The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors. Federal Reserve Bank of St. Louis Working Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to Federal Reserve Bank of St. Louis Working Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Photo courtesy of The Gateway Arch, St. Louis, MO. www.gatewayarch.com

and Jason Zweig for useful conversations and to Lipper Analytical Services for data on Texas municipal bond funds. Familiarity Breeds Investment by

This paper presents results from an experimental computer simulated stock market. In this market artificial intelligence algorithms take on the role of traders. They make predictions about the future, and buy and sell stock as indicated by their expectations of future risk and return. Prices are set endogenously to clear the market. Time series from this market are analyzed from the standpoint of well-known empirical features in real markets. The simulated market is able to replicate several of these phenomenon, including fundamental and technical predictability, volatility persistence, and leptokurtosis. Moreover, agent behavior is shown to be consistent with these features, in that they condition on the variables that are found to be significant in the time series tests. Agents are also able to collectively learn a homogeneous rational expectations equilibrium for certain parameters giving both time series and individual forecast values

We study a Lucas asset pricing model that is standard in all respects, except that the representative agent’s subjective beliefs about endowment growth are distorted. Using constant-relative-risk-aversion utility, with relative risk aversion coefficient below ten, and fluctuating beliefs that exhibit pessimism over expansions and optimism over contractions, our model is able to match the first and second moments of the equity premium and risk–free rate, as well as the persistence and predictability of excess returns found in the data.

In this paper we study the asset pricing implications of a parsimonious two-agent macroeconomic model with two key features: limited participation in the stock market and heterogeneity in the elasticity of intertemporal substitution. The parameter values for the model are taken from the business cycle literature and are not calibrated to match any financial statistic. Yet, with a risk aversion of two, the model is able to explain a large number of asset pricing phenomena including all the facts matched by the external habit model of Campbell and Cochrane (1999). Examples in this list include a high equity premium and a low risk-free rate; a counter-cyclical risk premium, volatility and Sharpe ratio; predictable stock returns with coefficients and R2 values of long-horizon regressions matching their empirical counterparts, among others. In addition the model generates a risk-free rate with low volatility (5.7 percent annually) and with high persistence. We also show that the similarity of our results to those from an external habit model is not a coincidence: the model has a reduced form representation which is remarkably similar to Campbell and Cochrane’s framework for asset pricing. However,themacroeconomic implications of the two models are quite different, favoring the limited participation model. Moreover, we show that policy analysis yields dramatically different conclusions in each framework.

Financial planners typically advise people to shift investments away from stocks and toward bonds as they age. The planners commonly justify this advice in three ways. They argue that stocks are less risky over a young person’s long investment horizon, that stocks are often necessary for young people to meet large financial obligations (like college tuition for their children), and that younger people have more years of labor income ahead with which to recover from the potential losses associated with stock ownership. This article uses economic reasoning to evaluate these three different justifications. It finds that the first two arguments do not make economic sense. The last argument is valid—but only for people with labor income that is relatively uncorrelated with stock returns. If a person’s labor income is highly correlated with stock returns, then that investor is better off shifting investments toward stocks over time. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. Most financial planners advise their clients to shift their investments away from stocks and toward bonds as they age.

The Euler equations of consumption are tested on the household consumption of nondurables and services, reconstructed from the CEX database. The estimated relative risk aversion coefficient of the representative household decreases, and the estimated unexplained mean equity premium decreases, as infra marginal asset holders are eliminated from the sample. These results provide evidence of limited capital market participation. The estimated unexplained mean equity premium decreases when the assumption of complete consumption insurance is relaxed. The estimated correlation between the equity premium and the cross-sectional variance of the households' consumption growth is negative, as required, if the relaxation of market completeness is to contribute towards the explanation of the premium. The overall evidence from asset prices in favor of relaxing the assumption of complete consumption insurance is weak. An extensive Monte Carlo investigation highlights the relationship between the economic implications of limited participation and the resulting statistical properties of commonly used test statistics. The simulation results provide direct evidence relating observation error in consumption and the resulting small-sample properties of the test statistics.

Macroeconomics was born as a distinct field in the 1940s, as a part of the intellectual response to the Great Depression. The term then referred to the body of knowledge and expertise that we hoped would prevent the recurrence of that economic disaster. My thesis in this lecture is that macroeconomics in this original sense has succeeded: Its central problem of depression-prevention has been solved, for all practical purposes, and has in fact been solved for many decades. There remain important gains in welfare from better fiscal policies, but I argue that these are gains from providing people with better incentives to work and to save, not from better fine tuning of spending flows. Taking U.S. performance over the past 50 years as a benchmark, the potential for welfare gains from better long-run, supply side policies exceeds by far the potential from further improvements in short-run demand management. My plan is to review the theory and evidence leading to this conclusion. Section I outlines the general logic of quantitative welfare analysis, in which policy comparisons

We study asset prices in an economy where investors derive direct utility not only from consumption but also from fluctuations in the value of their financial wealth. They are loss averse over these fluctuations, and the degree of loss aversion depends on their prior investment performance. We find that our framework can help explain the high mean, excess volatility, and predictability of stock returns, as well as their low correlation with consumption growth. The design of our model is influenced by prospect theory and by experimental evidence on how prior outcomes affect risky choice. I.

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