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Compiled from the Foundation for the Study of Cycles archive (Cycles Magazine, vols. 1950–1957)

Who He Was, According to the Archive

The archive gives Beveridge slightly more formal treatment than it gave Brunt — he's consistently referred to by his full title, "Sir William H. Beveridge," with a proper citation to his 1922 paper. But as with Brunt, the magazine offers no biographical detail beyond that: no dates, no institutional affiliation, nothing about his career outside this one body of work. He appears purely as the author of a single, monumental statistical study.

Note for verification: the magazine's silence on his biography means anything beyond what's below (his career, his other work, his life dates) is not sourced from these volumes and should be checked independently if you want to include it in your forum post.

The Core Work

Beveridge's contribution, as the Foundation describes it, was:

"Wheat Prices and Rainfall in Western Europe," Journal, Royal Astronomical Society, 85:412-78, London, 1922.

The 1953 volume gives the fullest description of the study's scale and method:

"One of the difficult pieces of work in the history of periodogram analysis was accomplished by Sir William H. Beveridge, to determine whether or not there were permanent cycles in wheat prices in Eastern and Western Europe. In view of the fact that England was for centuries a free-trade country, its wheat prices could be expected to run in consonance with those of the Continent. Sir William used index numbers so constructed that the upward leap in prices during the transition from medieval to modern times was removed, subjecting them to harmonic analysis over a range of approximately 900 years."

That figure is worth sitting with: 900 years of price data, harmonically analyzed by hand (this was 1922 — decades before any kind of computing assistance). Elsewhere the magazine specifies the working range more precisely as wheat prices in Europe from 1500 to 1869 — with Beveridge drawing on "a large number of tables of prices from nearly fifty places in six regions": Scotland and England, the Low Countries, France, North Germany, South Germany, and Austria, each region weighted equally.

What He Found

Beveridge's results, as summarized by the Foundation, were extraordinarily rich — almost too rich:

"The number of cycles is astonishing, but some of the longer ones may be combinations of short ones. Two cycles, with lengths of about 5 and 35 years, stand out strongly both in the price of wheat and in various weather records. Seven, with lengths of 5.7, 9.8, 12.8, 15.2, 19.9, 54.0, and 68.0 are about as strong as the first two in prices, but appear only faintly or not at all in the weather. Six more are mildly evident in both prices and weather, and hints of others are indicated by fine dotted lines."

A few specific cycle lengths recur throughout the archive as touchstones:

  • ~54 years — found "without correlation" to any known weather rhythm, this cycle stood out as a significant concentration of energy in Beveridge's data on its own terms. The Foundation connects this independently to a 54-year wave they trace in U.S. commodity prices back to 1790, and to what some observers dubbed a recurring "war cycle" (each ~54-year peak roughly coinciding with a major American war).

  • ~7.42 years — a minor cycle, closely bracketing Brunt's 7.50-year figure and Gillette's 7.47-year figure, treated by the Foundation as a significant three-way convergence across independent researchers and datasets.

  • ~9.75 years — in a later (1956) piece structured as a dialogue, Dewey notes that Beveridge's European wheat data showed a 9.75-year cycle, distinct from and unconnected to a 9.3-year cycle Dewey found in U.S. wheat prices — an interesting divergence rather than an agreement, worth noting since not every comparison in the archive lines up neatly.

Cross-Validation: Beveridge and Brunt Side by Side

The Foundation's December 1953 report includes what's probably the single most important piece of comparative work in the archive involving Beveridge: Figure 57, a direct visual comparison of Beveridge's wheat-price cycles against Brunt's independently-derived weather cycles. The write-up is explicit about the method and the payoff:

"The right-hand side of Figure 57 compares Beveridge's cycles with those found by Brunt in an elaborate harmonic analysis of rainfall, temperature, and atmospheric pressure in twelve European cities... The most obvious approaches to agreement between Beveridge and Brunt fall near 3½, 5, 8, 9½, and 35 years."

This is the crux of why the Foundation valued Beveridge so highly: an economist working from price ledgers and a meteorologist working from weather station records, using completely independent data, converged on strikingly similar cycle lengths. To Dewey and his colleagues, that kind of cross-domain agreement was the strongest available evidence that these weren't statistical artifacts.

A Third Voice: H. W. Clough's Corroboration

A 1953 letter to the magazine from H. W. Clough (identified as a former Meteorologist for the U.S. Weather Bureau) adds a third independent line of evidence, tracing the same wheat-price cycle back even further:

"Bruckner, in 1890, published his researches on a 35-year cycle in the temperature and rainfall of western Europe... Beveridge, in 1922, Jour. Roy. Stat. Society, gave a periodogram of wheat prices in England from 1500 to 1870, showing a period of considerable amplitude at 35.5 years."

