Tag Archives: Economics

The Economics of Brexit

In one of the eBooks that CEPR published in 2022 several authors draw first conclusions. From the introduction by Jonathan Portes:

The analyses in this eBook are very much a preliminary and incomplete account of the economic impacts of Brexit. In some cases, they raise as many questions as they answer.
For example, why have UK imports of EU goods fallen so sharply, while UK exports are much less affected, when (in contrast to the EU) the UK has not yet introduced the full panoply of import controls provided for under the TCA? Why has the large fall in the number of EU workers in some sectors – and a corresponding rise in vacancies – not translated into higher wages, at least in relative terms? Nevertheless, the overwhelming weight of the evidence presented suggests that – very much as economists predicted – Brexit has made the UK a less open economy, reduced UK trade in both goods and services, and increased prices for some products. Moreover, despite public scepticism of economists and their forecasts, our verdict is increasingly shared by the wider public (Surridge 2022).

However, as Fetzer points out, aggregate impacts are not the whole story by any means. His analysis suggests not only that the costs of Brexit are very unevenly distributed, but that, perhaps paradoxically, those areas that voted most heavily for Brexit are the worst affected, while London has escaped largely unscathed, at least so far.

Economics PhD Admissions

In an NBER working paper, Jessica Bai, Matthew Esche, W. Bentley MacLeod and Yifan Shi argue:

We introduce a model of the admissions process based upon standard agency theory and explore its implications with economics PhD admissions data from 2013-2019. We show that a subjective score that aggregates subjective ratings and recommendation letter features plays a more important role in determining admissions than an objective score based upon graduate record exam (GRE) scores. Subjective evaluations by references who write multiple letters are not only more influential than those of references who write one letter, but they are also more informative. Since multiple-letter references are also more highly ranked economists, this implies that there is a constraint on the supply of high-quality references. Moreover, we find that both the subjective and objective scores are correlated with job placement at a top economics department after the completion of the PhD. These indicators of individual achievement have a smaller effect than an undergraduate degree from an Ivy Plus school (i.e., Ivy League + Stanford, MIT, Duke, and Chicago). In the self-selected pool of applicants, Ivy Plus graduates are twice as likely to be admitted to a top 10 graduate program and are much more likely to obtain an assistant professor position at a top 10 program upon PhD completion. Given that Ivy Plus students must pass a stringent selection process to gain admission to their undergraduate program, we cannot reject the hypothesis that admission committees use information efficiently and fairly. However, this also implies that there may be a return to attending a selective undergraduate program in order to be pooled with highly skilled individuals.

“Life Among the Econ”

“Reserves for All: Political Rather Than Macroeconomic Risks,” CEPR, 2021

Chapter 5 in the CEPR eBook, November 24, 2021. HTML.

From the conclusion:

From a macroeconomic perspective, central banks can largely neutralise the consequences of CBDC. What is highly uncertain, however, is whether they would choose to do so – the political risks of ‘Reserves for All’ are first-order. The decision for or against CBDC thus should not only reflect the assessment of economic trade-offs, but also whether societies are confident in their ability to efficiently manage conflicts of interest. If not, and if they fear that the introduction of CBDC could further politicise banking and central banking, then the introduction of CBDC might constitute a risky regime change. It will be interesting to see how different [countries] judge this risk.

“CBDC: Considerations, Projects, Outlook,” CEPR/VoxEU, 2021

CEPR eBook, November 24, 2021. HTML.

VoxEU, November 24, 2021. HTML.

Retail central bank digital currency has morphed from an obscure fascination of technophiles and monetary theorists into a major preoccupation of central bankers. Pilot projects abound and research on the topic has exploded as private sector initiatives such as Libra/Diem have focused policymakers’ minds and taken the status quo option off the table. In this eBook, academics and policymakers review what we know about the economic, legal, and political implications of CBDC, discuss current projects, and look ahead.

