The Great Inflation and the Greenbook

Abstract

We assess whether recent empirical evidence that Federal Reserve learning caused the Great Inflation is consistent with forecasts published in the Greenbook. If the rise and fall in inflation really was caused by the Federal Reserve learning the Phillips curve then that should be fully reflected in Greenbook forecasts. It is not. The difficulty is that empirical evidence is predicated on the Federal Reserve making forecasts that are much more volatile than those in the Greenbooks. If consistency with Greenbook forecasts is required then evidence that Federal Reserve learning caused the Great Inflation is much weaker. Our results suggest a larger role for other causes than previously thought. * We greatly appreciate Tao Zha making available his C++ routines for Bayesian MCMC estimation. We also thank Knut Anton Mork, Antti Ripatti, and seminar participants at Bank of England, Birkbeck, Cardiff, Durham, Glasgow, Humboldt, Oslo (2nd Workshop on Monetary Policy), Queen's Belfast, Warwick and York for helpful comments and suggestions. Martin Ellison acknowledges support from an ESRC Research Fellowship, "Improving Monetary Policy for the 21st Century" (RES-000-27-0126). The views expressed in this paper do not necessarily reflect those of the ECB.

Evolution and Intelligent Design

“…I view the very simple statistical models in Section VI as parables that capture the situation that we are always in, namely, that our probability models are misspecified. 43 By stressing the possibility that learning has propelled us to a self-confirming equilibrium in which the government chooses an optimal policy based on a wrong model, the learning literature changes how we should think about generating the novel datasets and policies that will allow misguided governments to break out of the lack-of-experimentation traps to which self-confirming equilibria confine them.…”

“…43 This is the starting point of calibration in macroeconomics, i.e., the refusal to use maximum likelihood because the model builder views it as an approximation. 44 For a critical survey of this literature, see H. Peyton Young (2004).…”

On the initialization of adaptive learning in macroeconomic models

“…The idea can be traced back to the landmark work by Sargent et al (2006), where the estimation of the monetary authority's initial and consecutive stream of beliefs provided evidence in favor of Sargent's (1999) hypothesis on the "Conquest of American Inflation": namely, that the rise and fall of post-WWII inflation in the US can be attributed to the evolution of the monetary authority's beliefs about the tradeoff between inflation and unemployment. In spite of some early criticisms (see discussion in Carboni and Ellison, 2009), the approach of joint estimation of initials has been slowly incorporated into broader applications of adaptive learning. After being hinted as a possibility in Milani (2007Milani ( , p. 2071 and Huang et al (2009, p. 397), initial attempts have focused on the effects of the joint estimation of the initial matrix of second moments, R 0 (e.g., Milani, 2008Milani, , 2011, and more recently on the estimation of the complete set of learning initials (as in, e.g., Slobodyan and Wouters, 2012;Gaus and Ramamurthy, 2014).…”

2. Learning as a Rational Foundation for Macroeconomics and Finance

“…Recent papers include Ellison and Yates (2007) and Carboni and Ellison (2008), which emphasize the importance of policy-maker model uncertainty and the role of central bank learning in explaining the historical evolution of inflation and unemployment in the post 1950 period. Marcet and Nicolini (2003) use an open-economy extension of the standard seigniorage model of inflation, in which government spending is financed by printing money.…”