No. 607: February Employment and Unemployment, January Trade

COMMENTARY NUMBER 607
February Employment and Unemployment, January Trade

March 7, 2014

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Payroll Jobs Increased by 175,000, but the Number Employed Rose by 42,000;
Neither February 2014 Statistic Was Meaningful

Deliberate Misreporting Showed December Payrolls up by 84,000,
Where 67,000 Was the Consistent Number

February Unemployment: 6.7% (U.3), 12.6% (U.6), 23.2% (ShadowStats)

January Trade Data Hint at Troubled First-Quarter GDP

Year-to-Year M3 Growth Rose to 3.5% in February

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PLEASE NOTE: The next regular Commentary is scheduled for Thursday, March 13th, covering February 2014 retail sales. Publication of the expanded Special Commentary on 2013 GAAP accounting for the U.S. government and the Second Installment on the hyperinflation report also are planned in the week ahead.

ERRATA: As noted by several subscribers, yesterday’s Commentary No. 606, with initial estimates of GAAP-based accounting detail on the government’s fiscal operations, had a number of typos with intermittent misuse of “trillion” or “billion.” I apologize for the poor editing job and for any confusion it may have caused. The text for No. 606 has been corrected and re-posted.

Best wishes to all — John Williams

OPENING COMMENTS AND EXECUTIVE SUMMARY

Nothing Here Suggests a Pending Economic Rebound. Today’s (March 7th) reporting of February 2014 employment and unemployment detail still were consistent with a renewed slowing in economic activity. Where payrolls rose more than expected, the data were not meaningful. Where the unemployment rate rose unexpectedly, the numbers there were not meaningful, either. Of some substance, the year-to-year growth in not-seasonally-adjusted payrolls slowed markedly.

The trade balance reporting for January 2014 did not have large enough revisions in December and before to have meaningful impact on the second revision to fourth-quarter 2013 GDP, but the initial reporting of the January 2014 deficit was not a good sign for first-quarter GDP. If February’s number comes in close to January’s, then those two numbers will set the initial net-export-account reporting for the GDP, with a trade-deficit widening large enough to take roughly one-percent growth out of the “advance” first-quarter GDP estimate, due on April 30th.

Troubled Employment and Unemployment Reporting. The Bureau of Labor Statistics (BLS) deliberately publishes its seasonally-adjusted historical payroll-employment and household-survey (unemployment) data so that the numbers are neither consistent nor comparable with current headline reporting. The issues here have the potential of enabling near-term manipulation of the headline labor data, should someone choose to do so. The problems are discussed in the Concurrent Seasonal Factor Distortions segment of the Reporting Detail section.

This morning’s headline story that seasonally-adjusted unemployment rose to 6.7% in February, from 6.6% in January, is nonsense. January’s headline unemployment rate was recalculated and revised, along with the estimation process that was used in generating the February number. Where February’s headline rate was 6.7%, the revised January number could have been 6.5%, 6.7%, 6.9% … no one but the BLS knows for sure, and the BLS is not talking. It deliberately will not publish consistent prior numbers, for the expressed fear of “confusing” data users.

The same basic issues affect headline payroll-employment reporting. Where all recent headline employment numbers are recalculated along with estimation of the latest headline data, only two monthly changes are consistent. The estimate of seasonally-adjusted February payrolls at 137,699,000, up by 175,000 from a revised 137,524,000 in January, which was up by 129,000 from a revised 137,395,000 in December are the only numbers that are consistent and comparable in their current form. All the earlier numbers also were revised, but the changes were not published. Unlike the household survey, though, the BLS provides enough modeling detail for the payroll survey so that a third party can calculate earlier data on a consistent basis. ShadowStats affiliate ExpliStats.com does that.

The difference in the latest numbers is that the BLS will tell you today that December 2013 payrolls were up by 84,000 from an unrevised 137, 311,000 in November. When the February 2014 recalculations were done, however, the payroll gain in December—consistent with February 2014 reporting—was a 67,000 gain, versus a revised 137,328,000 employment level in November, not the current, artificially frozen headline December gain of 84,000 against a frozen, official payroll level of 137,311,000 in November.

The point remains that the seasonally-adjusted headline reporting here is of little substance. Not seasonally-adjusted data, however, are free of these distortions. On a year-to-year basis, the unadjusted annual payroll growth slowed to 1.54%, its lowest level in a year.

Headline Unemployment Rates—February 2014. Skewed by ongoing issues with unstable seasonal adjustments, headline unemployment (U.3) rose by 0.14-percentage point to 6.72% in February 2014, from 6.58% in January, technically a statistically-insignificant increase.

On an unadjusted basis, the unemployment rates are not revised and are consistent in reporting methodology. February’s unadjusted U.3 unemployment rate held even at 7.0% versus January.

