Robert Brusca

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607a.jpg" width="353">
Wholesale inventory trends tell a very positive story. We take out the volatile and special readings from autos and petroleum to look at aggregated stocks and sales trends for all other wholesale classifications. Once done we obtain the chart plotted on the left that shows sales have speeded up as inventories have slowed. They have done that now for the second month in a row on six-month trends. Moreover, it shows that the ramping down in inventories has hit a low and apparent turning point in its decelerating rate of growth, yet another indication that the industry might be through its adjustment phase. 
The table below on inventories and sales behavior provides industry detail and time horizon cohorts for that detail. Over three months all main categories, save two, show that sales growth has surpassed inventory growth. The trend of sales (S) outstripping inventories (I) is widespread. Indeed, the two categories that have sales growth above inventory growth are not deficient in their rate of growth by much. Six-month horizons also are very solid. The S&gt;I growth trend seems pretty solid and well-established for now. 
Additionally the I/S ratios are in good shape. The overall ratio for all of wholesaling is at a new low dating back to 1998. Durables excluding autos are in their bottom 18 percentile and for nondurables excluding petroleum the ratio is in its bottom 10 percentile. 
Conclusion: Overall inventories are in good shape relative to sales. The recent growth rates of inventories relative to sales are settled into a good set of relationships as well. And best of all is the fact that sales growth is on an uptrend. The wholesale report is quite constructive and upbeat.

<table border="0" cellspacing="0" width="100%">
<colgroup><col></colgroup>
<thead>
<tr>
Inventories: Wholesaling
<th scope="col">I:S ratio</th>
</tr>
</thead>
<tbody>
<tr class="even">
<td class="firstcol">All growth rates annualized</td>
<td colspan="6">Inventory-&amp;-Sales Trends: Wholesalers</td>
<td>Percent of</td>
</tr>
<tr class="odd">
<td class="firstcol">2007.Apr</td>
<td colspan="2">3-mos</td>
<td colspan="2">6-mos</td>
<td colspan="2">12-mos</td>
<td>Range</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp;</td>
<td>Sales</td>
<td>Inventories</td>
<td>Sales</td>
<td>Inventories</td>
<td>Sales</td>
<td>Inventories</td>
<td>1998-date</td>
</tr>
<tr>
<td class="firstcol">All Wholesaling</td>
<td>19.3%</td>
<td>4.3%</td>
<td>12.8%</td>
<td>4.6%</td>
<td>8.8%</td>
<td>7.1%</td>
<td>0.0%</td>
</tr>
<tr>
<td class="firstcol">Durables</td>
<td>9.2%</td>
<td>-1.7%</td>
<td>7.2%</td>
<td>0.4%</td>
<td>7.8%</td>
<td>5.2%</td>
<td>7.8%</td>
</tr>
<tr>
<td class="firstcol">Durables less autos</td>
<td>9.2%</td>
<td>2.2%</td>
<td>7.0%</td>
<td>3.0%</td>
<td>7.6%</td>
<td>7.8%</td>
<td>19.1%</td>
</tr>
<tr>
<td class="firstcol">Autos</td>
<td>9.4%</td>
<td>-21.0%</td>
<td>8.0%</td>
<td>-13.1%</td>
<td>8.7%</td>
<td>-7.6%</td>
<td>0.9%</td>
</tr>
<tr>
<td class="firstcol">Computers</td>
<td>3.6%</td>
<td>5.1%</td>
<td>-0.3%</td>
<td>0.8%</td>
<td>5.4%</td>
<td>10.6%</td>
<td>38.3%</td>
</tr>
<tr>
<td class="firstcol">Machinery</td>
<td>3.5%</td>
<td>-2.5%</td>
<td>8.4%</td>
<td>2.3%</td>
<td>5.7%</td>
<td>7.7%</td>
<td>33.0%</td>
</tr>
<tr>
<td class="firstcol">Other Durables</td>
<td>11.8%</td>
<td>4.2%</td>
<td>7.8%</td>
<td>3.5%</td>
<td>8.5%</td>
<td>7.6%</td>
<td>14.8%</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Non-durables</td>
<td>29.9%</td>
<td>15.7%</td>
<td>18.6%</td>
<td>12.4%</td>
<td>9.7%</td>
<td>10.4%</td>
<td>5.2%</td>
</tr>
<tr>
<td class="firstcol">Non-durables less Petrol</td>
<td>17.0%</td>
<td>12.2%</td>
<td>12.3%</td>
<td>12.9%</td>
<td>9.8%</td>
<td>11.0%</td>
<td>9.6%</td>
</tr>
<tr>
<td class="firstcol">Petroleum</td>
<td>94.5%</td>
<td>58.5%</td>
<td>46.4%</td>
<td>8.2%</td>
<td>9.3%</td>
<td>4.7%</td>
<td>45.2%</td>
</tr>
<tr>
<td class="firstcol">Groceries</td>
<td>21.7%</td>
<td>23.4%</td>
<td>21.8%</td>
<td>20.7%</td>
<td>15.3%</td>
<td>17.1%</td>
<td>50.4%</td>
</tr>
<tr>
<td class="firstcol">Other Non-durables</td>
<td>15.0%</td>
<td>9.6%</td>
<td>8.5%</td>
<td>11.0%</td>
<td>7.7%</td>
<td>9.6%</td>
<td>11.3%</td>
</tr>
</tbody>
</table>
</body>
</html>

Wholesale inventory trends tell a very positive story. We take out the volatile and special readings from autos and petroleum to look at aggregated stocks and sales trends for all other wholesale classifications. Once done we obtain [...]

