Survey evidence suggests that many investors form beliefs about future stock market returns by extrapolating past returns. Such beliefs are hard to reconcile with existing models of the aggregate stock market. We study a consumption-based asset pricing model in which some investors form beliefs about future price changes in the stock market by extrapolating past price changes, while other investors hold fully rational beliefs. We find that the model captures many features of actual prices and returns; importantly, however, it is also consistent with the survey evidence on investor expectations.

No abstract

We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals-an average of the asset's past price changes and the asset's degree of overvaluation. The two signals are in conflict, and investors "waver" over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles. We analyze the patterns of cash-flow news that generate the largest bubbles, the reasons why bubbles collapse, and the frequency with which they occur. The model also predicts that bubbles will be accompanied by high trading volume, and that volume increases with past asset returns. We present empirical evidence that bears on some of the model's distinctive predictions.

We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals-an average of the asset's past price changes and the asset's degree of overvaluation. The two signals are in conflict, and investors "waver" over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles. We analyze the patterns of cash-flow news that generate the largest bubbles, the reasons why bubbles collapse, and the frequency with which they occur. The model also predicts that bubbles will be accompanied by high trading volume, and that volume increases with past asset returns. We present empirical evidence that bears on some of the model's distinctive predictions. * The authors' affiliations are Yale School of Management, Harvard Business School, California Institute of Technology, and Harvard University, respectively. Comments are welcome.

No abstract

In this paper, a novel hollow substrate integrated waveguide (HSIW) is presented for realizing low-loss millimeter-wave (mm-wave) transmission lines embedded in multi-chip modules. A new analysis method for the HSIW is proposed by treating it as a combination of a two-dielectric loaded rectangular waveguide (RWG) and standard substrate integrated waveguide, where an effective dielectric constant, , is introduced. An HSIW prototype in the -band is fabricated using a progressive-lamination low-temperature co-fired ceramic technique. The measured results agree well with theoretical calculations and simulations. An average of 0.009-dB/mm loss is achieved in -band, which is comparable to an air-filled RWG. This shows that the technique has great potential for further development to realize highly integrated mm-wave modules.

We experimentally test a theory of risky choice in which the perception of a lottery payoff is noisy due to information processing constraints in the brain. We model perception using the principle of efficient coding, which implies that perception is most accurate for those payoffs that occur most frequently. Across two preregistered laboratory experiments, we manipulate the distribution from which payoffs in the choice set are drawn. In our first experiment, we find that risk taking is more sensitive to payoffs that are presented more frequently. In a follow-up task, we incentivize subjects to classify which of two symbolic numbers is larger. Subjects exhibit higher accuracy and faster response times for numbers they have observed more frequently. In our second experiment, we manipulate the payoff distribution so that efficient coding modulates the strength of valuation biases. As we experimentally increase the frequency of large payoffs, we find that subjects perceive the upside of a risky lottery more accurately and take greater risk. Together, our experimental results suggest that risk taking depends systematically on the payoff distribution to which the decision maker’s perceptual system has recently adapted. More broadly, our findings highlight the importance of imprecise and efficient coding in economic decision-making.

Regulatory policies designed to improve societal welfare by "nudging" consumers to make better choices are increasingly popular. The application of benefit-cost analysis (BCA) to this sort of regulation confronts difficult theoretical and applied issues. In this analysis we contribute a worked example of behavioral BCA of U.S. anti-smoking policies. Our conceptual framework extends the standard market-based approach to BCA to allow for individual failures to make lifetime-utility-maximizing choices of cigarette consumption. We discuss how our market-based approach compares to the health benefits approach and the "consumer surplus offset" controversy in recent BCAs of several health-related regulations. We use a dynamic population model to make counterfactual simulations of smoking prevalence rates and cigarette demand over time. In our retrospective BCA the simulation results imply that the overall impact of anti-smoking policies from 1964 to 2010 is to reduce the total cigarette consumption by 28%. At a discount rate of 3% the 1964-present value of the consumer benefits from anti-smoking policies through 2010 is estimated to be $573 billion ($2010). Although we are unable to develop a hard estimate of the policies' costs, we discuss evidence that suggests the consumer benefits substantially outweigh the costs. We then turn to a prospective BCA of future anti-smoking Food and Drug Administration (FDA) regulations. At a discount rate of 3%, the 2010-present value of the consumer benefits 30 years into the future from a simulated FDA tobacco regulation is estimated to be $100 billion. However, the nature of potential FDA tobacco regulations suggests that they might impose additional costs on consumers that make it less clear that the net benefits of the regulations will be positive.