Monetary Policy and Heterogeneous Expectations

This paper studies the implications for monetary policy of heterogeneous expectations in a New Keynesian model. The assumption of rational expectations is replaced with parsimonious forecasting models where agents select between predictors that are underparameterized. In a Misspecification Equilibrium agents only select the best-performing statistical models. We demonstrate that, even when monetary policy rules satisfy the Taylor principle by adjusting nominal interest rates more than one for one with inflation, there may exist equilibria with Intrinsic Heterogeneity. Under certain conditions, there may exist multiple misspecification equilibria. We show that these findings have important implications for business cycle dynamics and for the design of monetary policy.

Fear of model misspecifcation and the robustness premium

Robust decision making implies welfare costs or robustness premia when the approximating model is the true data generating process. To examine the importance of these premia at the aggregate level we employ a simple two-sector dynamic general equilibrium model with human capital and introduce an additional form of precautionary behavior. The latter arises from the robust decision maker s ability to reduce the effects of model misspecification through allocating time and existing human capital to this end. We find that the extent of the robustness premia critically depends on the productivity of time relative to that of human capital. When the relative efficiency of time is low, despite transitory welfare costs, there are gains from following robust policies in the long-run. In contrast, high relative productivity of time implies misallocation costs that remain even in the long-run. Finally, depending on the technology used to reduce model uncertainty, we fi nd that while increasing the fear of model misspecfi cation leads to a net increase in precautionary behavior, investment and output can fall.

The Known Unknowns of Governance.

Empirical researchers interested in how governance shapes various aspects of economic development frequently use the Worldwide Governance indicators (WGI). These variables come in the form of an estimate along with a standard error reflecting the uncertainty of this estimate. Existing empirical work simply uses the estimates as an explanatory variable and discards the information provided by the standard errors. In this paper, we argue that the appropriate practice should be to take into account the uncertainty around the WGI estimates through the use of multiple imputation. We investigate the importance of our proposed approach by revisiting in three applications the results of recently published studies. These applications cover the impact of governance on (i) capital flows; (ii) international trade; (iii) income levels around the world. We generally find that the estimated effects of governance are highly sensitive to the use of multiple imputation. We also show that model misspecification is a concern for the results of our reference studies. We conclude that the effects of governance are hard to establish once we take into account uncertainty around both the WGI estimates and the correct model specification.