The Rise and Fall of Cliometrics, and the Coming Rise of Cliodynamics

Posted on February 26, 2013 by


The latest issue of the Chronicle of Higher Education has two related articles, one on Ian Morris and another on cliodynamics. One interesting theme in the second article is the relationship between cliodynamics and cliometrics. Initially ‘cliometrics’ was a faintly derogatory term used by the detractors of the new economic history that arose in the early 1960s. But the new economic historians liked the term and started using it themselves, in a kind of intellectual judo. I admit that when I coined the term ‘cliodynamics’ I was influenced by cliometrics. However, cliometrics suggests measurement (and that is what the main, although not exclusive thrust of the new economic history was). Back in the late 1990s, when I first became interested in these questions, I thought that we needed a name that would be more evocative of mechanisms, not just data (although I would be the first to affirm that we need data – and the more of it, the better!). I liked ‘dynamics’ because the term implies not just a study of change, but also why change happens.

What happened to cliometrics? The article quotes Edward L. Ayers (a historian of the American Civil War and currently University of Richmond President) saying that historians already had “a brief love affair with quantification.” According to Ayers, cliometrics crested with the 1974 book Time on the Cross: The Economics of American Negro Slavery, and then faded away. This observation agrees with mine. I have discussed it with a number of people, trying to understand why this happened, and basically their answer is, “post-modernism happened.”

Interestingly enough, we can trace the rise and fall of cliometrics using the Google Ngram. Generally speaking this is a tricky tool to use, but in this case it gives good results (for reasons I will come back to in a minute). Here’s the frequency of ‘cliometrics’ appearing in the American English corpus (I focus on American books, because cliometrics was primarily an American development):

cliometrics_ngram

The peak is in 1978, not in 1974, but that’s a minor detail. Otherwise, an explosive rise followed by a gentle decline are quite clear.

So how do we explain it? Is it because the quantitative approach to history failed to yield new insights? Not at all. When Fogel and Engerman published their 1974 book, it was met with a withering storm of criticism. The debate got nasty. Some critics accused Fogel and Engerman of racism. Other critics zeroed in on problems with their analysis, and indeed there were several flaws. But Fogel and others corrected the mistakes and refined their methods. After several rounds of such back and forth, Fogel and his co-workers have satisfied those critics who focused on their analytical methods. And the verdict? It turned out that the efficiency of the slave plantation system was even greater than initially estimated. Slaves were 35 percent more efficient than free farmers.

In 1993 Robert Fogel got the Noble prize in economics for his work in new economic history.

time_on_the_cross

Even Ayers, who is clearly not enamored of quantitative approaches to history admits it: “they did change our understanding of slavery. People now believe that slavery was a profitable system.” And so they should. A politico-economic system that is completely unacceptable to us on moral grounds can nevertheless be more efficient when considered in purely economic terms.

So cliometrics failed not because it was poor science, but for other reasons. Essentially what killed it was a change in scientific fashion. Or academic fashion, since post-modernists consider their discipline as antithetical to science. Fashion swings affect not only skirt lengths; they also dictate what topics are considered to be hot in science. And just like with clothes, scientific fashion is cyclic.

I saw this in my first scientific discipline, ecology. Back in the 1920s ecologists, such as Charles Elton, discovered that populations of many animals go through boom-and-bust cycles. Mathematicians Vito Volterra and Alfred Lotka proposed models that explained such cycles on the basis of ecological interaction between predators and prey. For a while this was a very hot area of research – and then it faded away! During the 1960s and 1970s the ecologists turned away from the predator-prey theory, even though there were no data to disprove it.

Then, during the 1980s the idea came back. We did more modeling, more experiments, and it turned out that the old (by that point) theory was correct. That’s how I got my first papers in Nature and Science, to which the Chronicle article refers. One of our papers, Are Lemmings Prey or Predators?, was actually featured on the cover of Nature, a feat I have been so far unable to replicate.

The acceptance of quantification and mathematical modeling has gone through cycles in biology, anthropology, and history. In anthropology there was the new processual turn back in the 1960s and 1970s that was replaced by a ‘cultural turn.’ Now quantification is coming back.

In history the cycle actually precedes the rise of cliometrics. If we look at the frequency of ‘quantitative history’ we see that the first time this phrase appears in the American English corpus is around 1910.

quanthist_ngram

There were just a few books talking about quantitative history – it was more of a blip than a peak and it faded away. Then came the rise and fall of cliometrics (we can see that ‘quantitative history’ parallels ‘cliometrics’ almost precisely – so Google Ngram is reflecting something quite real). But the second peak did not completely fade away. The development of science is both cyclic and cumulative. Fashions come and go, but they leave behind them more substantial foundations for the next cycle.

So we are now (as I believe) in the third cycle. Cliodynamics is building on the previous success of cliometrics, but we now have better mathematical tools, more data, and we are addressing a much broader spectrum of questions. This time, we will not fade away!

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