This paper examines the quantitative importance of temporal aggregation bias in distorting parameter estimates and hypothesis tests. Our strategy is to consider two empirical examples in which temporal aggregation bias has the potential to account for results which are widely viewed as being...

I present an undetermined coefficients method for obtaining a linear approximating to the solution of a dynamic, rational expectations model. I also show how that solution can be used to compute the model's implications for impulse response functions and for second moments.

We investigate, by Monte Carlo methods, the finite sample properties of GMM procedures for conducting inference about statistics that are of interest in the business cycle literature. These statistics include the second moments of data filtered using the first difference and Hodrick-Prescott...

'No.' So says one model that is broadly consistent with postwar U.S. seasonal and business cycle data.

We describe and compare several algorithms for approximating the solution to a model in" which inequality constraints occasionally bind. Their performance is evaluated and compared" using various parameterizations of the one sector growth model with irreversible investment. We" develop...

This paper assesses the small sample properties of Generalized Method of Moments (GMM) based Wald statistics. The analysis is conducted assuming that the data generating process corresponds to (i) a simple vector white noise process and (ii) an equilibrium business cycle model. Our key findings...