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2000, SSRN Electronic Journal
The way in which individual expectations shape aggregate macroeconomic variables is crucial for the transmission and effectiveness of monetary policy. We study the individual expectations formation process and the interaction with monetary policy, within a standard New Keynesian model, by means of laboratory experiments with human subjects. We find that a more aggressive monetary policy that sets the interest rate more than point for point in response to inflation stabilizes inflation in our experimental economies. We use a simple model of individual learning, with a performance-based evolutionary selection among heterogeneous forecasting heuristics, to explain coordination of individual expectations and aggregate macro behavior observed in the laboratory experiments. Three aggregate outcomes are observed: convergence to some equilibrium level, persistent oscillatory behavior and oscillatory convergence. A simple heterogeneous expectations switching model fits individual learning as well as aggregate outcomes and outperforms homogeneous expectations benchmarks.
Journal of Monetary Economics
We use laboratory experiments to study individual expectations and aggregate macro behavior in a New Keynesian framework. Four different aggregate outcomes arise: convergence to equilibrium, explosive behavior along inflationary or deflationary spirals, persistent or dampened oscillations. A heuristics switching model, driven by relative performance, explains these patterns as emerging properties of the path-dependent self-organization process of heterogeneous expectations leading to coordination on an almost self-fulfilling rule. A more aggressive Taylor rule can manage the self-organization process adding negative feedback to the overall positive feedback system, making coordination on destabilizing trend-following expectations less likely and coordination on stabilizing adaptive expectations more likely.
SSRN Electronic Journal, 2015
Expectations play a crucial role in modern macroeconomic models. We replace the common assumption of rational expectations in a New Keynesian framework by the assumption that expectations are formed according to a heuristics switching model that has performed well in earlier work. We show how the economy behaves under these assumptions with a special focus on inflation volatility. Contrary to comparable models based on full rationality, the behavioral model predicts that inflation volatility can be lowered if the central bank reacts to the output gap in addition to inflation. We test the opposing theoretical predictions with a learning to forecast experiment. The experimental results support the behavioral model and the claim that reacting to the output gap in addition to inflation can indeed lower inflation volatility.
SSRN Electronic Journal, 2008
Expectations about the future are central for determination of current macroeconomic outcomes and the formulation of monetary policy. Recent literature has explored ways for supplementing the benchmark of rational expectations with explicit models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply expectational instability of private agents' learning. We use the standard New Keynesian model to illustrate this problem and survey the key results for interestrate rules that deliver both uniqueness and stability of equilibrium under econometric learning. We then consider some practical concerns such as measurement errors in private expectations, observability of variables and learning of structural parameters required for policy. We also discuss some recent applications, including policy design under perpetual learning, estimated models with learning, recurrent hyperinflation, and macroeconomic policy to combat liquidity traps and deflation.
Macroeconomic Dynamics, 2020
Drawing on a considerable empirical literature that reveals persistent and endogenously time-varying heterogeneity in inflation expectations, this paper embeds two inflation forecasting strategiesone based on costly ex ante full rationality or perfect foresight, and the second based on costless ex ante bounded rationality or extrapolative trend-followingin a dynamic macroeconomic model. Drawing also on the significant empirical evidence that inflation forecast errors may have to exceed some threshold before agents abandon their previously selected inflation forecasting strategy, we describe agents as switching between inflation forecasting strategies according to evolutionarily satisficing learning dynamics. We find that convergence to a long-run equilibrium consistent with growth, unemployment and inflation at their natural levels may be achieved even when heterogeneity in inflation expectations (with predominance of the extrapolative trend-following foresight strategy) is an attractor of an evolutionarily satisficing learning dynamic perturbed by mutant agents. Therefore, in keeping with robust empirical evidence, heterogeneity in strategies to form inflation expectations (with prevalence of boundedly rational expectations) can be a stable long-run equilibrium.
Handbook of Monetary Economics, 2010
This chapter investigates the implications of adaptive learning in the private sector's formation of inflation expectations for the conduct of monetary policy. We analyze the determinants of optimal monetary policy in the standard New Keynesian model, when the central bank minimizes an explicit loss function and has full information about the structure of the economy, including the precise mechanism generating private sector's expectations. The focus on optimal policy allows us to investigate how and to what extent a change in the assumption of how agents form their inflation expectations affects the principles of optimal monetary policy. It also provides a benchmark to evaluate simple policy rules. We find that departures from rational expectations increase the potential for instability in the economy, thereby strengthening the importance of managing (anchoring) inflation expectations. We also find that the simple commitment rule under rational expectations is robust when expectations are formed in line with adaptive learning.
