Evans, George W.

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

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Open Access
Stagnation Regime of the New Keynesian Model and Current US Policy
(University of Oregon, Dept of Economics, 2010-10-30) Evans, George W., 1949-
In Evans, Guse, and Honkapohja (2008) the intended steady state is locally but not globally stable under adaptive learning, and unstable deflationary paths can arise after large pessimistic shocks to expectations. In the current paper a modified model is presented that includes a locally stable stagnation regime as a possible outcome arising from large expectation shocks. Policy implications are examined. Sufficiently large temporary increases in government spending can dislodge the economy from the stagnation regime and restore the natural stabilizing dynamics. More specific policy proposals are presented and discussed.
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
Monetary Policy and Heterogeneous Expectations
(University of Oregon, Dept of Economics, 2010-04-30) Branch, William A.; Evans, George W., 1949-
This paper studies the implications for monetary policy of heterogeneous expectations in a New Keynesian model. The assumption of rational expec- tations is replaced with parsimonious forecasting models where agents select between predictors that are underparameterized. In a Misspecification Equilibrium agents only select the best-performing statistical models. We demonstrate that, even when monetary policy rules satisfy the Taylor principle by adjusting nominal interest rates more than one for one with inflation, there may exist equilibria with Intrinsic Heterogeneity. Under certain conditions, there may exist multiple misspecification equilibria. We show that these findings have important implications for business cycle dynamics and for the design of monetary policy.
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
Learning and Macroeconomics
(University of Oregon, Dept of Economics, 2008-07-11) Honkapohja, Seppo, 1951-; Evans, George W., 1949-
Expectations play a central role in modern macroeconomic theories. The econometric learning approach models economic agents as forming expectations by estimating and updating forecasting models in real time. The learning approach provides a stability test for rational expectations and a selection criterion in models with multiple equilibria. In addition, learning provides new dynamics if older data is discounted, models are misspecified or agents choose between competing models. This paper describes the E-stability principle and the stochastic approximation tools used to assess equilibria under learning. Applications of learning to a number of areas are reviewed, including the design of monetary and fiscal policy, business cycles, self-fulfilling prophecies, hyperinflation, liquidity traps, and asset prices.
Open Access
Learning about Risk and Return: A Simple Model of Bubbles and Crashes
(University of Oregon, Dept of Economics, 2008-01-31) Branch, William A.; Evans, George W., 1949-
This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they generate forecasts of the conditional variance of a stock’s return. Recursive updating of the conditional variance and expected return implies two mechanisms through which learning impacts stock prices: occasional shocks may lead agents to lower their risk estimate and increase their expected return, thereby triggering a bubble; along a bubble path recursive estimates of risk will increase and crash the bubble.
Open Access
Liquidity Traps, Learning and Stagnation
(University of Oregon, Dept of Economics, 2007-06-05) Evans, George W., 1949-; Guse, Eran A. (Eran Alan), 1975-; Honkapohja, Seppo, 1951-
We examine global economic dynamics under learning in a New Keynesian model in which the interest-rate rule is subject to the zero lower bound. Under normal monetary and fiscal policy, the intended steady state is locally but not globally stable. Large pessimistic shocks to expectations can lead to deflationary spirals with falling prices and falling output. To avoid this outcome we recommend augmenting normal policies with aggressive monetary and fiscal policy that guarantee a lower bound on inflation. In contrast, policies geared toward ensuring an output lower bound are insufficient for avoiding deflationary spirals.
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
Representations and Sunspot Stability
(University of Oregon, Dept of Economics, 2007-01-01) Evans, George W., 1949-; McGough, Bruce
By endowing his agents with simple forecasting models, or representations, Woodford (1990) found that finite state Markov sunspot equilibria may be stable under learning. We show that common factor representations generalize to all sunspot equilibria the representations used by Woodford (1990). We find that if finite state Markov sunspots are stable under learning then all sunspots are stable under learning, provided common factor representations are used.
