Working Paper: CEPR ID: DP18033
Authors: Simon Smith; Allan Timmermann; Jonathan Wright
Abstract: We revisit time-variation in the Phillips curve, applying new Bayesian panel methods with breakpoints to US and European Union disaggregate data. Our approach allows us to accurately estimate both the number and timing of breaks in the Phillips curve. It further allows us to determine the existence of clusters of industries, cities, or countries whose Phillips curves display similar patterns of instability and to examine lead-lag patterns in how individual inflation series change. We find evidence of a marked flattening in the Phillips curves for US sectoral data and among EU countries, particularly poorer ones. Conversely, evidence of a flattening is weaker for MSA-level data and for the wage Phillips curve. US regional data and EU data point to a kink in the price Phillips curve which remains relatively steep when the economy is running hot.
Keywords: Phillips Curve; Unemployment; Panel Data; Structural Breaks; Bayesian Analysis
JEL Codes: C11; C22; E51; E52
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| inflationary expectations and wage indexation (E31) | inflation dynamics (E31) |
| increased import penetration from China (F69) | weakening relationship between inflation and unemployment (E31) |
| declining unionization (J50) | weakening relationship between inflation and unemployment (E31) |
| trade (F19) | inflation dynamics (E31) |
| inflation dynamics (E31) | Phillips curve steepness (E31) |
| Phillips curve steepness (E31) | unemployment (J64) |