Coronavirus and The Affluent Society

The coronavirus pandemic has highlighted the importance of healthcare, food, shelter, and jobs to a greater extent than any other crisis since World War II. It is serving as a stark reminder that the health of loved ones and access to the basics are the most important things.

Fortunately, lawmakers recognize the existential risks of an economic breakdown and have responded with large stimulus measures. And they realize that they can continue to do so, with multiple rounds of stimulus if necessary. As President Trump, America’s first president to implicitly embrace modern monetary theory, replied when asked how we’ll pay for it: “It’s our money. We are the ones. It’s our currency.” As long as we remain within our nation’s resource constraints, we can simply print the money (or issue the debt) necessary to do the things we consider valuable.

Despite an acknowledgement that we have the ability to ensure that every American has access to life’s essentials, there is a risk that economics will eventually return to “business as usual”: a focus on efficiencies and GDP growth to the neglect of distributional concerns and building a resilient economy. This crisis is making the limits of the neoclassical framework clear. In The Affluent Society, first published in 1958, Ken Galbraith lamented our focus on GDP growth at the expense of a push for broad-based prosperity: “The ancient preoccupations of economic life -- with equality, security and productivity -- have now narrowed down to a preoccupation with productivity and production”. The basic framework of neoclassical economics was developed in the 18th and 19th centuries, when a stronger focus on productivity made sense. In the subsistence world of the Malthusian trap, a large drop in GDP meant starvation for a large part of the population. Today’s world is different -- we are wealthier than when we declared independence from Great Britain. But the priorities of economics have not been sufficiently updated to account for the material abundance of modern developed economies.

In the midst of the worsening crisis, economic forecasters are calling for a short-term drop in GDP of around 30 percent. These numbers sound harrowing. They are also a remarkable reminder that even if GDP drops by 40 or 50 percent, our nation is wealthy enough to provide decent healthcare, food, shelter, and jobs to every American, if we choose to do so.

Galbraith ends The Affluent Society with “To furnish a barren room is one thing. To continue to crowd in furniture until the foundation buckles is quite another. To have failed to solve the problem of producing goods would have been to continue man in his oldest and most grievous misfortune. But to fail to see that we have solved it, and to fail to proceed thence to the next tasks, would be fully as tragic.”

The next task is building a more resilient economy. President Roosevelt’s Second Bill of Rights, in which he declared employment, food, clothing, housing, medical care, social security, and education to be a right of every American, might be a good place to start. That is a matter for the democratic process to decide. Here’s hoping that the current tragedy will be a catalyst for policy that delivers more economic rights to all Americans. A stronger focus on equality and security, to go along with our focus on productivity, will make our economy fairer, stronger, and more resilient.

Ten Years and Beyond, Ten Years Ago: NSF's long-term research agenda

A criticism of my first two posts (coming from myself, as the lone reader of this blog), is that it is easier to criticize than to build. As the Wikipedia summary of the Cambridge capital controversy states "it was much easier to destroy neoclassical theory than to develop a full-scale alternative that can help us understand the world."

One group working to support innovative economic modeling is the National Science Foundation. Today, NSF's Directorate for Social, Behavioral and Economic Sciences (SBE) "supports research and infrastructure to advance understanding of a full range of human networks", through its Human Networks and Data Science (HNDS) program.

In this post I summarize an earlier effort. In 2010, the NSF's SBE invited economists to write

white papers describing the questions that are "likely to drive next generation research in the social, behavioral, and economic sciences." They called it "Ten Years and Beyond: Economists Answer NSF's Call for Long-Term Research Agendas". NSF received 252 papers from economists including Daron Acemoglu, David Autor, Andrew Lo, Raj Chetty, Stanley Fischer, and Hal Varian.

First, I highlight a couple of quotes from various papers and my thoughts on them, in particular their relevance to interdisciplinary agent-based models / theoretical macro. Then, I give a bit more of a summary of a few of the papers that were especially interesting to me.

Coronavirus: Making policy outside the database

In the middle of the coronavirus pandemic, fiscal policymakers, health professionals, and others are focused on critically important short-term decisions – whether to cut payroll taxes, send checks, act as the payer-of-last-resort, and so on – and rightly so. When policymakers were making similarly difficult decisions in 2009, Doyne Farmer and Duncan Foley wrote that one would assume that leaders in the US and abroad “are using sophisticated quantitative computer models to guide us out of the current economic crisis. They are not.” The same is true today.

Farmer and Foley pointed out that policymakers rely on two types of models to determine their response: empirical statistical models – which are fit to past data – and general equilibrium models – which assume a perfect world, thereby ruling out crises. These models have less-than-perfect explanatory ability due to their strong assumptions. Their main strength is high predictive power in stable periods. If GDP grew by 2 percent last year and we all maintain our routines, it’s generally a pretty good guess that GDP will grow by 2 percent this year.

