This paper examines the empirical significance of learning, a type of adaptive, boundedly rational expectations, in the U.S. economy within the framework of the New Keynesian model. Two popular specifications of the model are estimated: the standard three equation model that does not include capital, and an extended model that allows for endogenous capital accumulation. Estimation results for learning models can be sensitive to the choice for the initial conditions for agents expectations, so four different methods for choosing initial conditions are examined, including jointly estimating the initial conditions with the other parameters of the model. Maximum likelihood results show that learning under all methods for initial conditions lead to very similar predictions as rational expectations, and do not significantly improve the fit the model. The evolution of forecast errors show that the learning models do not out perform the rational expectations model during the run-up of inflation in the 1970s and the subsequent decline in the 1980s, a period of U.S. history which others have suggested learning may play a role. Despite the failure of learning models to better explain the data, analysis of the paths of expectations and structural shocks during the sample show that allowing for learning in the models can lead to different explanations for the data.

We introduce behavioral learning equilibria (BLE) into a multi-variate linear framework and apply it to New Keynesian DSGE models. In a BLE, boundedly rational agents use simple but optimal first-order autoregressive (AR(1)) forecasting rules whose parameters are consistent with the observed sample mean and autocorrelation of past data. We study the BLE concept in a standard three-equation New Keynesian model and develop an estimation methodology for the canonical Smets and Wouters (2007) model. A horse race between rational expectations equilibrium (REE), BLE and constant gain learning models shows that the BLE model outperforms the REE benchmark and is competitive with constant gain learning models in terms of in-sample and out-of-sample fitness. Sample autocorrelation learning of optimal AR(1) beliefs provides the best fit when short-term survey data on inflation expectations are considered in the estimation. As a policy application, we show that optimal Taylor rules under AR(1) expectations inherit history dependence, requiring a lower degree of interest rate smoothing than REE.

Inflation is regarded by the many as a menace that damages business and can only make life worse for households. Keeping it low depends critically on ensuring that firms and workers expect it to be low. So expectations of inflation are a key influence on national economic welfare. This collection pulls together a galaxy of world experts (including Roy Batchelor, Richard Curtin and Staffan Linden) on inflation expectations to debate different aspects of the issues involved. The main focus of the volume is on likely inflation developments. A number of factors have led practitioners and academic observers of monetary policy to place increasing emphasis recently on inflation expectations. One is the spread of inflation targeting, invented in New Zealand over 15 years ago, but now encompassing many important economies including Brazil, Canada, Israel and Great Britain. Even more significantly, the European Central Bank, the Bank of Japan and the United States Federal Bank are the leading members of another group of monetary institutions all considering or implementing moves in the same direction. A second is the large reduction in actual inflation that has been observed in most countries over the past decade or so. These considerations underscore the critical – and largely underrecognized - importance of inflation expectations. They emphasize the importance of the issues, and the great need for a volume that offers a clear, systematic treatment of them. This book, under the steely editorship of Peter Sinclair, should prove very important for policy makers and monetary economists alike.

This paper tests the ability of popular New Keynesian models, which are traditionally used to study monetary policy and business cycles, to match the data regarding a key channel for monetary transmission: the dynamic interactions between macroeconomic variables and their corresponding expectations. In the empirical analysis, we exploit direct data on expectations from surveys. To explain the joint evolution of realized variables and expectations, we adopt a DSGE-VAR approach, which allows us to estimate all models in the continuum between the extremes of an unrestricted VAR, on one side, and a DSGE model in which the cross-equation restrictions are dogmatically imposed, on the other side. Moreover, the DSGE-VAR approach allows us to assess the extent, as well as the main sources, of misspecification in the model. The paper's results illustrate the failure of New Keynesian models under the rational expectations hypothesis to account for the dynamic interactions between observed macroeconomic expectations and macroeconomic realizations. Confirming previous studies, DSGE restrictions prove valuable when the New Keynesian model is exempted from matching observed expectations. But when the model is required to match data on expectations, it can do so only by moving away, and hence substantially rejecting, DSGE restrictions. Finally, we investigate alternative models of expectations formation, including examples of extrapolative and heterogeneous expectations, and show that they can go some way toward reconciling the New Keynesian model with the data. Intermediate DSGE-VAR models, which avail themselves of DSGE prior restrictions, return to fit the data better than the unrestricted VAR. Hence, the results overall point to misspecification in the expectations formation side of the DSGE model, more than in the structural microfounded equations.

This book originated from a 2010 conference marking the fortieth anniversary of the publication of the landmark "Phelps volume," Microeconomic Foundations of Employment and Inflation Theory, a book that is often credited with pioneering the currently dominant approach to macroeconomic analysis. However, in their provocative introductory essay, Roman Frydman and Edmund Phelps argue that the vast majority of macroeconomic and finance models developed over the last four decades derailed, rather than built on, the Phelps volume's "microfoundations" approach. Whereas the contributors to the 1970 volume recognized the fundamental importance of according market participants' expectations an autonomous role, contemporary models rely on the rational expectations hypothesis (REH), which rules out such a role by design. The financial crisis that began in 2007, preceded by a spectacular boom and bust in asset prices that REH models implied could never happen, has spurred a quest for fresh approaches to macroeconomic analysis. While the alternatives to REH presented in Rethinking Expectations differ from the approach taken in the original Phelps volume, they are notable for returning to its major theme: understanding aggregate outcomes requires according expectations an autonomous role. In the introductory essay, Frydman and Phelps interpret the various efforts to reconstruct the field--some of which promise to chart its direction for decades to come. The contributors include Philippe Aghion, Sheila Dow, George W. Evans, Roger E. A. Farmer, Roman Frydman, Michael D. Goldberg, Roger Guesnerie, Seppo Honkapohja, Katarina Juselius, Enisse Kharroubi, Blake LeBaron, Edmund S. Phelps, John B. Taylor, Michael Woodford, and Gylfi Zoega.