Spatial aggregation bias in wage curve and NAWRU estimation

Damiaan Persyn

No 2020-02, JRC Working Papers on Territorial Modelling and Analysis from Joint Research Centre

Abstract: 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.

Keywords: Region; Growth; Unemployment; NAWRU; NAIRU; Wage Curve; Labor markets. (search for similar items in EconPapers)
JEL-codes: J30 J41 R23 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2020-04
New Economics Papers: this item is included in nep-lma and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:ipt:termod:202002

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