U.6 Unemployment Rate. The broadest unemployment rate published by the BLS, U.6 includes accounting for those marginally attached to the labor force (including short-term discouraged workers) and those who are employed part-time for economic reasons (i.e., they cannot find a full-time job).

A seasonally-adjusted and otherwise meaningless month-to-month decline in people working part-time for economic reasons and in short-term (unadjusted) discouraged workers, more than offset the increase in the headline U.3 unemployment, with the headline February 2014 U.6-unemployment at 12.6%, versus 12.7% in January. The unadjusted February U.6 rate dropped to 13.1%, from 13.5% in January.

Discouraged Workers. The count of short-term discouraged workers (never seasonally-adjusted) was 755,000 in February 2014, versus 837,000 in January. The discouraged worker count continues to reflect an increased rollover of short-term discouraged workers into the long-term discouraged workers category.

The current, official discouraged-worker number reflected the flow of the unemployed—increasingly giving up looking for work—leaving the headline U.3 unemployment category and being rolled into the U.6 measure as short-term “discouraged workers,” net of those moving from short-term discouraged-worker status into the netherworld of long-term discouraged-worker status. It is the long-term discouraged-worker category that defines the ShadowStats-Alternate Unemployment Measure. There appears to be a relatively heavy, continuing rollover from the short-term to the long-term category.

In 1994, “discouraged workers”—those who had given up looking for a job because there were no jobs to be had—were redefined so as to be counted only if they had been “discouraged” for less than a year. This time qualification defined away a large number of long-term discouraged workers. The remaining short-term discouraged workers (those discouraged less than a year) were included in U.6. More-complete definitions—including discussion on the increasing divergence between the ShadowStats number and U.3 and U.6—are found near the end of the Reporting Detail section.

The first graph following reflects headline February 2014 U.3 unemployment at 6.7%, up from 6.6% in January; headline U.6 unemployment at 12.6% in February 2014, versus 12.7% in January; and the headline ShadowStats unemployment measure holding at 23.2% in February 2014, versus January. The October 2013 ShadowStats reading of 23.4% was the series high (since 1994).

Two graphs follow. The first is of the ShadowStats unemployment measure, with an inverted scale. The higher the unemployment rate, the weaker will be the economy, so the inverted plot tends to move in tandem with plots of most economic statistics, where a lower number means a weaker economy.

The inverted-scale ShadowStats unemployment measure also tends to move with the employment-to-population ratio, which is plotted in the second graph following. Discouraged workers are not counted in the headline labor force, which continues to shrink. The labor force containing all unemployed (including total discouraged workers) plus the employed, however, tends to be correlated with the population, so the employment-to-population ratio tends to be something of a surrogate indicator of broad unemployment, and it has a strong correlation with the ShadowStats unemployment measure.

These graphs reflect detail back to the 1994 redefinitions of the household survey. Before 1994, data consistent with today’s reporting are not available.

Headline Payroll Employment—February 2014. The February payroll data were in the context of the revamped payroll series introduced in the benchmark revision of a month ago, as discussed in Commentary No. 598. The seasonally-adjusted, month-to-month headline payroll employment gain for February was a gain of 175,000, which was above market consensus, near the BLS trend model.

In turn, January payrolls rose by a revised 129,000, where December rose by a revised 84,000 versus November, but the December gain became non-comparable and inconsistent with the November data, as of the February reporting (December should have shown a 67,000 gain).

Annual Change in Payrolls. Not-seasonally-adjusted, year-to-year change in payroll employment is untouched by the concurrent-seasonal-adjustment issues, so the monthly comparisons of year-to-year change are reported on a consistent basis. The first reporting since the redefinition of the series last month (January reporting) showed a sharp slowing in annual growth. As noted last month, the redefinition of the series—not the standard benchmarking process—boosted reported annual growth in the last year, as discussed and graphed in the benchmark detail of Commentary No. 598. For February 2014, annual growth was 1.54%, the weakest annual growth since February 2013, and down from a revised 1.77% in January 2014, and an unrevised 1.71% in December 2013. Graphs of year-to-year payroll change are found in the Reporting Detail section

With the bottom-bouncing patterns of recent years, current annual growth has recovered from the post-World War II record 5.02% decline seen in August 2009. That 5.02% year-to-year decline remains the most severe annual contraction since the production shutdown at the end of World War II (a 7.59% annual decline in September 1945). Disallowing the post-war shutdown as a normal business cycle, the August 2009 annual decline was the worst since the Great Depression.

Still, even with the annual growth in the series since mid-2010 and the upside redefinition of payroll employment, the February 2014 level of employment still is shy by 666,000 jobs, or 0.5% in official reporting, from recovering its pre-recession high. The pre-recession high likely would be hit in the next four-to-five months, barring the economy turning lower in a renewed recession, which it appears to be doing.