However, as we see in times such as 2007-09 and today, the predictive power of these models becomes relatively nonexistent once the relationship between the models’ dependent and supposedly independent variables stop reflecting the behavior of the “complex networks of agents and institutions, stocks and flows, goods and services, money and credit”. Beyond the human tragedy, it is hard to know the full impact of empty streets, shuttered local retailers, and halted international supply lines. But clearly the statistical relationships of the empirical models and the assumptions of the general equilibrium models do not provide useable information to leaders during a pandemic. In the words of Bill Janeway in Doing Capitalism in the Innovation Economy, we are “living outside the database”.

Legacy economists and penguins

Why have top economists not updated their views in light of evidence that their main macroeconomic models aren't working? In short: inflexibility and too much intellectual investment in the old system to change now.

The DSGE model is so attractive, as I said, to the neatness freak in many economists that it is very hard for anything else to get any traction, and I hope that we can change that.

- Robert Solow in 2010 Congressional testimony

Standardization

Legacy software denotes a system that has been superseded by better technology but is difficult to replace because of its wide use. Similarly, the relevance of mainstream / legacy macroeconomics to real world analyses has been supplanted by other schools of thought. However, as in the case with old IT systems, legacy macroeconomics’ prominence is the result of a type of market failure, in which inertia and path dependence have resulted in the persistence of an inefficient equilibrium.

The economic research agenda since the 1970’s has resulted in a relatively high degree of

standardization, as legacy economists have converged on “a largely shared vision of both fluctuations and of methodology.” (Blanchard, 2009) Standardization has many benefits. For example, it enables us to call or text anyone, anywhere, regardless of our service provider or phone brand. Paul Samuelson believed that mathematical foundations provide a “natural language” for economists; they contribute greatly to informed discussions about policies and trade-offs. But, as Joseph Farrell and Garth Saloner showed in a widely-cited paper, standardization benefits can trap an industry in an inferior standard when a better alternative becomes available. (Farrell & Saloner, 1985) For example, it doesn’t matter whether Google+ was a “better” social network than Facebook – Facebook’s millions of users gave it an unassailable position. If we each had the choice of only one social media platform, anyone who switched to Google+ would have had an account on the world’s best social media site, and an empty news feed. Farrell and Saloner dubbed the excess inertia that can occur when early adopters bear a disproportionate share of these switching costs ("transient incompatibility costs") the penguin effect. “Penguins who must enter the water to find food often delay doing so because they fear the presence of predators. Each would prefer some other penguin to test the waters first.” (Farrell & Saloner, 1986) Legacy economists, like penguins, are stuck in a case of excess inertia.

Network effects

When technologies exhibit network effects (increasing returns based on number of users), multiple outcomes and equilibria are often possible. In economics, network effects are visible in levels of research support for various models. The aggregate research of non-establishment economists “is a fraction of what the mainstream tradition mounts, especially in core, policy-relevant domains like macroeconomics and public finance. Relative to the mainstream, the dissenters do not get much attention, and do not carry much weight.” (Winter) For young academics seeking tenure, prestige, and funding, the rational course of action is to become an expert in the mainstream models (DSGE, RBC, OLG) and work to improve them, without questioning too deeply the core assumptions (rational expectations, perfect foresight, importance of frictions and technology shocks, etc.) on which the entire framework is based. “The successful scholar is always the one who adds some marginal improvement to the dominant theories everyone is already accustomed to. If, however, a new theory falls outside of customary channels, it is certain to face general opposition whatever its empirical justification.” (Allais) And the empirical justification for the dominant framework is shaky.

Paul Romer has written that, due to convoluted models that rely on assumptions that are opaque and not credible, “For more than three decades, macroeconomics has gone backwards.” This concurs with Kenneth Arrow’s assessment. The man who developed the modern conception of general equilibrium (along with Gerard Debreu and Lionel McKenzie) concluded that the limitations of assuming rational behavior are “in contradiction to the very large bodies of empirical and theoretical research, which draw powerful implications from utility maximization.” (Arrow, 1986) Yet the research has continued.

Ad hoc additions hinder the shift to a better economics

Economists have tried to address some of these problems by adding “frictions” to their workhorse models. The intent of these frictions is to represent aspects of reality such as unemployment, a financial sector, or a role for government. But as Nobel laureate Robert Solow explains, “To try to do it in a logically tight way is extremely difficult.” For example, even in models with frictions, unemployment does not happen because there is no market available for a worker’s output -- there are simply glitches in the labor market. These frictions function as converters, in the sense that they hinder the shift to a more efficient equilibrium.

Farrell and Saloner explored how converters between otherwise incompatible technologies can hinder the shift to a more efficient equilibrium, finding “that the existence of converters can actually lead to less compatibility than would occur in their absence”. (Farrell & Saloner, 1992) In a similar sense, the process of adding frictions to models is a mechanism for legacy economists to acknowledge that the macroeconomics being taught at top universities does not represent the real world, while preventing the entrance of contrasting opinions or alternative theories.

