Gross job flows dynamics, defined as the behavior of creation and destruction of jobs at the establishment level, has become a topic of great interest in economics during recent years and researchers have resorted to different empirical methodologies in order to tease out its causes and consequences, as well as its connections to overall economic activity. In this context, my dissertation attempts to contribute to the debate by advancing the usefulness of frequency-domain techniques. I emphasize not only the relevance of the economic questions being examined, but also the unique perspective that frequency-domain techniques can provide. There are three major questions I pursue. The first is why equilibrium search models of labor market frictions have trouble explaining the observed persistence in employment fluctuations. I implement a frequency-domain decomposition of the employment growth rate to isolate the contributions coming from the job creation spectrum, the job destruction spectrum, and the cross-spectrum between the two. Among other results, I show that the failure to generate a negative contemporaneous correlation between job creation and job destruction at business cycle frequencies is behind the inability of the Mortensen-Pissarides (1994) canonical model to reproduce the empirical spectral shape of the employment growth series. The second question I tackle relates to the direction of causality between aggregate employment fluctuations and gross job reallocation. Recent macroeconomic models suggest an active role for reallocation dynamics over the business cycle, and my results can be interpreted as supporting evidence that such a role indeed exists, but at a low frequency range. The basic idea is to look for different causality relationships at different time-scales by combining wavelet techniques with a standard Granger causality test. Finally, the third question I address investigates the connections between labor productivity growth and the frequency content of the job reallocation series for four-digit level US manufacturing industries. My results indicate that industries with relatively more influential low frequencies display inferior productivity growth. I relate these findings to the literature and propose a simple theoretical model to explain them.