Interpreting Data By Arnold Kling

Two interesting examples.

1. John Taylor attempts to take on Krulong. He writes,

For all of 2007, spending was 19.6 percent of GDP. For all of 2021–after the impacts of the recession and the final year of the budget window–the budget submitted in February proposed spending equal to 24.2 percent of GDP. ..

Using the CBO baseline of January 2011 (which is below the February budget), mandatory spending would increase from 10.4 percent of GDP in 2007 to 14.0 percent of GDP in 2021.

The first sentence implies an ongoing Obama spending binge. However, the second sentence suggests that 3.6 of the 4.6 percentage point rise in government spending as a share of GDP comes from entitlements. I assume that was pretty much baked in before President Obama took office. Of course, one can still argue that President Obama should be doing more to either (a) curb entitlements, (b) find other spending cuts to offset entitlement growth, or (c) explicitly propose taxes that will pay for everything.

2. Richard Burkhauser and others have adjusted incomes for household size and government transfers. The result is that while on a pre-transfer basis, the bottom quintile of household incomes in 2007 was 33 percent below that of the bottom quintile in 1979 (please note that these are not the same households), on a post-transfer basis the income of the bottom quintile was 26 percent above the 1979 level.

The gist of the article is, “The poor are not as bad off as you think!.” However, one could just as easily interpret the data as saying, “The poor sure as heck need those income transfers!”

I think it’s pretty rare that one can make a definitive ideological point based on aggregate data. When people try, it is usually easy to come up with a reason to question their perspective.