Browsing Evans, George W. by Title

Branch, William A.; Evans, George W., 1949 (University of Oregon, Dept of Economics, November 13, 2006)[more][less]Branch, William A. Evans, George W., 1949 20070116T17:29:00Z 20070116T17:29:00Z 20061113 http://hdl.handle.net/1794/3797 40 p. 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 (riskadjusted) expected profits. A realtime 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. 364168 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 200614 Asset pricing Misspecification Behavioral finance Predictability Adaptive learning Asset Return Dynamics and Learning Working Paper

Chakraborty, Avik, 1975; Evans, George W., 1949 (University of Oregon, Dept of Economics, August 28, 2006)[more][less]Chakraborty, Avik, 1975 Evans, George W., 1949 20061002T21:14:10Z 20061002T21:14:10Z 20060828 http://hdl.handle.net/1794/3425 38 p. June 30, 2006. Revised August 28, 2006. 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. 767489 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 20068 Can Perpetual Learning Explain the Forward Premium Puzzle? Working Paper

Evans, George W., 1949 (University of Oregon, Dept. of Economics, March 31, 2003)[more][less]Evans, George W., 1949 20041019T16:33:38Z 20041019T16:33:38Z 20030331 http://hdl.handle.net/1794/233 14 p. Summarizes the OrphanidesWilliams argument, locates the paper within the rapidly growing literature on learning and monetary policy, and offers specific comments on natural extensions or alternative approaches. 162349 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;200329 Monetary policy Adaptive learning Comment on "Imperfect Knowledge, Inflation Expectations and Monetary Policy" by Athanasios Orphanides and John C. Williams Working Paper

Evans, George W., 1949; Guesnerie, R. (University of Oregon, Dept. of Economics, May 15, 2001)[more][less]Evans, George W., 1949 Guesnerie, R. 20030812T23:31:03Z 20030812T23:31:03Z 20010515 http://hdl.handle.net/1794/74 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. 0 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;20017 Economics Rationality Coordination on saddle path solutions: the eductive viewpoint Working Paper

Evans, George W., 1949; Guesnerie, R. (University of Oregon, Dept of Economics, October 10, 2003)[more][less]Evans, George W., 1949 Guesnerie, R. 20031215T19:29:59Z 20031215T19:29:59Z 20031010 http://hdl.handle.net/1794/131 We examine local strong rationality (LSR) in multivariate models with both forwardlooking 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 saddlepath 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. 0 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;200328 Mathematical and quantitative methods Mathematical methods and programming Game theory and bargaining theory Noncooperative games Existence and stability conditions of equilibrium Coordination on SaddlePath Solutions: The Eductive Viewpoint  Linear Multivariate Models Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951; Mitra, Kaushik, 1969 (University of Oregon, Dept of Economics, August 4, 2010)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 Mitra, Kaushik, 1969 20110209T23:29:32Z 20110209T23:29:32Z 20100804 http://hdl.handle.net/1794/10961 28 p. 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. en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;20103 Taxation Expectations Ramsey model Ricardian equivalence Does Ricardian Equivalence Hold When Expectations are not Rational? Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, June 23, 2003)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20031215T19:39:41Z 20031215T19:39:41Z 20030623 http://hdl.handle.net/1794/132 We introduce the Ecorrespondence 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. 244242 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;200327 The ECorrespondence Principle Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept. of Economics, April 6, 2002)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20030814T21:59:52Z 20030814T21:59:52Z 20020406 http://hdl.handle.net/1794/93 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 Estable, and therefore locally stable under adaptive learning, if F'(hat(x)) < 1. 237568 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;20029 Endogenous fluctuations Expectational stability Learnability Indeterminacy Existence of Adaptively Stable Sunspot Equilibria near an Indeterminate Steady State Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept. of Economics, January 14, 2002)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20030812T23:48:28Z 20030812T23:48:28Z 20020114 http://hdl.handle.net/1794/76 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 finitestate 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 finitestate Markov sunspot solutions are stable under learning if beta < 1. 0 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;20019 Indeterminacy Representations of solutions Learnability Expectational stability Endogenous fluctuations Microeconomics Expectational Stability of Stationary Sunspot Equilibria in a Forwardlooking Linear Model Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept. of Economics, August 3, 2001)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20030812T23:26:42Z 20030812T23:26:42Z 20010803 http://hdl.handle.net/1794/73 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. 0 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;20016 Macroeconomics Monetary policy (Targets, instruments, and effects) Mathematical and quantitative methods Information and uncertainty Expectations and the Stability Problem for Optimal Monetary Policies Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, July 6, 2009)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20110210T00:50:29Z 20110210T00:50:29Z 20090706 http://hdl.handle.net/1794/10967 32 p. We examine global economic dynamics under infinitehorizon learning in a New Keynesian model in which the interestrate 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. en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;20105 Adaptive learning Monetary policy Fiscal policy Zero Interest Rate Lower Bound Expectations, Deflation Traps and Macroeconomic Policy Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, July 12, 2003)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20031215T19:08:19Z 20031215T19:08:19Z 20030712 http://hdl.handle.net/1794/128 Using New Keynesian models, we compare Friedman's kpercent money supply rule to optimal interest rate setting, with respect to determinacy, stability under learning and optimality. First we review the recent literature: openloop interest rate rules are subject to indeterminacy and instability problems, but a properly chosen expectationsbased 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. 320,062 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;200330 Macroeconomics and monetary economics Prices, business fluctuations, and cycles Monetary policy Central banking, and the supply of money and credit Monetary policy (Targets, instruments, and effects) Price level Inflation (Finance) Deflation (Finance) Friedman's Money Supply Rule versus Optimal Interest Rate Policy Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, September 19, 2005)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20051215T16:42:42Z 20051215T16:42:42Z 20050919 http://hdl.handle.net/1794/1927 35 p. 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 Estability, 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 Estability governs SG stability. GSG algorithms with constant gain have a deeper justification in terms of parameter drift, robustness and risk sensitivity. 419658 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 200517 Adaptive learning Estability Recursive least squares Robust estimation Generalized Stochastic Gradient Learning Working Paper