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
Stable Finite-State Markov Sunspots
(University of Oregon, Dept of Economics, 2006-10-09) Evans, George W., 1949-; McGough, Bruce
We consider a linear univariate rational expectations model, with a predetermined variable, and study existence and stability of solutions driven by an extraneous finite-state Markov process. We show that when the model is indeterminate there exists a new class of kstate dependent sunspot equilibria in addition to the k-state sunspot equilibria (k-SSEs) already known to exist in part of the indeterminacy region. The new type of equilibria, which we call ergodic k-SSEs, are driven by a finite-state sunspot but can have an infinite range of values even in the nonstochastic model. Stability under econometric learning is analyzed using representations that nest both types of equilibria. 2-SSEs and ergodic 2-SSEs are learnable for parameters in proper subsets of the regions of their existence. Our results extend to models with intrinsic random shocks.
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
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
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
Model Uncertainty and Endogenous Volatility
(University of Oregon, Dept of Economics, 2005-10-18) Branch, William A.; Evans, George W., 1949-
This paper identifies two channels through which the economy can generate endogenous inflation and output volatility, an empirical regularity, by introducing model uncertainty into a Lucas-type monetary model. The equilibrium path of inflation depends on agents' expectations and a vector of exogenous random variables. Following Branch and Evans (2004) agents are assumed to underparameterize their forecasting models. A Misspecification Equilibrium arises when beliefs are optimal given the misspecification and predictor proportions based on relative forecast performance. We show that there may exist multiple Misspecification Equilibria, a subset of which are stable under least squares learning and dynamic predictor selection. The dual channels of least squares parameter updating and dynamic predictor selection combine to generate regime switching and endogenous volatility.
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
Near-Rational Exuberance
(University of Oregon, Dept of Economics, 2005-09-17) Bullard, James; Evans, George W., 1949-; Honkapohja, Seppo, 1951-
We study how the use of judgement or "add-factors" in macroeconomic forecasting may disturb the set of equilibrium outcomes when agents learn using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in standard macroeconomic environments. Examples include a simple asset pricing model and the New Keynesian monetary policy framework. Inclusion of judgement in forecasts can lead to self-fulfilling fluctuations, but without the requirement that the underlying rational expectations equilibrium is locally indeterminate. We suggest ways in which policymakers might avoid unintended outcomes by adjusting policy to minimize the risk of exuberance equilibria.
Open Access
Optimal Constrained Interest-rate Rules
(University of Oregon, Dept of Economics, 2005-05-19) Evans, George W., 1949-; McGough, Bruce
We show that if policy-makers compute the optimal unconstrained interest-rate rule within a Taylor-type class, they may be led to rules that generate indeterminacy and/or instability under learning. This problem is compounded by uncertainty about structural parameters since an optimal rule that is determinate and stable under learning for one calibration may be indeterminate or unstable under learning under a different calibration. We advocate a procedure in which policymakers restrict attention to rules constrained to lie in the determinate learnable region for all plausible calibrations, and that minimize the expected loss, computed using structural parameter priors, subject to this constraint.
Open Access
Monetary Policy, Expectations and Commitment
(University of Oregon, Dept of Economics, 2005-04-06) Evans, George W., 1949-; Honkapohja, Seppo, 1951-
This is a revised and shortened version of Working Paper 2002-11. Commitment in monetary policy leads to equilibria that are superior to those from optimal discretionary policies. A number of interest rate reaction functions and instrument rules have been proposed to implement or approximate commitment policy. We assess these rules in terms of whether they lead to an RE equilibrium that is both locally determinate and stable under adaptive learning by private agents. A reaction function that appropriately depends explicitly on private expectations performs particularly well on both counts.
Open Access
Monetary Policy, Endogenous Inattention, and the Volatility Trade-off
(University of Oregon, Dept of Economics, 2004-12-07) Branch, William A.; Carlson, John; Evans, George W., 1949-; McGough, Bruce
This paper addresses the output-price volatility puzzle by studying the interaction of optimal monetary policy and agents' beliefs. We assume that agents choose their information acquisition rate by minimizing a loss function that depends on expected forecast errors and information costs. Endogenous inattention is a Nash equilibrium in the information processing rate. Although a decline of policy activism directly increases output volatility, it indirectly anchors expectations, which decreases output volatility. If the indirect effect dominates then the usual trade-off between output and price volatility breaks down. This provides a potential explanation for the "Great Moderation" that began in the 1980's.