Browsing by Author "McGough, Bruce"

Now showing 1 - 16 of 16
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    Adaptive Learning in Continuous-Time: Techniques and Theory
    (University of Oregon, 2021-09-13) Lester, Chandler; McGough, Bruce
    How we model individual’s expectations and predictions in economic models playsan essential role in economic outcomes. We can assume that individuals are well informed and developed nuanced views on the economy, meaning they understand and have detailed knowledge of economic parameters and economic models, or we can suppose individuals are observant and develop perceptions of the economy and make decisions based on available data. One method of including this level of realistic behavior in economic models isadaptive learning. In adaptive learning models, agents use simple forecasting rules to make predictions about future values of economic variables or the state of the economy. The work presented in this dissertation builds a framework for examining these dynamics in a high-frequency setting. It is important to extend these behavioral modeling techniques to this setting because increasing data are available at higher frequencies. This work combines existing continuous-time modeling techniques with emerging research from economics to develop modelings in which an agent can respond to high-frequency information. This dissertation demonstrates that complex high-frequency learning is possibleand has potential benefits and improvements over discrete-time counterparts. The dominant theme of this work is defining and mathematically developing a framework for examining bounded rationality in continuous-time models. In chapter two, basic exogenous adaptive rules are explored in a simple Ramsey Model setting. Chapter three introduces shadow-price learning and more complicated endogenous learning rules, including a derivation of continuous-time recursive least squares and the definition of a continuous-time mapping between an agent’s perceptions and actuality. Chapter four builds on the dynamics defined in chapter three by applying them to a linearized Real Business cycle model. We find that the continuous-time learning dynamics offer some improvements to the volatility of predictions.
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    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.
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    Essays in Behavioral Macroeconomics
    (University of Oregon, 2024-08-07) Thompson, Jacob; McGough, Bruce
    This dissertation investigates a class of DSGE models with bounded rationality where agents use recursively updated forecasts to form expectations of future vari- ables The two chapters explore the implications of the model builder’s choice of initial forecasting model with which to endow agents. Each chapter estimates a different New Keynesian DSGE model, varying this initial model and finds that this has sub- stantial impacts on parameter estimates as well as the ability of the model to fit macroeconomic data series. Chapter 1 estimates a small scale, purely forward-looking DSGE model but relaxes the assumption of rational expectations. In so doing, it outlines the computational challenges of estimating such a model and the solutions thereto. It also introduces the reader to a new class of Bayesian posterior sampler called Sequential Monte Carlo which has key advantages over Markov Chain Monte Carlo samplers for the estimation of models with Adaptive Learning. I find two notable results: first, I find that one can greatly improve the ability of the model to explain the data by training agents’ initial forecasting model on pre-sample data. Second, I find that, for this particular DSGE model, the estimated slope of the Phillips Curve is significantly greater than under Rational Expectations. Chapter 2 estimates a small-scale DSGE model with habit persistence in household consumption and inflation indexation by price-setting firm, thereby inducing mechan- ical persistence in both the output and inflation processes. This chapter shows that the improved data-fit from training sample based initial beliefs is robust to the in- clusion of mechanical lags. It also shows how initial forecasting models trained on pre-sample data cause the DSGE model to exhibit impulse response functions that show the “price puzzle” despite the additional restrictions of the DSGE model, and what restrictions to impose to avoid this outcome.
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    Essays on Nominal GDP Targeting
    (University of Oregon, 2018-09-06) Brennan, Benjamin; McGough, Bruce
    The subject of this dissertation is nominal GDP (NGDP) targeting. In the wake of the Great Recession, some economists have proposed using some form of NGDP target to replace current monetary policy. We evaluate the desirability of NGDP targets based upon their ability to deliver unique and \learnable" equilibria and their welfare gains in the presence of nancial frictions. In the second chapter, we assess the determinacy and E-stability conditions for simple interest rate rules which respond to NGDP's deviation from target in a simple three-equation New Keynesian model. The rules under consideration target either NGDP level or growth, and can either be contemporaneous, one period ahead, or two periods ahead. We also allow for dierent types of information sets for the agents. In the third chapter, we compare welfare loss in consumption equivalent terms for NGDP targets with more conventional monetary policy in a New Keynesian model which features nancial frictions. Finally, in the fourth chapter we continue our analysis from chapter one but now allow for strictly positive trend inflation. We present findings for the relationship between trend inflation and the determinacy and E-stability of the equilibrium when using interest rate rules that target NGPD.
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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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    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?
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    Monetary Policy and Stable Indeterminacy with Inertia
    (University of Oregon, Dept. of Economics, 2004-03-29) Evans, George W., 1949-; McGough, Bruce
    We examine existence and stability under learning of sunspot equilibria in a New Keynesian model incorporating inertia. Indeterminacy remains prevalent, stable sunspots abound, and inertia in IS and AS relations do not significantly impact the policy region containing stable sunspots.
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    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.