Pretend Economists

In Foreign Affairs, Paul Romer criticizes “pretend economists” who pretend that economics—and they themselves—can answer normative questions on scientific grounds. He argues that “pretend economists” open the field to corruption.

The alternative is to make honesty and humility prerequisites for membership in the community of economists. The easy part is to challenge the pretenders. The hard part is to say no when government officials look to economists for an answer to a normative question. Scientific authority never conveys moral authority. No economist has a privileged insight into questions of right and wrong, and none deserves a special say in fundamental decisions about how society should operate. Economists who argue otherwise and exert undue influence in public debates about right and wrong should be exposed for what they are: frauds.

Arnold Kling’s “Specialization and Trade, A Re-Introduction to Economics”

Arnold Kling (2016), Specialization and Trade, A Re-Introduction to Economics, Washington, DC, Cato Institute.

Kling’s central theme in this short book of nine main chapters is that specialization, trade, and the coordination of individual plans by means of the price system and the profit motive play fundamental roles in modern economies. Most mainstream economists would agree with this assessment. Their models of trade, growth, and innovation certainly include the four elements, with varying emphasis.

But Kling criticizes the methodological approach adopted by post-world-war-II economics, which he associates with “MIT economics.” An MIT PhD himself, he argues that economics, and specifically macroeconomics, should adopt less of a mechanistic and more of an evolutionary perspective to gain relevance. In the second chapter, entitled “Machine as Metaphor,” Kling asserts that under the leadership of Paul Samuelson post-war (macro)economics framed economic issues as programming problems that resemble resource allocation problems in a wartime economy. Even as the discipline evolved, Kling contends, the methodology remained the same, pretending controllability by economist-engineers; in the process, the role of specialization was sidelined in the analysis.

I think that Kling is too harsh in his assessment. Economics and macroeconomics, in particular, has changed dramatically since the times of Paul Samuelson. The notion that, given enough instruments, any economic problem can be solved as easily as a system of equations, has lost attraction. Modern macroeconomic models are based on microeconomic primitives; they take gains from trade seriously; they involve expectations and frictions; and they do not suggest easy answers. The task of modern macroeconomics is not to spit out a roadmap for the economist-engineer but to understand mechanisms and identify problems that arise from misaligned incentives.

Kling is right, of course, when he argues that many theoretical models are too simplistic to be taken at face value. But this is not a critique against economic research which must focus and abstract in order to clarify. It rather is a critique against professional policy advisors and forecasters, “economic experts” say. These “experts” face the difficult task of surveying the vast variety of mechanisms identified by academic research and to apply judgement when weighing their relevance for a particular real-world setting. To be useful, “experts” must not rely on a single framework and extrapolation. Instead, they must base their analysis on a wide set of frameworks to gain independent perspectives on a question of interest.

In chapters three to five, Kling discusses in more detail the interplay of myriads of specialized trading partners in a market economy and how prices and the profit motive orchestrate it. In the chapter entitled “Instructions and Incentives,” Kling emphasizes that prices signal scarcity and opportunity costs are subjective. In the chapter entitled “Choices and Commands,” he discusses that command-and-control approaches to organizing a society face information, incentive, and innovation problems, unlike approaches that rely on a functioning price mechanism. And in the chapter “Specialization and Sustainability,” Kling makes the point that well-defined property rights and a functioning price mechanism offer the best possible protection for scarce resources and a guarantee for their efficient use. Sustainability additionally requires mechanisms to secure intergenerational equity.

I agree with Kling’s point that we should be humble when assessing whether market prices, which reflect the interplay of countless actors, are “right” or “wrong.” However, I would probably be prepared more often than Kling to acknowledge market failures of the type that call for corrective taxes. The general point is that Kling’s views expressed in the three chapters seem entirely mainstream. While we may debate how often and strongly market prices fail to account for social costs and benefits, the economics profession widely agrees that for a price system to function well this precondition must be satisfied.

