accumulates at \[\frac{db_t}{dt} = r_t b_t - s_t.\] If \(r>0\), \(s>0\), then the real value of debt is generically explosive for any initial debt but \(b_0=s/r\). Because of the transversality condition ruling out real explosions, the initial price level jumps so \(b_0=B_0/P_0=s/r\). But if \(r<0\), \(s<0\), then debt is stable. For any \(b_0\), debt converges, the transversality condition is satisfied. We lose fiscal price level determination. No, you can't take a present value of a negative cashflow stream with a negative discount rate and get a sensible present value. But \(r\) is not constant. The more debt, the higher the interest rate. So  \[\frac{db_t}{dt} = r(b_t) b_t - s_t.\] Linearizing around the steady state \(b=s/r\), \[\frac{db_t}{dt} = \left[r_t  + \frac{dr(b_t)}{db}\right]b_t - s.\] So even if \(r<0\), if more debt raises the interest rate enough, if \(dr(b)/db\) is large enough, dynamics are locally and it turns out globally unstable even with \(r<0\). Fiscal theory still works! You can work out an easy example with bonds in utility, \(\int e^{-\rho t}[u(c_t) + \theta v(b_t)]dt\), and simplifying further log utility \(u(c) + \theta \log(b)\). In this case \(r = \rho - \theta v'(b) = \rho - \theta/b\) (see the note for derivation), so debt evolves as \[\frac{db}{dt} = \left[\rho  - \frac{\theta}{b_t}\right]b_t - s = \rho b_t - \theta - s.\]Now the \(r<0\) part still gives stable dynamics and multiple equilibria. But if \(\theta>-s\), then dynamics are again explosive for all but \(b=s/r\) and fiscal theory works anyway. This is a powerful result. We usually think that in perfect foresight models, \(r>g\), \(r>0\) here, and consequently positive vs negative primary surpluses \(s>0\) vs. \(s<0\) is an important dividing line. I don't know how many fiscal theory critiques I have heard that say a) it doesn't work because r<g so present values explode b) it doesn't work because primary surpluses are always slightly negative. This is all wrong. The analysis, as in this example, shows is that fiscal theory can work fine, and doesn't even notice, a transition from \(r>0\) to \(r<0\), from \(s>0\) to \(s<0\). Financing a steady small negative primary surplus with a steady small negative interest rate, or \(r<g\) is seamless. The crucial question in this example is \(s<-\theta\). At this boundary, there is no equilibrium any more. You can finance only so much primary deficit by financial repression, i.e. squeezing down the amount of debt so its liquidity value is high, pushing down the interest costs of debt. The paper staples these two exercises together, and calibrates the above simulations to \(s<0\) and \(r<g\). But I bet they would look almost exactly the same with \(s>0\) and \(r>g\). \(r<g\) is not essential to the fiscal simulations.* The paper analyzes self-insurance against idiosyncratic shocks as the cause of a liquidity value of debt. That's interesting, and allows the authors to calibrate the liquidity value against microeconomic observations on just how much people suffer such shocks and want to insure against them. The Part I simulations are just that, heterogeneous agents in action. But this theoretical point is much broader, and applies to any economic force that pushes up the real interest rate as the volume of debt rises. Bonds in utility, here and in the paper's appendix, work. They are a common stand in for the usefulness of government bonds in financial transactions. And in that case, it's easier to extend the analysis to a capital stock, real estate, foreign borrowing and lending, gold bars, crypto, and other means of self-insuring against shocks. Standard ``crowding out'' stories by which higher debt raises interest rates work. (Blachard's r<g work has a lot of such stories.) The ``segmented markets'' stories underlying faith in QE give a rising b(r). So the general principle is robust to many different kinds of models. My note explores one issue the paper does not, and it's an important one in asset pricing. OK, I see how dynamics are locally unstable, but how do you take a present value when r<0? If we write the steady state \[b_t = \int_{\tau=0}^\infty e^{-r \tau}s d\tau = \int_{\tau=0}^T e^{-r \tau}s d\tau + e^{-rT}b_{t+T}= (1-e^{-rT})\frac{s}{r} + e^{-rT}b,\]and with \(r<0\) and \(s<0\), the integral and final term of the present value formula each explode to infinity. It seems you really can't discount with a negative rate. The answer is: don't integrate forward \[\frac{db_t}{dt}=r b_t - s \]to the nonsense \[ b_t = \int e^{-r \tau} s d\tau.\]Instead, integrate forward \[\frac{db_t}{dt} = \rho b_t - \theta - s\]to \[b_t = \int e^{-\rho \tau} (s + \theta)dt =  \int e^{-\rho \tau} \frac{u'(c_t+\tau)}{u'(c_t)}(s + \theta)dt.\]In the last equation I put consumption (\(c_t=1\) in the model) for clarity. Discount the flow value of liquidity benefits at the consumer's intertemporal marginal rate of substitution. Do not use liquidity to produce an altered discount rate.  