Experiments in Macroeconomics: Volume 17

Table of contents

(13 chapters)
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List of Contributors

Pages vii-viii
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Abstract

This article discusses the methodology of using laboratory methods to address macroeconomic questions. It also provides summaries of the articles in this volume.

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Abstract

Expectations play a crucial role in finance, macroeconomics, monetary economics, and fiscal policy. In the last decade a rapidly increasing number of laboratory experiments have been performed to study individual expectation formation, the interactions of individual forecasting rules, and the aggregate macro behavior they co-create. The aim of this article is to provide a comprehensive literature survey on laboratory experiments on expectations in macroeconomics and finance. In particular, we discuss the extent to which expectations are rational or may be described by simple forecasting heuristics, at the individual as well as the aggregate level.

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We design experimental economies based on a New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model. We apply shocks to tastes, productivity, and interest rate policy, and measure the persistence of these shocks. We find that, in a setting where goods are perfect substitutes, there is little persistence of output shocks compared to treatments with monopolistic competition, which perform similarly irrespective of whether or not menu costs are present. Discretionary central banking is associated with greater persistence than automated instrumental rules.

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This article explores the importance of accessible and focal information in influencing beliefs and attention in a learning-to-forecast laboratory experiment where subjects are incentivized to form accurate expectations about inflation and the output gap. We consider the effects of salient and accessible forecast error information and learning on subjects’ forecasting accuracy and heuristics, and on aggregate stability. Experimental evidence indicates that, while there is considerable heterogeneity in the heuristics used, subjects’ forecasts can be best described by a constant gain learning model where subjects respond to forecast errors. Salient forecast error information reduces subjects’ overreaction to their errors and leads to greater forecast accuracy, coordination of expectations, and macroeconomic stability. The benefits of this focal information are short-lived and diminish with learning.

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We design an experiment to investigate the influence of announced future variations in interest rates and prices on consumption decisions. In an experimental implementation of the discounted utility model, the subjects learn the entire paths of inflation and interest rates prior to deciding on a consumption path. We decompose the total change in consumption that results from changes in either interest rates or inflation rates into anticipation and impact effects. While impact effects are of similar orders of magnitude as in the model, future changes in inflation or interest rates exert substantially smaller effects on current consumption than predicted by the model.

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In this article, we survey experiments that are directly related to monetary policy and central banking. We argue that experiments can also be used as a tool for central bankers for bench testing policy measures or rules. We distinguish experiments that analyze the reasons for non-neutrality of monetary policy, experiments in which subjects play the role of central bankers, experiments that analyze the role of central bank communication and its implications, experiments on the optimal implementation of monetary policy, and experiments relevant for monetary policy responses to financial crises. Finally, we mention open issues and raise new avenues for future research.

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This article describes an experiment in a Kydland/Prescott type of environment with cheap talk. Individual evolutionary learning (IEL) acts as a policy maker that makes inflation announcements and decides on actual inflation rates. IEL evolves a set of strategies based on the evaluation of their counterfactual payoffs measured in terms of disutility of inflation and unemployment. Two types of private agents make inflation forecasts. Type 1 agents are automated and they set their forecast equal to the announced inflation rate. Type 2 agents are human subjects who submit their inflation forecast and are rewarded based on their forecast error. The fraction of each type evolves over time based on their performance. Experimental economies result in outcomes that are better than the Nash equilibrium. This article is the first to use an automated policy maker that changes and adapts its rules over time in response to the environment in which human subjects make choices.

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We study a microfounded search model of exchange in the laboratory. Using a within-subjects design, we consider exchange behavior with and without an intrinsically worthless token object. While these tokens have no redemption value, like fiat money they may foster greater exchange and welfare via the coordinating role of having prices of goods in terms of tokens. We find that welfare is indeed improved by the presence of tokens provided that the economy starts out with a supply of such tokens. In economies that operate for some time without tokens, the later surprise introduction of tokens does not serve to improve welfare. We also explore the impact of announced changes in the economy-wide stock of tokens (fiat money) on prices. Consistent with the quantity theory of money, we find that increases in the stock of money (tokens) have no real effects and mainly result in proportionate changes to prices. However, the same finding does not hold for decreases in the stock of money.

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DOI
10.1108/S0193-2306201417
Publication date
2014-11-12
Book series
Research in Experimental Economics
Editor
Series copyright holder
Emerald Publishing Limited
ISBN
978-1-78441-195-4
eISBN
978-1-78441-194-7
Book series ISSN
0193-2306