He contributed to the development of key ideas in the Keynesian economics of his generation and advocated government intervention in particular to stabilize output and avoid recessions.

His academic work included pioneering contributions to the study of investment, monetary and fiscal policy and financial markets.

Along with fellow neo-Keynesian economist James Meade in 1977,[7][8] Tobin proposed nominal GDP targeting as a monetary policy rule in 1980.

[9][10] Tobin received the Nobel Memorial Prize in Economic Sciences in 1981 for "creative and extensive work on the analysis of financial markets and their relations to expenditure decisions, employment, production and prices."

Tobin graduated summa cum laude in 1939 with a thesis centered on a critical analysis of Keynes' mechanism for introducing equilibrium involuntary unemployment.

In 1941, he interrupted graduate studies to work for the Office of Price Administration and Civilian Supply and the War Production Board in Washington, D.C.

[13] At the end of the war he returned to Harvard and resumed studies, receiving his Ph.D. in 1947 with a thesis on the consumption function written under the supervision of Joseph Schumpeter.

During 1961–62, he served as a member of John F. Kennedy's Council of Economic Advisers, under the chairman Walter Heller, then acted as a consultant between 1962 and 1968.

Here, in close collaboration with Arthur Okun, Robert Solow and Kenneth Arrow, he helped design the Keynesian economic policy implemented by the Kennedy administration.

In his 1958 article Tobin also led the way in showing how to deal with utility maximization under uncertainty with an infinite number of possible states.

As Palda explains "One way to get out of the mess of figuring out asset prices using a model of maximizing the expected utility of investing in stocks is to make assumptions about either preferences or the probabilities of the different possible states of the world.

When preferences contain only a linear and a squared term (a case of diminishing returns) or the probabilities of different stock returns follow a normal distribution (an equation that contains a linear and squared terms as parameters), a simple formulation of a person's investment choices becomes possible.