Robert Fogel, who died this week, won a Nobel for economics by mining historical data and in the process shook up the study of history forever. Just as with cholesterol, it seems there is good data mining and bad data mining. Fogel’s was undoubtedly the good kind.
As a teenager when World War Two was ending, he switched from chemistry and physics to study economics at Cornell because he feared, as did others, that when military spending was withdrawn the economy might retrench and sink back into a reprise of the Great Depression. It didn’t turn out that way.
Governments in the Western world switched from spending money on arms to spending on hospitals and schools and the buoyancy kept another slump at bay until the economy was on its feet. Fascinated by figures, as an academic Fogel applied quantitative methods used in economics to test whether historians’ hunches about the cause and effect of events were correct. His findings led to immense controversy and, eventually, a Nobel Prize.
He first tested whether, as was then commonly thought, railroads opened up America and provoked the surge in economic growth in the nineteenth century. When he looked closely at the data and ran it through computers, which had only recently become available, Fogel found that the great railroad barons had little to do with spurring growth.
Indeed, the building of railroads coast to coast amounted to a mere 2.7 percent extra growth. Different parts of America would have been turned over to agriculture, Fogel discovered, but the nation would have been almost as prosperous without Cornelius Vanderbilt, Leland Stanford, Jay Gould and the like.