SSRN Electronic Journal, 2021
This paper reviews the recent development and new findings of the literature on learning to forecast experiments (LtFEs). In general, the stylized finding in the typical LtFEs, namely the rapid convergence to the rational expectations equilibrium in negative feedback markets and persistent bubbles and crashes in positive feedback markets, is a robust result against several deviations from the baseline design (e.g., number of subjects in each market, price prediction versus quantity decision, short term versus long term predictions, predicting price or returns). Recent studies also find a high level of consistency between findings from forecasting data from the laboratory and the field, and forecasting accuracy crucially depends on the complexity of the task.
SSRN Electronic Journal
We introduce the concept of behavioral learning equilibrium (BLE) into a high dimensional linear framework and apply it to the standard New Keynesian model. For each endogenous variable, boundedly rational agents use a simple, but optimal AR(1) forecasting rule with parameters consistent with the observed sample mean and autocorrelation of past data. The main contributions of our paper are fourfold: (1) we derive existence and stability conditions of BLE in a general linear framework, (2) we provide a general method for Bayesian likelihood estimation of BLE, (3) we estimate the baseline NK model based on U.S. data and show that the relative model fit is better under BLE than REE, (4) we analyze optimal monetary policy under BLE and show that it differs from REE. In particular, we find that the transmission channel of monetary policy is stronger under BLE at the estimated parameter values.
2017
The paper studies how a prolonged period of subdued price developments may induce a de-anchoring of inflation expectations from the central bank's objective. This is shown within a framework where agents form expectations using adaptive learning, choosing among a set of alternative forecasting models. The analysis is accompanied by empirical evidence on the properties of inflation expectations in the euro area. Our results also suggest that monetary policy may lose effectiveness if delayed too much, as expectations are allowed to drift away from target for too long. JEL Classification: E31, E37, E58, D83
SSRN Electronic Journal, 2000
The applied literature on adaptive learning has mostly focused on small, linear models, where the minimum state variable (MSV) solution of the rational expectations equilibrium is used as the agents'perceived law of motion (PLM). In nonlinear models a closed-form MSV solution does not exist and if the model is medium or large-sized there is no univocal linear approximation that is eligible as a candidate PLM. Accordingly, heterogeneous expectations prevail and the process through which agents select (and change) a forecasting model becomes a necessary ingredient of the analysis; moreover, the temporary equilibrium of the learning process no longer converges to the REE, but rather approaches an asymptotic limit that depends on the speci…c form of the expectations equations and hence may be a¤ected by the communication strategies of the monetary policymaker. The objective of this paper is to assess whether in such a model economy, where expectations are mis-speci…ed, heterogeneous and ever changing, the optimal monetary policy exhibits properties that are similar to those found in the literature for small, linear models (e.g. Orphanides and Williams 2007). The main results are the following: (1) expectations heterogeneity is an intrinsic feature of the economy: no PLM succeeds in ruling out all the other forecasting models, though the most inaccurate ones are eventually dismissed; (2) contrary to previous …ndings, the monetary policymaker has no incentive to adopt more in ‡ation-averse policies to keep expectations anchored to targets: too strong a reaction to price shocks increases both in ‡ation and output volatility and tends to make the model unstable and non-learnable; (3) partial transparency seem to enhance somewhat welfare (but fully transparent policies do not), by reducing the slope of the term structure and the variability of long-term interest rates. A higher degree of transparency calls for stronger in ‡ation aversion, so partially recovering the …ndings by Orphanides and Williams.
Computing in Economics and Finance, 2006
We consider optimal policy when private sector expectations are formed through adaptive learning. Earlier research has found that adaptive learning is consistent with empirical evidence on private sector expectations. In this paper, we consider the (admittedly) extreme case of sophisticated central banking, whereby the central bank has full knowledge about the structure of the economy. Our results confirm that the management of inflation expectations is crucial for the conduct of monetary policy. n particular, when the private sector perceives that inflation persistence is high, optimal policy responds strongly to lagged inflation and inflation shocks thereby stabilizing inflation and anchoring inflation expectations. For our parametrization it does so at no cost for output gap stability
2016
In recent “learning to forecast ” experiments (Hommes et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations, and dampened fluctuations. We show that a simple model of individual learning can explain these different aggregate outcomes within the same experimental setting. The key idea is evolutionary selection among heterogeneous expectation rules, driven by their relative performance. The out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting and aggre-gate price behavior. (JEL C53, C91, D83, D84, G12) In the economy, today’s individual decisions crucially depend upon expectations or beliefs about future developments. For example, in speculative asset markets such as the stock market, an investor buys (sells) stocks today whe...
