Spatial aggregation bias in wage curve and NAWRU estimation

Arbeitspapier

I argue in this paper that the estimation of wage curves and NAWRUs at the country level suffers from spatial aggregation bias. Using European data for the years 2000-2017, I find steeper country level wage curves and higher NAWRUs, compared to estimating at the underlying regional level. The distribution of regional unemployment rates within countries over time is not mean-scaled. Regions with low unemployment rates are the main drivers of changes in aggregate unemployment. The steepness of a log-linear wage curve in regions with low unemployment dominates at the aggregate (country) level, overestimating wage pressure. Lagged wages are important in explaining wage growth, together with unemployment. This suggests that a wage curve fits the data better than the assumption of a NAWRU or long run natural rate of unemployment. With regional wage curves, spatial aggregation bias can produce aggregate data that resembles such a natural rate of unemployment, however.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: JRC Working Papers on Territorial Modelling and Analysis ; No. 02/2020

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Wages, Compensation, and Labor Costs: General ; Labor Contracts ; Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
• Thema: Region ; Growth ; Unemployment ; NAWRU ; NAIRU ; Wage Curve ; Labor markets

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Persyn, Damiaan
• Ereignis: Veröffentlichung
• (wer): European Commission, Joint Research Centre (JRC)
• (wo): Seville
• (wann): 2020

Weitere Informationen

• Handle: http://hdl.handle.net/10419/227682
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