It is challenging to elucidate the extrinsic effects of social, economic , policy or other substantive changes on the dynamics of  US drug approvals. Here, a novel approach, termed the Chronological Hurst Exponent (CHE), is proposed, which hypothesizes that changes in intrinsic long-range memory latent within the dynamics of time series data may be temporally associated with extrinsic variables . Using the monthly number  FDA Center for Drug Evaluation and Research (CDER) approvals from 1939 to 2019 as the data source, it is demonstrated that US approvals are found to have a distinct S-shaped (trichotomized) long-range CHE structure : an 8-year (1939-1947) Stagnated (random; H of 0.5) , a 27-year (1947-1974) Emergent (time-varying persistent; H between 0.5 and 0.9), and the 45-year (1974-2019) Saturated (persistent; H of 1) US Approvals Hurst Cycles . Further, dominant periodicities (resolved via wavelet analyses) are identified in the Saturated Period at 17, 8 and 4 years; thus, US Approvals have been following a Juglar/Kuznet mid-term cycle with Kitchin-like bursts. This work suggests that (1) macro-factors in the Emergent Period  have led to persistent growth in US  approvals enjoyed since 1974, (2) the CHE may be a valued method to explore the constancy of extrinsic pressures on time series data, and (3) adds further evidence that innovation-related economic cycles exist (as supported via the proxy metric of US drug approvals).
It is challenging to elucidate the effects of changes in external influences (such as economic or policy) on the rate of US drug approvals. Here, a novel approach, termed the Chronological Hurst Exponent (CHE), is proposed, which hypothesizes that changes in the long-range memory latent within the dynamics of time series data may be temporally associated with changes in such influences . Using the monthly number the FDA Center for Drug Evaluation and Research (CDER) approvals from 1939 to 2019 as the data source, it is demonstrated that the CHE has a distinct S-shaped structure demarcated by an 8-year (1939-1947) Stagnation Period , a 27-year (1947-1974) Emergent (time-varying Period, and a 45-year (1974-2019) Saturation Period . Further, dominant periodicities (resolved via wavelet analyses) are identified during the most recent 45-year CHE Saturation Period at 17, 8 and 4 years; thus, US drug approvals have been following a Juglar-Kuznet mid-term cycle with Kitchin-like bursts. As discussed, this work suggests that (1) changes in extrinsic factors (e.g., of economic and/or policy origin ) during the Emergent Period may have led to persistent growth in US drug approvals enjoyed since 1974, (2) the CHE may be a valued method to explore influences on time series data, and (3) innovation-related economic cycles exist (as viewed via the proxy metric of US drug approvals).
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(trichotomized) long-range CHE structure :
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