Evans, George W.

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https://hdl.handle.net/1794/3690

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Open Access
Adaptive Expectations, Underparameterization and the Lucas Critique
(University of Oregon, Dept. of Economics, 2001-11-29) Evans, George W., 1949-; Ramey, Garey
A striking implication of the replacement of adaptive expectations by Rational Expectations was the "Lucas Critique," which showed that expectation parameters, and endogenous variable dynamics, depend on policy parameters. We consider this issue from the vantage point of a bounded rationality, where for transparency we model bounded rationality by means of simple adaptive expectations.We show that for a range of processes, monetary policy remains subject to the Lucas critique. However, there are also regimes in which the expectation parameter is locally invariant and the Lucas critique does not apply.
Open Access
Adaptive Learning and Monetary Policy Design
(University of Oregon, Dept. of Economics, 2002-11-08) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
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.
Open Access
Adaptive Learning, Endogenous Inattention, and Changes in Monetary Policy
(University of Oregon, Dept of Economics, 2006-06-22) Branch, William A.; Evans, George W., 1949-; Carlson, John; McGough, Bruce
This paper develops an adaptive learning formulation of an extension to the Ball, Mankiw and Reis (2005) sticky information model that incorporates endogenous inattention. We show that, following an exogenous increase in the policymaker’s preferences for price vs. output stability, the learning process can converge to a new equilibrium in which both output and price volatility are lower.
Open Access
Anticipated Fiscal Policy and Adaptive Learning
(University of Oregon, Dept of Economics, 2007-02-18) Evans, George W., 1949-; Honkapohja, Seppo, 1951-; Mitra, Kaushik
We consider the impact of anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations. To model this we assume that agents combine limited structural knowledge with a standard adaptive learning rule. We analyze these issues using two well-known set-ups, an endowment economy and the Ramsey model. In our set-up there are important deviations from both rational expectations and purely adaptive learning. Our approach could be applied to many macroeconomic frameworks.
Open Access
Are Stationary Hyperinflation Paths Learnable?
(University of Oregon, Dept of Economics, 2003-03-17) Adam, Klaus; Evans, George W., 1949-; Honkapohja, Seppo, 1951-
Earlier studies of the seigniorage inflation model have found that the high-inflation steady state is not stable under adaptive learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is on stationary hyperinflationary paths near the high-inflation steady state. The hyperinflationary paths are stable under learning if agents can utilize contemporaneous data. However, in an economy populated by a mixture of agents, some of whom only have access to lagged data, stable inflationary paths emerge only if the proportion of agents with access to contemporaneous data is sufficiently high.
Open Access
Asset Return Dynamics and Learning
(University of Oregon, Dept of Economics, 2006-11-13) Branch, William A.; Evans, George W., 1949-
This paper advocates a theory of expectation formation that incorporates many of the central motivations of behavioral finance theory while retaining much of the discipline of the rational expectations approach. We provide a framework in which agents, in an asset pricing model, underparameterize their forecasting model in a spirit similar to Hong, Stein, and Yu (2005) and Barberis, Shleifer, and Vishny (1998), except that the parameters of the forecasting model, and the choice of predictor, are determined jointly in equilibrium. We show that multiple equilibria can exist even if agents choose only models that maximize (risk-adjusted) expected profits. A real-time learning formulation yields endogenous switching between equilibria. We demonstrate that a realtime learning version of the model, calibrated to U.S. stock data, is capable of reproducing many of the salient empirical regularities in excess return dynamics such as under/overreaction, persistence, and volatility clustering.
Open Access
Can Perpetual Learning Explain the Forward Premium Puzzle?
(University of Oregon, Dept of Economics, 2006-08-28) Chakraborty, Avik, 1975-; Evans, George W., 1949-
Under rational expectations and risk neutrality the linear projection of exchange rate change on the forward premium has a unit coefficient. However, empirical estimates of this coefficient are significantly less than one and often negative. We investigate whether replacing rational expectations by discounted least squares (or “perpetual”) learning can explain the result. We calculate the asymptotic bias under perpetual learning and show that there is a negative bias that becomes strongest when the fundamentals are strongly persistent, i.e. close to a random walk. Simulations confirm that perpetual learning is potentially able to explain the forward premium puzzle.
