Rational inattention,long-run consumption risk,and portfolio choice

This paper explores how the introduction of rational inattention (RI) – that agents process information subject to finite channel capacity – affects optimal consumption and investment decisions in an otherwise standard intertemporal model of portfolio choice. We first explicitly derive optimal consumption and portfolio rules under RI and then show that introducing RI reduces the optimal share of savings invested in the risky asset because inattentive investors face greater long-run consumption risk. We also show that the investment horizon matters for portfolio allocation in the presence of RI, even if investment opportunities are constant and the utility function of investors is constant relative risk aversion. Second, after aggregating across investors, we show that introducing RI can better explain the observed joint dynamics of aggregate consumption and the equity return. Finally, we show that RI increases the implied equity premium because investors under RI face greater long-run consumption risk and thus require higher compensation in equilibrium.     

Consumption dynamics under information processing constraints

This paper studies how “rational inattention” (RI)—a type of information processing constraint proposed by Sims [Sims, C.A., 2003. Implications of rational inattention, Journal of Monetary Economics 50 (3), 665–690]—affects the joint dynamics of consumption and income in a permanent income model with general income processes. Specifically, I propose an analytical approach to solve the multivariate permanent income model with RI and examine its implications for optimal consumption, saving, and welfare. It is shown that RI can affect the relative volatility of consumption and provide an endogenous propagation mechanism that disentangles the short-run and long-run responses of consumption to exogenous income shocks. I also explore how aggregation reduces the impact of the RI-induced endogenous noise on consumption and thus increases the smoothness of aggregate consumption. Finally, I compare RI with four alternative hypotheses (habit formation, signal extraction, robustness, and inattentiveness) by examining their implications for the joint behavior of consumption and income.     

PARTIAL IDENTIFICATION OF COUNTERFACTUAL CHOICE PROBABILITIES*

This article shows how to predict counterfactual discrete choice behavior when the presumed behavioral model partially identifies choice probabilities. The simple, general approach uses observable choice probabilities to partially infer the distribution of types in the population and then applies the results to predict behavior in unrealized choice settings. Two illustrative applications are given. One assumes only that persons have strict preferences. The other assumes strict preferences and utility functions that are linear in attribute bundles, with no restrictions on the shape of the distribution of preference parameters.     

Completing Incomplete Revealed Preference Under Limited Attention

This paper discusses how to improve the identification of the preference of a decision‐maker (DM) with limited attention proposed by Masatlioglu, Nakajima and Ozbay (2012). in “Revealed Attention”. Their identification method relies on choice reversals so the obtained revealed preference is often incomplete. We propose three approaches to address this problem. The first one is accommodating a model‐free approach, which respects the DM's choice in making a welfare analysis, as long as it does not contradict the revealed preference of Masatlioglu et al. The second approach incorporates the DM's exogenously obtained attention/inattention information into the model of Masatlioglu et al. The third approach is to take framings that influence the DM's attention into effect for the identification.     

PROBLEMS IN MODELING COMPLEX DYNAMIC INTERACTIONS: THE POLITICAL REALIGNMENT OF THE 1850s*

This paper argues that a model of sequential choice is superior to the standard rational choice model in explaining a process as complex and dynamic as the political realignment of the 1850s. Part 1 sketches the facts and processes that need to be encompassed by a model and identifies key branching points. Part 2 describes an appropriate model of sequential choice and discusses procedures for estimating transition probabilities and the impact of key variables on these transition probabilities. Part 3 identifies implicit assumptions of rational choice theory that limit its usefulness.     

Dynamic pricing and asymmetries in retail gasoline markets: What can they tell us about price stickiness?

Theoretical explanations for price stickiness used in businesses cycle models are diverse (e.g., information processing delays, rational inattention and fair pricing), with each theory resulting in a different implication for inflation dynamics. Using an autoregressive conditional binomial model and a data set consisting of daily observations of price and cost for 15 Philadelphia retail gasoline stations, we test which of these theories is most consistent with the observed pattern of price adjustment. Our findings of time dependence, asymmetry and the role of cost volatility are consistent with a combination of fairness considerations and rational inattention by producers.     

