Working Paper: NBER ID: w19693
Authors: S. Boraan Aruoba; Luigi Bocola; Frank Schorfheide
Abstract: We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional heteroskedasticity. We estimate a DSGE model with asymmetric wage/price adjustment costs and use predictive checks to assess its ability to account for nonlinearities. While it is able to match the nonlinear inflation and wage dynamics, thanks to the estimated downward wage/price rigidities, these do not spill over to output growth or the interest rate.
Keywords: No keywords provided
JEL Codes: C11; C32; C52; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| QAR models (C32) | nonlinear conditional mean dynamics of US output growth (C22) |
| QAR models (C32) | nonlinear conditional mean dynamics of inflation (C22) |
| QAR models (C32) | nonlinear conditional mean dynamics of nominal wage growth (C22) |
| QAR models (C32) | nonlinear conditional mean dynamics of interest rates (C22) |
| asymmetric wage-price adjustment costs (F16) | nonlinear inflation dynamics (E31) |
| asymmetric wage-price adjustment costs (F16) | nonlinear wage dynamics (J39) |
| asymmetric wage-price adjustment costs (F16) | output growth (O40) |
| asymmetric wage-price adjustment costs (F16) | federal funds rate (E52) |
| DSGE model (E13) | nonlinearities in GDP growth (O49) |
| DSGE model (E13) | nonlinearities in interest rates (E43) |