The narrowing gap versus the pre-recession high (with levels all favorably redefined with the January benchmarking, despite the actual benchmarking having been negative) can be seen in the following shorter-term graph of payroll employment level. In perspective, the longer-term graph of the employment level shows the extreme duration of the non-recovery in payrolls, the worst such circumstance of the post-Great Depression era.

January 2014 Trade Deficit Threatens First-Quarter 2014 GDP Growth. Initial quarterly estimates of GDP are based on only two months of trade data for a given quarter. If the February 2014 trade number should come in at the same level as the January 2014 number, the January and February trade detail could reduce the headline growth rate for the initial first-quarter GDP estimate (April 30th) by one-percent or so from what it would have otherwise.

The headline annual trade deficit for goods and services in 2013 widened in revision by $3.3 billion, to $474.9 billion from $471.5 billion. Only $0.3 billion of that was recast into a widening of the December 2013 deficit to a revised $39.0 billion, from initial reporting of $38.7 billion. The rest of the difference was distributed into each of the other months in 2013, with the bulk of the added trade shortfall being appended to third- and fourth-quarter 2013 activity.

Otherwise, the $0.1 billion headline monthly widening of the January 2014 headline trade deficit to $39.1 billion reflected largely offsetting small gains to exports and imports, with imports gaining about $0.1 billion more for the month than exports.

Nominal (Not-Adjusted-for-Inflation) January Trade Deficit. The headline nominal, seasonally-adjusted monthly trade deficit in goods and services for January 2014, on a balance-of-payments basis, widened minimally to $39.095 billion from a revised $38.975 billion in December 2013, but narrowed from a revised $42.139 billion in January 2013.

Real (Inflation-Adjusted) January 2014 Trade Deficit. Adjusted for seasonal factors, and net of oil-price swings and other inflation (2009 chain-weighted dollars, used for GDP deflation), the January 2014 merchandise trade deficit (no services) narrowed to $48.525 billion, from a revised $49.236 in December, and versus a revised $49.022 billion in January 2013.

The actual deficit now reported for fourth-quarter 2013 annualizes out to a revised $564.7 (previously $565.8), where the third-quarter annualizes out to an unrevised $583.4. The revisions here are small enough so as to indicate no further significant trade-deficit related revision in the second revision to fourth-quarter 2013 GDP due for release on March 28th.

The news, however, is not so happy for the first-estimate of first-quarter 2014 GDP, due on April 30th. Where the headline deficit of $48.525 in January 2014 annualizes out to a $582.3 billion deficit for the first-quarter, a similar reading in February—the last reading before the GDP estimate—would suggest that a widening of the first-quarter trade deficit could knock a full percentage point off the headline GDP growth.

[For greater detail on February labor conditions, and on the January trade numbers,
see the Reporting Detail section.]

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HYPERINFLATION WATCH

Money Supply and the Monetary Base. Annual growth in February 2014 M3 is on track to rebound to 3.5%, from a revised 3.1% (previously 3.0%) in January and from an unrevised 3.2% in December. Monthly year-to-year growth had held at or above 4.0% for the year before December 2012. The M3 initial estimate of February growth will be posted on the Alternate Data tab of www.shadowstats.com by the end of the day on March 8th.

Any revisions in the following numbers are due to the revisions of underlying data by the Federal Reserve. The seasonally-adjusted, preliminary estimate of month-to-month change for February 2014 money supply M3 is on track for a 0.6% gain, versus a revised 0.4% (previously 0.3%) gain in January. Estimated month-to-month M3 changes, however, remain less reliable than are the estimates of annual growth.

Initial Growth Estimates for February M1 and M2. For February 2014, early estimates of year-to-year and month-to-month changes follow for the narrower M1 and M2 measures (M2 includes M1, M3 includes M2). Full definitions of the measures are found in the Money Supply Special Report. M2 for February 2014 is estimated to have shown year-to-year growth of roughly 6.3%, versus a revised 5.4% (previously 5.2%) in January, with month-to-month change estimated at roughly a 0.9% gain in February, versus a revised 0.5% (previously 0.2%) gain in January. The early estimate of M1 for February is for year-to-year growth of roughly 9.9%, versus a revised 8.9% (previously 8.3%) in January, with a month-to-month February gain of 1.3%, versus a revised 1.3% (previously 0.8%) gain in January.

St. Louis Fed’s Monetary Base Hits Historic High. Mirroring ongoing QE3 quantitative-easing activity, the monetary base has continued in uncharted territory in terms of historical level, despite two incremental rounds of tapering, minor pullbacks the Fed’s purchases of Treasury securities. Year-to-year growth for the near-term cycle, however, is topping out at the moment, since the year-ago comparison is taking in the initial monetary base pick-up from the expansion of QE3 at the onset of 2013.