Shunning uncertainty: The neglect of learning opportunities

Financial, managerial, and medical decisions often involve alternatives whose possible outcomes have uncertain probabilities. In contrast to alternatives whose probabilities are known, these uncertain alternatives offer the benefits of learning. In repeat-choice situations, such learning brings value. If probabilities appear favorable (unfavorable), a choice can be repeated (avoided). In a series of experiments involving bets on the colors of poker chips drawn from bags, decision makers often prove to be blind to the learning opportunities offered by uncertain probabilities. They forgo significant expected payoffs when they shun uncertain alternatives in favor of known ones. Worse, when information is revealed, many make choices contrary to learning. Priming with optimal strategies offers little improvement. Such decision makers violate identified requirements for making rational decisions.     

TOWARD BEHAVIORAL MODELING OF ALASKA GROUNDFISH FISHERIES: A DISCRETE CHOICE APPROACH TO BERING SEA/ALEUTIAN ISLANDS TRAWL FISHERIES

This article implements a discrete choice model of fishery participation in the multispecies trawl fisheries of the Bering Sea/Aleutian Islands Region off Alaska. Nonparametric estimates of the operation-specific moments of quasirent by fishery and week are used to explain probabilities of choosing different target fisheries. There are pronounced risk aversion, seasonal, and relative performance effects. Notably, the model runs with regularly collected data, so this type of discrete choice modeling can be used routinely in the management and policy evaluation process. Improvements are needed, though, in both the quality and the extent of economic data on fisheries in Alaska and elsewhere in the United States. (JEL Q22, C25, Q28)     

DIMENSIONALITY AND DISAGREEMENT: ASYMPTOTIC BELIEF DIVERGENCE IN RESPONSE TO COMMON INFORMATION

We provide a model of boundedly rational, multidimensional learning and characterize when beliefs will converge to the truth. Agents maintain beliefs as marginal probabilities instead of joint probabilities, and agents' information is of lower dimension than the model. As a result, for some observations, agents may face an identification problem affecting the role of data in inference. Beliefs converge to the truth when these observations are rare, but beliefs diverge when observations presenting an identification problem are frequent. Robustly, two agents with differing priors who observe identical, unambiguous information may disagree forever, with stronger disagreement the more information received.     

The Influence of IMF Programs on the Re-election of Debtor Governments

The paper develops a model explaining why IMF programs are less likely to be concluded before national election dates. Since conclusion of an IMF arrangement may signal the incumbent's incompetence, rational voters use this signal when deciding upon his re-election. In order to demonstrate competence, politicians may therefore decide not to conclude IMF programs prior to elections. The model also shows that re-election probabilities of politicians who nevertheless conclude arrangements at election times depend on the state of the economy. Using panel data for 96 countries between 1976 and 1997, the model is tested empirically. The results show that conclusion of an IMF arrangement within six months prior to an election increases re-election probabilities when GDP growth is low, but reduces the chance to win an election with high growth rates.     

Compensating Variation and Hicksian Choice Probabilities in Random Utility Models that are Nonlinear in Income

In this paper we discuss Hicksian demand and compensating variation in the context of discrete choice. We first derive Hicksian choice probabilities and the distribution of the (random) expenditure function in the general case when the utilities are nonlinear in income. We subsequently derive exact and simple formulae for the expenditure and choice probabilities under price (policy) changes conditional on the initial utility level. This is of particular interest for welfare measurement because it enables the researcher to compute the distribution of compensating variation in a simple way. We also derive formulae for the joint distribution of expenditure, the choice before and after a policy change has been introduced.     