[These alternative theories and methods are the complexity economics and agent-based modeling that I'll focus on in this blog. For the moment, here's Leigh Tesfatsion's site. It provides a great summary of agent-based computational economics and many useful links.]

Herding and cascades

The change in macroeconomic research since the 1970’s has “come with the destruction of some knowledge, and suffers from extremism and herding.” (Blanchard, 2009) This behavior is consistent with the finding that, even when network effects are not present, herding ("uniform social behavior") occurs as a result of informational cascades – situations in which “it is optimal for an individual, having observed the actions of those ahead of him, to follow the behavior of the preceding individual without regard to his own information.” (Bikhchandani, Hirshleifer, & Welch, 1992). However, informational cascades are vulnerable to shocks and thus can be fragile: they explain not only uniform behavior but also instances of drastic change.

Cracks in legacy economics, exposed by the financial crisis, have continued to expand. Larry Summers has recently written that “We have come to agree with the point long stressed by Post Keynesian economists & recently emphasized by Palley that the role of specific frictions in economic fluctuations should be de-emphasized relative to a more fundamental lack of aggregate demand.” As it becomes increasingly clear that current mainstream economic modeling cannot effectively accommodate the world we live in – including low interest rates, corporate finance behavior, and not-perfectly-rational humans – alternative theories with stronger empirical justification should receive more support.

Next steps

There are some parallels between today and 1939. After a decade of economic hardship, the U.S. was facing slower population growth and uncertain productivity growth. A sense of unease pervaded the establishment that mainstream economic thought did not provide an effective framework for addressing new problems. “We are moving swiftly out of the order in which those of our generation were brought up, into no one knows what.” (Hansen, 1939)

The U.S. was morbidly “rescued” from its 1930's economic malaise by World War II. There are other ways to revitalize economic dynamism, whether we dig holes, build pyramids, or invest in infrastructure, research, and education. At the very least, I am convinced by the argument that “there needs to be more pluralism. Just like in the sixteenth century, after the Christian Reformation, there may no longer be a true church.” (Vines & Wills, 2018)

References

• Arrow, K. J. (1986). Rationality of Self and Others in an Economic System. The Journal of Business, pp. 385-399.
• Bikhchandani, S., Hirshleifer, D., &; Welch, I. (1992). A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy, Vol. 100, No. 5: pp. 992-1026.
• Blanchard, O. J. (2009). The State of Macro. Annual Review of Economics, 209-228.
• Cassidy, J. (2009). How Markets Fail. New York: Penguin Group.
• Farrell, J., & Saloner, G. (1985). Standardization, Compatibility, and Innovation. RAND Journal of Economics, Vol. 16, No. 1: pp. 70-83.
• Farrell, J., & Saloner, G. (1986). Installed Base and Compatibility: Innovation, Product Preannouncements, and Predation. The American Economic Review, 940-955.
• Farrell, J., & Saloner, G. (1992). Converters, Compatibility, and the Control of Interfaces. Journal of Industrial Economics, Vol. 40, No. 1: pp. 9-35.
• Hansen, A. H. (1939). Economic Progress and Declining Population Growth. The American Economic Review, Vol. 29, No. 1: pp. 1-15.
• Vines, D., & Wills, S. (2018). The rebuilding macroeconomic theory project: an analytical assessment. Oxford Review of Economic Policy, Vol. 34, Issue 1-2: pp. 1-42.

Why I'm starting this blog

The macroeconomics many of us learn in school -- and that the most prominent professors rely on to inform not just students but also policymakers -- isn't working.

The "dynamic stochastic general equilibrium" models that missed the financial crisis assume a world in equilibrium in which people are rational and have perfect foresight. Everything we do is based on reasoning deductively to maximize utility. Billionaires don't exist, companies don't hoard cash, and price is the measure of everything. There is no cultural or institutional evolution, no explanation for how innovation happens, and no human interaction ... everything is deathly perfect.

The focus of this blog, however, won't be to argue that the mainstream general equilibrium macroeconomic models are based on a fantasy world and therefore are not useful for ours. Nobel laureates including Paul Romer and Joseph Stiglitz explain it convincingly.

Instead, most posts will be summaries of the theories and people that explain the economy of the world we actually live in. The blog will cover topics such as evolutionary economics, complexity science, innovation processes, increasing returns / lock-in, and agent-based computational economics.

The political economist Mark Blyth "got annoyed enough to write a book" about the harmful effects of implementing austerity programs during recessions such as the eurozone crisis. If you write about "something that annoys the crap out of you [...] you'll never get fed up" with researching the topic.

I've had too many conversations with brilliant students at top PhD programs who have not heard of the reality-based economics that could help us develop better policies. The universities that give students a PhD based on mastery of a sliver of quantitative economics (one that even the professors know is wrong!) without teaching or even mentioning other areas that might be more useful avenues of research are doing their students a disservice (and maybe being socially negligent). Good economics is important for all of us.

I got annoyed enough to start a blog.