Estimating Unobservable Inflation Expectations in the New Keynesian Phillips Curve

Francesca Rondina

doi:10.3390/econometrics6010006

Abstract

This paper uses an econometric model and Bayesian estimation to reverse engineer the path of inflation expectations implied by the New Keynesian Phillips Curve and the data. The estimated expectations roughly track the patterns of a number of common measures of expected inflation available from surveys or computed from financial data. In particular, they exhibit the strongest correlation with the inflation forecasts of the respondents in the University of Michigan Survey of Consumers. The estimated model also shows evidence of the anchoring of long run inflation expectations to a value that is in the range of the target inflation rate.

Highlights

Expectations about future values of inflation and other economic variables play a central role in macroeconomic models
Another approach, which has become increasingly common in recent years, is to use survey data, or other measures that can be extracted from the observable data, as a proxy for expectations
This paper employed an econometric model to estimate the model-consistent path of inflation expectations emerging from the New Keynesian Phillips Curve (NKPC) and the data

Summary

Introduction

Expectations about future values of inflation and other economic variables play a central role in macroeconomic models. It is not surprising that the question of how to measure expectations has been at the center of a long stream of research in empirical macroeconomics One branch of this literature, which builds upon the original work of McCallum (1976), has focused on the development of econometric-based measures that can be employed to approximate expectations in the models to be estimated. Another approach, which has become increasingly common in recent years, is to use survey data, or other measures that can be extracted from the observable data, as a proxy for expectations

Methods

Results

Conclusion