As shown in the accompanying graphs, the monetary base (St. Louis Fed) was at a seasonally-adjusted (SA) two-week average level of $3,897.6 billion as of March 5th, an all-time high, with year-to-year growth at 33.7%. The latest of the regular fortnightly data are reflected in the next two graphs following.

Hyperinflation Outlook. With the First Installment of Hyperinflation 2014—The End Game Begins published, a new Hyperinflation Summary for this section will be added in conjunction with the publication of the Second Installment, which is planned in the week ahead. The second and final installment will cover historical and prospective economic activity, as well as possible protective and preventative actions and reactions at both a personal and federal level, versus the unfolding circumstance. It also will include new analysis of the 2013 GAAP-based financial statements of the United States government (released February 27th) and detail from the Federal Reserve’s 2013 annual flow-of-funds analysis (released on March 6th). The new material in the Second Installment will supplement and update the basic material already available to ShadowStats readers in Chapters 4, 5 and 9 of Hyperinflation 2012.

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REPORTING DETAIL

EMPLOYMENT AND UNEMPLOYMENT (February 2014)

Reporting-Quality Issues Surface Anew. The Bureau of Labor Statistics (BLS) deliberately publishes its seasonally-adjusted historical payroll-employment and household-survey (unemployment) data so that the numbers are neither consistent nor comparable with current headline reporting. The problems here are discussed in the Concurrent Seasonal Factor Distortions section. Today’s (March 7th) headline story that seasonally-adjusted unemployment rose to 6.7% in February from 6.6% in January is nonsense. January’s headline unemployment rate was recalculated and revised, along with the estimation process that was used in generating the February number. Where February’s headline rate was 6.7%, the revised January number could have been 6.5%, 6.7%, 6.9% … no one but the BLS knows for sure, and the BLS is not talking. It deliberately will not publish consistent prior numbers, for fear of “confusing” data users.

The same basic issues affect headline payroll-employment reporting. Where all recent headline employment numbers are recalculated along with estimation of the latest headline data, only two monthly changes are consistent. The estimate of seasonally-adjusted February payrolls at 137,699,000, up by 175,000 from a revised 137,524,000 in January, which was up by 129,000 from a revised 137,395,000 in December are the only numbers that are consistent and comparable in their current form. All the earlier numbers also were revised but the changes were not published. Unlike the household survey, though, the BLS provides enough modeling detail for the payroll survey so that a third party can calculate earlier data on a consistent basis. ShadowStats affiliate ExpliStats.com does that.

The difference in the latest numbers is that the BLS will tell you today that December 2013 payrolls were up by 84,000 from an unrevised 137, 311,000 in November. When the February 2014 recalculations were done, though, the payroll gain in December—consistent with February 2014 reporting—was a 67,000 gain, versus a revised 137,328,000 employment level in November, not the current, artificially frozen headline December gain of 84,000 against a frozen, official payroll level of 137,311,000 in November.

PAYROLL SURVEY DETAIL. The February 2014 payroll data were published today, March 7th by the Bureau of Labor Statistics (BLS) and are in the context of the revamped payroll series introduced in the benchmark revision of a month ago, as discussed in Commentary No. 598. The seasonally-adjusted, month-to-month headline payroll employment gain for February was a gain of 175,000 +/- 129,000 (95% confidence interval), which was above market consensus, near the BLS trend model. Reporting issues, however, suggest that a 95% confidence interval of +/- 200,000 could be justified. The current numbers continue to be so far out of balance as to be absolutely meaningless, here, due partially to concurrent-seasonal-factor distortions.

In turn, January payrolls rose by a revised 129,000 (previously 113,000), where December rose by a revised 84,000 (previously 75,000) versus November, but the December gain became non-comparable and inconsistent with the November data, as of the February reporting (December should have shown a 67,000 gain).

In addition to bogus upside bias factors, an ongoing reporting problem here remains that the BLS publishes only two prior months of consistent data with the concurrent-seasonally-adjusted payrolls. Accordingly, where the published December number no longer is consistent with November reporting, related month-to-month comparisons have no meaning, given the BLS adjustment and reporting policies discussed in Concurrent Seasonal Factors Distortions. This also is an issue related to the household-survey reporting of the unemployment rate, where there is no attempt to publish any comparable month-to-month numbers, except for once-per-year annual revisions to the seasonally-adjusted data in December. The problem is that the all recent seasonally-adjusted data are revised every month, but the revisions are not published, even though the headline reporting is in the context of those changes.

Where the actual concurrent-seasonally-adjusted payroll data by month can be calculated for the payrolls, based on modeling detail made available by the BLS, ShadowStats affiliate ExpliStats.com was able to estimate the consistent, actual revised (but not published) month-to-month gain for December 2013 versus November, was 67,000, instead of the headline 84,000. The 17,000 differential is noticeable in the latest graph of the concurrent-seasonal-factor distortions, the section by the same name.