In the sixth chapter, entitled “Trade and Trust,” Kling argues that specialization rests on cultural evolution and learning and more broadly, that modern economic systems require institutions that promote trust. Independently of the norms a particular society adopts, it must implement the basic social rule,

[r]eward cooperators and punish defectors.

How this is achieved (even if it is against the short-run interest of an individual) varies. Incentive mechanisms may be built on the rule of law, religion, or reputation. And as Kling points out societies almost always rely on some form of government to implement the basic social rule. In turn, this creates problems of abuse of power as well as “deception” and “demonization.” Mainstream economists would agree. In fact, incentive and participation constraints, lack of commitment, enforcement, and self-enforcement are at center stage in many of their models of partial or general equilibrium. Similarly, the role of government, whether benevolent or representing the interests of lobby groups and elites, is a key theme in modern economics.

Chapter seven, entitled “Finance and Fluctuations,” deals with the role of the financial sector. Kling argues that finance is a key prerequisite for specialization and since trust is a prerequisite for finance, swings in trust—waves of optimism and pessimism—affect the economy. No mainstream macroeconomist will object to the notion that the financial sector can amplify shocks. Seminal articles (which all were published well before the most recent financial crisis) exactly make that point. But Kling is probably right that the profession’s workhorse models have not yet been able to incorporate moods, fads, and manias, the reputation of intermediaries, and the confidence of their clients in satisfactory and tractable ways, in spite of recent path-breaking work on the role of heterogenous beliefs.

In chapter eight, Kling focuses on “Policy in Practice.” He explains why identifying market failure in a model is not the same as convincingly arguing for government intervention, simply because first, the model may be wrong and second, there is no reason to expect government intervention to be frictionless. I don’t know any well-trained academic economist who would disagree with this assessment (but many “experts” who are very frighteningly confident about their level of understanding). The profession is well aware of the insights from Public Choice and Political Economics, although these insights might not be as widely taught as they deserve. And Kling is right that economists could explain better why real-world policy selection and implementation can give rise to new problems rather than solely focusing on the issue of how an ideal policy might improve outcomes.

To me, the most interesting chapters of the book are the first and the last, entitled “Filling in Frameworks” and “Macroeconomics and Misgivings,” respectively. In the first chapter, Kling discusses the difference between the natural sciences and economics. He distinguishes between scientific propositions, which a logical flaw or a contradictory experiment falsifies, and “interpretive frameworks” a.k.a. Kuhn’s paradigms, which cannot easily be falsified. Kling argues that

[i]n natural science, there are relatively many falsifiable propositions and relatively few attractive interpretive frameworks. In the social sciences, there are relatively many attractive interpretive frameworks and relatively few falsifiable propositions.

According to Kling, economic models are interpretative frameworks, not scientific propositions, because they incorporate a plethora of auxiliary assumptions and since experiments of the type run in the natural sciences are beyond reach in the social sciences. Anomalies or puzzles do not lead economists to reject their models right away as long as the latter remain useful paradigms to work with. And rightly so, according to Kling: For an interpretative framework with all its anomalies is less flawed than intuition which is uninformed by a framework. At the same time, economists should remain humble, acknowledge the risk of confirmation bias, and remain open to competing interpretative frameworks.

In the chapter entitled “Macroeconomics and Misgivings,” Kling criticizes macroeconomists’ reliance on models with a representative agent. I agree that representative agent models are irrelevant for applied questions when the model implications strongly depend on the assumption that households are literally alike, or that markets are complete such that heterogeneous agents can perfectly insure each other. When “experts” forecast macroeconomic outcomes based on models with a homogeneous household sector then these forecasts rest on very heroic assumptions, as any well-trained economist will readily acknowledge. Is this a problem for macroeconomics which, by the way, has made a lot of progress in modeling economies with heterogeneous agents and incomplete markets? I don’t think so. But it is a problem when “experts” use such inadequate models for policy advice.

