Positive momentum continues to drive the US economy forward, keeping recession risk low and providing upbeat estimates for the near-term outlook. With the White House poised to sign tax-cut legislation this week, the macro trend looks set to receive fresh stimulus to keep economic growth bubbling. The probability of recession in the near term, as a result, remains virtually nil.

Using data published to date for November’s economic profile reflects a solid a trend for key indicators through last month. Econometric projections point to a continuation of the bullish drift through January.

Wall Street economists are expecting that fourth-quarter GDP growth will cool a bit to a 2.7% increase, down from 3.3% in Q3, according to Dec. 19 survey data via CNBC. But from a business-cycle perspective that forecast, if accurate, will suffice to keep US output on track to stay solidly positive through the end of the year.

In line with the upbeat macro releases of late, the latest estimate of recession risk for the US remains effectively zero as of November, based on The Capital Spectator’s business-cycle benchmarks, which reflect a diversified set of economic datasets. (For a more comprehensive review of the macro trend on a weekly basis, see The US Business Cycle Risk Report.)

Aggregating the data in the table above continues to translate into a strong positive bias overall. The Economic Trend and Momentum indices (ETI and EMI, respectively) remain well above their respective danger zones (50% for ETI and 0% for EMI). When/if the indexes slide below those tipping points, the declines will mark clear warning signs that recession risk is elevated and a new downturn is likely. The analysis is based on a methodology that’s profiled in my book on analyzing 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 in this framework indicates that the odds remain effectively zero that NBER will declare November as the start of a new recession.

For some insight into the near-term outlook, consider how ETI may evolve as new data is published. One way to project 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 in R. The ARIMA model calculates the missing data points for each indicator for each month — in this case through January 2018. (Note that September 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 through next month.

Forecasts are always suspect, but recent projections of ETI for the near-term future have proven to be 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 subject to greater 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 more perspective on the track record of the forecasts, here are the previous business-cycle risk updates for the last three months:

21 Nov 2017
24 Oct 2017
20 Sep 2017

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.