Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/82405 
Authors: 
Year of Publication: 
2003
Series/Report no.: 
Sveriges Riksbank Working Paper Series No. 158
Publisher: 
Sveriges Riksbank, Stockholm
Abstract: 
The purpose of this study is to investigate if the wage setting in certain sectors of the Swedish economy influences the wage setting in other sectors. The theoretical background is the Scandinavian model of inflation, which states that the wage setting in the sectors exposed to international competition should influence the wage setting in the sheltered sectors of the economy. The Johansen maximum likelihood cointegration approach is applied to quarterly data on Swedish sector wages for the period 1980:1–2002:2. Different vector error correction (VEC) models are created based on assumptions of which sectors are and which sectors are not exposed to international competition. The wage adaptability between sectors is then tested by imposing restrictions on the estimated VEC models. Finally, Granger causality tests are performed in the different restricted/unrestricted VEC models to test for sector wage leadership. The empirical results indicate large wage adaptability between manufacturing, construction, wholesale and retail trade, the central government sector and the municipalities and county councils sector. This is in line with the assumptions of the Scandinavian model. Furthermore, the empirical results indicate low wage adaptability between the financial sector and manufacturing, and between the financial sector and the two public sectors. The Granger causality tests provide strong evidence of the existence of intersectoral wage causality, but no evidence of a wage leading role in line with the assumptions of the Scandinavian model for any of the sectors.
Subjects: 
Sector wage linkages
Wage leadership
Wage adaptability
Scandinavian model of inflation
Exposed and sheltered sectors
Vector error correction (VEC) models
JEL: 
C32
J30
J51
J52
Document Type: 
Working Paper

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