Morgan Stanley Finds A “Stunning Divergence” In The Economic Data

Since we first highlighted the data, there has been a great deal of attention paid to the post-election divergence between the so-called soft (sentiment) data in the US, and the hard (quantifiable) data.

Morgan Stanley’s chief equity and rates strategists note “the divergence is stunning.”

Upside surprises appear to be completely driven by the soft data while hard data are simply coming in about as expected. This was underscored by the fact the Fed made little revision to its economic forecasts at the March FOMC meeting. Essentially, the hard data are unfolding in line with the Fed’s 2017 outlook.

There is a Record Gap Between the Strength of ‘Hard’ and ‘Soft’ US Macro Data

Simply put, the hard data on the economy is still looking far too soft.

Morgan Stanley offers an additional compelling take on capturing this hard versus soft divergence.

Compare the New York Federal Reserve Bank’s current 1Q GDP tracking vs ours – FRBNY is currently tracking 1Q GDP at 3.0% versus us around 1%. The difference is larger than usual and is being driven by the fact that the New York Fed incorporates soft data into its tracking (attempting to tie it econometrically to GDP, a very hard thing to do especially in real-time). Our method translates the incoming hard data into its GDP equivalent. Note that the Atlanta Fed’s GDPNow tracking also focuses on hard data and is currently tracking 1% for 1Q GDP (Exhibit 2).

Will the hard and soft data reconcile, and in what direction? Optically, a 2Q GDP bounce back would perhaps be taken by markets as the hard data correcting to the soft data—in other words, risk appetite may find renewed inspiration as positive hard data unfolds. But from an economist’s point of view, smoothing through the volatility simply looks like the outlook for around 2% growth remains intact. Moreover, we do expect that the breadth of the 2Q rebound in hard data will be fairly limited, with a swing in consumption as the main driver of the expected 2Q upside, followed by a slightly better net trade and inventory profile. As a consequence, we would not necessarily expect ‘hard data’ surprise indices to start racing higher if the factors behind the 2Q growth rebound remain narrowly confined to a few sectors as we expect.

Additionally, as we noted previously, the problem – for the hope enthusiasts – is the last 5 times that the gap between perceived economic reality and actual economic reality was near this high, the S&P 500 had a troblesome few weeks/months after:

• JUL 2007 -12%
• JUN 2009 -9%
• APR 2010 -17%
• MAR 2011 -19%
• NOV 2014 -6%

Still, this time will probably be different.