Clough goes on to describe his own 1905 and 1939 papers extending this line of research, arriving at cycle lengths of 36.5 and 37 years respectively — all clustering around the same neighborhood as Beveridge's 35.5-year figure. This kind of layered corroboration, spanning Brückner (1890) → Beveridge (1922) → Clough (1905, 1939), is a good illustration of how this small community of researchers kept rediscovering and refining each other's results over six decades, often without much interdisciplinary contact.

Why He Mattered to the Foundation

Dewey's team treated Beveridge the same way they treated Brunt: not as a source of cycle theory, but as an independent, rigorous data source against which theirs and others' findings could be tested. The scale of his underlying dataset (900 years, fifty locations, six regions) made him one of the most heavily-cited authorities in the entire archive for pre-20th-century economic cycle data — arguably second only to Brunt in how often he's invoked as a cross-check.

Suggested Forum Angle

Given how directly Beveridge and Brunt cross-reference each other in Figure 57, it might work well to present them as a pair on your forum — the economist and the meteorologist, working independently in the 1920s, converging on nearly the same set of cycle lengths from completely different kinds of records. That convergence, more than either man's individual biography, seems to be the real story the Foundation was trying to tell.

 

]]> Commodities RayTomes https://cyclesresearchinstitute.org/community/commodities/sir-william-beveridge-and-wheat-price-cycles/ Commodities https://cyclesresearchinstitute.org/community/commodities/commodities/ Sat, 18 Jul 2026 21:24:09 +0000 For actual commodity prices or futures and related matters. Please state clearly what commodity and where (exchange etc)

]]> Commodities RayTomes https://cyclesresearchinstitute.org/community/commodities/commodities/ Commodity Price Cycles https://cyclesresearchinstitute.org/community/commodities/commodity-price-cycles/ Sat, 18 Jul 2026 05:24:54 +0000 Commodity Price Cycles

First published: 2023

Brief summary

World Bank working paper using a dynamic factor model on 39 commodity prices (1970-2019) to separate common global cyclical components from idiosyncratic disturbances, examining both the long-term commodity supercycle and shorter-term cycles within it.

Article

Commodity Price Cycles is a peer-reviewed working paper published by World Bank Policy Research Working Paper in 2023. It focuses on world Bank working paper using a dynamic factor model on 39 commodity prices (1970-2019) to separate common global cyclical components from idiosyncratic disturbances, examining both the long-term commodity supercycle and shorter-term cycles within it.

The data source is panel of 39 commodity prices, monthly 1970:01-2019:12. It also considers dynamic factor model separates common global/group cyclical factors from idiosyncratic price movements. The study references the 2000-2014 commodity supercycle. This gives the cycle claim a specific numerical and evidential setting rather than presenting periodicity only as a visual impression.

The paper addresses these questions with a two-step approach employing a dynamic factor model to estimate common global and group components alongside idiosyncratic disturbances in a panel of 39 commodity prices from 1970 to 2019. The interpretation is strongest when it survives detrending, structural-break tests, changing market composition and out-of-sample validation.

For cycles researchers, the article brings together commodity price cycles, dynamic factor model, commodity supercycle, global price factors. It is relevant to commodity-cycle research because long waves, business-cycle components and structural breaks can overlap in price records.

Because it is a peer-reviewed working paper, the article is a strong starting point for discussion in the Commodities forum, although its conclusions should still be compared with later replications and updated datasets.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/commodity-price-cycles/ Breaks, Trends and Correlations in Commodity Prices in the Very Long-Run https://cyclesresearchinstitute.org/community/commodities/breaks-trends-and-correlations-in-commodity-prices-in-the-very-long-run/ Sat, 18 Jul 2026 05:24:52 +0000 Breaks, Trends and Correlations in Commodity Prices in the Very Long-Run

First published: 2022

Brief summary

Analysis of a 700-year historical commodity price dataset (eight agricultural and industrial commodities) finds a mean periodicity of commodity cycles ranging between 30 and 35 years, alongside major structural breaks tied to historical events.

Article

Breaks, Trends and Correlations in Commodity Prices in the Very Long-Run is a peer-reviewed journal article published by Energy Economics (ScienceDirect) in 2022. It analyses a 700-year historical commodity price dataset (eight agricultural and industrial commodities) and finds a mean periodicity of commodity cycles ranging between 30 and 35 years, alongside major structural breaks tied to historical events.

The analysis focuses on mean 30-35 years. The data source is historical commodity price data spanning over 700 years across eight agricultural and industrial commodities. This gives the cycle claim a specific numerical and evidential setting rather than presenting periodicity only as a visual impression.