This is another deep, and frequently violated point. Our discount factor tricks do not work in infinite-horizon models. \(1=E(R_{t+1}^{-1}R_{t+1})\) works just as well as \(1 = E\left[\beta u'(c_{t+1})/u'(c_t)\right] r_{t+1}\) in a finite horizon model, but you can't always use \(m_{t+1}=R_{t+1}^{-1}\) in infinite period models. The integrals blow up, as in the example. This is a good thesis topic for a theoretically minded researcher. It's something about Hilbert spaces. Though I wrote the discount factor book, I don't know how to extend discount factor tricks to infinite periods. As far as I can tell, nobody else does either. It's not in Duffie's book. In the meantime, if you use discount factor tricks like affine models -- anything but the proper SDF -- to discount an infinite cashflow, and you find "puzzles," and "bubbles," you're on thin ice. There are lots of papers making this mistake. A minor criticism: The paper doesn't show nuts and bolts of how to calculate a HAFT model, even in the simplest example. Note by contrast how trivial it is to calculate a bonds in utility model that gets most of the same results. Give us a recipe book for calculating textbook examples, please!Obviously this is a first step. As FTPL quickly adds sticky prices to get reasonable inflation dynamics, so should HAFT. For FTPL (or FTMP, fiscal theory of monetary policy; i.e. adding interest rate targets), adding sticky prices made the story much more realistic: We get a year or two of steady inflation eating away at bond values, rather than a price level jump. I can't wait to see HAFT with sticky prices. For all the other requests for generalization: you just found your thesis topic. Send typos, especially in equations. Updates*Greg wrote, and pointed out this isn't exactly right. "In the standard r>g, s>0 case, an increase desire to hold real assets (such as more income risk) leads to a lower real rate and higher real debt - the standard "secular stagnation" story. With r<g, s<0, an increased desire to hold real assets leads to higher real rates and higher debt." To understand this comment, you have to look at the supply and demand graph in the paper, or in my note. The "supply" of debt in the steady state \(b = s/r/), plotted with \(r\) as a function of \(b\) flips sign from a declining curve to a rising curve when \(s\) and \(r\) change sign. The "demand" \( r(b)) is upward sloping. So when demand shifts out, \(b\) rises, but \(r\) falls when \(r>0\) and rises when \(r<0\). With positive interest rates, you produce a greater amount of real debt, for the same surplus, with a lower real interest rate. With negative interest rates and a negative surplus, you produce more debt with a less negative real rate. Hmm. The \(r<g\) region is still a little weird. There is also the possibility of multiple equilibria, like the New-Keynesian zero bound equilibria; see the paper and note.  Erzo Luttmer has a related HAFT paper, "Permanent Primary Deficits, Idiosyncratic Long-Run Risk, and Growth." It's calibrated in much more detail, and also more detailed on the r<g and long run deficit questions. It includes fiscal theory (p. 14) but does not seem centrally focused on inflation. I haven't read it yet, but it's important if you're getting in to these issues. I still regard r<g as a technical nuisance. In most of the cases here, it does not relieve the government of the need to repay debts, it does not lead to a Magic Money Tree, and it does not undermine fiscal price level determination. I am still not a fan of OLG models, which delicately need the economy truly to go on for infinite growth. I'm not totally persuaded HA is first-order important for getting aggregate inflation dynamics right. The Phillips curve still seems like the biggest rotten timber in the ship to me. But these issues are technical and complex, and I could be wrong. Attention is limited, so you have to place your bets in this business; but fortunately you can still read after other people work it out!  Noah Kwicklis at UCLA has a very interesting related paper "Transfer Payments, Sacrifice Ratios, and Inflation in a Fiscal Theory HANK"I numerically solve a calibrated Heterogeneous Agent New-Keynesian (HANK) model that features nominal rigidities, incomplete markets, hand-to-mouth households, nominal long-term government debt, and active fiscal policy with a passive monetary policy rule to analyze the implications of the fiscal theory of the price level (FTPL) in a setting with wealth and income inequality. In model simulations, the total cumulative inflation generated by a fiscal helicopter drop is largely determined by the size of the initial stimulus and is relatively insensitive to the initial distribution of the payments. In contrast, the total real GDP and employment response depends much more strongly on the balance sheets of the transfer recipients, such that payments to and from households with few assets and high marginal propensities to consume (MPCs) move aggregate output much more strongly than payments to or from households with low MPCs.... 

