This article provides new insights into the cyclical behavior of consumer and producer real wages in the USA and Germany. We apply two methods for the estimation of the cyclical components from the data: the approach based on the structural time series models and the ARIMA-model-based approach combined with the canonical decomposition and a band-pass filter. We examine the extracted cycles drawing on two wavelet concepts: wavelet coherence and wavelet phase angle. In contrast to the analysis in the time or frequency domains, wavelet analysis allows for the identification of possible changes in cyclical patterns over time.