U.S. Wholesale Inventories Signal Smoother Sailing

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607a.jpg" width="353">
Wholesale inventory trends tell a very positive story. We take out the volatile and special readings from autos and petroleum to look at aggregated stocks and sales trends for all other wholesale classifications. Once done we obtain the chart plotted on the left that shows sales have speeded up as inventories have slowed. They have done that now for the second month in a row on six-month trends. Moreover, it shows that the ramping down in inventories has hit a low and apparent turning point in its decelerating rate of growth, yet another indication that the industry might be through its adjustment phase. 
The table below on inventories and sales behavior provides industry detail and time horizon cohorts for that detail. Over three months all main categories, save two, show that sales growth has surpassed inventory growth. The trend of sales (S) outstripping inventories (I) is widespread. Indeed, the two categories that have sales growth above inventory growth are not deficient in their rate of growth by much. Six-month horizons also are very solid. The S&gt;I growth trend seems pretty solid and well-established for now. 
Additionally the I/S ratios are in good shape. The overall ratio for all of wholesaling is at a new low dating back to 1998. Durables excluding autos are in their bottom 18 percentile and for nondurables excluding petroleum the ratio is in its bottom 10 percentile. 
Conclusion: Overall inventories are in good shape relative to sales. The recent growth rates of inventories relative to sales are settled into a good set of relationships as well. And best of all is the fact that sales growth is on an uptrend. The wholesale report is quite constructive and upbeat.