Inflation is back together with a new season of America's favorite sport: zero-contact, finger-pointing. I thought I'd sit back and share a few thoughts with you on the subject on this cold Saturday afternoon. Use the comments section below to let me know what you think.In one corner, I see some pundits somehow wanting to blame the 2021 inflation on workers. Workers are somehow forcing their improved bargaining positions on employers, raising the costs of production, with some or all of these costs passed on to consumers. Then, as workers see their real wages erode, the cycle begins anew begetting the dreaded "wage-price spiral." Those pesky workers. There's no doubt something to the idea that wage demands can lead to higher prices (and why shouldn't workers want cost-of-living adjustments?) But what is the evidence that this behavior was the impulse behind the 2021 inflation? While it's difficult to tell just by eye-balling the data, I think it's reasonable (under this hypothesis) to see wage growth precede (or at least be coincident with) inflation. Unfortunately (for this hypothesis), this is not what we see in the data. In the diagram below, use the Atlanta Fed's Wage Growth Tracker to construct nominal wage inflation for the bottom (green) and top (yellow) wage quintiles. This is plotted against CPI inflation (blue). Another problem for this hypothesis is that wage inflation is moving in the wrong direction for the top three wage quintiles over the Covid era. What we see here is a clear acceleration in the rate of inflation, followed by modest acceleration in wage inflation for the bottom quintile and a deceleration in wage inflation for the top quintile. In 2021, real wages across all quintiles declined (according to this data). So much for increased worker bargaining power. [Note: it is quite likely that net income for the bottom one or two quintiles increased, thanks to government transfers.] On the other side of the political spectrum, we see pundits and politicians blaming the 2021 inflation on "corporate greed." Framing the issue in terms of "corporate greed" is not especially helpful, in my humble opinion. The substantive part of this claim is that large firms were somehow able to leverage their pricing power in 2021 into higher profit margins and record corporate profits. There is, in fact, some evidence in support of this. The diagram below plots profit margins for firms in the Compustat database. Profit margin below is computed on an after tax basis (net income divided by sales). The data is divided between large and not-large firms. Large firms are those in the top 10% of sales volume. By this measure, profit margins seem remarkably stationary over long periods of time. There is some evidence of a modest secular increase in margins c. 2003. Large firms have higher margins. But the part I want to focus on here is near the end of the sample. Profit margins for 90% of firms seem close to their historical average. We see some evidence that profit margins for the top 10% of firms increased in 2021. But this increase peaked in Q3 and then declined back to historical norms in Q4. While the spike in profit-margins likely contributed to inflation, it hardly seems like a smoking gun. And the Q4 reversion to the mean suggests that "corporate greed" is not likely to be a source of inflationary pressure in 2022. Well, if workers and firms are not to blame, then who or what is left? There's the C-19 shock itself, of course, along with the effects it has had on the global supply chain. But the 19 in C-19 refers to the year 2019 (and 2020). We're talking about 2022 here. Sure, the supply chain issues are still with us. But at most, I think they account for a substantial change in relative prices (goods becoming more expensive than services) and an increase in the cost-of-living (an increase in the price-level--not a persistent increase in the rate of growth of the price-level). While the factors above no doubt contributed in some way to the 2021 inflation dynamic, let's face it--the size and persistence of the inflation was mainly policy-induced. The smoking gun here seems to be the sequence of the C-19 fiscal transfers. As we know, this had the unusual and remarkable effect of increasing personal disposable income throughout most of the pandemic. The Fed also had a role to play here because it accommodated the fiscal stimulus (normally, one might have expected a degree of monetary policy tightening to partially off-set the inflationary impulse of fiscal stimulus). Below I plot retail sales (actual vs trend) and the timing of the fiscal actions. I used retail sales here (I think I got this from Jason Furman), but the picture looks qualitatively similar using PCE (the path of nominal PCE went above trend in 2021 and not earlier in the way retail sales did). Just eye-balling the data above, I'd say the CARES Act was a major success (especially under the circumstances). The subsequent two programs might have been scaled back a bit and/or targeted in a more efficient manner. And, knowing what we know now, the Fed could have started its tightening cycle in 2021. Having said this, I wouldn't go so far as to say these were flagrant policy mistakes--given the circumstances. If there was a policy mistake, it was in not having a well-defined state-contingent policy beforehand equipped to deal with a global pandemic. Not having that plan in place beforehand, I think monetary and fiscal policy reacted reasonably well.Policymaking in real-time is hard. And policy, whether formulated