The government’s big-picture update due on Apr. 28 may suggest otherwise, based on recent polling. The median estimate for the “advance” GDP report via CNBC’s Rapid Update survey of economists (as of Apr. 18), for example, sees Q1 output rising by just 0.9% — less than half the 2.1% pace in last year’s Q4. If the projection is accurate, the news will inspire new claims that the US macro trend is sliding over to the dark side. Anything’s possible, of course, but a review of the numbers published to date across a broad range of indicators signals that forward momentum is intact, even if the upcoming GDP results look wobbly.
The probability of an NBER-defined recession has started is still close to zero, based on numbers through March via the Capital Spectator’s proprietary business-cycle indexes. The nearly complete profile for last month shows that just two of 14 indicators in our model are negative, which implies that the economy will continue to sidestep a new downturn. (For a more comprehensive read on business-cycle analysis on a weekly basis, see The US Business Cycle Risk Report.)
Aggregating the data in the table above continues to indicate that the broad trend remains convincingly positive. The Economic Trend and Momentum indices (ETI and EMI, respectively) were unchanged in March, holding on to gains that unfolded in previous months. As a result, both benchmarks remain well above their respective danger zones: 50% for ETI and 0% for EMI. When/if the indexes fall below those tipping points, we’ll have clear warning signs that recession risk is at a critical level, in which case a new downturn will be likely. The analysis is based on a methodology outlined in my book on monitoring the business cycle.
Translating ETI’s historical values into recession-risk probabilities via a probit model also points to low business-cycle risk for the US through last month.Analyzing the data with this methodology indicates that the odds are virtually nil that NBER will declare March as the start of a new recession.
For perspective on looking ahead, consider how ETI may evolve as new data is published. One way to project future values for this index is with an econometric technique known as an autoregressive integrated moving average (ARIMA) model, based on calculations via the “forecast” package for R. The ARIMA model calculates the missing data points for each indicator for each month — in this case through May 2017 (Jan. 2017 is currently the latest month with a full set of published data). Based on today’s projections, ETI is expected to remain well above its danger zone in the immediate future.
Forecasts are always suspect, but recent projections of ETI for the near-term future have proven to be relatively reliable guesstimates vs. the full set of published numbers that followed. That’s not surprising, given ETI’s design to capture the broad trend based on multiple indicators. Predicting individual components, by contrast, is prone to far more uncertainty. The assumption here is that while any one forecast for a given indicator will likely be wrong, the errors may cancel out to some degree by aggregating a broad set of predictions. That’s a reasonable view, according to the generally accurate historical record for the ETI forecasts in recent years.
The current projections (the four black dots in the chart above) suggest that the economy will continue to expand. The chart above also includes the range of vintage ETI projections published on these pages in previous months (blue bars), which you can compare with the actual data (red dots) that followed, based on current numbers.
For additional perspective on judging the track record of the forecasts, here are the previous updates for the last three months:
Note: ETI is a diffusion index (i.e., an index that tracks the proportion of components with positive values) for the 14 leading/coincident indicators listed in the table above. ETI values reflect the 3-month average of the transformation rules defined in the table. EMI measures the same set of indicators/transformation rules based on the 3-month average of the median monthly percentage change for the 14 indicators. For purposes of filling in the missing data points in recent history and projecting ETI and EMI values, the missing data points are estimated with an ARIMA model.