In an earlier post in my “long waves” series I wrote briefly about the war school and the different theories that existed within it. After this post, I plan mostly to move on from Joshua Goldstein’s 1988 book, Long Cycles: Prosperity and War in the Modern Age. In summary, there are three “war” theories: The leadership cycle school, based on the work of Modelski; the world-system school, led by Wallerstein; and the power transition school, which has emerged from the research of Organski. Goldstein summarises these differences well:

The leadership cycle school focuses on the role of global war in establishing a new international order under a world leader roughly every century. The neo-Marxist world-system school focuses on hegemony and rivalry in the core of the world economy, linking hegemonic cycles to pairs of long waves. The power transition school focuses on changes in national power and their effects on war and hegemony.

The idea of hegemony

The idea of hegemony is central. The core idea of the leadership school, which was influenced by the work of Arnold Toynbee, is that a country will assume leadership of the international economic and monetary system, and in doing so will also carry an “undue share” of the costs involved. The idea is associated with the rise of world trade; Goldstein quotes Kindleberger:

The international economic and monetary system needs leadership, a country which is prepared, consciously or unconsciously, under some system of rules that it has internalized, to set standards of conduct for other countries ; and to seek to get others to follow them, to take on an undue share of the burdens of the system.

Early on, Modelski tried to connect the leadership cycle to economic long waves, but moved away from that. The model here is of century-long cycles, in which a new leader supplants the old one after a war. There is a common thread: the leaders controlled trade through naval power, and, from the Dutch onwards, also led the world in finance. And while leadership follows military victory, it also follows innovation – institutional and political, as well as military. One of the clearest examples can be seen in Britain in the late 17th century, with the political settlement of the 1688 Revolution and the invention of the central bank. It may also be more than a curiosity that Britain co-opted a Dutch king at the time.
And it’s worth noting that there’s some nuance here. Each war was fought against a challenger, which also aspired to hegemony, and these can be identified to some extent in the work of Dehio, who influenced Arnold Toynbee. And actually, it’s a little more complex again: the powers that won each of the wars typically did so in a coalition, and the new challenger usually emerges when the coalition fractures after victory – except in the 18th century.

So: Modelski argues that geopolitical leadership is entwined with economic leadership. Goldstein notes that the basis for this theory is weakened by the way Modelski selected the list of innovations and because his dating of long waves is out of sync with other scholars after 1890. And a sample of five is maybe too small to be wholly convinced of patterns.

The core and the periphery

Modelski’s theory is very much about the leadership of the core, advanced economies, and that’s a good link to the world-system school, which focusses on core/periphery relationships. The work here is principally by Wallerstein and Hopkins, and it connects the “war school” much more explicitly with economic cycles. They argue that long economic waves come in pairs that affect the core and periphery differently.

As with Modelski, the hegemonic power is the leader because it has built significant advantages, in commerce, finance, and production (agricultural and industrial). But there’s still a problem here – as with Modelski’s early work – in linking the economic waves with the leadership waves. And the hegemonic waves look like a better fit with the historical evidence than do the economic waves.

As with Modelski, the emerging hegemonic power builds its power through sea (later sea and air), avoiding the expense of large land-based armies. But eventually, it has to take on the cost of a land army to head off the threat of a land-based challenger. Wallerstein sees three hegemonies, as opposed to Modelski’s five: the Dutch, 1625-72, the British, 1815-73, and the United States, 1945-67. Each fought a thirty year was for superiority, which ended with the large-scale reorganisation of the international order (The Treaty of Westphalia, The Concert of Europe, the United Nations/Bretton Woods.)

Leading edge innovation

Nicole Bousquet, who worked with Wallerstein, argues that the emergence of hegemonic power reflects a short-to-medium term advantage in leading edge innovation, which is eroded as it is is diffused and copied. The seeds of decline come when the hegemonic power looks for incremental innovation in processes that have historically served it well rather than looking for “major changes in the methods of production.” Of course, this is an argument that is common these days in discussions of organisational change.

I’m not going to spend much time here on the third school, the “power transition” group, since much of the thinking behind it appears to be largely empirical, with only a modest causal story behind it. Gilpin suggests that the nation-state behaves “rationally” and that states attempt to change the international system when the perceived benefits to them exceed the perceived costs. Conversely, the system ins stable only when no actor believes this to be the case. Put like this, it seems to be a subset of other theories in that it sees hegemonic wars as the principle driver of change, but with a more limited theory sitting behind it. And the purpose of a good theory is to help us to model the world better.

