Authored by Mike Shedlock via MishTalk.com,
Gross Domestic Product (GDP) and Gross Domestic Income (GDI) are two measures of the same thing. But the difference is now over two percentage points, the third largest in history.
GDP and GDI data from BEA, calculation and chart by Mish
In dollar terms, the discrepancy is the largest ever. However, percentage comparisons are a better measure which is why I created a new chart today to show the percentage point differences.
There is a strong tendency to revery to the mean. However, reversion to the mean does not imply GDP will fall. GDI could overshoot to catch up.
However, based on where the economy is right now, I would expect GDI to drop with GDP dropping more on a relative basis.
Earlier today, I reported More Soft Economic Data, Q1 GDP Revised Lower, Q4 GDI Significantly Lower
Regarding the first bullet point, I calculated revised GDP at 1.2509 percent which the BEA rounded to 1.3.
The Philadelphia Fed prefers GDI over GDP but it prefers a blend (not an average) which it calls GDPplus even more. Note that GDPE = GDP and GDPI = GDI in the discussion below.
The GDPplus Working Paper is mostly geekish math, but there are some readable snips.
Aggregate real output is surely the most fundamental and important concept in macroeconomic theory. Surprisingly, however, significant uncertainty still surrounds its measurement. In the U.S., in particular, two often-divergent GDP estimates exist, a widely-used
expenditure-side version, GDPE [GDP], and a much less widely-used income-side version, GDPI [GDI].
Nalewaik (2010) and Fixler and Nalewaik (2009) make clear that, at the very least, GDPI deserves serious attention and may even have properties in certain respects superior to those of GDPE. That is, if forced to choose between GDPE and GDPI , a surprisingly strong case exists for GDPI . But of course one is not forced to choose between GDPE and GDPI , and a GDP estimate based on both GDPE and GDPI may be superior to either one alone. In this paper we propose and implement a framework for obtaining such a blended estimate.