Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach

Arbeitspapier

The New-Keynesian Phillips curve has recently become an important ingredient in monetary policy models. However, using limited information methods, the empirical support for the New-Keynesian Phillips curve appear to be mixed. This paper argues, by means of Monte Carlo simulations with a simple New-Keynesian sticky price model, that single equations methods, e.g. GMM, are likely to produce imprecise and biased estimates. Then, it is argued that estimating the model with full information maximum likelihood (FIML) is a useful way of obtaining better estimates. Finally, a version of the model used in the Monte Carlo simulations is estimated on U.S. data with FIML and although the pure forward-looking New-Keynesian Phillips curve is rejected, a version with both forward- and backward-looking components provides a reasonable approximation of U.S. inflation dynamics.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Sveriges Riksbank Working Paper Series ; No. 129

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Evaluation, Validation, and Selection ; Monetary Policy
• Subject: Monetary policy rule ; New-Keynesian Phillips curve ; Rational expectations IS-curve ; Backward-looking Phillips curve ; Measurement errors ; Full Information Maximum Likelihood estimation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lindé, Jesper
• Event: Veröffentlichung
• (who): Sveriges Riksbank
• (where): Stockholm
• (when): 2001

Further information

• Handle: http://hdl.handle.net/10419/82401
• Last update: 10.03.2025, 11:44 AM CET