“Trend Model” Beat the Consensus on the Headline Payroll Gain. As discussed in Commentary No. 605, and as generally described in Payroll Trends, the trend indication from the BLS’s concurrent-seasonal-adjustment model—prepared by our affiliate www.ExpliStats.com —indicates the March 2014 monthly payroll change as a 178,000 gain, based on the trend structured by BLS modeling of February’s reporting.

The trend indication sometimes hit, sometimes misses the actual headline reporting. For example, the trend indication for February 2014 was for a 183,000 monthly gain, where market consensus purportedly was looking for something 40,000 to 50,000 jobs below that. With the actual headline number at 175,000, the trend indication was closer to the headline number than was the market consensus. In more-normal economic times, the trend number becomes the basis for the consensus outlook, more often than not.

Construction Payrolls. The accompanying graph of construction employment updates the graph accompanying the coverage of January 2014 construction spending in Commentary No. 605. In the context of prior-period revisions, headline February 2014 construction employment rose by 15,000 in the month, versus an upwardly revised 50,000 (previously 48,000) in January and a revised 20,000 (previously 22,000) headline jobs loss in December. Total February construction jobs still were 23.1% shy of the pre-recession peak for the series in April 2006.

Annual Change in Payrolls. Not-seasonally-adjusted, year-to-year change in payroll employment is untouched by the concurrent-seasonal-adjustment issues, so the monthly comparisons of year-to-year change are reported on a consistent basis. The first reporting since the redefinition of the series last month (January reporting) showed a sharp slowing in annual growth. As noted last month, the redefinition of the series—not the standard benchmarking process—boosted reported annual growth in the last year, as discussed and graphed in the benchmark detail of Commentary No. 598. For February 2014, annual growth was 1.54%, the weakest annual growth since February 2013, and down from a revised 1.77% (previously 1.74%) in January 2014, an unrevised 1.71% in December 2013, and an unrevised 1.85% in November.

With the bottom-bouncing patterns of recent years, current annual growth has recovered from the post-World War II record 5.02% decline seen in August 2009, as shown in the accompanying graphs. That 5.02% decline remains the most severe annual contraction since the production shutdown at the end of World War II (a trough of a 7.59% annual contraction in September 1945). Disallowing the post-war shutdown as a normal business cycle, the August 2009 annual decline was the worst since the Great Depression.

The narrowing gap versus the pre-recession high (with levels all favorably redefined with the January benchmarking, despite the actual benchmarking having been negative) can be seen in the shorter-term graph of payroll employment level (see Opening Comments). In perspective, the longer-term graph of the employment level shows the extreme duration of the non-recovery in payrolls, the worst such circumstance of the post-Great Depression era.

Concurrent Seasonal Factor Distortion. There are serious and deliberate reporting flaws with the government’s seasonally-adjusted, monthly reporting of employment and unemployment. Each month, the BLS uses a concurrent-seasonal-adjustment process to adjust both the payroll and unemployment data for the latest seasonal patterns. As each series is calculated, the adjustment process also revises the history of each series, recalculating prior reporting, for every month, on a basis that is consistent with the new seasonal patterns of the headline numbers.

The BLS, however, uses the current estimate but does not publish the revised history, even though it calculates the consistent new data each month. As a result, headline reporting generally is neither consistent with, nor comparable to earlier reporting, and month-to-month comparisons of these popular numbers usually are of no substance, other than for market hyping or political propaganda.

The BLS explains that it avoids publishing consistent, prior-period revisions so as not to “confuse” its data users. No one seems to mind if the published earlier numbers are wrong, particularly if unstable seasonal-adjustment patterns have shifted prior jobs growth or reduced unemployment into current reporting, without any formal indication of the shift from the previously-published historical data.

February 2014 Inconsistencies. Despite the one-month of revisions each year, as in December 2013, when recent history was restated on a consistent basis, all the monthly unemployment-related data became inconsistent again with the January 2014 reporting.

While the 175,000 nonfarm payroll jobs gain reported for February 2014 was consistent with the revised 129,000 jobs in January, it was not consistent with the revised 84,000 increase in December. The number consistent the February concurrent-seasonal-adjustment factors show the revised December increase to be 67,000, instead of the 84,000. The February 2014 number also is not consistent with November 2013 or with any other earlier published data.

Payroll Growth Is Consistent Only One-Month Back, With Heavy Distortions Usual. With the payroll series, the level of payrolls is released for the headline month, and for the two prior months, on a consistent basis. That means that only the current headline month-to-month change and the change for the prior month are consistent and comparable. Unlike the household-survey circumstance, however, the BLS makes available the seasonal-adjustment models and data so that others can calculate the payroll revisions. ExpliStats.com has done so for the accompanying graph.