Kling argues that the dynamic process of creative destruction that characterizes modern economies requires ongoing change in the patterns of specialization and trade and that this generates unemployment. Mainstream models of innovation and growth capture this process, at least partially; they explain how investment in new types of capital and “ideas” can generate growth and structural change. And the standard framework for modeling labor markets features churn and unemployment (as well as search and matching) although, admittedly, it does not contain a detailed description of the sources of churn. The difference between the mainstream’s and Kling’s view of how the macroeconomy operates thus appears to be a difference of degree rather than substance. And the difference between these views and existing models clearly also reflects the fact that modeling creative destruction and its consequences is difficult.

Kling is a sharp observer when he talks about the difference between “popular Keynesianism” and “rigor-seeking Keynesianism.” The former is what underlies the thinking of many policy makers, central bankers, or journalists: a blend of the aggregate-demand logic taught to undergraduates and some supply side elements. The latter is a tractable simplification of a micro-founded dynamic general equilibrium model with frictions whose properties resemble some key intuitions from popular Keynesianism.

The two forms of Keynesianism help support each other. Popular Keynesianism is useful for trying to convince the public that macroeconomists understand macroeconomic fluctuations and how to control them. Rigor-seeking Keynesianism is used to beat back objections raised by economists who are concerned with the ways in which Keynesianism deviates from standard economics, even though the internal obsessions of rigor-seeking Keynesianism have no traction with those making economic policy.

There is truth to this. But in my view, this critique does not undermine the academic, rigor-seeking type of Keynesianism while it should undermine our trust in “experts” who work with the popular sort which, as Kling explains, mostly is confusing for a trained economist.

In the end, Kling concludes that it is the basics that matter most:

[B]etter economic outcomes arise when patterns of sustainable specialization and trade are formed. … It requires the creative, decentralized, trial-and-error efforts of thousands of entrepreneurs and millions of households … Probably the best thing that the government can do to encourage new forms of specialization is to rethink existing policies that restrict competition, discourage innovation, and retard mobility.

This is a reasonable conclusion. But it is neither a falsifiable proposition nor an interpretive framework. It is the synthesis of many interpretive frameworks, weighed by Kling. In my own view, the weighting is based on too harsh an assessment according to which many modern macroeconomic models are irrelevant.

Kling’s criticism of contemporaneous macroeconomics reads like a criticism of the kind of macroeconomics still taught at the undergraduate level. But modern macroeconomics has moved on—it is general equilibrium microeconomics. Its primary objective is not to produce the one and only model for economist-engineers or “experts” to use, but rather to help us understand mechanisms. A good expert knows many models, is informed about institutions, and has the courage to judge which of the models (or mechanisms they identify) are the most relevant in a specific context. We don’t need a new macroeconomics. But maybe we need better “experts.”

Marx was Right—Partly

According to René Scheu in the NZZ.

Die zehn «Massregeln» für die «fortgeschrittensten Länder», in die das «Kommunistische Manifest» mündet, lesen sich aus heutiger Sicht wie ein sozialdemokratisches Programm, dem auch viele softbürgerliche Politiker sogleich vorbehaltlos zustimmen würden. Starke Progressivsteuer, Geldmonopol der Nationalbank, Zentralisation des Transportwesens, nationale Industriepolitik, Verstaatlichung des Bauernstandes und unentgeltliche Erziehung aller Kinder gehören längst zu den Errungenschaften avancierter Wohlfahrtsstaaten – damit sind wohlgemerkt bereits sechs der zehn Punkte erfüllt….

Marxens Kritik zielt nicht auf den Unternehmer und Eigentümer als solchen, sondern auf den Bourgeois, der auf der faulen Haut liegt und auf Kosten anderer lebt. …

Der Verfasser des «Manifests» ist kein Moralist, sondern ein geradezu passionierter Ökonomist der ersten Stunde.

