How to Deal with High Frequency Nowcast Economic Data

• Posted by DynamicHedge
• on July 11th, 2014

Moar GDP revisions, that’s what we need (said no one)!

The Atlanta Fed has introduced a new dataset called a “nowcast” for GDP called GDPNow. A nowcast is economic model that produces predictions without the need for any human judgement. This model will produce publicly available nowcasts of GDP 5-6 times per month as a supplement the traditional report-and-revise system for GDP. Institutions have been producing reports like this internally for a long time, but this represents the first time the broad public will have access to this information.

Incidentally, nowcasting is becoming increasingly popular in meteorology and economics (I’ll let that one sit with you for a minute).

Here is the Atlanta Fed:

The growth rate of real gross domestic product (GDP) measured by the U.S. Bureau of Economic Analysis (BEA) is a key metric of the pace of economic activity. It is one of the four variables included in the economic projections of Federal Reserve Board members and Bank presidents for every other Federal Open Market Committee (FOMC) meeting. As with many economic statistics, GDP estimates are released with a lag whose timing can be important for policymakers. For example, of the four scheduled 2014 release dates of an “advance” (or first) estimate of GDP growth, two are on the second day of a scheduled FOMC meeting with the other two on the day after the meeting. In preparation for FOMC meetings, policymakers have the Fed Board staff projection of this “advance” estimate at their disposal. These projections—available through 2008 at the Philadelphia Fed’s Real Time Data Center—have generally been more accurate than forecasts from simple statistical models. As stated by economists Jon Faust and Jonathan H. Wright in a 2009 paper, “by mirroring key elements of the data construction machinery of the Bureau of Economic Analysis, the Fed staff forms a relatively precise estimate of what BEA will announce for the previous quarter’s GDP even before it is announced.”

The Atlanta Fed GDPNow model also mimics the methods used by the BEA to estimate real GDP growth. The GDPNow forecast is constructed by aggregating statistical model forecasts of 13 subcomponents that comprise GDP. Other private forecasters use similar approaches to “nowcast” GDP growth. However, these forecasts are not updated more than once a month or quarter, are not publicly available, or do not have forecasts of the subcomponents of GDP that add “color” to the top-line number. The Atlanta Fed GDPNow model fills these three voids.

What’s happening here is that economic data is becoming higher frequency and probably higher quality than ever before. This is a good thing for the market as a whole as more frequent data leads to increased market efficiency. But what’s good for the market isn’t always good for those looking for an edge. More accuracy in data means generally means less need for price discovery and less edge available for market participants.

I am not nearly smart enough to incorporate GDPNow into my toolset with any hope of creating a meaningful edge. As data quality improves and markets become more efficient it means that fewer obvious “fat pitches” will come along. There will always be an edge but it seems that the edge increasingly coming in the form of being tactical and lower frequency. I wrote a while back called Fundamental Top-Down Macro for the Brain Damaged where I joked that my model was so simple that even a person with brain damage could follow it.

The more high frequency the world becomes, the more I gravitate to low frequency “brain damaged” models.

 

H/T Calculated Risk: New Tool from Atlanta Fed: GDPNow

 

blog comments powered by Disqus