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software denotes a system that has been superseded by better technology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.