beforehand or not, must necessarily balance risks. There was a risk of undershooting the support directed to households. We saw this during the foreclosure crisis a decade ago. And there was a risk of overdoing it in some manner. Keep in mind that it was not clear when the legislation was passed how 2021 would unfold. Similarly, for the Fed--perhaps still feeling the sting of having moved too soon and too fast in the past, hopeful that inflation would decline later in the year--delayed its tightening cycle to 2022. It wasn't perfect. But taken together, the economic policy responses had their intended effect of redistributing income to those who suffered disproportionate economic harm during the pandemic. Finally, what does all this mean for inflation going forward? Well, as I suggested above, I don't think we have to worry about a wage-price spiral (the fiscal policy I think is necessary to support such a phenomenon is not likely to be present). Profit margins appear to be declining (reverting to their long-run averages). The money transfers associated with the last fiscal package are gone for 2022. No big spending bills seem likely to pass in 2022. For better or worse, we're talking a considerable amount of "fiscal drag" here (although, some have pointed to how flush state government coffers are at the moment). Hopefully (fingers crossed), supply-chain problems will continue to be solved. If so, then all of this points to disinflation (a decline in the rate of inflation) going forward. Some recent promising signs as well: [1] month-over-month CPI inflation has declined for two consecutive months (November and December); and [2] the ECI (employment cost index) decelerated in Q4 of 2021. (These numbers are notoriously volatile, so don't put too much stock in the direction. But still, it's better than seeing them go the other way.)Some caveats are in order, of course. In December 2020, I suggested we prepare for a "temporary" burst of inflation in 2021. While this came to pass, the level of inflation surprised me (to be fair, I hadn't incorporated the ARP in my assessment, but even if I had, I think I still would have been surprised). Moreover, I was also surprised by the persistence of inflation--I thought it would decelerate more rapidly (even given the ARP). This just serves to remind me how bad I am at forecasting. Someone recently mentioned a great quote by Rudi Dornbusch: "In economics, things take longer to happen than you think they will, and then they happen faster you thought they could." I can relate to this. Inflation may turn out to be more persistent that I am suggesting. But how might this happen, given the disinflationary forces I cited above? One reason may have to do with the tremendous increase in outside assets the private sector has been compelled to absorb--the increase in the national debt has manifested itself as an increase in private sector wealth. Jason Furman sees this as "excess saving." The question going forward is whether the private sector will be compelled to spend this (nominal) wealth (it already has done so, as my chart above shows) or continue to save (not spend) it? It is possible that this "pent up demand" will be spent over a prolonged period of time. The effect of this would be to keep inflation elevated higher than it would otherwise be (serving to reduce real nominal wealth). How long this might take, I have no idea. But even so, it seems clear that the effect cannot persist indefinitely. At some point the debt-to-GDP ratio will decline to its equilibrium position (D/Y has already started to decline; see here). Another reason why inflation forecasts should be discounted is that it's very difficult to forecast future contingencies. What might happen, for example, if Russia invades the Ukraine this year? Events like these will create disruptions and there's not much monetary and fiscal policy can do about them. But whatever happens, I think the long-run fiscal position of the U.S. will remain anchored (Americans will demand this). And remember, the Fed is bound by its Congressional mandates to keep inflation "low and stable." The Fed's record on inflation since the Volcker years has been pretty good. I'm betting that the record will be equally good over the next 10 years.***PS. I see some people out there strongly asserting it is a "fact" that fiscal policy did not cause the 2021 inflation (see here, for example). The reason, evidently, is because inflation is a global phenomenon. There's something to this, of course. After all, C-19 is a global pandemic. But this reasoning nevertheless seems faulty to me. First, the USD is the global reserve currency. It's quite possible that the U.S. exported some of its inflation to the world (much in the way it did in the 1970s). Second, many other countries (like Canada, for example) adopted similar fiscal policies. Those countries with less expansive fiscal policies also displayed lower inflation, as far as I know. Rather than deflect the blame, we should own it here. Fiscal policy had a lot of positive effects too (e.g., lowering child poverty). The challenge, as always, is to develop ways to calibrate these policies in a more effective manner.