Evans, George W.

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

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Browsing Evans, George W. by Subject "E-stability"

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    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.
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    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.
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    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.
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    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.