Looking at evidence

It turns out that there is good data on war, starting with Levy’s taxonomy of 119 wars, published in the early ‘80s. 64 of these are “Great Power” wars. In Chapter 11 Goldstein uses a number of measures to assess the intensity of wars, including the number of battle fatalities, which is an index of severity; the ratio of fatalities to population, an index of intensity; the presence or absence of war in a given year (incidence); and the number of wars of a given type in a given year (frequency).

From the “severity” time series, Goldstein identifies a fifty year cycle of war in which wars typically coincide with the late stages of the upswing, but only every one hundred years do competing great powers take each other on. He hypothesises that this is because war is expensive and you need to build resources to wage it. But there is a bug in this story, which is that the timing of World War II is off; it happens at the end of a downswing. There are two, related ways of looking at this. The first is to say that it is the unfinished version of World War I. The second is to observe that at the start of the 20th century, the core grew, from a European scale to global scale, as Japan, the United States, and, effectively, Russia/USSR were drawn into the core system, and that World War II was part of this adjustment process.

Three eras of war

The second observation is that there are effectively some “super-cycles” running alongside these long war cycles. Goldstein’s analysis of intensity suggests three eras. The first is to 1648, in which Great Power wars fluctuate up and down with around 10,000 casualties per year, and the peaks are identifiable but not truly distinctive. The second, between 1648 and 1815, sees an order of magnitude shift, to a casualty level during Great Power wars that run at about 100,000 a year, with distinctive differences in intensity between Great Power wars and others, and periods of peace afterwards. The third, after 1815, involves less fighting, but with huge, short, peaks, and another jump in the order of magnitude to around two million fatalities per year. As it happens, these three “eras” correspond to Wallerstein’s analysis.

And cutting through his pages of analysis, Goldstein is confident enough of the relationships between the data to argue that wars occur just before the end of an up-cycle, when states are richest. In Chapter 12, he sketches out a causal diagram.

Source: Joshua Goldstein

The argument as to why wars occur at the end of an upswing hangs on three points.

• The biggest wars occur only when the core countries can afford them, which is after a sustained period of stable economic growth (p.261)
• Upswings cause several great powers to grow at the same time, leading to more competition for world resources and markets. The “lateral pressure” increases the propensity towards conflicts between the core countries (p.262)
• Economic growth has a psychological effect on a society, creating a more “gung-ho” social mood. (p.262)

‘Total war’ and after

In practice, of course, wars have a complex impact on society and economy, playing out through taxation, earnings, capital investment, innovation, inflation, and so on. Arguably, the experience of the “total war” of 1939-45, and the development of far more destructive weapons since then, has also changed our view of war as an instrument of hegemonic transition. (Toynbee talked about the social memory of war as influencing future war behaviour). This might be a way of understanding both the heavy social investment in our culture of memory, as the generations that fought the last world war die out, and also the new military doctrines about asymmetric warfare.

More fundamentally, we may be moving (back) to a new era under which our wars are fought on our behalf by mercenaries, and with low casualty rates, as they were in the first of Wallerstein’s three eras.  It is, though, too soon to be sure: if the cyclical theories are right, we are just moving into the foothills of next hegemonic conflict, and will watch them playing out over the next 30 years or so.

In my last post summarising some of the key ideas in Joshua Goldstein’s book on long waves, I looked at the different schools and some of the evidence. In this one, I’m going to look at the model he constructs on the dynamics of a long wave, and its link to innovation. (Discussion of the war school(s) will follow in another post). But I also realise that I haven’t spent enough time on his work on whether long waves or long cycles exist at all. So I’m going to start there.

Collecting evidence

In Chapter 4, Goldstein brings together the long wave dates going back to 1485 from 33 different scholars (I added a 34th from a book published more recently). These are data sets that operate at different scales (e.g. national, regional or continental) with different data (e.g. prices, production) and with very differently levels of granularity. The full dataset included 55 series, as follows:

• Prices: 28 series
• Production: 10 series
• Innovation and invention: 9 series
• Capital investment: 2 series
• Trade: 4 series
• Real wages: 2 series

I’ve reassembled the dates he derives from these into a spreadsheet, which still needs some work to extract the dates as charts. But it does suggest that there is reasonable consistency between the dates of different scholars working in different schools, and that there are reasonable regular cycles of downswing and upswing.