Open Access
Comment on "Imperfect Knowledge, Inflation Expectations and Monetary Policy" by Athanasios Orphanides and John C. Williams
(University of Oregon, Dept. of Economics, 2003-03-31) Evans, George W., 1949-
Summarizes the Orphanides-Williams argument, locates the paper within the rapidly growing literature on learning and monetary policy, and offers specific comments on natural extensions or alternative approaches.
Open Access
Coordination on saddle path solutions: the eductive viewpoint
(University of Oregon, Dept. of Economics, 2001-05-15) Evans, George W., 1949-; Guesnerie, R.
We investigate local strong rationality (LSR) in a one step forward looking univariate model with memory one. Eductive arguments are used to determine when common knowledge (CK) that the solution is near some perfect foresight path is sufficient to trigger complete coordination on that path (I.e. the path is LSR). Coordination of expectations is shown to depend on three factors: the nature of the CK initial beliefs, the degree of structural heterogeneity and the information structure. Our sufficient conditions for LSR precisely reflect these features and provide basic consistent justifications for the choice of the saddle path solution.
Open Access
Coordination on Saddle-Path Solutions: The Eductive Viewpoint -- Linear Multivariate Models
(University of Oregon, Dept of Economics, 2003-10-10) Evans, George W., 1949-; Guesnerie, R.
We examine local strong rationality (LSR) in multivariate models with both forward-looking expectations and predetermined variables. Given hypothetical common knowledge restrictions that the dynamics will be close to those of a specified minimal state variable solution, we obtain eductive stability conditions for the solution to be LSR. In the saddlepoint stable case the saddle-path solution is LSR provided the model is structurally homogeneous across agents. However, the eductive stability conditions are strictly more demanding when heterogeneity is present, as can be expected in multisectoral models. Heterogeneity is thus a potentially important source of instability even in the saddlepoint stable case.
Open Access
Does Ricardian Equivalence Hold When Expectations are not Rational?
(University of Oregon, Dept of Economics, 2010-08-04) Evans, George W., 1949-; Honkapohja, Seppo, 1951-; Mitra, Kaushik, 1969-
This paper considers the Ricardian Equivalence proposition when expectations are not rational and are instead formed using adaptive learning rules. We show that Ricardian Equivalence continues to hold provided suitable additional conditions on learning dynamics are satisfied. However, new cases of failure can also emerge under learning. In particular, for Ricardian Equivalence to obtain, agents’ expectations must not depend on government’s financial variables under deficit financing.
Open Access
The E-Correspondence Principle
(University of Oregon, Dept of Economics, 2003-06-23) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We introduce the E-correspondence principle for stochastic dynamic expectations models as a tool for comparative dynamics analysis. The principle is applicable to equilibria that are stable under least squares and closely related learning rules. With this technique it is possible to study, without explicit solving for the equilibrium, how properties of the equilibrium are affected by changes in the structural parameters of the model. Even if qualitative comparative dynamics results are not obtainable, a quantitative version of the principle can be applied.
Open Access
Existence of Adaptively Stable Sunspot Equilibria near an Indeterminate Steady State
(University of Oregon, Dept. of Economics, 2002-04-06) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We examine the nonlinear model x_t = E_t F(x_(t+1)). Markov SSEs exist near an indeterminate steady state, hat(x)=F(hat(x)), provided |F'(hat(x)| > 1. Despite the importance of indeterminancy in macroeconomics, earlier results have not provided conditions for the existance of adaptively stable SSEs near an indeterminate steady state. We show that there exists Markov SSEs near hat(x) that are E-stable, and therefore locally stable under adaptive learning, if F'(hat(x)) < -1.
Open Access
Expectational Stability of Stationary Sunspot Equilibria in a Forward-looking Linear Model
(University of Oregon, Dept. of Economics, 2002-01-14) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We consider the stability under adaptive learning of the complete set of solutions to the model x_i=beta(Ei*)(x_i+1) when |beat| >1. In addition to the fundamentals solution, the literature describes both finite-state Markov sunspot solutions and autoregressive solutions depending on an arbitrary martingale difference sequence. We clarify the relationships between these solutions and show that the stability properties of equilibria may depend crucially on the representations used by agents in the learning process. Autoregressive forms of solutions are not learnable, but finite-state Markov sunspot solutions are stable under learning if beta < -1.