The authors report that three quarters of the commodity prices contain a unit root and that mean periodicity of cycles range between 30 and 35 years, depending on the commodity, using a historical commodity price data set spanning over 700 years. The interpretation is strongest when it survives detrending, structural-break tests, changing market composition and out-of-sample validation.

For cycles researchers, the article brings together commodity price cycles, long-run prices, 30–35-year periodicity, structural breaks. It is relevant to commodity-cycle research because long waves, business-cycle components and structural breaks can overlap in price records.

Because it is a peer-reviewed journal article, the article is a strong starting point for discussion in the Commodities forum, although its conclusions should still be compared with later replications and updated datasets.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/breaks-trends-and-correlations-in-commodity-prices-in-the-very-long-run/ Understanding Fluctuations Through Multivariate Circulant Singular Spectrum Analysis https://cyclesresearchinstitute.org/community/commodities/understanding-fluctuations-through-multivariate-circulant-singular-spectrum-analysis/ Sat, 18 Jul 2026 05:24:50 +0000 Understanding Fluctuations Through Multivariate Circulant Singular Spectrum Analysis

First published: 2020

Brief summary

Applies multivariate circulant singular spectrum analysis to a panel of energy commodity prices (oil, natural gas, coal, propane), identifying a dominant 96-month (8-year) common cycle explaining over 20% of shared variability across commodities.

Article

Understanding Fluctuations Through Multivariate Circulant Singular Spectrum Analysis is a preprint published by arXiv in 2020. It applies multivariate circulant singular spectrum analysis to a panel of energy commodity prices (oil, natural gas, coal, propane), identifying a dominant 96-month (8-year) common cycle explaining over 20% of shared variability across commodities.

The analysis focuses on 96 months (8 years), explaining 20.3% of variability. The data source is panel of oil (Brent, Dubai, WTI), natural gas (Europe, US, Japan), coal (Australia, South Africa) and propane price series. 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: The second component in terms of relevance is the 96-month, 8-year, cycle. Within the 20.3% of variability explained by this cycle, it is mainly described by co-movement of oil prices with European natural gas, while coal and propane show distinct phase relationships. The interpretation is strongest when it survives detrending, structural-break tests, changing market composition and out-of-sample validation.

For cycles researchers, the article brings together singular spectrum analysis, energy commodities, 8-year cycle, commodity co-movement. It is relevant to commodity-cycle research because long waves, business-cycle components and structural breaks can overlap in price records.

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

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/understanding-fluctuations-through-multivariate-circulant-singular-spectrum-analysis/ Does the Commodity Super Cycle Matter? https://cyclesresearchinstitute.org/community/commodities/does-the-commodity-super-cycle-matter/ Sat, 18 Jul 2026 05:24:48 +0000 Does the Commodity Super Cycle Matter?

First published: 2020

Brief summary

NBER working paper documenting that world commodity prices display long cycles with a periodicity of 20 to 30 years, termed commodity price 'super cycles', and estimates their importance for economic activity across 24 economies.

Article

Does the Commodity Super Cycle Matter? is a peer-reviewed working paper published by National Bureau of Economic Research (NBER) in 2020. It focuses on NBER working paper documenting that world commodity prices display long cycles with a periodicity of 20 to 30 years, termed commodity price 'super cycles', and estimates their importance for economic activity across 24 economies.

The analysis focuses on 20-30 years (commodity price super cycles). The data source is World Bank Commodity Price database (Pink Sheet) and Global Financial Data, quarterly 1960Q1-2018Q4 across 24 economies. 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: World commodity prices are known to display long cycles. These cycles have a periodicity of 20 to 30 years and are called commodity price super cycles, though less work has been devoted to estimating the importance of these cycles for economic activity. The interpretation is strongest when it survives detrending, structural-break tests, changing market composition and out-of-sample validation.

For cycles researchers, the article brings together commodity supercycle, 20–30-year cycle, world commodity prices, economic activity. It is relevant to commodity-cycle research because long waves, business-cycle components and structural breaks can overlap in price records.

Because it is a peer-reviewed working paper, the article is a strong starting point for discussion in the Commodities forum, although its conclusions should still be compared with later replications and updated datasets.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/does-the-commodity-super-cycle-matter/ Super-Cycles of Commodity Prices Since the Mid-Nineteenth Century https://cyclesresearchinstitute.org/community/commodities/super-cycles-of-commodity-prices-since-the-mid-nineteenth-century/ Sat, 18 Jul 2026 05:24:47 +0000 Super-Cycles of Commodity Prices Since the Mid-Nineteenth Century

First published: 2013

Brief summary

Applies a band-pass filter approach, grounded in spectral analysis theory, to decompose 150+ years of real commodity price data into cyclical components, identifying long-run 'super-cycles' distinct from shorter business-cycle fluctuations.

