DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these...

DSGE models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of introducing nonfundamental shocks for the estimation of DSGE model parameters and propose a method to select the structural shocks driving...

What are the drivers of business cycle fluctuations? And how many are there? By documenting strong and predictable co-movement of real variables during the business cycle in a sample of advanced economies, we argue that most business cycle fluctuations a re d riven b y o ne major factor. The...

DSGE models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of introducing nonfundamental shocks for the estimation of DSGE model parameters and propose a method to select the structural shocks driving...

DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are \non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these...

DSGE models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of introducing nonfundamental shocks for the estimation of DSGE model parameters and propose a method to select the structural shocks driving...

We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. Observational equivalence, partial and weak identification problems are...

We propose two methods to choose the variables to be used in the estimation of the structural parameters of a singular DSGE model. The first selects the vector of observables that optimizes parameter identification; the second the vector that minimizes the informational discrepancy between the...

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature...

We investigate identification issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model-based impulse responses. Observational equivalence, partial and weak identification problems are...