Journal of Economic Dynamics and Control, 2005
This paper investigates the role that imperfect knowledge about the structure of the economy plays in the formation of expectations, macroeconomic dynamics, and the efficient formulation of monetary policy. Economic agents rely on an adaptive learning technology to form expectations and to update continuously their beliefs regarding the dynamic structure of the economy based on incoming data. The process of perpetual learning introduces an additional layer of dynamic interaction between monetary policy and economic outcomes. We find that policies that would be efficient under rational expectations can perform poorly when knowledge is imperfect. In particular, policies that fail to maintain tight control over inflation are prone to episodes in which the public's expectations of inflation become uncoupled from the policy objective and stagflation results, in a pattern similar to that experienced in the United States during the 1970s. Our results highlight the value of effective communication of a central bank's inflation objective and of continued vigilance against inflation in anchoring inflation expectations and fostering macroeconomic stability.
This paper discusses an experimental study on the formation of expectation within a New Keynesian macroeconomic framework. The novelty of this paper (one of the earlier paper) is that each subject was asked to forecast both the inflation rate and output gap at the same time, which is an improvement over the existing literature. We find a lot of heterogeneity in expectation formation and also the model switching nature by the subjects.
American Economic Journal: Microeconomics, 2012
In recent 'learning to forecast' experiments with human subjects , three different patterns in aggregate asset price behavior have been observed: slow monotonic convergence, permanent oscillations and dampened fluctuations. We construct a simple model of individual learning, based on performance based evolutionary selection or reinforcement learning among heterogeneous expectations rules, explaining these different aggregate outcomes. Out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting behavior as well as aggregate price behavior.
In recent 'learning to forecast' experiments with human subjects (Hommes, et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations and dampened fluctuations. We
Journal of Economic Behavior & Organization, 2009
In recent 'learning to forecast' experiments with human subjects , three different patterns in aggregate asset price behavior have been observed: slow monotonic convergence, permanent oscillations and dampened fluctuations. We construct a simple model of individual learning, based on performance based evolutionary selection or reinforcement learning among heterogeneous expectations rules, explaining these different aggregate outcomes. Out-of-sample predictive power of our switching model is higher compared to the rational or other homogeneous expectations benchmarks. Our results show that heterogeneity in expectations is crucial to describe individual forecasting behavior as well as aggregate price behavior.
The Economic Journal, 2013
We analyze the e¤ects of social learning in a widely-studied monetary policy context. Social learning might be viewed as more descriptive of actual learning behavior in complex market economies. Ideas about how best to forecast the economy's state vector are initially heterogeneous. Agents can copy better forecasting techniques and discard those techniques which are less successful. We seek to understand whether the economy will converge to a rational expectations equilibrium under this more realistic learning dynamic. A key result from the literature in the version of the model we study is that the Taylor Principle governs both the uniqueness and the expectational stability of the rational expectations equilibrium when all agents learn homogeneously using recursive algorithms. We …nd that the Taylor Principle is not necessary for convergence in a social learning context. We also contribute to the use of genetic algorithm learning in stochastic environments.
Journal of Money, Credit, and Banking, 2003
We review the recent work on interest rate setting, which emphasizes the desirability of designing policy to ensure stability under private agent learning. Appropriately designed expectations based rules can yield optimal rational expectations equilibria that are both determinate and stable under learning. Some simple instrument rules and approximate targeting rules also have these desirable properties. We take up various complications in implementing optimal policy, including the observability of key variables and the required knowledge of structural parameters. An additional issue that we take up concerns the implications of expectation shocks not arising from transitional learning effects.
2002
Various measures indicate that inflation expectations evolve sluggishly relative to actual inflation. In addition, they often fail conventional tests of unbiasedness. These observations are sometimes interpreted as evidence against rational expectations. The authors embed, within a standard monetary dynamic stochastic general-equilibrium model, an information friction and a learning mechanism regarding the interest-rate-targeting rule that monetary policy authorities follow. The learning mechanism enables optimizing economic agents to distinguish between transitory shocks to the policy rule and occasional shifts in the inflation target of monetary policy authorities. The model's simulated data are consistent with the empirical evidence. When the information friction is activated, simulated inflation expectations fail conventional unbiasedness tests much more frequently than in the complete-information case when this friction is shut down. These results suggest that an important size distortion may occur when conventional tests of unbiasedness are applied to relatively small samples dominated by a few significant shifts in monetary policy and sluggish learning about those shifts.
SSRN Electronic Journal, 2003
In this paper we analyse disinflation policy in two environments. In the first, the central bank has perfect knowledge, in the sense that it understands and observes the process by which private sector inflation expectations are generated; in the second, the central bank has to learn the private sector inflation forecasting rule. With imperfect knowledge, results depend on the learning scheme that is employed. Here, the learning scheme we investigate is that of least-squares learning (recursive OLS) using the Kalman filter. A novel feature of a learningbased policy -as against the central bank's disinflation policy under perfect knowledge -is that the degree of monetary accommodation (the extent to which the central bank accommodates private sector inflation expectations) is no longer constant across the disinflation, but becomes state-dependent. This means that the central bank's behaviour changes during the disinflation as it collects more information.
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