Evans, George W., 1949; McGough, Bruce (University of Oregon, Dept of Economics, June 3, 2006)[more][less]Evans, George W., 1949 McGough, Bruce 20061002T19:53:24Z 20061002T19:53:24Z 20060603 http://hdl.handle.net/1794/3422 36 p. We consider optimal monetary policy in New Keynesian models with inertia. First order conditions, which we call the MJBalternative, are found to improve upon the timeless perspective. The MJBalternative 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 MJBalternative is considered via construction of interestrate 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 Estable equilibrium. Further, the “policy manifold” of all interestrate rules consistent with the MJBalternative is classified, and open regions of this manifold are shown to correspond to indeterminate models and unstable equilibria. 593049 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 20065 Monetary policy Taylor rules Indeterminacy Estability Implementing Optimal Monetary Policy in NewKeynesian Models with Inertia Working Paper

Evans, George W., 1949; McGough, Bruce (University of Oregon, Dept. of Economics, July 25, 2002)[more][less]Evans, George W., 1949 McGough, Bruce 20030815T20:59:39Z 20030815T20:59:39Z 20020725 http://hdl.handle.net/1794/98 We extend common factor analysis to a multidimensional 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 RBCtype models? 670720 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;200214 Stability Earning Expectations Sunspots Business cycles Macroeconomics Microeconomics Economic stabilization Indeterminacy and the Stability Puzzle in NonConvex Economies Working Paper

Evans, George W., 1949; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, January 11, 2005)[more][less]Evans, George W., 1949 Honkapohja, Seppo, 1951 20050322T22:27:29Z 20050322T22:27:29Z 20050111 http://hdl.handle.net/1794/655 27 p. This is the text of an interview with Thomas J. Sargent. The interview will be published in Macroeconomic Dynamics. 200361 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 20052 Rational expectations (Economic theory) An Interview with Thomas J. Sargent Working Paper

Branch, William A.; Evans, George W., 1949 (University of Oregon, Dept. of Economics, May 16, 2003)[more][less]Branch, William A. Evans, George W., 1949 20031211T19:46:23Z 20031211T19:46:23Z 20030516 http://hdl.handle.net/1794/126 We introduce the concept of a Misspecification Equilibrium to dynamic macroeconomics. Agents choose between a list of misspecified econometric models and base their selection on relative forecast performance. A Misspecification Equilibrium is an equilibrium stochastic process in which agents forecast optimally given their choices, with the forecasting model parameters and predictor proportions endogenously determined. For appropriate conditions on the exogenous driving process and the degree of feedback of expectations, the Misspecification Equilibrium will exhibit Intrinsic Heterogeneity. With Intrinsic Heterogeneity more than one misspecified model receives positive weight in the distribution of predictors across agents, even in the neoclassical limit in which only the most successful predictors are used. 502,648 bytes application/pdf en_US University of Oregon, Dept. of Economics University of Oregon Economics Department Working Papers;200332 Mathematical and quantitative methods Macroeconomics and monetary economics Expectations Prices, business fluctuations, and cycles Speculations Mathematical methods and programming Existence and stability conditions of equilibrium Intrinsic Heterogeneity in Expectation Formation Working Paper

Branch, William A.; Evans, George W., 1949 (University of Oregon, Dept of Economics, January 31, 2008)[more][less]Branch, William A. Evans, George W., 1949 20080320T16:40:42Z 20080320T16:40:42Z 20080131 http://hdl.handle.net/1794/5776 42 p. This paper demonstrates that an asset pricing model with leastsquares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are riskaverse 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. 3742112 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 20081 Risk Asset pricing Bubbles Adaptive learning Stocks  Prices Learning about Risk and Return: A Simple Model of Bubbles and Crashes Working Paper

Honkapohja, Seppo, 1951; Evans, George W., 1949 (University of Oregon, Dept of Economics, July 11, 2008)[more][less]Honkapohja, Seppo, 1951 Evans, George W., 1949 20090109T17:24:10Z 20090109T17:24:10Z 20080711 http://hdl.handle.net/1794/8264 51 p. 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 Estability 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, selffulfilling prophecies, hyperinflation, liquidity traps, and asset prices. en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers;20083 Estability Persistent learning dynamics Sunspots Asset prices Business cycles Monetary policy Stochastic approximation Least squares Learning and Macroeconomics Working Paper

Evans, George W., 1949; Guse, Eran A. (Eran Alan), 1975; Honkapohja, Seppo, 1951 (University of Oregon, Dept of Economics, June 5, 2007)[more][less]Evans, George W., 1949 Guse, Eran A. (Eran Alan), 1975 Honkapohja, Seppo, 1951 20071024T19:34:44Z 20071024T19:34:44Z 20070605 http://hdl.handle.net/1794/5131 34 p. We examine global economic dynamics under learning in a New Keynesian model in which the interestrate 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. 792892 bytes application/pdf en_US University of Oregon, Dept of Economics University of Oregon Economics Department Working Papers ; 20079 Adaptive learning Monetary policy Fiscal policy Zero interest rate lower bound Indeterminacy Liquidity Traps, Learning and Stagnation Working Paper