Myopia, Inattention, and Bounded Rationality
Friday, Jan. 4, 2019 2:30 PM - 4:30 PM
- Chair: George-Marios Angeletos, Massachusetts Institute of Technology
Myopia and Anchoring
AbstractWe consider a stationary setting featuring forward-looking behavior, slow learning, and higher- order uncertainty. We obtain an observational equivalence result that recasts the aggregate dy- namics of this setting as that of a representative-agent model featuring two distortions: myopia in the sense of extra discounting of the future; and anchoring of the current outcome to the past outcome, as in models featuring habit persistence, adjustment costs, or momentum. This builds a bridge to the DSGE literature; it also distinguishes our approach from an emerging literature on bounded rationality that captures the first feature (myopia) but misses the second feature (anchor- ing). We further show that the as-if distortions are larger when the general-equilibrium interaction is stronger; this property reflects the role of higher-order uncertainty and helps reduce the gap between macroeconomic and microeconomic estimates of adjustment frictions. We illustrate the quantitative potential of our theory in the context of inflation by showing how it can help rational- ize existing estimates of the Hybrid NKPC while also matching survey evidence on expectations. We discuss additional applications to consumption, investment, and asset prices.
Myopia and Discounting
AbstractWe assume that perfectly patient agents estimate the value of future events by generating noisy, unbiased simulations and combining those signals with priors to form posteriors. These posterior expectations exhibit as-if discounting: agents make choices as if they were maximizing a stream of known utils weighted by a discount function, D(t): This as-if discount function reáects the fact that estimated utils are a combi- nation of signals and priors, so average expectations are optimally shaded toward the mean of the prior distribution, generating behavior that partially mimics the proper- ties of classical time preferences. When the simulation noise has variance that is linear in the eventís horizon, the as-if discount function is hyperbolic, D(t) = 1=(1+ t). Our agents exhibit systematic preference reversals, but have no taste for commitment because they su§er from imperfect foresight, which is not a self-control problem. In our framework, agents that are more skilled at forecasting (e.g., those with more intelligence) exhibit less discounting. Agents with more domain-relevant experience exhibit less discounting. Older agents exhibit less discounting (except those with cognitive decline). Agents who are encouraged to spend more time thinking about an intertemporal tradeo§ exhibit less discounting. Agents who are unable to think carefully about an intertemporal tradeo§ ñe.g., due to cognitive load ñexhibit more discounting. In our framework, patience is highly unstable, áuctuating with the accuracy of forecasting.
Economic Agents as Imperfect Problem Solvers
AbstractWe develop a tractable model of limited cognitive perception of the optimal policy function. Agents allocate cognitively costly reasoning effort to generate signals about the optimal action conditional on the observed objective state. Accumulated signals update beliefs about the entire function, but mostly about the optimal action conditional on states close to the realizations where reasoning occurred. Agents reason more when observing unusual states, producing state- and history-dependent responses akin to salient thinking. The typical individual and aggregate actions exhibit non-linearity, endogenous persistence and volatility clustering. Individual behavior also displays stochastic choice, biases in systematic behavior, and cross-sectional volatility clusters.
- E7 - Macro-Based Behavioral Economics
- E0 - General