Dynamic Duopoly with Inattentive Firms

This paper analyzes an infinite horizon dynamic duopoly with stochastic demand in which firms face costs of absorbing and processing information. Our main result is that the structure of dates at which firms choose to absorb information differ starkly between price and quantity competition. Firms synchronize their actions under price competition whereas they plan sequentially and in an alternating manner under quantity competition. The reason is that under quantity competition the planning firm reduces the uncertainty in the residual demand curve of the inattentive firm which renders planning less attractive for that firm. The opposite holds true under price competition.Inattentiveness, Price Competition, Quantity Competition, Synchronization

The rigidity of choice: lifetime savings under information-processing constraints

This paper studies the implications of information-processing limits on the consumption and savings behavior of households through time. It presents a dynamic model in which consumers rationally choose the size and scope of the information they want to process about their fi�nancial possibilities, constrained by a Shannon channel. The model predicts that people with higher degrees of risk aversion rationally choose higher information. This happens for precautionary reasons since, with fi�nite processing rate, risk averse consumers prefer to be well informed about their fi�nancial possibilities before implementing consumption plan. Moreover, numerical results show that consumers with processing capacity constraints have asymmetric responses to shocks, with negative shocks producing more persistent effects than positive ones. This asymmetry results into more savings. I show that the predictions of the model can be effectively used to study the impact of tax reforms on consumers spending. The results are qualitatively consistent with the evidence on tax rebates (2001, 2008).Consumption, Rational Inattention, Dynamic programming

Inattentive Producers

I present and solve the problem of a producer who faces costs of acquiring, absorbing, and processing information. I establish a series of theoretical results describing the producer's behavior. First, I find the conditions under which she prefers to set a plan for the price she charges, or instead prefers to set a plan for the quantity she sells. Second, I show that the agent rationally chooses to be inattentive to news, only sporadically updating her information. I solve for the optimal length of inattentiveness and characterize its determinants. Third, I explicitly aggregate the behavior of many such producers. I apply these results to a model of inflation. I find that the model can fit the quantitative facts on post-war inflation remarkably well, that it is a good forecaster of future inflation, and that it survives the Lucas critique by fitting also the pre-war facts on inflation moderately well.

A Sticky-Information General Equilibrium Model for Policy Analysis

This paper presents a dynamic stochastic general-equilibrium model with a single friction in all markets: sticky information. In this economy, agents are inattentive because of the high cost of acquiring, absorbing and processing information, so that the actions of consumers, workers and firms are slow to incorporate news. This paper presents the details of the behavior of an economy with pervasive inattentiveness functions, and develops a set of algorithms that solve the model quickly. It then applies these to estimate the model using post-1986 data for the United States and post-1993 for the Eurozone, and to conduct counterfactual policy experiments. The end result is a laboratory that is rich enough to account for the dynamics of at least five macroeconomic series (inflation, output, hours, interest rates, and wages), and which can be used to inform applied monetary policy.

Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

This paper presents an inverse reinforcement learning~(IRL) framework for Bayesian stopping time problems. By observing the actions of a Bayesian decision maker, we provide a necessary and sufficient condition to identify if these actions are consistent with optimizing a cost function. In a Bayesian (partially observed) setting, the inverse learner can at best identify optimality wrt the observed actions. Our IRL algorithm identifies optimality and then constructs set valued estimates of the cost function. To achieve this IRL objective, we use novel ideas from Bayesian revealed preferences stemming from microeconomics. We illustrate the proposed IRL scheme using two important examples of stopping time problems, namely, sequential hypothesis testing and Bayesian search. Finally, for finite datasets, we propose an IRL detection algorithm and give finite sample bounds on its error probabilities

Inattentive Consumers

This paper studies the consumption decisions of agents who face costs of acquiring, absorbing and processing information. These consumers rationally choose to only sporadically update their information and re-compute their optimal consumption plans. In between updating dates, they remain inattentive. This behavior implies that news disperses slowly throughout the population, so events have a gradual and delayed effect on aggregate consumption. The model predicts that aggregate consumption adjusts slowly to shocks, and is able to explain the excess sensitivity and excess smoothness puzzles. In addition, individual consumption is sensitive to ordinary and unexpected past news, but it is not sensitive to extraordinary or predictable events. The model further predicts that some people rationally choose to not plan, live hand-to-mouth, and save less, while other people sporadically update their plans. The longer are these plans, the more they save. Evidence using U.S. aggregate and microeconomic data generally supports these predictions.