<table border="0" cellspacing="0" width="100%">
<colgroup><col></colgroup>
<thead>
<tr>
Inventories: Wholesaling
<th scope="col">I:S ratio</th>
</tr>
</thead>
<tbody>
<tr class="even">
<td class="firstcol">All growth rates annualized</td>
<td colspan="6">Inventory-&amp;-Sales Trends: Wholesalers</td>
<td>Percent of</td>
</tr>
<tr class="odd">
<td class="firstcol">2007.Apr</td>
<td colspan="2">3-mos</td>
<td colspan="2">6-mos</td>
<td colspan="2">12-mos</td>
<td>Range</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp;</td>
<td>Sales</td>
<td>Inventories</td>
<td>Sales</td>
<td>Inventories</td>
<td>Sales</td>
<td>Inventories</td>
<td>1998-date</td>
</tr>
<tr>
<td class="firstcol">All Wholesaling</td>
<td>19.3%</td>
<td>4.3%</td>
<td>12.8%</td>
<td>4.6%</td>
<td>8.8%</td>
<td>7.1%</td>
<td>0.0%</td>
</tr>
<tr>
<td class="firstcol">Durables</td>
<td>9.2%</td>
<td>-1.7%</td>
<td>7.2%</td>
<td>0.4%</td>
<td>7.8%</td>
<td>5.2%</td>
<td>7.8%</td>
</tr>
<tr>
<td class="firstcol">Durables less autos</td>
<td>9.2%</td>
<td>2.2%</td>
<td>7.0%</td>
<td>3.0%</td>
<td>7.6%</td>
<td>7.8%</td>
<td>19.1%</td>
</tr>
<tr>
<td class="firstcol">Autos</td>
<td>9.4%</td>
<td>-21.0%</td>
<td>8.0%</td>
<td>-13.1%</td>
<td>8.7%</td>
<td>-7.6%</td>
<td>0.9%</td>
</tr>
<tr>
<td class="firstcol">Computers</td>
<td>3.6%</td>
<td>5.1%</td>
<td>-0.3%</td>
<td>0.8%</td>
<td>5.4%</td>
<td>10.6%</td>
<td>38.3%</td>
</tr>
<tr>
<td class="firstcol">Machinery</td>
<td>3.5%</td>
<td>-2.5%</td>
<td>8.4%</td>
<td>2.3%</td>
<td>5.7%</td>
<td>7.7%</td>
<td>33.0%</td>
</tr>
<tr>
<td class="firstcol">Other Durables</td>
<td>11.8%</td>
<td>4.2%</td>
<td>7.8%</td>
<td>3.5%</td>
<td>8.5%</td>
<td>7.6%</td>
<td>14.8%</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Non-durables</td>
<td>29.9%</td>
<td>15.7%</td>
<td>18.6%</td>
<td>12.4%</td>
<td>9.7%</td>
<td>10.4%</td>
<td>5.2%</td>
</tr>
<tr>
<td class="firstcol">Non-durables less Petrol</td>
<td>17.0%</td>
<td>12.2%</td>
<td>12.3%</td>
<td>12.9%</td>
<td>9.8%</td>
<td>11.0%</td>
<td>9.6%</td>
</tr>
<tr>
<td class="firstcol">Petroleum</td>
<td>94.5%</td>
<td>58.5%</td>
<td>46.4%</td>
<td>8.2%</td>
<td>9.3%</td>
<td>4.7%</td>
<td>45.2%</td>
</tr>
<tr>
<td class="firstcol">Groceries</td>
<td>21.7%</td>
<td>23.4%</td>
<td>21.8%</td>
<td>20.7%</td>
<td>15.3%</td>
<td>17.1%</td>
<td>50.4%</td>
</tr>
<tr>
<td class="firstcol">Other Non-durables</td>
<td>15.0%</td>
<td>9.6%</td>
<td>8.5%</td>
<td>11.0%</td>
<td>7.7%</td>
<td>9.6%</td>
<td>11.3%</td>
</tr>
</tbody>
</table>
 Slight Relief for Gasoline Prices as Inventories Loosen. But What Is Happening to West Texas Intermediate? 
by <a href="/comment/Stone.html">Carol Stone</a> June 7, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607e.jpg" width="353">
As prices are sustained at stratospheric levels, we&#39;re all learning the mechanics of gasoline production. Special conditions that matter little at $1.00/gallon become significantly more important at $3.00. It&#39;s also hard to know what represents ordinary supply-demand movement and what is a &quot;special condition&quot;.
The Energy Information Administration of the Department of Energy (EIA) publishes its weekly petroleum situation every Wednesday, with gasoline prices measured through the Monday just before and other data taken as of the previous Friday. In this week&#39;s report, released yesterday morning, the national average retail price of &quot;regular grade&quot; gasoline fell -- that&#39;s &quot;fell&quot; -- in the week to June 4 by 5.2 cents to $3.157/gallon. The prior week, which included the Memorial Day weekend, saw a minuscule 0.9-cents decline. Small though this was, it is notable that the price did not rise further despite the holiday weekend driving.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607b.jpg" width="353">
