Keynesians vs monetarists A Granger Causality match Guy Lion April 2006 Hey Keynes, your [Tax] Cuts are no uppercut. Milton, where is your [Money] Velocity? I am Clive Granger who decides Causality
We will use Granger causality to referee a match in economic theory between Keynesians and monetarists.
Both claim their respective tools are best to manage GDP.
We will test which tools better “Granger cause” quarterly GDP changes.
John Maynard Keynes (1883 – 1946) stated that a counter-cyclical fiscal policy was effective in managing the business cycle.
This means running a Budget Deficit when the economy is decelerating. And, running a Budget Surplus when economy is accelerating.
Keynes suggested government (net) spending affected aggregate demand without affecting price (inflation).
Milton Friedman (1912 - ) stated the Money Supply has a direct impact on economic growth and inflation.
Milton relied on Irving Fisher’s (1867–1947) Quantity Theory: MV = PQ or
Money Supply x Velocity of Money = Price x Quantity.
The best way to manage the economy is to target a conservative Money Supply growth and stick to it. This way, you control inflation.
Keynesians vs Monetarists fighting stands
Keynesians do not believe monetary variables (M1, M2, M3) affect macroeconomic variables (GDP, CPI). This may be due to change in Velocity of Money being a countervailing force to change in Money Supply. Thus, for them “money does not matter.”
For monetarists, fiscal policies are not effective because interest rate is a countervailing force to fiscal stimulus (the “crowding out” theory). And, because of the Quantity Theory [MV = PQ] Money Supply does have a direct impact on macroeconomic variables (GDP, CPI). Thus, for them “money is everything.”
A Budget Deficit proxy variable
Budget Deficit data is annual. That’s a problem.
As an alternative we looked at Treasury levels from one quarter to the next.
Disaggregate Interest refinancing from Deficit financing as shown below.
Granger Causality review
Develop a Base case autoregressive model using dependent variable and its lagged values as independent variable.
Develop a Test case model by adding a second lagged independent variable you want to test.
Calculate the square of the residual errors for the two models and run a t test (unpaired) to check if the residuals are significantly lower when you add tested second variable. [We will run the non-parametric Mann-Whitney test to observe P value differences].
Redo steps 1 through 3, but reverse the direction. By comparing the tests significance or P value, you can see if A Granger causes B more than B Granger causes A.
We will skip step 4 because we are not interested on whether GDP impacts fiscal or monetary policies, but on whether fiscal or monetary policies have a greater impact on GDP.
Selecting the lagged variable for GDP Data source: quarterly data since second quarter 1959 to 3d quarter 2005. Source: BEA (GDP), Flow of Funds (Treasury -> Deficit Financing), Federal Reserve (M2).
Granger Causality GDP Output P values for both test models are too high. In the Mann-Whitney test, the Milton model is going in the wrong direction. The avg. rank went up. That’s bad.
Keynes vs Milton slugfest
Conclusion [Milton to Granger] I feel tired right now. Keynes wins by Granger causing decision.