Which isn’t to say that cycles are exactly the same length, or would need to be for the theory to hold. Goldstein quotes Kondratiev, who argued repetition is more important than periodicity.

The “regularity “of long waves should refer not to periodicity but to “the regularity of their repetition in time” and to the international synchrony of different economic series.

Immanuel Wallerstein uses the analogy of breathing:

Physiologists do not argue about whether breathing occurs . Nor do they assume that this regular, repetitive phenomenon is always absolutely identical in form or length. …  [Nonetheless] all animals breathe, repetitively and reasonably regularly.

Testing hypotheses

From this Goldstein found himself able to conclude that long waves do exist. Then, based on the statistical analysis that I touched on briefly, he reviewed the main hypotheses, on the economic factors influencing long waves, of different scholars, looking particularly at hypotheses from different schools or scholars that contradicted each other, and which therefore could not both be true.

The main hypotheses from the different researchers which hold up – I’ve simplified his account in Chapter 10 for the purposes of blogging – are as follows, in bold. The failed hypotheses are in italics:

1. Long waves exist in prices, production, and investment (vs: Long waves exist in prices only)
2. Production increases precede price increases (vs: Production phases are synchronous with price phases.)
3. Innovations cluster at one point on the long wave (vs: Innovations do not occur in clusters.)
4. Innovations cluster late in the downswing (vs: Innovations cluster early in the upswing.)
5. Capital investment increases early in the upswing (vs: Capital investment increases on the downswing.)
6. Long waves do not exist in trade (vs: Long waves exist in world trade.)
7. Long waves exist in wages (vs: Long waves do not exist in wages.)
8. Class struggle peaks late in the upswing (vs: Class struggle peaks late in the downswing.)

Wheels of change

The third step in building up this picture was to look at the leading and lagging indicators of change, which Goldstein portrays as a wheel, a literal cycle.

It’s worth walking through this. The whole cycle is around 50 years, although this should be taken as a guideline rather than a rule. The downswing runs down the right hand side of the wheel, with production hitting a trough at around ten years, and investment at about 15. Because, on his analysis, innovation peaks just ahead of the upswing, we see that peak at around 20 years. After around 25 years, the downswing moves into an upswing (and as discussed in the previous post there are multiple interpretations as to why). The upswing is a mirror image of the downswing; production peaks about ten years into the upswing, with an investment peak following 15 years in, and finally an investment trough just before the upswing runs out of momentum.

The innovation problem

But there’s a problem here. The question of when innovation occurs in the cycle has been central to discussions of long waves, even though the innovation school, descended from Schumpeter through Gerhard Mensch and Christopher Freeman, is only one of three economic schools, as discussed in the previous post. The reason it’s central is because it’s also a question that’s implicit in both the other schools.

If capital investment starts to increase again, why does that happen? Or, looking at it through the lens of the “capitalist crisis” school, how is it that the crisis, which has triggered the downswing, get resolved? The answer, in brief, is that leading edge production becomes reorganised or reinvigorated in some way to improve the returns on investment.

The problem I have with Goldstein’s characterisation of the innovation peak coming five years before the end of the downswing is that it seems too late to permit such reconfiguration; there simply isn’t enough time to do it. It’s worth considering a couple of the dates of the Troughs from Goldstein’s base case to explain what I mean.

The web and the monoplane

The date of the Trough at the end of the last downswing is around 2000 (I’m using Markku Wilenius’ estimate here), so T-5⋍1995. The world wide web might therefore qualify as such an innovation; Tim Berners-Lee had written the code by 1989 (though his first iteration was much earlier) but the first commercial application was by Netscape in 1994, although the available market was tiny (less than 5% of homes in leading markets such as the US and the UK.) The end-date for the previous Trough was 1940, using Goldstein’s base case data, T-5⋍1935. And you can date some significant innovations from this time, such as the monoplane and the television, though again, the initial markets were small.

But all three of these innovations (browser, plane, television) were resting on innovation cycles that started much earlier: the earlier 1970s in the case of Netscape, the early 1900s in the case of the monoplane. It’s the difference between a “follower” technology and a “platform” technology. So it comes down to what type of innovation we’re talking about.

