Economic resonance frequency - Fourier analysis

The Fourier transform is computed using the Fast Fourier Transform (FFT) algorithm. The amplitude spectrum is plotted, showing the amplitudes of different frequency components present in the growth data. Peaks in the amplitude spectrum represent dominant frequencies, indicating the frequencies at which the growth data responds most efficiently to regulatory changes.

The red circles mark the identified peaks in the amplitude spectrum, representing the dominant frequencies. Interpretation: The visualizations provide insights into the frequency characteristics of historical growth data for economic sectors. By analyzing the dominant frequencies identified through Fourier analysis, policymakers and analysts can gain a better understanding of the frequencies at which economic sectors respond most efficiently to regulatory adjustments.

This information can inform decision-making processes aimed at optimizing regulatory changes to promote economic growth and stability. In summary, the script facilitates the analysis of historical growth data for economic sectors through Fourier analysis, offering valuable insights into the frequency dynamics and Economic Resonance Frequency (ERF) of the simulated data.