It’s always difficult to know exactly why the stock market is falling (or if a decline is even based on a reasonable interpretation of macro events). But it’s a safe bet that rising investor anxiety over the outlook for the US economy is a contributing factor in the recent slide. It’s debatable if the haircut is overdone, although it’s clear that an attitude adjustment on US economic prospects is front and center in the crowd’s thinking.

Estimates of near-term growth have softened lately, such as this week’s review of nowcasts for the upcoming fourth-quarter GDP report.  Yet recession risk remains low, based on the data published to date. The near-term outlook offers a similar profile. In short, the deceleration in the macro trend for the US doesn’t appear destined to deteriorate into a contraction in the immediate future, at least not yet.

The macro calculus could change, of course, depending on the incoming data. But using the results available today strongly suggests that there’s still a healthy tailwind, albeit a tailwind that’s lost momentum lately.

Surprising? Not really. The Capital Spectator’s read on the numbers has been noting for several months that US growth has peaked (see here and here, for instance). The latest run of data continues to support this view. The same can be said for projecting slower but still-moderate growth for early 2019. Leaving aside the dubious game of speculating on what might happen deep into next year, it’s fair to say that the numbers available right now (along with cautious near-term projections of the macro trend) continue to anticipate that a moderate expansion will prevail.

Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno

Let’s start by looking at what just happened. A broad set of indicators reflects a virtually nil probability that a new NBER-defined downturn began in November. (For a more comprehensive review of the macro trend with weekly updates, see The US Business Cycle Risk Report.) Based on this data, the Dec. 24 update of the Chicago Fed’s National Activity Index (via the three-month average) for November will likely confirm that recession risk remained low last month.

Aggregating the data in the table above continues to indicate a positive trend overall through last month, albeit a trend that’s downshifted through most of this year. Despite the deceleration, 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 fall below those tipping points, the declines will mark warning signs that recession risk is elevated and a new downturn has started or is near. The analysis is based on a methodology that’s profiled in my book on monitoring the business cycle.

Although ETI and EMI remain in positive terrain,  both indexes have been falling in 2018, as shown in the chart below. The deceleration may run its course at some point and stabilize, and so its premature to read too much into the downside bias at this point. As the historical record for these indexes reminds, periods of deceleration can sometimes be temporary affairs that eventually lead to rebounds rather than recessions.

Translating ETI’s historical values into recession-risk probabilities via a probit model 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 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 2019. (Note that September 2018 is currently the latest month with a complete set of published data for ETI.) Based on today’s projections, ETI is expected to remain above its danger zone through next month. Nonetheless, the ongoing slide in ETI  warrants monitoring because the possibility exists that the index will fall through the critical 50% mark at some point in 2019, which would indicate the start of a new NBER-defined recession.

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, based on 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 in the immediate future. The chart also shows 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 ETI forecasts, here are the vintage projections in the past three months:

23 November 2018
19 October 2018
20 September 2018

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.