And I think that Goldstein is actually talking about an application, as Drucker would put it; the full set of systems that allow a product or service to start to make a market.

Social institutions

There are a couple of other theories that help to square this particular circle. The first is from the Social Structures of Accumulation [SSA] school, which originates with David Gordon, and is represented now by David Kotz, Terrence McDonough and  Michael Reich. [1] Their edited collection, Social Structures of Accumulation, argues, in summary, that the set of social institutions that support any period of capital accumulation eventually run out of steam, and need to be redesigned or reinvented. As Gordon, Edwards, and Reich argue (p18),

Successful capital accumulation either runs up against limits imposed by the existing institutional structure or begin to destabilise that structure. … (p23) an economy that expands within the same social structure of accumulation is likely to encounter diminishing returns to continual expansion.

Reinvention is a slow process, and it takes time to align the institutions around the new regime of accumulation; the bits of the whole social structure take time to fall into place. However (p22):

“Once installed it pays off over a long period of time.”

New types of abundance

For me, this connects, at least intellectually, with the work of Carlota Perez. Her model describes each wave, or “surge” as made up of two parts: an installation phase, driven by finance capital, and a deployment phase, driven by production capital, separated by a crash. (There’s a fuller explanation here). The engine for the next upturn (deployment) emerges from the end of the previous upturn. Here’s why: as the core technology of a deployment phase saturates its market, returns start to fall, and capital starts moving to new, and more speculative, areas, looking for a better rate of return.

Each of the Perez surges, which map well enough onto the Kondratiev long cycles, is started, at least in hindsight, by an innovation which opens up a new type of abundance. The Intel microprocessor opened up an abundance in 1971; the Henry Ford production line in 1908/1913 opened up an abundance of things; Stephenson’s Rocket (1829) opened up an abundance of speed. And so on.

But it takes societies time to build up the knowledge, institutions, business models and social practices to make the most of this new abundance, to turn it into a new technology platform and a new market. (It’s also worth noting that it’s me that’s making the connection between the two schools, and I could be misrepresenting her thinking, since none of the leading SSA authors are in her index or bibliography.

Types of innovation

When you go back to the writings of the innovation school in the 1980s, you find them wrestling with these distinctions. In an essay in Long Waves in the World Economy, for example, van Duijn makes a distinction between four types of innovation:

• Major product innovations which create new industries
• Major product innovations in existing industries
• Process innovations in existing industries, and
• Process innovations in basic sectors.

I’m not going to go into this here in any detail, since this post is already on the long side. But I suspect that to get to a fuller understanding of the dynamics of long waves, we need a richer understanding of different types of innovation and how they play out at different points of the cycle. For example, the ten years between the Trough and the production peak in Goldstein’s model is, I suspect, when process innovations are at their most intense. That’s certainly what’s happened in the ICT wave.

The ‘war peak’ and the ‘war trough’ on the diagram is worth more than a passing comment. So, for now, it will have to wait: other than to say that Goldstein argues reasonably convincingly that war is linked to economic cycles.

1. Thanks to Francis Green for pointing me to the Social Structures literature.
Other posts on long waves can be found here.

The second post in my series on long wave theories

The idea of long waves is associated with the Russian economist Nikolai Kondratiev, who was eventually shot by Stalin for his troubles. But the first versions of the theory came from two Dutch scholars a decade earlier, van Gelderen and de Wolff. Kondratiev studied price data (and therefore effectively was looking at long swings in economic investment activity), but other long wave theorists have developed their theories based on different drivers of change, from innovation, to capitalist restructuring, to long-run capital investment, to war.

My plan in these posts was to review the different theories by re-reading the various theorists, but the American academic Joshua Goldstein has done a lot of this work in some detail in his 1988 book Long Cycles: Prosperity and War in the Modern Age, and has also posted the whole of the book online. I’d say his book is essential reading if you’re interested in the idea of long wave theory.

This post will draw on some of my wider reading, but will mostly synthesise the painstaking work that Goldstein has done.