And according to The Economist:

  • Modern “capitalism” often reduces to rent seeking: The Economist mentions “corporate bureaucrats”, “management consultants”, “professional board members”, “retired politicians (who spend their twilight years sponging off firms they once regulated)”.
  • It is global (WEF).
  • It has a tendency towards monopoly (Google, Facebook, …).
  • It yields an army of casual workers (gig economy).
  • But Marx overestimated poverty and underestimated reform.

Isaiah Berlin: Karl Marx and his Environment.

Neoliberalism—Narrow and Broad

In the Boston Review, Dani Rodrik discusses neoliberalism and argues that

mainstream economics shades too easily into ideology, constraining the choices that we appear to have and providing cookie-cutter solutions.

Rodrik emphasizes that sound economics implies context specific policy recommendations.

And therein lies the central conceit, and the fatal flaw, of neoliberalism: the belief that first-order economic principles map onto a unique set of policies, approximated by a Thatcher–Reagan-style agenda.

But he also stresses that the

principles [of economics] are not entirely content free. China, and indeed all countries that managed to develop rapidly, demonstrate their utility once they are properly adapted to local context. Conversely, too many economies have been driven to ruin courtesy of political leaders who chose to violate them.

In Rodrik’s view

[e]conomists tend to be very good at making maps, but not good enough at choosing the one most suited to the task at hand.

I have argued elsewhere that the main job of economists is to create maps, not to choose among them. See also the earlier post on Ariel Rubinstein’s excellent discussion of Rodrik’s recent book.

On Publishing and Cost Benefit Analysis

On his blog, Gilles Saint-Paul comments on the publication process in economics.

Of course I was wrong in all accounts. The publication process in economics is not a publication process, it is a validation process by which we acquire a certain rank in a certain pecking order. Submitting a paper to a journal has nothing to do with research dissemination, it is far more similar to taking an exam or participating in a sports competition. The actual dissemination takes place mostly orally, in seminars and conferences; these seminars and conferences are also important validation events, because they allow authors to signal some of their characteristics that may influence their position in the pecking order, while not being easy to infer from their papers.

Now, when you take an exam as a student, you are graded by your professor, not by a fellow student – who would be a competitor if this exam is actually a contest. …

Yet this is the way our own profession is organized. Each submission is “peer reviewed’, that is, it has to be accepted by anonymous referees who happen to be participating in the same beauty contest as the author(s), most often in the same subcategory. At a minimum, as believers of cost-benefit analysis, we should consider that the journal editors and referees themselves perform a cost-benefit analysis when deciding whether or not to publish a paper. I must say that if I apply such a theory to explain my own experience with acceptances and rejections, I easily get an R2 of 80 %.

On the State of Macroeconomics

In a paper, Ricardo Reis defends macroeconomics against various critiques. He concludes:

I have argued that while there is much that is wrong with macroeconomics today, most critiques of the state of macroeconomics are off target. Current macroeconomic research is not mindless DSGE modeling filled with ridiculous assumptions and oblivious of data. Rather, young macroeconomists are doing vibrant, varied, and exciting work, getting jobs, and being published. Macroeconomics informs economic policy only moderately and not more nor all that differently than other fields in economics. Monetary policy has benefitted significantly from this advice in keeping inflation under control and preventing a new Great Depression. Macroeconomic forecasts perform poorly in absolute terms and given the size of the challenge probably always will. But relative to the level of aggregation, the time horizon, and the amount of funding, they are not so obviously worst than those in other fields. What is most wrong with macroeconomics today is perhaps that there is too little discussion of which models to teach and too little investment in graduate-level textbooks.

Models Make Economics A Science

In the Journal of Economic Literature, Ariel Rubinstein discusses Dani Rodrik’s “superb” book “Economics Rules.” The article nicely articulates what economics and specifically, economic modeling is about. Some quotes (emphasis my own) …

… on the nature of economics:

[A] quote … by John Maynard Keynes to Roy Harrod in 1938: “It seems to me that economics is a branch of logic, a way of thinking”; “Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world.”