Time-dependent event cross-impact analysis: Results from a new model

This time-dependent event cross-impact model involves four stages. In the first stage, an undisturbed world view, prior to new information being obtained, is projected for a set of events to occur with specified probability densities over an indefinite time horizon. In the second stage, the estimator fills in the cells of a cross-impact matrix with qualitative estimates of the strength and direction of the impacts. Qualitative cross-impacts are converted to aaquantitative form by the analyst conducting the excercise. In the third stage, it is assumed that new information becomes known to the estimator causing him to project anew the time-dependent probabilities of the events in the set. In the fourth and final stage, an event cross-impact simulation model is constructed in system dynamics and run to produce new probability densities of the event set. These densities take into account both the cross-impacts between events and the effect of the newly obtained information. The possible results include both shifts of the most likely time of occurence and changes in the cumulative probability of the events. The chief usefulness of the model is that it provides a method of foreshortening the time required by decision-makers to take into account the effect of new information on the probability of events occuring over a time period.     

A theory of Bayesian decision making with action-dependent subjective probabilities

This paper presents a complete, choice-based, axiomatic Bayesian decision theory. It introduces a new choice set consisting of information-contingent plans for choosing actions and bets and subjective expected utility model with effect-dependent utility functions and action-dependent subjective probabilities which, in conjunction with the updating of the probabilities using Bayes’ rule, gives rise to a unique prior and a set of action-dependent posterior probabilities representing the decision maker’s prior and posterior beliefs.     

DYNAMIC WAGE AND EMPLOYMENT EFFECTS OF ELDER PARENT CARE

This article formulates and estimates a dynamic discrete choice model of elder parent care and work to analyze how caregiving affects a woman's current and future labor force participation and wages. The model incorporates parental health changes, human capital accumulation, and job offer availability. The estimates indicate that women face low probabilities of returning to work or increasing work hours after a caregiving spell. I use the estimated model to simulate the caregiving, employment, and welfare effects of a longer unpaid work leave than currently available under the Family and Medical Leave Act, a paid leave, and a caregiver allowance.     

Rational dictators and the killing of innocents: Data from Stalin’s archives

We posit a rational choice model of dictatorship to explain the tendency of dictators to repress innocent citizens. This model demonstrates that, when the quality of information about regime enemies is low, a rational dictator will knowingly kill and imprison citizens who are not real enemies. We use the formerly secret Stalin archives to test this proposition against the stylized facts of Stalin’s three major repressions.     

Rationally inattentive consumption choices

This paper analyzes how information-processing limitations affect consumption in a dynamic full-fledged non-linear quadratic Gaussian (LQG) setting. In the model, risk-averse consumers rationally choose the quantity and quality of information to process about their wealth, while constrained by a Shannon channel. The main contribution of the paper is methodological. It proposes a solution to rational inattention problems in rich theoretical environments. The main prediction of the model is that consumption responses to wealth shocks are asymmetric, with negative shocks producing faster and stronger reaction than positive shocks. The model also predicts that information-processing constraints increase persistence and volatility of consumption behavior.     

Large deviations and multinomial probit choice

We consider a discrete choice model in which the payoffs to each of an agent?s n actions are subjected to the average of m i.i.d. shocks, and use tools from large deviations theory to characterize the rate of decay of the probability of choosing a given suboptimal action as m approaches infinity. Our model includes the multinomial probit model of Myatt and Wallace (2003) [5] as a special case. We show that their formula describing the rates of decay of choice probabilities is incorrect, provide the correct formula, and use our large deviations analysis to provide intuition for the difference between the two.     

THE IDENTIFICATION AND ECONOMIC CONTENT OF ORDERED CHOICE MODELS WITH STOCHASTIC THRESHOLDS*

This article extends the widely used ordered choice model by introducing stochastic thresholds and interval‐specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with different stopping times. We establish conditions for nonparametric identification. We interpret the ordered choice model as a special case of a general discrete choice model and as a special case of a dynamic discrete choice model.