Article

Super-Cycles of Commodity Prices Since the Mid-Nineteenth Century is a peer-reviewed journal article published by World Development (ScienceDirect) in 2013. It applies a band-pass filter approach, grounded in spectral analysis theory, to decompose 150+ years of real commodity price data into cyclical components, identifying long-run 'super-cycles' distinct from shorter business-cycle fluctuations.

The method uses uses band-pass (BP) filter to decompose commodity price time series into cyclical components across a range of periodicities/frequencies. The data source is real commodity prices since the mid-19th century. 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: Recent statistical decomposition techniques focused on filtering methods are particularly useful in identifying super-cycles; the band-pass filter approach allows economic time series to be decomposed into cyclical components of a range of periodicities. The interpretation is strongest when it survives detrending, structural-break tests, changing market composition and out-of-sample validation.

For cycles researchers, the article brings together commodity supercycles, long-run commodity prices, band-pass filter, price cycles. It is relevant to commodity-cycle research because long waves, business-cycle components and structural breaks can overlap in price records.

Because it is a peer-reviewed journal article, the article is a strong starting point for discussion in the Commodities forum, although its conclusions should still be compared with later replications and updated datasets.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/super-cycles-of-commodity-prices-since-the-mid-nineteenth-century/ Cycles Index: wheat, cotton and commodity cycles https://cyclesresearchinstitute.org/community/commodities/cycles-index-wheat-cotton-and-commodity-cycles/ Sat, 18 Jul 2026 05:03:26 +0000 Cycles Index: wheat, cotton and commodity cycles

First published: 2004

Brief summary

CRI’s cycle index includes wheat prices, cotton production, cotton prices, cattle, coal and other commodity cycles.

Article

9.6- (9 2/3-) year cycle wheat acreage harvested; 95-96; 106

9.6- (9 2/3-) year cycle wheat acreage planted; 95; 106

18.33- (18 1/3)- year cycle wheat acreage; 345; 349; 444; 611

10-12-year cycle wheat and barley bumper crops; 266

32.82-month (2.735-year) cycle wheat price index; 731; 734

Additional summary

The index continues with many commodity entries, including cotton production and prices, coal production and consumption, cattle cycles and food-related series.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/cycles-index-wheat-cotton-and-commodity-cycles/ A 5.54 year cycle in Oil Prices https://cyclesresearchinstitute.org/community/commodities/a-5-54-year-cycle-in-oil-prices/ Sat, 18 Jul 2026 05:03:25 +0000 A 5.54 year cycle in Oil Prices

First published: 2005

Brief summary

CRI PDF by Ray Tomes on a proposed 5.54-year cycle in oil prices.

Article

A 5.54 year cycle in Oil Prices

By Ray Tomes Cycles Research Institute November 2005

In the 1940s, 1970s and 2000s the price of oil was unstable and rapidly rising. Between these periods it was more steady with fluctuations both up and down. These three eras are the same times that the USA was involved in expensive wars – WW II, Vietnam and Iraq, and it is natural to consider that there is a relation between the oil price increases and weakness in the US dollar.

The possibility of an increase to the general region of $300 per barrel between now and mid 2013 cannot be dismissed as fanciful.

Additional summary

The remainder argues that a 5.54-year cycle is dominant in oil prices and compares it with other cycles reported in wheat prices, stock prices and other series.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/a-5-54-year-cycle-in-oil-prices/ Baltic Exchange Market Information https://cyclesresearchinstitute.org/community/commodities/baltic-exchange-market-information/ Sat, 18 Jul 2026 04:58:07 +0000 Baltic Exchange Market Information

First published: 2016

Brief summary

Freight indices useful for shipping and commodity cycles.

Article

The Baltic Exchange produces freight-market assessments and indices based on rates reported by participating shipbrokers. Its measures cover dry bulk, tanker, gas and container shipping routes and vessel classes.

The Baltic Dry Index combines selected dry-bulk freight assessments and is often used as an indicator of conditions in the market for transporting commodities such as iron ore, coal and grain. It is a freight-rate index, not a direct measure of commodity prices or world trade volume.

Shipping rates respond to cargo demand, vessel supply, fuel costs, port congestion, route disruptions and the geographic distribution of trade. Because ships take time to build, changes in fleet capacity can contribute to pronounced market expansions and contractions.

Index composition and calculation methods can change, and some detailed data require a subscription. Historical analysis should document the specific index, route definitions, vessel assumptions and any methodological breaks.

Source details and credits

]]> Commodities CRI https://cyclesresearchinstitute.org/community/commodities/baltic-exchange-market-information/