A central feature of modern economic theory is forward-looking decision-making by firms and households. Expectations of economic agents are therefore a key component of macroeconomic theories of consumption, investment, inflation and the business cycle. The rational expectations (RE) approach provides the benchmark theory of expectation formation: expectations are assumed to be rational in the sense that agents do not make any systematic errors, given the available information. Two fundamental issues in connection with RE are attainability, i.e. whether boundedly rational agents can arrive at RE through a learning process, and the possibility of multiple RE equilibria. Additional realistic relaxations of RE in the direction of bounded rationality can have potentially major implications for macroeconomic policy. The proposed research investigates the implications of learning and bounded rationality for business cycles, asset prices and macroeconomic policy. The research builds on earlier theoretical work on learning and model misspecification. The research focuses on five interconnected lines of research. (i) Liquidity traps, learning and stagnation. Under adaptive learning there is the possibility of the economy, after severe negative shocks, slipping into a deflationary spiral and stagnation. The project investigates how the right combination of monetary and fiscal policy can avoid disinflation and stagnation. (ii) Endogenous inattention. This project considers the implications for economic fluctuations when the rate of information acquisition is chosen optimally, weighing costs against benefits. Monetary policies that stabilize the aggregate price path can reduce both price and output variance due to endogenous changes in the information acquisition rate. (iii) Underparameterization and endogenous volatility. This line of research shows how dynamic predictor selection between misspecified models can lead to parameter drift and regime switching of the type apparently present in the macro data. (iv) Near-rational exuberance. This project shows that, under certain conditions, the use of judgment in economic forecasting can lead to self-fulfilling fluctuations in otherwise well-behaved models. Policies to avoid the risk of such exuberance equilibria are studied. (v) Structural uncertainty and monetary policy. Uncertainty about key structural parameters needed for policy compounds the potential risks of indeterminacy or instability under learning. This research shows how to devise optimal policy rules that minimize these risks. Technical topics connected with these lines of research are also pursued, including alternative learning mechanisms, resonant frequency sunspots in multivariate models, eductive stability, anticipated policy changes, heterogeneity and empirical calibration. Other applications, such as exchange rate models and asset price behavior, are also investigated.
The broader aim of the project is to inform policymakers of the need to take into account adaptive learning and bounded rationality by private agents and policymakers themselves. The importance of learning, expectations, model uncertainty and misspecification for monetary and fiscal policy is increasingly being recognized by central bank research departments and policymakers, as shown by the workshops and conferences on these topics held in recent years by the Cleveland and Atlanta Federal Reserve Banks, the Bundesbank and the European Central Bank. Some of the proposed project is collaborative with researchers in the Federal Reserve System. The research is expected to be disseminated widely in seminars, workshops and conferences, at universities, central banks and high-level conferences. The project will also support the research of graduate students. Past NSF grants by the PI have supported research on related topics and led to PhD theses and academic appointments at research universities.