[Rodrik] … declares: “Models make economics a science” … He rejects … the … common justification given by economists for calling economics a science: “It’s a science because we work with the scientific method: we build hypotheses and then test them. When a theory fails the test, we discard it and either replace it or come up with an improved version.” Dani’s response: “This is a nice story, but it bears little relationship to what economists do in practice …”

… on models, forecasts, and tests:

A good model is, for me, a good story about an interaction between human beings …

A story is not a tool for making predictions. At best, it can help us realize that a particular outcome is possible or that some element might be critical in obtaining a particular result. … Personally, I don’t have any urge to predict anything. I dread the moment (which will hopefully never arrive) when academics, and therefore also governments and corporations, will be able to predict human behavior with any accuracy.

A story is not meant to be “useful” in the sense that most people use the word. I view economics as useful in the sense that Chekhov’s stories are useful—it inspires new ideas and clarifies situations and concepts. … [Rodrik] is aware … “Mischief occurs when economists begin to treat a model as the model. Then the narrative takes on a life of its own and becomes dislodged from the setting that produced it. It turns into an all-purpose explanation that obscures alternative, and potentially more useful, story lines”.

A story is not testable. But when we read a story, we ask ourselves whether it has any connection to reality. In doing so, we are essentially trying to assess whether the basic scenario of the story is a reasonable one, rather than whether the end of the story rings true. … Similarly, … testing an economic model should be focused on its assumptions, rather than its predictions. On this point, I am in agreement with Economics Rules: “. . . what matters to the empirical relevance of a model is the realism of its critical assumptions”.

… on facts:

The big “problem” with interpreting data collected from experiments, whether in the field or in the lab, is that the researchers themselves are subject to the profession’s incentive system. The standard statistical tests capture some aspects of randomness in the results, but not the uncertainty regarding such things as the purity of the experiment, the procedure used to collect the data, the reliability of the researchers, and the differences in how the experiment was perceived between the researcher and the subjects. These problems, whether they are the result of intentional sleight of hand or the natural tendency of researchers to ignore inconvenient data, make me somewhat skeptical about “economic facts.”

General Equilibrium Theory up to Arrow and Debreu

On his blog A Fine Theorem, Kevin Bryan discusses the history of economic thought leading from the classical economists and Walras to Arrow and Debreu.

My read of the literature on GE following Arrow is as follows. First, the theory of general equilibrium is an incredible proof that markets can, in theory and in certain cases, work as efficiently as an all-powerful planner. That said, the three other hopes of general equilibrium theory since the days of Walras are, in fact, disproven by the work of Arrow and its followers. Market forces will not necessarily lead us toward these socially optimal equilibrium prices. Walrasian demand does not have empirical content derived from basic ordinal utility maximization. We cannot rigorously perform comparative statics on general equilibrium economic statistics without assumptions that go beyond simple utility maximization. From my read of Walras and the early general equilibrium theorists, all three of those results would be a real shock.

Economics as Bullshit Detection

In separate blog posts, Russ Roberts and John Cochrane have called for humility on the part of economists. Asking “What do economists know?,” Roberts and Cochrane point out—correctly—that economics is not as strong on quantification as some economists and many pseudo economists pretend, and as is often expected from economists.

Economics is not the same as applied statistics although the latter can help clarify, at least to some extent, the empirical relevance of economic theories. Correlation does not imply causation. Identifying assumptions that aim at establishing causal claims based on correlation analysis deserve skepticism, especially when the process that led to the empirical results remains in the dark (see notes on replicability here, here, here).

Sound economics heavily relies on consistency checking, or bullshit detection in Cochrane’s words. It insists on keeping accounting identities in mind and never forgetting about incentives. And it is acutely aware of the fact that good models are nothing more than consistent stories—but at least they are consistent stories.