The graph reflects the reset of all the prior year’s data based on the March 2013 revision of last month, with distortions already in place for the first and second months published (January and February 2014) being plotted.

The differences by month reflect current headline reporting versus whatever that data show for the actual, consistent, seasonally-adjusted numbers, each month. Without the BLS’s deliberate reporting distortions, the plotted lines would be flat and at zero.

Distortions in the current post-benchmark environment are evident, even though the first data were based on the initial public reporting of the benchmark revision. The reason for this is that the BLS actually runs the benchmark revision, internally, based on October numbers. With subsequent internal runs in November, December and January, the new accounting will encompass and be skewed by three months of revisions, now four months, with February

Note: Issues with the BLS’s concurrent-seasonal-factor adjustments and related inconsistencies in the monthly reporting of the historical time series are discussed and detailed further in the ShadowStats.com posting on May 2, 2012 of Unpublished Payroll Data.

Birth-Death/Bias-Factor Adjustment. Despite the ongoing, general overstatement of monthly payroll employment, the BLS adds in upside monthly biases to the payroll employment numbers. The continual overstatement is evidenced usually by regular and massive, annual downward benchmark revisions (2011 and 2012, excepted). As discussed in the benchmark detail of Commentary No. 598, the regular benchmark revision to March 2013 payroll employment was to the downside by 119,000, where the BLS had overestimated standard payroll employment growth. At the same time, the BLS separately redefined the payroll survey so as to include 466,000 workers who had been in a category not previously counted in payroll employment. The latter event was little more than a gimmicked, upside fudge-factor, used to mask the effects of the regular downside revisions to employment surveying, and likely is the excuse behind the increase in the annual bias factor, where the new category cannot be surveyed easily or regularly by the BLS.

Indeed, particularly unusual here is that despite the BLS modeling having overstated recent jobs creation by 119,000, adjustment to the annual upside biases added into payroll estimation process each month was increased by about 180,000 on an annual basis, instead of being reduced, which would have been expected otherwise.

Historically, the upside-bias process was created simply by adding in a monthly “bias factor,” so as to prevent the otherwise potential political embarrassment to the BLS of understating monthly jobs growth. The “bias factor” process resulted from such an actual embarrassment, with the underestimation of jobs growth coming out of the 1983 recession. That process eventually was recast as the now infamous Birth-Death Model (BDM), which purportedly models the effects of new business creation versus existing business bankruptcies.

February 2014 Bias. The not-seasonally-adjusted February 2014 bias was a monthly add-factor of plus 124,000, versus what had been a plus 102,000 in February 2013, versus a minus 307,000 add-factor in January 2013. The aggregate upside bias for the trailing twelve months was raised to 806,000, as best can be estimated, from the pre-benchmark 624,000 twelve-month aggregate as of December 2013, or to a monthly average of 67,000 (previously 52,000) jobs created out of thin air, on top of some indeterminable amount of other jobs that are lost in the economy from business closings. Those losses simply are assumed away by the BLS in the BDM, as discussed below.

Problems with the Model. The aggregated upside annual reporting bias in the BDM reflects an ongoing assumption of a net positive jobs creation by new companies versus those going out of business. Such becomes a self-fulfilling system, as the upside biases boost reporting for financial-market and political needs, with relatively good headline data, while often also setting up downside benchmark revisions for the next year, which traditionally are ignored by the media and the politicians. Where the BLS cannot measure meaningfully the impact of jobs loss and jobs creation from employers starting up or going out of business, on a timely basis (within at least five years, if ever), or by changes in household employment that just have been incorporated into the redefined payroll series, such information is guesstimated by the BLS along with the addition of a bias-factor generated by the BDM.

Positive assumptions—commonly built into government statistical reporting and modeling—tend to result in overstated official estimates of general economic growth. Along with these happy guesstimates, there usually are underlying assumptions of perpetual economic growth in most models. Accordingly, the functioning and relevance of those models become impaired during periods of economic downturn, and the current, ongoing downturn has been the most severe—in depth as well as duration—since the Great Depression.

Indeed, historically, the BDM biases have tended to overstate payroll employment levels—to understate employment declines—during recessions. There is a faulty underlying premise here that jobs created by start-up companies in this downturn have more than offset jobs lost by companies going out of business. So, if a company fails to report its payrolls because it has gone out of business (or has been devastated by a hurricane), the BLS assumes the firm still has its previously-reported employees and adjusts those numbers for the trend in the company’s industry.

Further, the presumed net additional “surplus” jobs created by start-up firms are added on to the payroll estimates each month as a special add-factor. These add-factors are set now to add an average of 67,000 jobs per month in the current year. The aggregate average overstatement of employment change easily exceeds 100,000 jobs per month.