Sceptics

Of course, the first thing to say is that there are still people who think that the whole idea is moonshine. The economist Paul Samuelson called long waves “science fiction,” and in the mid-1980s it was possible for an academic, Tom Kitwood, to write an article called “A Farewell Wave to the Theory of Long Waves”, arguing that “No clear means have yet been devised for classifying the major long-wave theorists .” The other half of this – as the Marxist economist Ernest Mandel observed – is that interest in long wave theories tends to pick up in economic downturns, and dissipate in the upturns.

Teasing out the evidence

In his book, Goldstein goes about teasing out both the evidence and the different schools of long wave theorists. In this post I’m going to look specifically at these two aspects of his work.

So Goldstein focusses on the four long wave schools that were visible when he wrote the book in the late-1980s. Three of these are economic: the innovation school, associated with Schumpeter, Mensch, and latterly Christopher Freeman, which he characterises as “liberal,” in that the system remakes itself within the existing economic framework; the capital investment school associated with Kondratiev and Forrester, which he characterises as “conservative” in that the long waves are seen as the normal working of the system; and the capitalist crisis theory of Trotsky and Mandel, which sees long waves as driven by the repeated restructuring of the system in the face of crisis.

Figure 1: Main economic ‘long wave’ schools of thought

Looking at the economic schools, which are summarised in the figure, what separates them is competing views of rationality. Why do capitalist firms choose (or not) to invest, at one time rather than another, and why?

The war school, which comes out of a different tradition, connects long shifts in national economic hegemony with military and diplomatic competition. Goldstein sees similar differences in worldview within this group of scholars.

The “innovation” school here is based around the work of Modelski, on leadership cycles, which sees new countries emerging into global leadership through innovation in political structure and military techniques. The “conservative” school is the “power transition” school, based on the work of Organski, in which national transitions are a result of changing national capabilities. The “revolutionary” school, associated with Immanuel Wallerstein, sees change resulting from competition between the states in the global core as they try to control the states in the global periphery.

Figure 2: Similarities in perspectives

It’s worth noting that there are some theories that are left out of Goldstein’s schema, because they hadn’t emerged fully in the 1980s, and I’ll discuss these in later posts. These are the “secular cycles” model associated with Peter Turchin, which connects wages, prices, and elite competition; the “social structures of accumulation” model, stemming from David Gordon, which comes out of the capitalist crisis tradition but focuses of the economic, political and social institutions that enable accumulation; and the “generational” model of Strauss and Howe, which, it seems to me, sits apart from all of the other models.

Competing worldviews

One of the reasons why ideas about long waves lacked credibility when Goldstein wrote the book was precisely because these differences in worldview meant that it was all but impossible to evaluate the claims made by different groups of scholars. There’s a fascinating chapter, “Knowledge Cumulation in the Long Cycle Field” where he reviews the relative fragmentation of the whole field through different epistemological lenses, including theories of science (Kuhn, Popper, Lakatos) and the interactions – or not – between the different groups of communities of scholars, partly impeded by the interdisciplinary nature of the field, which creates its own problems of terminology, language, translation and knowledge transfer. Goldstein’s response to this fragmentation was a painstaking analysis of the hypotheses that sit beneath the work of the different schools, some of which are contradictory, to identify which were supported by evidence and which not. That’s a big subject, which I’ll come back to in another post.

For the moment, it’s worth just stepping back to an earlier piece of analysis in the book, where he simply lists (or not so simply; it’s an impressive effort in synthesis) the seven different groups of evidence that long wave researchers have drawn on in their analysis, and assesses the state of the evidence.

Long wave arguments …

This list is taken directly from Chapter 4, on “Empirical Arguments” (pp 64-65).

1. Prices: Are there synchronous long price waves in the core countries? How early can they be found, and in what countries? These questions interest almost all long wave scholars since prices are the most readily available economic data and since all schools posit long waves of prices.
2. Production: Are there alternating phases of fast and slow growth in core countries’ production? In what countries and time periods can they be found? These questions are central to the capitalist crisis school as well as to certain liberal critics who see long waves as “only price waves.”
3. Innovation and Invention: Are waves or clusters of innovations synchronous with long waves? Are they directly or inversely correlated with economic growth phases? These questions are central to the innovation school.
4. Capital Investment: Do spurts of capital investment correlate with the early upswing of the long wave? The correlation of investment levels with long waves is of particular concern to the capital investment school.
5. Trade: Do levels of exports or other indicators of international trade follow the long wave phases? Trade concerns some members of the capitalist crisis school who see capitalism as production for a world market.
6. Real Wages and Working-Class Behavior: Do real wages fluctuate with the long wave? Do strikes and other worker protests follow long wave phases? These questions concern the capitalist crisis school.
7. War: Do major wars tend to occur at one point in the long wave? Does the timing of major wars correlate with long wave phases? These questions concern the war school.