Economics in Theodor Herzl’s “The Jewish State”

On his blog, Tyler Cowen summarizes the economics in Theodor Herzl’s “The Jewish State.”

Herzl favored selling European homes and businesses of departing Jews and buying land in Argentina or Palestine, at a profit, through a land acquisition company incorporated in London. Poor Jews from Romania and Russia would supply cheap labor and be rewarded by their own houses eventually. Herzl favored short working weeks, a democratic monarchy or the aristocratic republic of Renaissance Venice.

Economics: The Core

The Economist reviews core ideas in economics. The introductory article to a new series points out that

economists’ fundamental mission is not to forecast recessions but to explain how the world works.

It argues that economists have delivered and it discusses six exemplary areas of economic research:

  • Nash equilibrium (article, August 20);
  • Mundell-Fleming trilemma (article, August 27);
  • Minsky financial instability (article, July 30);
  • Stolper-Samuelson trade effects on wages (article, August 6);
  • Keynes fiscal multiplier (article, August 13); and
  • Akerlof et al information asymmetries (article, July 23).

Refreshingly, the article argues that

[t]hese breakthroughs are adverts not just for the value of economics, but also for three other things: theory, maths and outsiders.

I agree. But the value of economics also derives from more elementary insights, related to, for example,

  • budget and resource constraints;
  • the information content of prices;
  • public choice; or
  • the link between monetary aggregates and the general price level.

Today, these latter insights might appear even more trivial than those picked by The Economist. But they are central, and emphasizing them might lead to different policy conclusions than the common focus on economic frictions and aggregate demand.

Show Me The Model

Three opinion leaders in the blogosphere have laid out how they think about the macroeconomy. They talk about “models” but unfortunately don’t deliver. Instead, they provide lists of beliefs or facts to be explained. Economics is a science precisely because it has progressed beyond such lists. Economists build models—consistent, well-structured and clearly specified (and thus, mathematically formulated) stories.

But here are the lists: Scott Sumner’s “Musical Chairs model” (blog):

In the short run, employment fluctuations are driven by variations in the NGDP/Wage ratio.

Monetary policy drives NGDP, by influencing the supply and demand for base money.

Nominal wages are sticky in the short run, and hence NGDP shocks cause variations in employment in the same direction.

In the long run, wages are flexible and adjust to changes in NGDP. Unemployment returns to the natural rate (currently about 5% in the US.)

Tyler Cowen’s “model” (blog):

In world history, 99% of all business cycles are real business cycles.  No criticism of RBC can change this fact.  Furthermore the propagation mechanism for a “Keynesian business cycle” (arguably a misleading phrase) also relies on RBC theory.

In the more recent segment of world history, a lot of cycles have been caused by negative nominal shocks.  I consider the Christina and David Romer “shock identification” paper (pdf, and note the name order) to be one of the very best pieces of research in all of macroeconomics.  Sometimes central banks tighten when they shouldn’t, and this leads to a recession, due mainly to nominal wage stickiness.

Workers are laid off because employers are often (not always) afraid to cut their nominal wages, for fear of busting workplace morale, or in Europe often for legal and union-related reasons.

Overall I favor a nominal gdp rule for monetary policy.  But most of its gains would come in a few key historical episodes, such as 1929-1932, or 2008-2009.  In most periods I don’t think we know what the correct monetary policy should be, nor do we know that it matters.  Still, that uncertainty does not militate against an ngdp rule.

Once workers are unemployed, nominal wage stickiness is no longer the main reason why they stay unemployed.  In fact nominal wage stickiness is largely taken out of the equation because there is no preexisting nominal wage contract for these workers.  There may, however, be some residual stickiness due to irrational reservation wages, also known as voluntary unemployment due to stupidity.  (You will find a different perspective in Scott’s musical chairs model, which I may cover more soon.)

