Research Publication

An extensive literature in macroeconomics and public finance uses dynamic stochastic general equilibrium models to study consumption, savings, capital accumulation, and asset pricing and to analyze alternative policies. Except for a few special cases, the economies studied cannot be analyzed using “paper and pencil” style analysis. It is often difficult to produce general theorems that are true for all parameter values of dynamic general equilibrium models. This is a general feature of nonlinear dynamic models in economics as well as in the physical sciences. For such models, knowing which parameters govern behavior is essential for understanding their empirical content and for providing quantitative answers to policy questions. For the numerical output of a dynamic equilibrium model to be interesting, the inputs need to be justified as empirically relevant. There are two sources of information that are commonly used in rationalizing parameter values. One is the behavior of time series averages of levels or ratios of key variables. These time series averages are often matched to the steady state implications of versions of the models that abstract from uncertainty. The other input is from microeconomic evidence. In this essay we discuss the use of evidence from both sources, concentrating mostly on microeconomic evidence. See King and Rebelo (1998) and Taylor (1998) for extensive discussions of calibrating real business cycle and staggered contract models, respectively.