Real wages and the cycle: the view from the frequency domain
In the time domain, the observed cyclical behavior of the real wage hides a range of economic influences that give rise to cycles of differing lengths and amplitudes. This may serve to produce a distorted picture of wage cyclicality. Here, we employ frequency domain methods that allow us decompose wages into cyclical components and to assess the relative contribution of each component. These are discussed in relation to wages alone (the univariate case) and to wages in relation to production or employment-based measures of the cycle (multivariate). In the multivariate dimension, we derive methods for determining whether (i) wage and business cycles cohere (ii) lead-lag or contemporaneous relationships exist and (iii) the degree of coherency between wage and business cycles is time dependent. We establish that real wages are strongly procyclical and that the business cycle is the dominant associated influence.
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3-5 years Kitchin 7-10 years Juglar A-Changin A/Cp A/Pp W/Cp A/Pp W/Cp W/Pp acyclical amplitude Appendix A.4 association Augurzky C. M. Schmidt average hourly earnings B. M.S. van Praag BKM Filter Boeri business cycle co-movements confidence interval consumer price index contemporaneous correlation countercyclical Critical Values cycle length cycle measure cyclical behavior D. A. Cobb-Clark decompose decomposition Difference filter dominant cycle Dustmann earnings excluding overtime employment employment-based measure Explained Variance Ferrer-i-Carbonell Figure Fourier transform frequency by frequency frequency domain G. A. Pfann Hodrick-Prescott filter hourly earnings excluding Immigrant industrial production Juglar cycle Kitchin cycle labor economics Labor Market lead-lag relationship linear Modified Baxter-King Filter multivariate observed cyclical Optimal Migration Duration output overall variance parameters peak-to-peak periodogram phase shift phase spectrum procyclical producer price index production-based real wage Rosholm Section series Xt total variance univariate University of Stirling variable W/Cp W/Pp A/Cp W/Pp A/Cp A/Pp wave Woitek