Introduction to Social Macrodynamics: Secular Cycles and Millennial Trends
Introduction to Social Macrodynamics: Secular Cycles and Millennial Trends by Andrey Korotayev, Artemy Malkov, and Daria Khaltourina. Moscow: URSS, 2006.
Human society is a complex nonequilibrium system that changes and develops constantly. Complexity, multivariability, and contradictions of social evolution lead researchers to a logical conclusion that any simplification, reduction, or neglect of the multiplicity of factors leads inevitably to the multiplication of error and to significant misunderstanding of the processes under study. The view that any simple general laws are not observed at all with respect to social evolution has become totally dominant within the academic community, especially among those who specialize in the Humanities and who confront directly in their research the manifold unpredictability of social processes. A way to approach human society as an extremely complex system is to recognize differences of abstraction and time scale between different levels. If the main task of scientific analysis is to detect the main forces acting on systems so as to discover fundamental laws at a sufficiently coarse scale, then abstracting from details and deviations from general rules may help to identify measurable deviations from these laws in finer detail and shorter time scales. Modern achievements in the field of mathematical modeling suggest that social evolution can be described with rigorous and sufficiently simple macrolaws.
The first book of the Introduction (Compact Macromodels of the World System Growth. Moscow: URSS, 2006) discusses general regularities of the World System long-term development. It is shown that they can be described mathematically in a rather accurate way with rather simple models. In this book the authors analyze more complex regularities of its dynamics on shorter scales, as well as dynamics of its constituent parts paying special attention to «secular» cyclical dynamics. It is shown that the structure of millennial trends cannot be adequately understood without secular cycles being taken into consideration. In turn, for an adequate understanding of cyclical dynamics the millennial trend background should be taken into account.
Introduction: Millennial Trends
- Chapter 1. Secular Cycles
- Chapter 2. Historical Population Dynamics in China: Some Observations
- Chapter 3. A New Model of Pre-Industrial Political-Demographic Cycles (by Natalia Komarova and Andrey Korotayev)
- Chapter 4. Secular Cycles and Millennial Trends
- Appendix 1. An Empirical Test of the Kuznets--Kremer Hypothesis
- Appendix 2. Compact Mathematical Models of the World System's Development and Macroperiodization of the World System's History
From the review by Robert Bates Graber
From the review by Robert Bates Graber (Professor Emeritus of Anthropology, Division of Social Science, Truman State University) of "Introduction to Social Macrodynamics" (Three Volumes. Moscow: URSS, 2006) (published in Social Evolution & History. Vol. 7/2 (2008)): This interesting work is an English translation, in three brief volumes, of an amended and expanded version of the Russian work published in 2005. In terms coined recently by Peter Turchin, the first volume focuses on “millennial trends,” the latter two on “secular cycles” a century or two in duration.
The second volume is subtitled Secular Cycles and Millennial Trends. Chapter 1 stresses that demographic cycles are not, as often has been thought, unique to China and Europe, but are associated with complex agrarian systems in general; and it reviews previous approaches to modeling such cycles. Due to data considerations, the lengthy chapter 2 focuses on China. In the course of assessing previous work, the authors, though writing of agrarian societies in particular, characterize nicely what is, in larger view, the essential dilemma reached by every growing human population: "In agrarian society within fifty years such population growth [0.6 percent per year] leads to diminishing of per capita resources, after which population growth slows down; then either solutions to resource problems (through some innovations) are found and population growth rate increases, or (more frequently) such solutions are not found (or are not adequate), and population growth further declines (sometimes below zero)" (p. 61–62). (Indeed, for humans, technological solutions that raise carrying capacity are always a presumptive alternative to demographic collapse; therefore, asserting—or even proving—that a particular population “exceeded its carrying capacity” is not sufficient to account logically for the collapse of either a political system or an entire civilizations.) Interestingly, the authors find evidence that China’s demographic cycles, instead of simply repeating themselves, tended to increase both in duration and in maximum pre-collapse population. In a brief chapter 3 the authors present a detailed mathematical model which, while not simulating these trends, does simulate (1) the S-shaped logistic growth of population (with the effects of fluctuating annual harvests smoothed by the state’s functioning as a tax collector and famine-relief agency); (2) demographic collapse due to increase in banditry and internal warfare; and (3) an “intercycle” due to lingering effects of internal warfare. Chapter 4 offers a most creative rebuttal of recent arguments against population pressure’s role in generating pre-industrial warfare, arguing that a slight negative correlation, in synchronic cross-cultural data, is precisely what such a causal role would be expected to produce (due to time lags) when warfare frequency and population density are modeled as predator and prey, respectively, using the classic Lotka-Volterra equations. Chapter 4 also offers the authors’ ambitious attempt to directly articulate secular cycles and millennial trends. Ultimately they produce a model that, unlike the basic one in chapter 3, simulates key trends observed in the Chinese data in chapter 2: "the later cycles are characterized by a higher technology, and, thus, higher carrying capacity and population, which, according to Kremer’s technological development equation embedded into our model, produces higher rates of technological (and, thus, carrying capacity) growth. Thus, with every new cycle it takes the population more and more time to approach the carrying capacity ceiling to a critical extent; finally it “fails” to do so, the technological growth rates begin to exceed systematically the population growth rates, and population escapes from the “Malthusian trap” " (p. 130).