Biography of Christopher Sims
One of Sims’s earliest famous contributions was his work on money-income causality, which was cited by the Nobel committee. Money and income move together, but which causes which? Milton Friedman argued that changes in the money supply caused changes in income, noting that the supply of money often rises before income rises. Keynesians such as James Tobin argued that changes in income caused changes in the amount of money. Money seems to move first, but causality, said Tobin and others, still goes the other way: people hold more money when they expect income to rise in the future.
Which view is true? In 1972 Sims applied Clive Granger’s econometric test of causality. On Granger’s definition one variable is said to cause another variable if knowledge of the past values of the possibly causal variable helps to forecast the effect variable over and above the knowledge of the history of the effect variable itself. Implementing a test of this incremental predictability, Sims concluded “[T]he hypothesis that causality is unidirectional from money to income [Friedman’s view] agrees with the postwar U.S. data, whereas the hypothesis that causality is unidirectional from income to money [Tobin’s view] is rejected.”
These are two of the opening paragraphs of the biography of Christopher Sims, the latest addition to The Concise Encyclopedia of Economics. Sims, along with Thomas Sargent, was co-winner of the Nobel Prize in economics in 2011.
Another excerpt, on the Lucas critique and large-scale macro-models:
While rejecting the structural interpretation of large-scale macromodels, Sims did not reject the models themselves, writing: “[T]here is no immediate prospect that large-scale macromodels will disappear from the scene, and for good reason: they are useful tools in forecasting and policy analysis.” Sims conceded that the Lucas critique was correct in those cases in which policy regimes truly changed. But he argued that such regime changes were rare and that most economic policy was concerned with the implementation of a particular policy regime. For that purpose, the large-scale macromodels could be helpful, since what was needed for forecasting was a model that captured the complex interrelationships among variables and not one that revealed the deeper structural connections.
Because of the complexity of Sims’s work, I leaned more heavily than usual on other economists to give me help with the bio. Tyler Cowen and Kevin Hoover, especially Kevin (which makes sense because he’s a macroeconomist), both members of my advisory board for the Encyclopedia helped a lot, as did my Hoover colleague John Cochrane.