US Economic Profile
James Picerno | Jul 18, 2014 06:42AM ET
There’s still plenty to worry about (Nowcasting The Business Cycle: A Practical Guide For Spotting Business Cycle Peaks
Let’s dive into the numbers, starting with a summary of ETI and EMI’s individual components:
Reviewing the historical record for ETI and EMI shows that both business cycle benchmarks are well above their respective danger zones: 50% for ETI and 0% for EMI. When the indexes fall below those tipping points, we’ll have clear warning signs that recession risk is elevated. For now, however, there’s still a comfortable margin between current values for June (84.4% for ETI and 9.3% for EMI) and the danger zones.
Translating ETI’s historical values into recession-risk probabilities via a business cycle dates —will declare last month as the start of a new recession.
Now let’s consider how ETI’s values may evolve as new data is published in the near future. One way to estimate expected values for this index is with an econometric technique known as an autoregressive integrated moving average R, a statistical software environment. The ARIMA model calculates the missing data points for each indicator, for each month through August 2014. (April 2014 is currently the latest month with a complete set of published data). Based on today’s projections, ETI is expected to remain well above its danger zone in the near term.
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Forecasts are always suspect, of course, but recent projections of ETI for the near-term future term have proven to be relatively reliable guesstimates vs. the full set of monthly reported numbers that followed. (That’s not surprising, given the broadly diversified nature of ETI. Predicting individual components, by contrast, is prone to far more uncertainty in the short run.) As such, the latest projections (the four black bars on the right in the chart above) offer support for cautious optimism. The chart above also includes the vintage ETI projections published on these pages in previous months, which you can compare with the complete monthly sets of actual data that followed, based on current numbers (red circles). The assumption here is that while any one forecast for a given indicator is likely to be wrong, the errors may cancel one another out to some degree by aggregating a broad set of predictions into ETI.
For additional perspective on judging the value of the forecasts based on the historical record, here are the previous updates for the last three months:
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