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The Recession Warning With an Asterisk

By RecessionALERT on February 25, 2026 in Reflections

For over 2 years now, our commentary has made the point that the labor market – more particularly Payroll Employment and the Employment Level household surveys – were the “last man standing” in a sea of negative or weak leading data. For this reason, the NBER coincident models (all 3 of them) were not confirming recession. However the latest Friday BLS downward revisions, on top of countless before them, are becoming the straw that could break the camels’ back. The […]

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U.S economy almost back to par growth

By RecessionALERT on March 25, 2012 in Reflections

The U.S Coincident SuperIndex, which estimates U.S economic current growth, is within a whisker of returning to the growth rate normally averaged by the economy after 33 months into an expansion, as shown by the chart on the left. However, cumulative growth since the start of the expansion still remains sub-par (right chart) due to 22 months of sub-par growth. The recent 5 months of growth, coupled with almost reaching the par growth level are encouraging, but the sub-par cumulative expansion […]

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IMPORTANT DISCLAIMERS: Although many of our models rely heavily on back-testing, optimisation and probability methods, please note that past performance is NO GUARANTEE for future returns. No system devised by man can predict the future, let alone the future of the markets and economies. What we have are sets of mathematical models that use historical data and varying theories to pinpoint places in time when the STATISTICAL LIKELYHOOD of calling the start and end to recessions is the greatest. In the midst of all the best mathematical models, you can have geo-political events, wars, terrorist attacks, natural disasters and even nuclear accidents that tip everything upside down. This is always a risk factor you need to factor in on any recession call no matter how confident you are in a signal. The SuperIndexes are created through mathematical and statistical optimisation techniques that best fit the historical NBER data. There is no guarantee that out-of-sample performance will match that of prior in-sample performance.