We last checked in with the energy markets three weeks ago, and we highlighted the light inventory situation for gasoline, unusual for the post-winter season, which has pushed gasoline prices to record highs. We attributed this to demand conditions that weren&#39;t nearly as weak this winter as has traditionally been the case. It&#39;s also evident from the second graph that even as demand for gasoline has grown, refiners have not been able to keep up. We show refining capacity utilization and we&#39;ve drawn a line at 90%. Almost continuously since the middle of 1993, utilization has been well above this reference line. If we graph the variable with bars, they point up and down around the &quot;horizontal reference&quot;. We see easily then that Hurricanes Katrina and Rita hurt refiners badly, and it&#39;s clear that refinery utilization rates have remained well below our reference point even as they have increased somewhat over the last few weeks. Thus, refining has not recovered from those big 2005 storms, leaving the industry -- and prices -- more vulnerable to ordinary operating outages.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607d.jpg" width="353">
Another quirk in these data concerns the relationship between prices of various crudes, especially the US base, West Texas Intermediate (WTI) as delivered at Cushing, Oklahoma. As the EIA explain in <a href="http://tonto.eia.doe.gov/oog/info/twip/twiparch/070502/twipprint.html">This Week in Petroleum</a> for May 2, conditions regarding the oil itself and also the operation of the Cushing Hub have depressed the price of WTI relative to other oils. In the third graph, WTI is seen to be lower over the last 3 months or so than Brent and Indonesian oil, which are both &quot;heavier&quot; and should have lower prices than WTI. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070607c.jpg" width="353"> So when the price of gasoline has risen more than proportionately to the crude oil we&#39;re most familiar with, it may not be so much that refiners are trying to gouge their customers. In fact, the &quot;crack spread&quot; for Brent crude, while still high by past comparisons, has come down markedly from its recent levels. A similar measure for WTI fell last week, but it remains about $5 more per barrel than Brent, when the usual condition has been for the WTI crack spread to be marginally less than the Brent spread (since the crude is usually more expensive to begin with). As we noted at the beginning of this commentary, it makes one wonder if this mismatch of WTI and Brent (and other crude oils) is a &quot;special condition&quot; to be discounted as temporary, or is it a characteristic of the increasing supply/demand strains in the world energy market and in the US in particular? In that event, both energy suppliers and users would want factor the new relationships into their operating strategies.
The data here on prices and US inventories are in the OILWKLY database. Haver Analytics analysts perform seasonal adjustment on some demand and supply series; these are maintained in our WEEKLY database. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">Select Oil Market Indicators</th>
<th scope="col">June 4</th>
<th scope="col">May 28</th>
<th scope="col">May 21</th>
<th scope="col">Month- Ago Week</th>
<th scope="col">Year-Ago Week</th>
<th scope="col">2006</th>
<th scope="col">2005</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Gasoline, US Regular Grade (cents/gal)</td>
<td>315.7</td>
<td>320.9</td>
<td>321.8</td>
<td>305.4</td>
<td>289.2</td>
<td>257.2</td>
<td>227.0</td>
</tr>
<tr>
<td class="firstcol">Crude Oil: West Texas Intermediate ($/barrel)</td>
<td>June 1</td>
<td>May 25</td>
<td>May 18</td>
<td>63.79</td>
<td>71.50</td>
<td>66.13</td>
<td>56.50</td>
</tr>
<tr class="odd">
<td class="firstcol">63.94</td>
<td>64.94</td>
<td>63.61</td>
</tr>
<tr>
<td class="firstcol"> UK Brent &nbsp;</td>
<td>68.91</td>
<td>70.32</td>
<td>66.92</td>
<td>66.92</td>
<td>69.43</td>
<td>65.19</td>
<td>54.58</td>
</tr>
<tr class="odd">
<td class="firstcol">Refinery Utilization (%)</td>
<td>89.63</td>
<td>91.08</td>
<td>91.10</td>
<td>89.03</td>
<td>90.97</td>
<td>89.36</td>
<td>90.35</td>
</tr>
<tr>
<td class="firstcol">Gasoline Stock: Days&#39; Supply</td>
<td>21.3</td>
<td>21.0</td>
<td>21.0</td>
<td>20.9</td>
<td>22.5</td>
<td>22.7</td>
<td>22.8</td>
</tr>
</tbody>
</table>
</body>
</html>