HOUSEHOLD SURVEY DETAILS. Generally, the seasonally-adjusted household-survey data are worthless. The monthly concurrent-seasonal-factor adjustment process used in generating the headline numbers regenerates all seasonal factors every month, unique to the most recent month. Yet, the revamped and consistent historical detail is not published, except once per year, in December. All the historical data shift anew with the subsequent January reporting, but that new detail never is published.

Where, for example, the seasonally-adjusted headline unemployment rate for February 2014 of 6.72% was based on a set of seasonal adjustments unique to February 2014, and the adjusted unemployment rate for January was revised along with the February seasonal-adjustment calculations, the new historical result for January was not published. The prior headline reporting of 6.58% for the January 2014 unemployment rate remained in place, although it was inconsistent with the February 2014 number. This is true for every month going back for at least five years of BLS accounting, and it is allowed deliberately by the BLS, even though consistent, historical data are calculated by and known to the Bureau.

Headline Household Employment. The household survey counts the number of people with jobs, as opposed to the payroll survey that counts the number of jobs (including multiple job holders more than once). On that basis, headline February 2014 employment rose by just 42,000 for the month, versus a 523,000 month-to-month increase in January, and today’s headline increase of 175,000 in payroll jobs. Again, the household-survey numbers simply are not comparable month-to-month on a meaningful basis.

Headline Unemployment Rates. Skewed by ongoing issues with seasonal adjustments, headline unemployment (U.3) rose by 0.14-percentage point to 6.72% in February 2014, from 6.58% in January, technically a statistically-insignificant increase. The official 95% confidence interval around the monthly change in the headline U.3 rate is +/- 0.23-percentage point. That is meaningless, however, in the context of the comparative month-to-month reporting-inconsistencies created by the concurrent seasonal factors.

On an unadjusted basis, the unemployment rates are not revised and are consistent in reporting methodology. February’s unadjusted U.3 unemployment rate held at 7.0% versus January, up from 6.5% in December, 6.6% in November and versus 7.0% in October.

ShadowStats-Alternate Unemployment Rate. Adding back into the total unemployed and labor force the ShadowStats estimate of the growing ranks of excluded, long-term discouraged workers, broad unemployment—more in line with common experience, as estimated by the ShadowStats-Alternate Unemployment Measure—held at 23.2% in February 2014, the same as in January. That is down minimally from 23.4% in October, which was the series high (back to 1994). The ShadowStats estimate reflects the increasing toll of unemployed leaving the headline labor force. Where the ShadowStats-alternate estimate generally is built on top of the official U.6 reporting, it tends to follow its relative monthly movements and its annual revisions. Accordingly, the alternate measure often will suffer some of the same seasonal-adjustment woes that afflict the base series, including underlying annual revisions.

As seen in the usual graph of the various unemployment measures (in the Opening Comments), there continues to be a noticeable divergence in the ShadowStats series versus U.6, and the ShadowStats series and U.6 versus U.3. The reason for this is that U.6, again, only includes discouraged workers who have been discouraged for less than a year. As the discouraged-worker status ages, those that go beyond one year fall off the government counting, even as new workers enter “discouraged” status. A similar pattern of U.3 unemployed becoming “discouraged” and moving into the U.6 category also accounts for the early divergence between the U.6 and U.3 categories.

With the continual rollover, the flow of headline workers continues into the short-term discouraged workers category (U.6), and from U.6 into long-term discouraged worker status (a ShadowStats measure). There was a lag in this happening as those having difficulty during the early months of the economic collapse, first moved into short-term discouraged status, and then, a year later into long–term discouraged status, hence the lack of earlier divergence between the series. The movement of the discouraged unemployed out of the headline labor force has been accelerating. While there is attrition in long-term discouraged numbers, there is no set cut off where the long-term discouraged workers cease to exist. See the Alternate Data tab for historical detail.

Generally, where the U.6 largely encompasses U.3, the ShadowStats measure encompasses U.6. To the extent that the decline in U.3 reflects unemployed moving into U.6, or the decline in U.6 reflects short-term discouraged workers moving into the ShadowStats number, the ShadowStats number continues to encompass all the unemployed, irrespective of the series from which they otherwise may have been ejected.

Two further related graphs found in the Opening Comments section are of the ShadowStats-Alternate Unemployment Measure, with an inverted scale, the employment-to-population ratio, which has a high correlation with the inverted ShadowStats measure.

Great Depression Comparisons. As discussed in previous writings, an unemployment rate above 23% might raise questions in terms of a comparison with the purported peak unemployment in the Great Depression (1933) of 25%. Hard estimates of the ShadowStats series are difficult to generate on a regular monthly basis before 1994, given the reporting inconsistencies created by the BLS when it revamped unemployment reporting at that time. Nonetheless, as best estimated, the current ShadowStats level likely is about as bad as the peak actual unemployment seen in the 1973-to-1975 recession and in the double-dip recession of the early-1980s.