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    Monetary policy, indeterminacy and learning
    (University of Oregon, Dept. of Economics, 2003-10-11) Evans, George W., 1949-; McGough, Bruce
    The development of tractable forward looking models of monetary policy has lead to an explosion of research on the implications of adopting Taylor-type interest rate rules. Indeterminacies have been found to arise for some specifications of the interest rate rule, raising the possibility of increased economic fluctuations due to a dependence of expectations on extraneous sunspots. Separately, recent work by a number of authors has shown that sunspot equilibria previously thought to be unstable under private agent learning can in some cases be stable when the observed sunspot has a suitable time series structure. In this paper we generalize the common factor technique, used in this analysis, to examine standard monetary models that combine forward looking expectations and predetermined variables. We consider a variety of specifications that incorporate both lagged and expected inflation in the Phillips Curve, and both expected and inertial elements in the policy rule. We find that some policy rules can indeed lead to learnable sunspot solutions and we investigate the conditions under which this phenomenon arises.
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    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.
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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.
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    Sectoral Prices and Price-setting
    (University of Oregon, 2016-10-27) Fulton, Chad; McGough, Bruce
    This dissertation explores the price-setting behavior of firms both theoretically and empirically. The first portion constructs a theoretical model of price-setting in which firms are rationally inattentive: they cannot perfectly attend to all sources of uncertainty. By accommodating multiple sources of uncertainty within the model, it is possible to reasonably calibrate key parameters of the model. This bolsters the case for rational inattention as a microfounded alternative to ad-hoc mechanisms in order to generate price-stickiness and it not only allows for multiple sectors but demonstrates why their introduction is important. The second portion contributes to the empirical literature exploring disaggregated price series. Taking into account the lessons from the theoretical model, a combination of dynamic factor and unobserved component models are applied to explicitly model heterogenous dynamic processes for sectoral prices. The key finding is that models with enforced homogenous dynamics are outperformed under a variety of criteria. More importantly, models with enforced homogenous dynamics can generate erroneous conclusions with respect to the speed of price responses to aggregate and idiosyncratic shocks. A large body of recent empirical work on price-setting, including the empirical exercise described above, estimates a dynamic factor model using a relatively simple and partially non-parametric method. This method is valid in large samples, but alternative parametric methods exist that may be more efficient in small samples. The final portion of this dissertation compares methods for the estimation of dynamic factor models, including non-parametric, classical, and Bayesian techniques. The results of a Monte Carlo experiment validate the use of the partially non-parametric method, but find that the Bayesian approach may provide weakly superior results.
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    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.
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    Stable Noisy K-state Markov Sunspots
    (University of Oregon, Dept. of Economics, 2002-07-18) Evans, George W., 1949-; McGough, Bruce
    We consider a linear stochastic univariate rational expectations model, with a predetermined variable, and consider solutions driven by an extraneous finite state Markov process as well as by the fundamental noise. We obtain conditions for existence of noisy k-state sunspot equilibria (noisy k-SSEs) and, for the case k=2, of noisy k-state dependent sunspot equilibria (noisy k-*SDSs). k-*SDSs are driven by a finite stable sunspot but have an infinite range of values even in the nonstochastic model. Stability under econometric learning is analyzed using representations that nest both types of solution. For the case k=2, we find that noisy 2-SSEs and noisy 2-*SDSs are learnable for parameters in proper subsets of the regions of their existence.
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    Stable Sunspot Solutions in Models with Predetermined Variables
    (University of Oregon, Dept. of Economics, 2002-04-17) Evans, George W., 1949-; McGough, Bruce
    We consider a linear stochastic univariate rational expectations model, with a predetermined variable, and provide alternative representations of SSEs (stationary sunspot equilibria). For a strict subset of the parameter space there exist SSEs that are locally stable under least squares learning provided agents use a common factor representation for their estimated law of motion. These results indicate that for some parameter regions SSEs are more likely to arise under private agent learning than previously recognized.
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    The Effects of News Shocks and Bounded Rationality on Macroeconomic Volatility
    (University of Oregon, 2017-09-06) Dombeck, Brian; McGough, Bruce
    This dissertation studies the impact embedding boundedly rational agents in real business cycle-type news-shock models may have on a variety of model predictions, from simulated moments to structural parameter estimates. In particular, I analyze the qualitative and quantitative effects of assuming agents are boundedly rational in a class of DSGE models which attempt to explain the observed volatility and comovements in key aggregate measures of U.S. economic performance as the result of endogenous responses to information in the form of ``news shocks''. The first chapter explores the theoretical feasibility of relaxing the rational expectations hypothesis in a three-sector real business cycle (RBC) model which generates boom-bust cycles as a result of periods of optimism and pessimism on the part of households. The second chapter determines whether agents forming linear forecasts of shadow prices in a nonlinear framework can lead to behavior approximately consistent with fully informed individuals in a one-sector real business cycle model. The third chapter analyzes whether empirical estimates of the relative importance of anticipated shocks may be biased by assuming rational expectations. By merging the two hitherto separate but complementary strands of literature related to bounded rationality and news shocks I am able to conduct in-depth analysis of the importance of both the information agents have and what they choose to do with it. At its core, the study of news in macroeconomics is a study of the specific role alternative information sets play in generating macroeconomic volatility. Adaptive learning on the other hand is concerned with the behavior of agents given an information set. Taken together, these fields jointly describe the input and the ``black box'' which produce model predictions from DSGE models. While previous research has been conducted on the effects of bounded rationality or news shocks in isolation, this dissertation marks the first set of research explicitly focused on the interaction of these two model features.