Carol Stone, CBE

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606c.jpg" width="353">
Australian GDP grew 1.6% in Q1, up from 1.1% in Q4 and the strongest quarter since Q4 2003. This compared with 1.3% expected in one major forecast survey. Year-to-year growth was 4.0%. Data for Australia are contained in Haver&#39;s ANZ database and in G10+ as well as numerous international databases from the OECD, IMF and others.
The pick-up resulted from positive inputs in several demand areas. Private consumption was up 1.5% compared to 1.2% the quarter before. Exports expanded 1.4%, up from 1.0%, while growth in imports was lower, 2.1% from 6.5%. This latter, of course, helps raise the total growth rate since imports enter the GDP calculation negatively. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606d.jpg" width="353">
Fixed capital formation grew nicely as well, although the Q1 rise of 2.0% was less than Q4&#39;s 2.6%. It is important to note here the impact of the privatization of the telephone and telecommunications utility in Australia, Telstra. The government sold this company to private owners in November and it enters the GDP accounts in the private investment category for the first time in this report. Thus, the 5.8% surge in private fixed investment and the 16.9% plunge in public investment exaggerate the underlying movements. The Australian Bureau of Statistics reports that private investment would still have looked pretty good, at 4.8% growth in Q1, if the telephone company had been in the private sector all during Q4 as well. Public investment would still have fallen in Q1, but by &quot;only&quot; 7.5%. These latter growth rates are recorded in a footnote in our ANZ menu.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606c.jpg" width="353">
Interestingly, among the various industrial sectors, manufacturing output declined, despite the gain in overall GDP. Gross value added in manufacturing eased by 0.5%, although that did follow two very good quarters of 1.7% and 2.0%. Agricultural output also declined, but only 0.3% and far less than in the prior two quarters. So agriculture actually contributed to the increase in GDP growth by subtracting less. Construction activity gained 2.5%, a reputable figure, but less than Q4&#39;s 3.9%. The best performances came in retail trade, up 2.4%, and finance, up 2.3%, with both at least a percentage point stronger than the quarter before. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">AUSTRALIA, % Chg,&nbsp; Chn A$, Q3/2004-Q2/2005</th>
<th scope="col">Q1 2007*</th>
<th scope="col">Q4 2006*</th>
<th scope="col">Q3 2006*</th>
<th scope="col">Year Ago</th>
<th scope="col">2006</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Real GDP</td>
<td>1.6</td>
<td>1.1</td>
<td>0.5</td>
<td>4.0</td>
<td>2.7</td>
<td>2.7</td>
<td>3.7</td>
</tr>
<tr class="odd">
<td class="firstcol">Private Consumption</td>
<td>1.5</td>
<td>1.2</td>
<td>0.7</td>
<td>4.2</td>
<td>3.1</td>
<td>3.0</td>
<td>5.7</td>
</tr>
<tr class="odd">
<td class="firstcol">Gross Fixed Capital Formation</td>
<td>2.0</td>
<td>2.6</td>
<td>-0.5</td>
<td>5.8</td>
<td>6.3</td>
<td>7.8</td>
<td>7.5</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp; Private</td>
<td>5.8**</td>
<td>0.9</td>
<td>-1.5</td>
<td>7.1</td>
<td>5.4</td>
<td>7.6</td>
<td>7.1</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp; Public</td>
<td>-16.9**</td>
<td>-11.3</td>
<td>5.2</td>
<td>-2.1</td>
<td>11.9</td>
<td>8.7</td>
<td>9.9</td>
</tr>
<tr class="odd">
<td class="firstcol">Exports</td>
<td>1.4</td>
<td>1.0</td>
<td>0.2</td>
<td>4.6</td>
<td>3.4</td>
<td>2.4</td>
<td>4.6</td>
</tr>
<tr class="odd">
<td class="firstcol">Imports</td>
<td>2.1</td>
<td>6.5</td>
<td>-0.5</td>
<td>11.4</td>
<td>7.7</td>
<td>8.5</td>
<td>15.3</td>
</tr>
<tr>
<td class="firstcol">&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="odd">
<td class="firstcol">Manufacturing</td>
<td>-0.5</td>
<td>2.0</td>
<td>1.8</td>
<td>3.3</td>
<td>-1.3</td>
<td>0.2</td>
<td>0.0</td>
</tr>
<tr class="odd">
<td class="firstcol">Finance &amp; Insurance</td>
<td>2.3</td>
<td>1.0</td>
<td>0.9</td>
<td>5.9</td>
<td>6.1</td>
<td>2.5</td>
<td>3.7</td>
</tr>
</tbody>
</table>
</body>
</html>

