A new perspective to rational expectations: maximin rational expectations equilibrium

We introduce a new notion of rational expectations equilibrium (REE) called maximin rational expectations equilibrium (MREE), which is based on the maximin expected utility (MEU) formulation. In particular, agents maximize maximin expected utility conditioned on their own private information and the information that the equilibrium prices generate. Maximin equilibrium allocations need not to be measurable with respect to the private information of each individual and with respect to the information that the equilibrium prices generate, as it is in the case of the Bayesian REE. We prove that a maximin REE exists universally (and not generically as in Radner (1979) and Allen (1981)), it is effcient and incentive compatible. These results are false for the Bayesian REE

Rational expectations business cycle models: a survey

Development of rational expectations models of the business cycle has been the central issue in macroeconomics over the last 15 years. The postulate that expectations are rational imposes considerable discipline on business cycle analysis. In this essay we review the current literature on rational expectations models of business cycles with specific attention focused on the extent to which the rational expectations perspective has generated a new understanding of economic fluctuations.Macroeconomics ; Business cycles ; Rational expectations (Economic theory)

Jargon alert : Rational expectations

Economics

"Rational Expectations": A Correction

macroeconomics, rational expectations, unemployment

Are Inflation Expectations Rational?

Several recent papers report evidence of an apparent statistical bias in inflation expectations and interpret these findings as overturning the rational expectations hypothesis. In this paper, we investigate the validity of such an interpretation. We present a computational dynamic general equilibrium model capable of generating aggregate behavior similar to the data along several dimensions. By construction, model agents form "rational" expectations. We run a standard regression on equilibrium realizations of inflation and inflation expectations over sample periods corresponding to those tests performed on actual data and find evidence of an apparent bias in inflation expectations. Our experiments suggest that this incorrect inference is largely the product of a small sample problem, exacerbated by short-run learning dynamics in response to infrequent shifts in monetary policy regimes.Regime changes; Learning dynamics; Monte Carlo exp eriments; Sample size.

Rational expectations modelling in O.R

The conventional OR approach to managing a system is, in outline, firstly to create a model of the existing system, secondly, to investigate changes in the model which improve or control the behaviour of the model and thirdly, to implement these changes in the system. It is assumed that the model incorporating these changes will be a valid representation of the system after the changes, in as far as the original model was a valid representation of the original system, and can thus be used to assess the benefits and disbenefits arising from the changes

(WP 2016-02) The Limits of Central Bank Forward Guidance under Learning

Central bank forward guidance emerged as a pertinent tool for monetary policymakers since the Great Recession. Nevertheless, the effects of forward guidance remain unclear. This paper investigates the effectiveness of forward guidance while relaxing two standard macroeconomic assumptions: rational expectations and frictionless financial markets. Agents forecast future macroeconomic variables via either the rational expectations hypothesis or a more plausible theory of expectations formation called adaptive learning. A standard Dynamic Stochastic General Equilibrium (DSGE) model is extended to include the financial accelerator mechanism. The results show that the addition of financial frictions amplifies the differences between rational expectations and adaptive learning to forward guidance. The macroeconomic variables are overall more responsive to forward guidance under rational expectations than under adaptive learning. During a period of economic crisis (e.g. a recession), output under rational expectations displays more favorable responses to forward guidance than under adaptive learning. These differences are exacerbated when compared to a similar analysis without financial frictions. Thus, monetary policymakers should consider the way in which expectations and credit frictions are modeled when examining the effects of forward guidance

Estimating a small DSGE model under rational and measured expectations: some comparisons

Using European panel data and GMM system estimation, we explore the empirical performance of the standard three-equation New Keynesian macro model under different informational assumptions. As a benchmark, we consider the performance of the model under rational expectations and revised (final) data. Alternatively, instead of imposing rational expectations hypothesis we use real- time information, ie Consensus Economics survey data, to generate empirical proxies for expectations in the model and the current output gap in the Taylor rule. We demonstrate that, contrary to the assumption of rational expectations, the errors in measured expectations and real-time current output gaps are positively autocorrelated. We produce evidence that the use of real-time variables (including measured expectations) improves the empirical performance of the New Keynesian model. Relaxation of the rational expectations hypothesis makes a noticeable difference for the parameters of the New Keynesian model, especially in the Taylor rule.DSGE model; survey expectations; GMM system estimation; expectations; estimation

Survey Expectations

This paper focuses on survey expectations and discusses their uses for testing and modeling of expectations. Alternative models of expectations formation are reviewed and the importance of allowing for heterogeneity of expectations is emphasized. A weak form of the rational expectations hypothesis which focuses on average expectations rather than individual expectations is advanced. Other models of expectations formation, such as the adaptive expectations hypothesis, are briefly discussed. Testable implications of rational and extrapolative models of expectations are reviewed and the importance of the loss function for the interpretation of the test results is discussed. The paper then provides an account of the various surveys of expectations, reviews alternative methods of quantifying the qualitative surveys, and discusses the use of aggregate and individual survey responses in the analysis of expectations and for forecasting.models of expectations formation, survey data, heterogeneity, tests of rational expectations