Monetary stimulus to be effective needs to be applied very early in the job destruction process of a recession.  It is much harder to put the pieces back together again, so urgency is of the essence.

The successful reemployment of workers depends upon a matching problem, a’la Pissarides, Mortensen, and others.  Yet this matching problem is poorly understood, and it can involve a mix of nominal and real imperfections.  Sometimes it is solved more quickly than expected, such as in the recent UK experience, and other times more slowly than expected, as in current Spain.  Most of the claims you will read about this reemployment of workers are wrong, enslaved to ideology or dogmatism, or at the very least unjustified.  Hardly anyone wants to admit this.

Really bad recessions involve deficient aggregate demand, negative shocks to intermediation, some chronic supply-side problems, negative wealth effects, and increases in the risk premium, all together.  It is hard to find a quick fix.  Furthermore models where AS and AD curves are independent and separable are often misleading, despite their analytic convenience.

Given that weak AD is only one of the problems in a bad downturn, and that confidence, risk, and supply side problems matter too, the best question to ask about fiscal policy is how well the money is being spent.  The “jack up AD no matter” approach is, in the final political equilibrium, not doing good fiscal policy any favors.

You should neither rule out nor overstate the relevance of Hayek and Minsky.  Their views have much in common, despite the difference in ideological mood affiliation and who — government or the market — gets blamed for the downturn.  For really bad recessions, usually both institutions are complicit to say the least.

All propositions about real interest rates are wrong.

The Economist’s Free Exchange response to Cowen’s model (blog):

Supply-side policy is hard. Why is America the richest large economy in the world? Well, because output per person has grown at about 2% per year, on average, for a very long time. How did it manage that? I have a long list of policy choices and characteristics and historical accidents that I believe contributed, but I would find it very difficult to say which of those factors were most important. If someone gave me free reign over the German economy and asked me to raise its output per person to American levels, I know the sorts of things I would do, but I have a low level of confidence that I could succeed, or even close much of the gap, within a generation.

That doesn’t mean that supply-side policy should be ignored. Supply-side reforms (of the sort this newspaper tends to favour) are politically difficult to achieve, but many of them are probably at least somewhat useful and should be undertaken whenever the political environment is amenable (though with very modest expectations regarding detectable effects on growth).

With supply-side policy, the precision of a policy action is not the problem; accuracy is. With demand-side policy, it is the opposite: it is pretty easy to meet broad policy goals, so long as you’re not too concerned about hitting them square on the nose.

We know what an economy with way too much demand looks like. It has high and accelerating inflation.

We know what an economy with way too little demand looks like. It has high unemployment and deflation.

Within those two extremes, it can be tricky to identify exactly where an economy stands: how close or far away from potential output it is.

Both too much and too little demand are economically costly, but history suggests that too little demand is far more economically costly and politically risky than too much demand. So policy should err on the side of too much demand rather than too little.

The determined use of monetary policy is almost always going to be sufficient to generate the right sort of “too much demand”. But an independent central bank might not always be able to muster the appropriate determination. In some cases a central bank may flounder until a clear political consensus emerges supporting the determined use of monetary policy.

It is generally unwise for countries to sacrifice monetary-policy autonomy, either by adopting a constraining exchange-rate regime or by introducing an excessive level of capital-account openness.

In countries with autonomous monetary policy, which are stuck at the zero lower bound on interest rates, fiscal policy is almost by definition too tight, and it is probably quite difficult to conduct fiscal stimulus in a way that generates long-run economic costs. That is because the long-run supply-side and fiscal benefits of getting off the ZLB are probably pretty large.

Fiscal policy is subject to political constraints, and it may be easier to introduce a large stimulus in emergency situations if the pre-emergency public-debt burden is low. That suggests that prudence in normal times is a good idea (though do remember point number 10).

Don’t subsidise debt.

The level of financial- and banking-sector liberalisation at which it can be demonstrated persuasively that further liberalisation will generate net benefits is probably not that high.