Australian GDP grew 1.6% in Q1, up from 1.1% in Q4 and the strongest quarter since Q4 2003. This compared with 1.3% expected in one major forecast survey. Year-to-year growth was 4.0%. Data for Australia are contained in Haver's ANZ [...]

Australia GDP Up 1.6% in Q1; Best Quarter in 3 Years

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606b.jpg" width="353">
The first issue to grapple with in trying to assess the Challenger report is that its data are not seasonally adjusted. At the same time it is clear that this series has seasonal patterns. To get around this we compare the data to the year before.. We also have created the accompanying chart that plots each month of the year in a non-binding tunnel bearing two values representing averages for each month drawn from the period of recession and depressed growth as well as from the pre-recession times when layoffs were much lower. We add, as another reference line to the chart, the midpoint between these two cases. The chart reveals that the 2007 figures were regularly at or below the midpoint line until May when the level of layoffs is higher relative to that standard. It may be that the economy is throwing off more layoffs in May than what is normal either because of calendar quirks or because of a real deterioration that is setting in.
But the chart, even though it uses NSA data, flags May 2007 as a month of backtracking on reducing layoffs. 
The comprehensive table below provides even more comparisons. May ranks as the fifth highest layoff total in the past 14 years. April was also the fifth highest layoff month. March had ranked 9th and layoffs appeared as if they were diminishing. The three-month average ranks sixth over these same 14 years. The six-month average ranks eighth. The 12-month is displayed in the table and as of May that ranks 8th. So the ranking has been creeping up as we shorten the length to measure the moving average or to look at the month directly. The improving trend is not so clear any more, indeed it appears to have switched to one of deterioration. We can see that there has been some slippage compared to historic standards; standards that are free from the effects of seasonality. 
A slight bump up in the layoff pace is not an unequivocal message. 
But the steadiness of the slippage of the rankings on shorted moving averages is indicative of a true deterioration. A pick up in layoffs need not be a sign of economic weakness, however. At the moment both jobless claims and nonfarm job growth are indicating that the job market is solid &#150; as is the 4.5% rate of unemployment. Layoffs are another way to supply labor to an already tight labor market. We know that manufacturing firms continue to shed employees and have been doing so for decades. With the pick up in M&amp;A activity it is no surprise that layoffs step-up since that is one common result of mergers and their drive for greater efficiency. 
The gradual up turn in layoffs is a trend to be aware of, but is not yet a clear signal for policy. It may be constructive or it may be a sign of true erosion and of encroaching weakness. It bears watching.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col></colgroup>
<thead>
<tr>
Summary Of Announced Corporate Layoffs
<th scope="col">Rank of</th>
<th scope="col">&quot;13-Yr&quot;</th>
</tr>
</thead>
<tbody>
<tr class="grey8">
<td colspan="4">Challenger, Gray and Christmas:</td>
<td>3-Mo Avg</td>
<td>6-Mo Avg</td>
<td>12-Mo Avg</td>
<td>12-Mo</td>
<td>Rank Of</td>
</tr>
<tr class="grey7">
<td class="firstcol">&nbsp;</td>
<td>May</td>
<td>Apr</td>
<td>Mar</td>
<td>May</td>
<td>May</td>
<td>May</td>
<td>Average</td>
<td>May</td>
</tr>
<tr class="grey6">
<td class="firstcol">Announced Layoffs: 2007</td>
<td>71,115</td>
<td>70,672</td>
<td>48,997</td>
<td>63,595</td>
<td>65,736</td>
<td>67,523</td>
<td>8</td>
<td>5</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. Year ago (2006):</td>
<td>53,716</td>
<td>59,688</td>
<td>64,975</td>
<td>59,460</td>
<td>79,514</td>
<td>84,503</td>
<td>6</td>
<td>9</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. Year ago (2005):</td>
<td>82,283</td>
<td>57,861</td>
<td>86,396</td>
<td>75,513</td>
<td>89,387</td>
<td>88,218</td>
<td>5</td>
<td>2</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. 2-Years ago (2004):</td>
<td>73,368</td>
<td>72,184</td>
<td>68,034</td>
<td>71,195</td>
<td>83,569</td>
<td>89,500</td>
<td>4</td>
<td>4</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. 3-Years ago (2003):</td>
<td>68,623</td>
<td>146,399</td>
<td>85,396</td>
<td>100,139</td>
<td>110,622</td>
<td>113,426</td>
<td>2</td>
<td>6</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo .4-Years ago (2002):</td>
<td>84,978</td>
<td>112,649</td>
<td>102,315</td>
<td>99,981</td>
<td>139,686</td>
<td>154,906</td>
<td>1</td>
<td>1</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.5-years ago (2001):</td>
<td>80,140</td>
<td>165,564</td>
<td>162,867</td>
<td>136,190</td>
<td>131,037</td>
<td>74,439</td>
<td>7</td>
<td>3</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.6-years ago (2000):</td>
<td>27,036</td>
<td>37,291</td>
<td>55,783</td>
<td>40,037</td>
<td>41,644</td>
<td>103,205</td>
<td>3</td>
<td>12</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.7-years ago (1999):</td>
<td>55,231</td>
<td>54,399</td>
<td>68,984</td>
<td>59,538</td>
<td>70,553</td>
<td>65,201</td>
<td>9</td>
<td>8</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.8-years ago (1998):</td>
<td>27,631</td>
<td>48,758</td>
<td>23,028</td>
<td>33,139</td>
<td>45,637</td>
<td>39,950</td>
<td>11</td>
<td>11</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.9-years ago (1997):</td>
<td>21,004</td>
<td>15,214</td>
<td>50,182</td>
<td>28,800</td>
<td>34,646</td>
<td>31,851</td>
<td>13</td>
<td>13</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.10-years ago (1996):</td>
<td>30,845</td>
<td>30,810</td>
<td>37,486</td>
<td>33,047</td>
<td>47,598</td>
<td>41,526</td>
<td>10</td>
<td>10</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.11-years ago (1995):</td>
<td>58,530</td>
<td>15,678</td>
<td>27,809</td>
<td>34,006</td>
<td>33,240</td>
<td>35,253</td>
<td>12</td>
<td>7</td>
</tr>
<tr class="grey4">
<td class="firstcol">Comparative Data</td>
<td>May</td>
<td>Apr</td>
<td>Mar</td>
<td colspan="3">Values for previous months</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="grey3">
<td class="firstcol">Recession &amp; Post Recession</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>3-Mo</td>
<td>6-Mo</td>
<td>12-Mo</td>
<td>Month of</td>
<td>May</td>
</tr>
<tr class="grey3">
<td class="firstcol">&nbsp; Median (3-Yrs)</td>
<td>80,140</td>
<td>146,399</td>
<td>102,315</td>
<td>100,139</td>
<td>131,037</td>
<td>113,426</td>
<td>tends to be</td>
<td>lower than</td>
</tr>
<tr class="grey2">
<td class="firstcol">Pre-Recession (1995-2000)</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>Apr</td>
<td>60.0%</td>
</tr>
<tr class="grey2">
<td class="firstcol">&nbsp; Median (6-Yrs)</td>
<td>29,238</td>
<td>83,524</td>
<td>77,190</td>
<td>79,759</td>
<td>90,588</td>
<td>88,822</td>
<td>of the</td>
<td>time</td>
</tr>
<tr class="grey1">
<td class="firstcol">MIDPOINT-Median</td>
<td>54,689</td>
<td>114,962</td>
<td>89,753</td>
<td>89,949</td>
<td>110,812</td>
<td>101,124</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="grey1">
<td class="firstcol">% of Pre &amp; Post Gap</td>
<td>82.3%</td>
<td>-20.4%</td>
<td>-112.2%</td>
<td>-79.3%</td>
<td>-61.4%</td>
<td>-86.6%</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
</tbody>
</table>
</body>
</html>

The first issue to grapple with in trying to assess the Challenger report is that its data are not seasonally adjusted. At the same time it is clear that this series has seasonal patterns. To get around this we compare the data to the [...]