The Great Depression unemployment rate of 25% was estimated well after the fact, with 27% of those employed working on farms. Today, less that 2% of the employed work on farms. Accordingly, a better measure for comparison with the ShadowStats number would be the Great Depression peak in the nonfarm unemployment rate in 1933 of roughly 34% to 35%.

U.S. TRADE BALANCE (January 2014)

January Trade Deficit Generates a Cautionary Signal for First-Quarter 2014 GDP Growth. Initial quarterly estimates of GDP are based on only two months of trade data for the given quarter. If the February 2014 trade number should come in at the same level as the January 2014 number, published this morning (March 7th), the January and February trade detail could reduce the headline growth rate for initial first-quarter GDP estimate (April 30th) by one-percent or so from what it would have otherwise.

Nominal (Not-Adjusted-for-Inflation) January Trade Deficit. The BEA and the Census Bureau reported today, March 7th, that the nominal, seasonally-adjusted monthly trade deficit in goods and services for January 2014, on a balance-of-payments basis, widened minimally to $39.095 billion from a revised $38.975 billion (previously $38.701 billion) in December 2013, but narrowed from an unrevised $42.139 billion in January 2013.

Energy-Related Petroleum Products. Not-seasonally-adjusted lower prices and higher physical imports of oil in January 2014 largely offset each other in aggregate trade deficit impact.

For January 2014, the not-seasonally-adjusted average price of imported oil fell to $90.21 per barrel, from $91.34 in December 2013 and against $94.08 per barrel in January 2013.

Not-seasonally-adjusted, physical oil import volume in January 2014 averaged 8.275 million barrels per day, up from 7.428 million in December, but down from 8.411 million in January 2013.

Ongoing Cautions on Data Quality. As previously discussed, potentially heavy distortions in headline data continue from seasonal adjustments, much as has been seen in other economic releases, such as retail sales and payrolls, where the headline number reflects month-to-month change. As has been discussed frequently (see Hyperinflation 2012 for example), the extraordinary length and depth of the current business downturn have disrupted regular seasonality patterns. Accordingly, the markets should not rely heavily on the accuracy of the monthly headline data.

Real (Inflation-Adjusted) January 2014 Trade Deficit. Adjusted for seasonal factors, and net of oil-price swings and other inflation (2009 chain-weighted dollars, used for GDP deflation), the January 2014 merchandise trade deficit (no services) narrowed to $48.525 billion, from a revised $49.236 (previously $49.535 billion) in December, and versus a revised $49.022 billion (previously $49.021) billion in January 2013.

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WEEK AHEAD

Much Weaker-Economic and Stronger-Inflation Reporting Likely in the Months and Year Ahead. Although shifting to the downside, market expectations generally still appear to be overly optimistic as to the economic outlook. Expectations should continue to be hammered, though, by continuing, downside corrective revisions and continued, disappointing headline economic activity. The initial stages of that process have been seen in the recent reporting of December and January payroll, retail sales, housing and industrial production data, and in the December trade-balance detail.

That corrective circumstance and underlying weak economic fundamentals remain highly suggestive of deteriorating business activity. Accordingly, weaker-than-consensus economic reporting should become the general trend until such time as the unfolding “new” recession receives general recognition.

Stronger inflation reporting remains likely. Upside pressure on oil-related prices should reflect intensifying impact from a weakening U.S. dollar in the currency markets, and from ongoing global political instabilities. The dollar faces pummeling from continuing QE3, the ongoing U.S. fiscal-crisis debacle, a weakening U.S. economy and deteriorating U.S. and global political conditions (see Hyperinflation 2014—The End Game Begins). Particularly in tandem with a weakened dollar, reporting in the year ahead generally should reflect much higher-than-expected inflation.

A Note on Reporting-Quality Issues and Systemic Reporting Biases. Significant reporting-quality problems remain with most major economic series. Ongoing headline reporting issues are tied largely to systemic distortions of seasonal adjustments. The data instabilities were induced by the still-evolving economic turmoil of the last seven-to-eight years, which has been without precedent in the post-World War II era of modern economic reporting. These impaired reporting methodologies provide particularly unstable headline economic results, where concurrent seasonal adjustments are used (as with retail sales, durable goods orders, employment and unemployment data), and they have thrown into question the statistical-significance of the headline month-to-month reporting for many popular economic series.

PENDING RELEASES:

Retail Sales (February 2014). The February 2014 retail sales estimate is scheduled for release on Thursday, March 13th, by the Census Bureau. With the consumer still in an extreme liquidity bind, odds again favor headline retail sales reporting coming in below-market expectations, which appear to be for minimal headline monthly growth. An outright month-to-month contraction in seasonally-adjusted sales remains a fair possibility, again, even before adjustment for consumer inflation.

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