Overconfidence, subjective perception and pricing behavior

We study the implications of overconfidence for price setting in a monopolistic competition setup with incomplete information. Our price-setters overestimate their abilities to infer aggregate shocks from private signals. The fraction of uninformed firms is endogenous; firms can obtain information by paying a fixed cost. We find two results: i) overconfident firms are less inclined to acquire information relative to the rational benchmark; ii) prices might exhibit excess volatility driven by non-fundamental noise. We explore the empirical predictions of our model for idiosyncratic price volatility

Managing expectations and fiscal policy

This paper studies an optimal fiscal policy problem of Lucas and Stokey (1983) but in a situation in which the representative agent's distrust of the probability model for government expenditures puts model uncertainty premia into history-contingent prices. This situation gives rise to a motive for expectation management that is absent within rational expectations and a novel incentive for the planner to smooth the shadow value of the agent's subjective beliefs to manipulate the equilibrium price of government debt. Unlike the Lucas and Stokey (1983) model, the optimal allocation, tax rate, and debt become history dependent despite complete markets and Markov government expenditures.

Optimal Taxation and Debt with Uninsurable Risks to Human Capital Accumulation

We consider an economy where individuals face uninsurable risks to their human capital accumulation and analyze the optimal level of linear taxes on capital and labor income together with the optimal path of government debt. We show that in the presence of such risks, it is beneficial to tax both labor and capital and to issue public debt. We also assess the quantitative importance of these findings, and show that the benefits of government debt and capital taxes both increase with the magnitude of idiosyncratic risks and the degree of relative risk aversion

Macroeconomics after the Crisis: Time to Deal with the Pretense-of-Knowledge Syndrome

The recent financial crisis has damaged the reputation of macroeconomics, largely for its inability to predict the impending financial and economic crisis. To be honest, this inability to predict does not concern me much. It is almost tautological that severe crises are essentially unpredictable, for otherwise they would not cause such a high degree of distress. What does concern me about my discipline is that its current core—by which I mainly mean the so-called dynamic stochastic general equilibrium approach—has become so mesmerized with its own internal logic that it has begun to confuse the precision it has achieved about its own world with the precision that it has about the real one. This is dangerous for both methodological and policy reasons. To be fair to our field, an enormous amount of work at the intersection of macroeconomics and corporate finance has been chasing many of the issues that played a central role during the current crisis, including liquidity evaporation, collateral shortages, bubbles, crises, panics, fire sales, risk-shifting, contagion, and the like. However, much of this literature belongs to the periphery of macroeconomics rather than to its core. I will discuss the distinction between the core and the periphery of macroeconomics as well as the futile nature of the integrationist movement—that is, the process of gradually bringing the insights of the periphery into the dynamic stochastic general equilibrium structure. I argue that the complexity of macroeconomic interactions limits the knowledge we can ever attain, and that we need to place this fact at the center of our analysis. We should consider what this complexity does to the actions and reactions of the economic agent, and seek analytical tools and macroeconomic policies that are robust to the enormous uncertainty to which we are confined