Challenger Lay Offs Stay Elevated

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606a.jpg" width="353">
Productivity is trending lower for manufacturing (MFG) as well as overall for nonfarm businesses. The accompanying chart makes the downturn clear. For nonfarm business the erosion seems to date back to mid-2005. For nonfarm productivity it looks like a trend decline is still in train - that would be very bad news indeed. It&#146;s bad enough that productivity has slowed to 1% Yr/Yr. 
With productivity at 1% Yr/Yr and population growth at about 1% Yr/Yr, GDP growth faces strong constraints. While labor force growth can surpass population growth, one-half of one percent is about all the extra growth it might be prudent to look for. And to encourage greater labor force participation it generally takes higher wages and that would be a problem for the Fed since it is trying to keep inflation contained. On balance, 2.5% growth seems about the limit to GDP under this new productivity growth rate scenario. 
Of course productivity is a fickle series. The chart on the left shows a good deal of variation in Yr/Yr growth. Quarterly growth in productivity and GDP can move around by a lot more. Still it is the trend we should be most concerned with. That is what the Fed will be looking at as it makes an assessment of its own policy options. 
The main implication of structurally weaker productivity growth is that the Fed will be seeing the economy with a lower speed limit. This is something markets have been having a hard time dealing with for sometime now. We have seen the slowing in labor force growth that has meant that 118K jobs per month (in nonfarm payrolls) is all that the job market needs to produce to steady the unemployment rate. Now a lower GDP number will also associate with that weaker job growth. 
The paradox is that this low growth will not be a cause for alarm that growth is slipping, rather the Fed will get worried about inflation pressures and speeding at growth rates that used to be quite acceptable and sustainable. 
Productivity is one of the most important contributors to growth and it is one of the most volatile. As such it is a variable that is hard to pin down. Even so the Fed will not be pleased with the new result and the trend it hints at. 
A diminished trend in productivity means that wage pressures can become inflation problems more easily. With high productivity in train sizeable wage increases can be blunted and &#145;paid for&#146; by accelerated productivity growth. But when productivity growth is low, firms have to be more careful about giving in to wage demands since the productivity cushion is smaller. 
In Q1 2007 compensation per hour of 3.2% less productivity of 1% leaves unit labor costs higher by 2.2%. In Q4 of 2005 compensation per hour of 3.7% translated into unit labor costs of just +1.5% because productivity was up by 2.1%. 
With the Fed putting the top of its inflation comfort zone at 2% in terms of Core PCE it is easy to see that wages are to be held in a narrow band if productivity stays this low and if the Fed is to be successful in keeping inflation at bay.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
Nonfarm Productivity
</tr>
</thead>
<tbody>
<tr class="even">
<td class="firstcol">Year/Year Pct</td>
<td>07/Q1</td>
<td>06/Q4</td>
<td>06/Q3</td>
<td>06/Q2</td>
<td>06/Q1</td>
<td>05/Q4</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Unit Labor Cost</td>
<td>2.2%</td>
<td>4.0%</td>
<td>2.6%</td>
<td>3.1%</td>
<td>3.6%</td>
<td>1.5%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Output/Hr</td>
<td>1.0%</td>
<td>1.6%</td>
<td>0.9%</td>
<td>1.9%</td>
<td>2.0%</td>
<td>2.1%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Comp/Hr</td>
<td>3.2%</td>
<td>5.6%</td>
<td>3.5%</td>
<td>5.1%</td>
<td>5.7%</td>
<td>3.7%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Real Comp/Hr</td>
<td>0.7%</td>
<td>3.6%</td>
<td>0.1%</td>
<td>1.0%</td>
<td>1.9%</td>
<td>0.0%</td>
</tr>
<tr>
<td colspan="7">Manufacturing</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Unit Labor Cost</td>
<td>-0.4%</td>
<td>0.7%</td>
<td>-2.3%</td>
<td>0.1%</td>
<td>2.0%</td>
<td>-1.2%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Output/Hour</td>
<td>3.5%</td>
<td>3.9%</td>
<td>4.2%</td>
<td>3.6%</td>
<td>4.1%</td>
<td>4.6%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Comp/Hour</td>
<td>3.1%</td>
<td>4.6%</td>
<td>1.8%</td>
<td>3.7%</td>
<td>6.1%</td>
<td>3.4%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Real Comp/Hour</td>
<td>0.6%</td>
<td>2.6%</td>
<td>-1.5%</td>
<td>-0.3%</td>
<td>2.3%</td>
<td>-0.4%</td>
</tr>
</tbody>
</table>
</body>
</html>

Productivity is trending lower for manufacturing (MFG) as well as overall for nonfarm businesses. The accompanying chart makes the downturn clear. For nonfarm business the erosion seems to date back to mid-2005. For nonfarm [...]

