Rational Expectations and Ambiguity: A Comment on Abel (2002)

Abel (2002) proposes a resolution of the riskfree rate and the equity premium puzzles} by considering pessimism and doubt. Pessimism is characterized by subjective probabilistic beliefs about asset returns that are stochastically dominated by the objective distribution of these returns. The subjective distribution is characterized by doubt if it is a mean-preserving spread of the objective distribution. This note offers a decision theoretic foundation of Abel's ad-hoc definitions of pessimism and doubt under the assumption that individuals exhibit ambiguity attitudes in the sense of Schmeidler (1989). In particular, we show that the behavior of a representative agent, who resolves her uncertainty with respect to the true distribution of asset returns in a pessimistic way, is the equivalent to pessimism in Abel's sense. Furthermore, a representative agent, who takes into account pessimistic as well as optimistic considerations, may result in the equivalent to doubt in Abel's sense.

Moment estimation in Auerbach-Kotlikoff models: How well do they match the data?

Despite their widespread use for the analysis of economic questions, a formal and systematic calibration methodology has not yet been developed for Auerbach-Kotlikoff (Auerbach and Kotlikoff 1987) overlapping generations (AK-OLG) models. Calibration as estimation in macroeconomics involves choosing free parameters by matching moments of simulated models with those of the data. This paper maps this approach into the framework of AK-OLG models. The paper further evaluates the back-fitting properties of three different versions of a prototype AK-OLG model along a number of dimensions of mostly US data for the time period 1960-2003.

Improving Tatonnement Methods for Solving Heterogeneous Agent Models

This paper modifies standard block Gauss-Seidel iterations used by tatonnement methods for solving large scale deterministic heterogeneous agent models. The composite method between first- and second-order tatonnement methods is shown to considerably improve convergence both in terms of speed as well as robustness relative to conventional first-order tatonnement methods. In addition, the relative advantage of the modified algorithm increases in the size and complexity of the economic model. Therefore, the algorithm allows significant reductions in computational time when solving large models. The algorithm is particularly attractive since it is easy to implement - it only augments conventional and intuitive tatonnement iterations with standard numerical methods.

Rational Expectations and Ambiguity: A Comment on Abel

Abel (2002) proposes a resolution of the riskfree rate and the equity premium puzzles by considering pessimism and doubt. Pessimism is characterized by subjective probabilistic beliefs about asset returns that are stochastically dominated by the objective distribution of these returns. The subjective distribution is characterized by doubt if it is a mean- preserving spread of the objective distribution. This note offers a decision theoretic foundation of Abel's ad-hoc definitions of pessimism and doubt under the assumption that individuals exhibit ambiguity attitudes in the sense of Schmeidler (1989). In particular, we show that the behavior of a representative agent, who resolves her uncertainty with respect to the true distribution of asset returns in a pessimistic way, is the equivalent to pessimism in Abel's sense. Furthermore, a representative agent, who takes into account pessimistic as well as optimistic considerations, may result in the equivalent to doubt in Abel's sense.

A Parsimonious Model of Subjective Life Expectancy

This paper develops a theoretical model for the formation of subjective beliefs on individual survival expectations. Data from the Health and Retirement Study (HRS) indicate that, on average, young respondents underestimate their true survival probability whereas old respondents overestimate their survival probability. Such subjective beliefs violate the rational expectations paradigm and are also not in line with the predictions of the rational Bayesian learning paradigm. We therefore introduce a model of Bayesian learning which combines rational learning with the possibility that the interpretation of new information is prone to psychological attitudes. We estimate the parameters of our theoretical model by pooling the HRS data. Despite a parsimonious parametrization we find that our model results in a remarkable fit to the average subjective beliefs expressed in the data.

Attitude polarization

Psychological evidence suggests that people’s learning behavior is often prone to a “myside bias”or “irrational belief persistence”in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive conditions under which beliefs may diverge in the learning process and thus conform with the psychological evidence. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a speci…c feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.

Investment Behavior under Ambiguity: The Case of Pessimistic Decision Makers

We define pessimistic, respectively optimistic, investors as CEU (Choquet expected utility) decision makers who update their pessimistic, respectively optimistic, beliefs according to a pessimistic (Dempster-Shafer), respectively optimistic, update rule. This paper then demonstrates that, in contrast to optimistic investors, pessimistic investors may strictly prefer investing in an illiquid asset to investing in a liquid asset. Key to our result is the dynamic inconsistency of CEU decision making, implying that a CEU decision maker ex ante prefers a different strategy with respect to prematurely liquidating an uncertain long-term investment project than after learning her liquidity needs. Investing in an illiquid asset then serves as a commitment device guaranteeing an ex ante favorable outcome.

On attitude polarization under Bayesian learning with non-additive beliefs

Ample psychological evidence suggests that people’s learning behavior is often prone to a "myside bias" or "irrational belief persistence" in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive conditions under which beliefs may diverge in the learning process despite the fact that all agents observe the same - arbitrarily large - sample, which is drawn from an "objective" i.i.d. process. Furthermore, one of our learning scenarios results in attitude polarization even in the case of common priors. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a specific feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.Non-additive Probability Measures, Choquet Expected Utility Theory, Bayesian Learning, Bounded Rationality

Improving Tatonnement Methods of Solving Heterogeneous Agent Models

This paper modifies standard block Gauss-Seidel iterations used by tatonnement methods for solving large scale deterministic heterogeneous agent models. The composite method between first- and second-order tatonnement methods is shown to considerably improve convergence both in terms of speed as well as robustness relative to conventional first-order tatonnement methods. In addition, the relative advantage of the modified algorithm increases in the size and complexity of the economic model. Therefore, the algorithm allows significant reductions in computational time when solving large models. The algorithm is particularly attractive since it is easy to implement – it only augments conventional and intuitive tatonnement iterations with standard numerical methods.

A Parsimonious Model of Subjective Life Expectancy

This paper develops a theoretical model for the formation of subjective beliefs on individual survival expectations. Data from the Health and Retirement Study (HRS) indicate that, on average, young respondents underestimate their true sur- vival probability whereas old respondents overestimate their survival probability. Such subjective beliefs violate the rational expectations paradigm and are also not in line with the predictions of the rational Bayesian learning paradigm. We therefore introduce a model of Bayesian learning which combines rational learn- ing with the possibility that the interpretation of new information is prone to psychological attitudes. We estimate the parameters of our theoretical model by pooling the HRS data. Despite a parsimonious parametrization we find that our model results in a remarkable fit to the average subjective beliefs expressed in the data.