One of my friends wrote, “if you look at our past four economic recoveries (Reagan, Clinton, Bush, and Obama) and compare them with the deficit, a very clear pattern emerges: the higher the deficit, the weaker the recovery. It seems to me that if you compare them with level of taxation, another pattern emerges: the higher the taxes, the stronger the recovery. I'm not claiming that higher taxes result in economic recovery, but it's clearly not the death-knell of the economy.”
In true nerd fashion, I reacted by making charts. You can take the Black Belt out of Six Sigma but you can’t take Six Sigma out of the Black Belt.
The first chart shows growth in Gross Domestic Product (GDP) as a function of the previous years’ Federal budget surplus or deficit. The technical details are below. As you can see, there is no clear correlation between the size of the deficit and the strength of a recovery. Although the Clinton recovery, during a time of budget surplus was strong, and the Bush recovery, during a time of above average deficits was weak, the Reagan recovery, during a time of even bigger deficits, was the strongest of all.
When you look at the entire data set, rather than just the three peak recovery years, no correlation between deficits and GDP emerges. Within the margin of error, the trend line is flat.
Taxes tell a different story. Again, there is no clear pattern in the peak recovery years. For the data set as a whole, there is a statistically significant trend: higher taxes equals lower growth. Every one percent increase in Federal revenues as a percentage of GDP corresponds to a 0.55% percent decrease in GDP growth. Taxes aren’t a death knell to the economy, but they do damage.
Although there is a correlation between taxes and growth, it is a weak one. Combined with the absence of correlation with deficits, the data suggests that Milton Friedman was right: other things drive the economy far more than fiscal policy. Monetary policy is one driver. As Friedman said in a 1996 interview, “One of the things I have tried to do over the years is to find cases where fiscal policy is going in one direction and monetary policy is going in the opposite. In every case the actual course of events follows monetary policy. I have never found a case in which fiscal policy dominated monetary policy and I suggest to you as a test to find a counter-example.”
Technology is another driver. The invention of the World Wide Web was clearly a factor in the strength of the Clinton recovery.
It should also be noted that the data falls into a narrow range. For almost the entire post-war period, the Federal account balance varied between a deficit of five percent of GDP and a surplus of two percent. But one data point sticks out dramatically - 2010. With deficits in excess of 10%, President Obama is taking us into new territory. The economic consequences of that remain to be seen.
Technical Details: The Federal tax and deficit data used in the charts comes from the “Fiscal Year 2012 Budget, Table 1.1—Summary of Receipts, Outlays, and Surpluses or Deficits (-): 1789–2016”, and is available from the Office of Management and Budget. The GDP data used comes from the “Current-Dollar and ‘Real’ Gross Domestic Product”, April 28, 2011, and is available from the Bureau of Economic Analysis.
The slopes of the trend lines and the uncertainty in the slopes were calculated using the Excel LINEST function which uses the least-squares method for fitting a line to the data. My claim above that there is no correlation between deficits and GDP growth is based on the slope of the trend line being less than the deviation. In the case of taxes, the slope is between two and three deviations.
My friend pointed out that, “There's going to be a lag between policy changes and their effect.” The charts are based on a one-year lag, e.g. the 2010 GDP is plotted against 2009 deficit and receipts. I found the one-year lag gave the strongest correlation (highest R-value).
I identified the various economic recoveries with the years in which economic growth peaked. I make no claim that this is the best way, or even a good way to measure the strength of a recovery.