Open Access
Expectations and the Stability Problem for Optimal Monetary Policies
(University of Oregon, Dept. of Economics, 2001-08-03) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
A fundamentals based monetary policy rule, which would be the optimal monetary policy without commitment when private agents have perfectly rational expectations, is unstable if in fact these agents follow standard adaptive learning rules. This problem can be overcome if private expectations are observed and suitable incorporated into the policy maker's optimal rule. These strong results extend to the case in which there is simultaneous learning by the policy maker and the private agents. Our findings show the importance of conditioning policy appropriately, not just on fundamentals, but also directly on observed household and firm expectations.
Open Access
Expectations, Deflation Traps and Macroeconomic Policy
(University of Oregon, Dept of Economics, 2009-07-06) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We examine global economic dynamics under infinite-horizon learning in a New Keynesian model in which the interest-rate rule is subject to the zero lower bound. As in Evans, Guse and Honkapohja (2008), we find that under normal monetary and fiscal policy the intended steady state is locally but not globally stable. Unstable deflationary paths can arise after large pessimistic shocks to expectations. For large expectation shocks pushing interest rates to the zero lower bound, temporary increases in government spending can be used to insulate the economy from deflation traps.
Open Access
Friedman's Money Supply Rule versus Optimal Interest Rate Policy
(University of Oregon, Dept of Economics, 2003-07-12) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
Using New Keynesian models, we compare Friedman's k-percent money supply rule to optimal interest rate setting, with respect to determinacy, stability under learning and optimality. First we review the recent literature: open-loop interest rate rules are subject to indeterminacy and instability problems, but a properly chosen expectations-based rule yields determinacy and stability under learning, and implements optimal policy. We show that Friedman's rule also can generate equilibria that are determinate and stable under learning. However, computing the mean quadratic welfare loss, we find for calibrated models that Friedman's rule performs poorly when compared to the optimal interest rate rule.
Open Access
Generalized Stochastic Gradient Learning
(University of Oregon, Dept of Economics, 2005-09-19) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We study the properties of generalized stochastic gradient (GSG) learning in forwardlooking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG algorithms are sensitive to units of measurement and we show that there is a transformation of variables for which E-stability governs SG stability. GSG algorithms with constant gain have a deeper justification in terms of parameter drift, robustness and risk sensitivity.
Open Access
Implementing Optimal Monetary Policy in New-Keynesian Models with Inertia
(University of Oregon, Dept of Economics, 2006-06-03) Evans, George W., 1949-; McGough, Bruce
We consider optimal monetary policy in New Keynesian models with inertia. First order conditions, which we call the MJB-alternative, are found to improve upon the timeless perspective. The MJB-alternative is shown to be the best possible in the sense that it minimizes policymakers’ unconditional expected loss, and further, it is numerically found to offer significant improvement over the timeless perspective. Implementation of the MJB-alternative is considered via construction of interest-rate rules that are consistent with its associated unique equilibrium. Following Evans and Honkapohja (2004), an expectations based rule is derived that always yields a determinate model and an E-stable equilibrium. Further, the “policy manifold” of all interest-rate rules consistent with the MJB-alternative is classified, and open regions of this manifold are shown to correspond to indeterminate models and unstable equilibria.
Open Access
Indeterminacy and the Stability Puzzle in Non-Convex Economies
(University of Oregon, Dept. of Economics, 2002-07-25) Evans, George W., 1949-; McGough, Bruce
We extend common factor analysis to a multi-dimensional setting by considering a bivariate reduced form consistent with many Real Business Cycle type models. We show how to obtain new representations of sunspots and find that there are parameter regions in which these sunspots are stable under learning. However, once the parameters are restricted to coincide with those generated by certain standard models of indeterminacy, we find, under one information assumption, that no stable sunspots exist, and under another information assumption, that they exist only for a very small part of the indeterminacy region. This leads to the following puzzle: why does indeterminacy almost always imply instability in RBC-type models?