Sargent and Sims’s work is particularly relevant today as it explains the way that peoples’ expectations of the future can impact their current behavior. This is reflected in every economics story today that uses the phrase “policy uncertainty.”
Their work came along at a time when Keynesian economic models were facing challenges: There were theoretical challenges by economists like Milton Friedman and Robert Lucas, both of whom have previously won Nobel Prizes, but there were also empirical challenges. Keynesian economics didn’t seem to make much sense of the 1970s when the economy experienced high unemployment and high inflation, whereas it had worked pretty well in explaining macroeconomic trends in the 1960s.
Part of these failures had to do with the fact that these earlier Keynesian models relied on people’s naiveté. They worked so long as people could be fooled by government. For example, government-induced inflation might boost the economy if enough producers are fooled into thinking that higher prices are the result of increased demand for their products. Sargent’s work explains how people’s beliefs about the future impact their behavior. He found that if you make modest assumptions about peoples’ ability to understand how policy will affect their future, Keynesian policy prescriptions like short-term fiscal or monetary stimulus don’t work very well.
Sims developed econometric techniques that allow economists to test theories using real-world data in a more independent fashion. Previous techniques left too much up to the researcher’s preconceived beliefs, allowing for the possibility of bias. But Sims’s techniques allowed economists to test theories without making restrictive preconceived assumptions about the way certain variables relate to one another.
For example, Sims showed how one might test theories of unemployment by examining the way that unemployment at a certain time might be determined by unemployment in previous periods and by the values of other variables like inflation in previous periods.