Individuals must often choose among discrete actions with imperfect information about their payoffs. Before choosing, they have an opportunity to study the payoffs, but doing so is costly. This creates new choices such as the number of and types of questions to ask. We model these situations using the rational inattention approach to information frictions. We find that the decision maker's optimal strategy results in choosing probabilistically in line with a generalized multinomial logit model, which depends both on the actions' true payoffs as well as on prior beliefs.

We study a market with rationally inattentive consumers who are unsure of the terms of the offers made by firms, but can acquire information about the terms at a cost. In a symmetric equilibrium, the price set by firms is continuously increasing in the cost of information for consumers and decreasing in the number of firms operating. In addition, favorable a priori information about a firm leads it to set a higher price, and a new entrant can increase demand for incumbents. When consumers have heterogeneous costs of information, firms selling low-quality products may choose to set the highest prices.

We show that, in a general family of linearized structural macroeconomic models, knowledge of the empirically estimable causal effects of contemporaneous and news shocks to the prevailing policy rule is sufficient to construct counterfactuals under alternative policy rules. If the researcher is willing to postulate a loss function, our results furthermore allow her to recover an optimal policy rule for that loss. Under our assumptions, the derived counterfactuals and optimal policies are robust to the Lucas critique. We then discuss strategies for applying these insights when only a limited amount of empirical causal evidence on policy shock transmission is available.

The prevailing neo‐Wicksellian view holds that the central bank's objective is to track the natural rate of interest ( r * ), which itself is largely exogenous to monetary policy. We challenge this view using a fixed‐cost model of durable consumption demand, in which expansionary monetary policy prompts households to accelerate purchases of durable goods. This yields an intertemporal trade‐off in aggregate demand as encouraging households to increase durable holdings today leaves fewer households acquiring durables going forward. Interest rates must be kept low to support demand going forward, so accommodative monetary policy today reduces r * in the future. We show that this mechanism is quantitatively important in explaining the persistently low level of real interest rates and r * after the Great Recession.

Should the generosity of unemployment benefits and the progressivity of income taxes depend on the presence of business cycles? This paper proposes a tractable model where there is a role for social insurance against uninsurable shocks to income and unemployment, as well as business cycles that are inefficient due to the presence of matching frictions and nominal rigidities. We derive an augmented Baily–Chetty formula showing that the optimal generosity of the social insurance system depends on a macroeconomic stabilization term. This term pushes for an increase in generosity when the level of economic activity is more responsive to social programmes in recessions than in booms. A calibration to the US economy shows that taking concerns for macroeconomic stabilization into account substantially raises the optimal unemployment insurance replacement rate but has a negligible impact on the optimal progressivity of the income tax. More generally, the role of social insurance programmes as automatic stabilizers affects their optimal design.

Most countries have automatic rules in their tax-and-transfer systems that are partly intended to stabilize economic fluctuations. This paper measures their effect on the dynamics of the business cycle. We put forward a model that merges the standard incomplete-markets model of consumption and inequality with the new Keynesian model of nominal rigidities and business cycles, and that includes most of the main potential stabilizers in the U.S. data and the theoretical channels by which they may work. We find that the conventional argument that stabilizing disposable income will stabilize aggregate demand plays a negligible role in the dynamics of the business cycle, whereas tax-and-transfer programs that affect inequality and social insurance can have a larger effect on aggregate volatility. However, as currently designed, the set of stabilizers in place in the U.S. has had little effect on the volatility of aggregate output fluctuations or on their welfare costs despite stabilizing aggregate consumption. The stabilizers have a more important role when monetary policy is constrained by the zero lower bound, and they affect welfare significantly through the provision of social insurance.

In recent years, central banks have increasingly turned to forward guidance as a central tool of monetary policy. Standard monetary models imply that far future forward guidance has huge effects on current outcomes, and these effects grow with the horizon of the forward guidance. We present a model in which the power of forward guidance is highly sensitive to the assumption of complete markets. When agents face uninsurable income risk and borrowing constraints, a precautionary savings effect tempers their responses to changes in future interest rates. As a consequence, forward guidance has substantially less power to stimulate the economy.

We provide new time-varying estimates of the housing wealth effect back to the 1980s. We use three identification strategies: ordinary least squares with a rich set of controls, the Saiz housing supply elasticity instrument, and a new instrument that exploits systematic differences in city-level exposure to regional house price cycles. All three identification strategies indicate that housing wealth elasticities were if anything slightly smaller in the 2000s than in earlier time periods. This implies that the important role housing played in the boom and bust of the 2000s was due to larger price movements rather than an increase in the sensitivity of consumption to house prices. Full-sample estimates based on our new instrument are smaller than recent estimates, though they remain economically important. We find no significant evidence of a boom–bust asymmetry in the housing wealth elasticity. We show that these empirical results are consistent with the behaviour of the housing wealth elasticity in a standard life-cycle model with borrowing constraints, uninsurable income risk, illiquid housing, and long-term mortgages. In our model, the housing wealth elasticity is relatively insensitive to changes in the distribution of loan-to-value (LTV) for two reasons: first, low-leverage homeowners account for a substantial and stable part of the aggregate housing wealth elasticity; second, a rightward shift in the LTV distribution increases not only the number of highly sensitive constrained agents but also the number of underwater agents whose consumption is insensitive to house prices.