Ceridan-UCLA Index: Negative Trend Continues December 2011

The Ceridian-UCLA Pulse of Commerce Index™ (PCI) rose 0.2 percent in December following the 1.1 percent increase in October and a 0.1% increase in November. Econintersect uses the PCI raw data to help forecast Main Street economy – and our analysis is that the index is Down 2.74% month-over-month and down 3.7% year-over-year.

The data has been in a long term “less good” trend – but the November data continues to confirm the downward trend in the data has been broken.

Both the authors of Pulse of Commerce Index and Econintersect see diesel consumption as an important economic pulse point. Both use the data in different ways, apply different methodologies to analyze the data, and offer slightly different conclusions

According to the economists at the UCLA Anderson School of Economics:

With all three months of the fourth quarter now available, we are able to make an informed assessment of the likely rate of growth of fourth quarter GDP. The fourth quarter PCI was up over the third quarter; but only by 0.5 percent at an annualized rate. The good news here is that this positive 0.5 percent growth of rate for the PCI in the fourth quarter was much better than the third quarter, which suffered a decline at an annualized rate of 4.2 percent.  The PCI annualized rate of growth of 0.5 percent in the fourth quarter is consistent with an estimated GDP growth in the range of 0–2 percent.

Although Wall Street economists have jacked up their “backcasts” for fourth quarter GDP growth to 3 percent or higher, the fundamentals as indicated by the fourth-quarter PCI are not so favorable.  Many of these Wall Street economists are basing their improved forecasts on expectations regarding a healthy contribution of inventories to GDP growth. The PCI does not support this view. The PCI measures inventories destined for factories, stores and homes, and the third quarter decline in the PCI correctly anticipated the large negative contribution of inventories to GDP growth. The BEA estimate of the inventory contribution to GDP growth for the third quarter has been varying around -1.5 percent as the data are revised, and is currently at -1.4 percent.  That is almost as large as the estimated GDP growth of 1.8 percent. Absent that inventory negative, the rate of growth would have been 2.2 percent.

The fourth quarter PCI of plus 0.5 percent suggests only a modest positive contribution of inventories in the fourth quarter, which implies a GDP forecast that is not as optimistic as many Wall Street economists.  However, with real retail sales growing more rapidly than the PCI over the last two quarters, the first half of next year may be an inventory-rebuilding period, allowing inventories to make a substantial contribution to GDP growth. This would be very supportive of the recent improvement in the labor market, which may finally be entering a positive-feedback loop during which more jobs help create even more jobs.

The weakness in the PCI this month translates into continued weakness in the PCI-based forecast for Industrial Production. The predicted value for December’s Industrial Production based on the PCI is 0.3 percent.

The transport network in the USA is almost exclusively fueled by diesel – and diesel consumption makes a good proxy for forward economic activity (as transport occurs, on average, one to two months before consumption). Caveat is that this index is based on road use of diesel.

The PCI is modeled using Ceridian’s diesel distribution network to forecast economic growth – primarily Industrial Production and GDP. Econintersect extracts the unadjusted (not modeled) diesel index for its economic model. Graphically, the unadjusted data has a slightly different feel.

Both the three month moving average and the December 2011 growth is negative.  The size of the negative data in December is a concern – and also shows an 18 month negative trend line which is now negative.  Rail data for December is strongly positive, so I would tend to discount the negative implications of this data.

I will revisit this analysis if other transport data are negative in December.

Caveats on the Use of this Index

This is a post Great Recession index which has little real time history on foretelling economic activity. This model works in hindsight. A positive point for this index is that there is usually little backward revision.

Diesel consumption per ton mile is improving at rate which Econintersect has no means to quantifying in the U.S. But on a global basis, this improvement is likely well over 1% and could be as high as 5% per year such as:

  • There have been significant inroads for fuel conservation by placing trailers on higher efficiency railroads;
  • There has been some conversion of diesel trucks to using LPG;
  • Not only has current environmental standards forced conversion to more efficient diesel technology – the rising price of diesel alone has forced truckers to upgrade to the higher efficiency trucks / engines / trailers/ use management;

  • Tractor design continues towards more aerodynamic design.

Although it is true that diesel moves the goods necessary for the economy, using diesel data without an efficiency adjustment likely will provide incorrect conclusions. Therefore, it is trend lines, not specific values, which are important. It is very likely this index is UNDERSTATING the economy by an amount equal to the indeterminate efficiency improvement rate.

Monthly diesel use can vary with the weather or other natural causes making is index noisy. For this reason, Econintersect uses the three-month moving average for modeling economic activity.

The PCI diesel consumption is based on roadway diesel sales – not railroads, sea or air transport. The Achilles heel of this index might be its inability to adjust for alternative non-truck transport.

Econintersect determines the month-over-month change by subtracting the current month’s year-over-year change from the previous month’s year-over-year change. This is the best of the bad options available to determine month-over-month trends – as the preferred methodology would be to use multi-year data (but the New Normal effects and the Great Recession distort historical data).

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