The application of time-series statistical techniques to macroeconomics enables economists to test for the presence of business cycles and other important dynamic regularities in macroeconomic data. This project consists of work on four topics in time-series econometrics and applied macroeconomics. The first topic is aimed at advancing econometric methods for analyzing models that imply multi-period conditional moment restrictions. These methods are applied in analyzing the implications of nonlinear asset pricing models. The second topic is to build and test structural models of seasonality. This analysis should enhance our understanding of the sources of the pronounced seasonal components observed in economic time series. The third topic is to extend the class of models of durable goods pricing and analyze the quantitative implications of these models. Particular attention is focused on models in which the distribution of durable goods influences asset prices. The fourth topic is to develop econometric methods for analyzing continuous time models of fluctuations and asset prices. Among other things, these methods and models aid our understanding of lumpy information flows and the interaction between aggregation- over-time in measured consumption and local durability in preferences.