Obviously different schools have different centres of gravity, but these cover the issues that the schools he’s reviewing are interested in.

… and evidence

He then looks at the quality of the evidence behind each of the seven.

• The evidence on prices is good, in both the industrial period (post-1790) and pre-industrial, with clear differential movements in changes in prices in upswings and downswings, and relatively high levels of agreement among scholars about the dates of turning points.
• On production, Kondratiev’s work – which involved some complex equations – was roundly criticised at the time by other Russian scholars, but later work – all from the capitalist crisis school – suggests that it is possible to identify shifts in long-run economic growth rates that correspond to upswings and downswings.
• On innovation, Goldstein notes, “ There is no consensus on how to measure innovation” (p 92) and you get this impression very strongly when reading Long Waves In The World Economy, edited by Christopher Freeman, where it’s clear that different academics are effectively talking across each other by discussing different types of innovation. One of the splits within this group, at least in the ’70s and ’80s, was between those who associated innovation peaks with the downswing and those who saw them occurring early in the upswing – quite a fundamental difference. Goldstein concludes: “ To summarize, the empirical evidence for long waves in innovation is mixed” (p 96). In her book Technological Revolutions and Financial Capital, published in 2002, Carlota Perez proposes an elegant solution to this dispute, but I’m planning to discuss that another time.
• On capital investment, trade, and real wages,  he found that there had been “almost no empirical work”, so they were impossible to assess.

In summary then: “Quantitative empirical studies of long waves over the past sixty years have produced some areas of convergent results and other areas of unresolved dispute.”  In the next ‘long waves’ post I’ll review Goldstein’s work on the different long wave hypotheses. I’m also planning to spend more time on the ‘war school’ in another post.

It’s fairly clear, if you spend any time doing futures work, that there are some recurring patterns that seem to evolve over one or two generations, or more. As part of a personal research project, I have started re-reading these “long wave” theories to try to understand their similarities and differences, and I’ll be blogging about my reading as I go.

An obvious starting point in this journey is Jim Dator’s long survey of the area, “From Tsunamis to Long Waves and Back”, drawn from the archive of the journal Futures, and published over two articles in Futures in 1999. The essay – recombined – can be found here.

Here I’m just going to pull out some extracts that seem to shape the landscape.

Images of the future

His starting point is that futures work is actually about the story of “images of the future”:

“Futures studies doesn’t study the ‘future’,” I like to say, “because ‘the future’ does not exist. What does exist and what can and should be studied, are ‘images of the future’ which each person (culture, class, gender, etc.) has, and which form the basis for individual and collective acts in the present which then impact upon ‘the future.’

And in fact this idea is at the heart of the work of what one might call the “Hawai’i” school of futures, which Dator founded and nurtured: the whole idea of futures archetypes, and the scenarios meta-analysis that preceded them, was designed to understand patterns of images of the future. And the layers of CLA, similarly, are designed to explore these images through different frames. But images on their own are not enough:

I believe it is also necessary to develop (from one’s image of the future) a “theory of social change and stability” and “methods for anticipating and inventing preferred futures” in order to be a useful futurist or to develop a fuller and deeper understanding of what futures studies is.

Dator’s futures practice drew on six theories and their accompanying methods:
•    Images as motivators of individual and group action;
•    Technology as an agent of social change;
•    Age-cohort analysis;
•    Cyclical and wave theories;
•    Emerging issues analysis;
•    Social invention and design.

Joining the dots

As he acknowledges in the essay his perspective on technology is probably over-developed, while in contrast he’s given less thought to age-cohort theories (largely represented by the work of Strauss and Howe) and barely any to cyclical or wave theories, while being a fan of Immanuel Wallerstein, who includes Kondratiev’s long wave or K-wave thinking among his influences.

This changed in the mid-‘90s when his imagination was fired by a series of articles that seemed to open the possibility of connecting these two areas.

