A Hard-Science Approach to Kondratieff's Economic Cycle (Homicides section)
First published: 2024
Brief summary
Applies a physics-style periodic-signal approach to social data, finding US homicide rates correlate strongly (r=0.87) with a 54-year sine wave, peaking during declining phases of the long Kondratieff economic cycle.
Article
A Hard-Science Approach to Kondratieff's Economic Cycle (Homicides section) is a preprint published by arXiv in 2024. It applies a physics-style periodic-signal approach to social data, finding US homicide rates correlate strongly (r=0.87) with a 54-year sine wave, peaking during declining phases of the long Kondratieff economic cycle.
The analysis focuses on 54 years (homicide rate cycle), correlation r=0.87 with fitted sine wave. The data source is US Census Bureau Statistical Abstract and FBI Crime in the United States, 5-year sampling through 2014. This gives the cycle claim a specific numerical and evidential setting rather than presenting periodicity only as a visual impression.
The article reports the following result: Homicides in the U.S. rise and fall periodically with no particular trend; the correlation with a regular sine wave of 54-year period is r = 0.87, with homicides peaking during the declining phases of the Kondratieff cycle. The interpretation is strongest when it survives detrending, autocorrelation controls, structural-break tests and comparison with stochastic or random-walk alternatives.
For cycles researchers, the article brings together homicide cycles, kondratieff cycle, 54-year sine wave, social periodicity. It is relevant to social-cycle research because apparent waves in historical or behavioural data must be separated from seasonality, autocorrelation, structural change and random walks.
Because it is a preprint, the work should be read alongside later peer-reviewed publications and independent replications. It remains useful because the proposed cycle, dataset and analytical approach are stated clearly enough to be scrutinised.
Source details and credits
- Source / publisher: arXiv
- Source type: Preprint
- URL type: PDF
- Credits: arXiv
- URL: https://arxiv.org/pdf/2410.05285