On Data Divergences

We always find the divergence between good art and money fascinating.

As an example, take the Academy Awards presentation for the 2016 film season. Our favorite nominated films seemed to garner the lowest sales at the box office. Of the films nominated for Best Picture, our favorite, Hell or High Water, garnered a mere $27 million. Moonlight, the winner of the Best Picture Oscar, pocketed only a bit more, coming in around $28 million. Elle, one of our favorite films of the year, which featured a tour de force performance from Best Actress-nominated Isabelle Huppert, only took in $2 million in ticket sales! The divergence between these measly takes and bigger box office sales north of $150 million for some of the other flawed and uninteresting nominated films, such as Hidden Figures, La La Land and Arrival, is breathtaking.

And this reminds us of another divergence we are noticing in macroeconomic data these days: the divergence between “soft” and “hard” economic data.

Soft data is based on surveys and sentiment and does not necessary correspond directly to economic activity and actual dollars, which would be considered hard data. An example of soft data is the National Federation of Independent Business’s Small Business Optimism Index, which polls small business owners on how they feel about the future. Today they are very optimistic (orange line in the chart below) but not yet pulling the trigger to spend actual dollars (blue line):

Since the presidential election back in November, the aggregate soft economic data has been improving meaningfully while the hard economic data has — so far — not improved:

The liftoff of soft data suggests a boost in confidence since the election and President Trump’s anticipated pro-growth agenda. Unlike the divergence between good art and money, which most likely will never reverse, we hope the hard economic data improves and catches up with sentiment.
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