The first was a 1994 article by Berry and Kim, that set out explicitly to do this, followed by a paper by Carlos Mallman on “generational billows”: “I now saw that they might well be parts of the same theory/method: Howe and Strauss’ four generations and eras seem to be related to the four phases of a Kondratieff wave.” (See Figure, below). And of course, there’s a whole set of literature, which I’ll discuss in another post, on the relationship between technology and economic waves.

It’s probably worth backing up here for a moment.

Four phases

Strauss and Howe’s four generations, covered in their books Generations and The Fourth Turning, unfold over a period of 80 years, through four distinct phases: Crisis-High-Awakening-Unravelling – with the next Crisis following the Unravelling. That’s the simplest version, but they have a whole set of layers of generational attitudes sitting within this story: your attitudes are shaped by the societal background in which you grew up, and your interaction with your parents, who are the products of a different phase. I’ll be coming back to The Fourth Turning later in the research.

Kondratiev, a Russian economist, studied 19th and early 20th century price data and concluded that economies moved through 50-60 year cycles, with an upswing followed by a period of stagnation which gives way to a downswing. His waves – although of different length – are also sometime described as a four-phase cycle of Prosperity-Recession-Depression-Recovery. A paper by van Duijn, mentioned by Dator, maps these onto a four-phase technology model, of Growth-Maturity-Decline-Introduction,  “such that the introduction of the technology which is to drive the next long wave happens during the lowest point in the current long wave.”

Kondratiev problems

There are problems with the Kondratiev waves: an article by Jos Delbeke observed “its inability to incorporate consistently endogenous variables in the explanation of turning points.” The data is erratic, and it seems that even his disciples can’t agree completely on when later waves start or finish. Although his name is associated with the waves, he was building on the work of Dutch economists.

And there are at least three schools of thought as to why you might get such long waves, running through innovation (also drawing on Schumpeter), capital investment cycles, and “the political economy of capitalist development” (drawing on Mandel). Again, I’m not going to go into detail on these here, since they’ll be explored in a later post, but it is worth noting that the work of Carlota Perez, who is more associated with the innovation school, nonetheless seems to integrate the capital investment school within her long wave (or long surge) model.

Figure: Systems patterns

Cultural and social

By Dator’s account, Mallman and Lemarchand argue that their long-term “billows” are not just technological or economic, but cultural and social. Their underlying cycle is 39 years long, which – I haven’t read the article yet – may or may not link to a heuristic I have developed through my work that sees political crises and institutional innovation in the UK running on a lagged 40-year cycle. (Political crises: 1890s/1930s/1970s/2010s: Institutional innovation: 1900s/1940s/1980s.)

The Italian physicist Cesare Marchetti, meanwhile, has found 55 year “social pulses” in all sorts of data, from transport infrastructure investment to murder, while Brian Berry tried to link Utopian communities to K-waves in a book, America’s Utopian Experiments,  that accumulated scathing reviews from assorted historians.

The final observation that Dator makes in his article is from a 1984 Futures article by Immanuel Wallerstein, who notes that “A long-standing witticism has it that the credibility of the existence of long economic cycles is a function of whether or not the discussion on this topic takes place during the A-phase of expansion or the B-phase of economic stagnation.” They have more credibility during a stagnation period. And given that he was writing in 1999, Dator also has a prescient observation about the impact of “massive and increasing consumer debt creation” on extending the phases or delaying recession.

Patterns of change

There’s at least one whole further school of long wave historians, represented by Peter Turchin and his work on secular cycles, which isn’t covered in Dator’s review of the field (most of this published work has emerged since 1999), which looks at the interchange between demographics, resources, relative prices and political power, which I’ll also be re-reading for my project. These cycles are typically longer. And one of the open research questions for me is the extent to which we might have to think about cycles of different lengths interacting in different ways.

One last thought from me: the patterns of change described here all follow general patterns of systemic change. If one thinks of the Panarchy model, developed by Gunderson and Hollings from studying the life of forests, it has a cycle that also goes through four stages: Expansion (or Exploitation)-Conservation-Release-Reorganisation. At the very least it seems reasonable to believe that human and social systems might follow similar systemic patterns.

Several of the Futures essays referenced by James Dator have been collected in Christopher Freeman (ed), (1984), Long Waves In The World Economy, published by Frances Pinter. The image of Jim Dator at the top of this post is from Trends FM, and it is used with thanks.