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If You’re So Smart, Why Aren’t You Rich? Belief Selection in Complete and Incomplete Markets
, 2001
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Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data
 JOURNAL OF POLITICAL ECONOMY
, 2003
"... Recently, economists have developed methods for structural estimation of auction models. Many researchers object to these methods because they find the rationality assumptions used in these models to be implausible. In this paper, we explore whether structural auction models can generate reasonable ..."
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Cited by 31 (4 self)
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Recently, economists have developed methods for structural estimation of auction models. Many researchers object to these methods because they find the rationality assumptions used in these models to be implausible. In this paper, we explore whether structural auction models can generate reasonable estimates of bidders’ private information. Using bid data from auction experiments, we estimate four alternative structural models of bidding in firstprice sealedbid auctions: 1) risk neutral BayesNash, 2) risk averse BayesNash, 3) a model of learning and 4) a quantal response model of bidding. For each model, we compare the estimated valuations and the valuations assigned to bidders in the experiments. We find that a slight modification of Guerre, Perrigne and Vuong’s (2000) procedure for estimating the risk neutral BayesNash model to allow for bidder asymmetries generates quite reasonable estimates of the structural parameters.
The Efficiency of an Artificial Stock Market with Heterogeneous Intelligent Agents
, 1999
"... In this paper, we construct an artificial equity market using an Artificial Neural Network (ANN). Based on the heterogeneous beliefs and trading strategies prevailing in actual equity markets, we divide traders into three groups: value traders, momentum traders and noise traders. Characteristically, ..."
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Cited by 1 (0 self)
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In this paper, we construct an artificial equity market using an Artificial Neural Network (ANN). Based on the heterogeneous beliefs and trading strategies prevailing in actual equity markets, we divide traders into three groups: value traders, momentum traders and noise traders. Characteristically, value traders are endowed with an ANN learning mechanism that allows them to forecast the dividend growth rate. A doubleauction market setting is adopted as our market mechanism for simulating the market structure. Our artificial market is able to replicate several important features of real markets, including excess volatility, volatility persistence, and serial autocorrelation of stock returns. The profitability of three trading strategies are compared. On average, value traders exhibit the highest Sharpe ratio and significantly positive excess returns. The rational expectations equilibrium emerges for only one of the three experiments.
The Market Selection Hypothesis
, 1999
"... It is conventional to assume that traders in asset markets have rational expectations about asset returns, and choose savings rates and portfolios as if they maximize expected utility using these beliefs. As the hypothesis that traders are expected utility maximizers places few restrictions on behav ..."
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It is conventional to assume that traders in asset markets have rational expectations about asset returns, and choose savings rates and portfolios as if they maximize expected utility using these beliefs. As the hypothesis that traders are expected utility maximizers places few restrictions on behavior in the absence of the rational expectations hypothesis, much attention has been
DSGE Estimation of Models with Learning ∗
, 2011
"... I investigate how a model that assumes learning might interact with a rational expectations data generating process. Milani (2007b) asserts that if agents are learning and there is no conditional heteroscedasticity then an econometrician may be fooled into estimating ARCH/GARCH models. In addition, ..."
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I investigate how a model that assumes learning might interact with a rational expectations data generating process. Milani (2007b) asserts that if agents are learning and there is no conditional heteroscedasticity then an econometrician may be fooled into estimating ARCH/GARCH models. In addition, I evaluate the contribution of a new endogenous gain, which I have proposed in previous paper, may yield on the fit of the NK model. Initial indications suggest the an endogenous gain can significantly increase the value of the likelihood function, which could mean that model comparison, using Bayes factor analysis, would support a model with an endogenous gain.
SELFFULLING PROPHECIES AND THE BUSINESS CYCLE *
, 1997
"... This paper was originally circulated in 1984 as CARESS working paper 8412.2 ..."
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This paper was originally circulated in 1984 as CARESS working paper 8412.2
Preliminary
, 2000
"... This paper considers whether “liquidity trap ” issues have important bearing on the desirability of inflation targeting as a strategy for monetary policy. From a theoretical perspective, it has been suggested that “expectation trap ” and “indeterminacy ” dangers are created by variants of inflation ..."
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This paper considers whether “liquidity trap ” issues have important bearing on the desirability of inflation targeting as a strategy for monetary policy. From a theoretical perspective, it has been suggested that “expectation trap ” and “indeterminacy ” dangers are created by variants of inflation targeting, the latter when forecasts of future inflation enter the policy rule. This paper argues that these alleged dangers are probably not of practical importance. From an empirical perspective, a quantitative openeconomy model is developed and the likelihood of encountering a liquidity trap is explored for several policy rules. Also, it is emphasized that, if the usual interest rate instrument is immobilized by a liquidity trap, there is still an exchangerate channel by means of which monetary policy can exert stabilizing effects. The relevant target variable can still be the inflation rate.