U.S. Productivity is Down and Unit Labor Costs are Up

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606a.jpg" width="353">
Productivity is trending lower for manufacturing (MFG) as well as overall for nonfarm businesses. The accompanying chart makes the downturn clear. For nonfarm business the erosion seems to date back to mid-2005. For nonfarm productivity it looks like a trend decline is still in train - that would be very bad news indeed. It&#146;s bad enough that productivity has slowed to 1% Yr/Yr. 
With productivity at 1% Yr/Yr and population growth at about 1% Yr/Yr, GDP growth faces strong constraints. While labor force growth can surpass population growth, one-half of one percent is about all the extra growth it might be prudent to look for. And to encourage greater labor force participation it generally takes higher wages and that would be a problem for the Fed since it is trying to keep inflation contained. On balance, 2.5% growth seems about the limit to GDP under this new productivity growth rate scenario. 
Of course productivity is a fickle series. The chart on the left shows a good deal of variation in Yr/Yr growth. Quarterly growth in productivity and GDP can move around by a lot more. Still it is the trend we should be most concerned with. That is what the Fed will be looking at as it makes an assessment of its own policy options. 
The main implication of structurally weaker productivity growth is that the Fed will be seeing the economy with a lower speed limit. This is something markets have been having a hard time dealing with for sometime now. We have seen the slowing in labor force growth that has meant that 118K jobs per month (in nonfarm payrolls) is all that the job market needs to produce to steady the unemployment rate. Now a lower GDP number will also associate with that weaker job growth. 
The paradox is that this low growth will not be a cause for alarm that growth is slipping, rather the Fed will get worried about inflation pressures and speeding at growth rates that used to be quite acceptable and sustainable. 
Productivity is one of the most important contributors to growth and it is one of the most volatile. As such it is a variable that is hard to pin down. Even so the Fed will not be pleased with the new result and the trend it hints at. 
A diminished trend in productivity means that wage pressures can become inflation problems more easily. With high productivity in train sizeable wage increases can be blunted and &#145;paid for&#146; by accelerated productivity growth. But when productivity growth is low, firms have to be more careful about giving in to wage demands since the productivity cushion is smaller. 
In Q1 2007 compensation per hour of 3.2% less productivity of 1% leaves unit labor costs higher by 2.2%. In Q4 of 2005 compensation per hour of 3.7% translated into unit labor costs of just +1.5% because productivity was up by 2.1%. 
With the Fed putting the top of its inflation comfort zone at 2% in terms of Core PCE it is easy to see that wages are to be held in a narrow band if productivity stays this low and if the Fed is to be successful in keeping inflation at bay.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
Nonfarm Productivity
</tr>
</thead>
<tbody>
<tr class="even">
<td class="firstcol">Year/Year Pct</td>
<td>07/Q1</td>
<td>06/Q4</td>
<td>06/Q3</td>
<td>06/Q2</td>
<td>06/Q1</td>
<td>05/Q4</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Unit Labor Cost</td>
<td>2.2%</td>
<td>4.0%</td>
<td>2.6%</td>
<td>3.1%</td>
<td>3.6%</td>
<td>1.5%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Output/Hr</td>
<td>1.0%</td>
<td>1.6%</td>
<td>0.9%</td>
<td>1.9%</td>
<td>2.0%</td>
<td>2.1%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Comp/Hr</td>
<td>3.2%</td>
<td>5.6%</td>
<td>3.5%</td>
<td>5.1%</td>
<td>5.7%</td>
<td>3.7%</td>
</tr>
<tr class="odd">
<td class="firstcol">NF Real Comp/Hr</td>
<td>0.7%</td>
<td>3.6%</td>
<td>0.1%</td>
<td>1.0%</td>
<td>1.9%</td>
<td>0.0%</td>
</tr>
<tr>
<td colspan="7">Manufacturing</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Unit Labor Cost</td>
<td>-0.4%</td>
<td>0.7%</td>
<td>-2.3%</td>
<td>0.1%</td>
<td>2.0%</td>
<td>-1.2%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Output/Hour</td>
<td>3.5%</td>
<td>3.9%</td>
<td>4.2%</td>
<td>3.6%</td>
<td>4.1%</td>
<td>4.6%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Comp/Hour</td>
<td>3.1%</td>
<td>4.6%</td>
<td>1.8%</td>
<td>3.7%</td>
<td>6.1%</td>
<td>3.4%</td>
</tr>
<tr class="odd">
<td class="firstcol">MFG Real Comp/Hour</td>
<td>0.6%</td>
<td>2.6%</td>
<td>-1.5%</td>
<td>-0.3%</td>
<td>2.3%</td>
<td>-0.4%</td>
</tr>
</tbody>
</table>
Challenger Lay Offs Stay Elevated 
by <a href="/comment/Brusca.html">Robert Brusca</a> June 6, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606b.jpg" width="353">
The first issue to grapple with in trying to assess the Challenger report is that its data are not seasonally adjusted. At the same time it is clear that this series has seasonal patterns. To get around this we compare the data to the year before.. We also have created the accompanying chart that plots each month of the year in a non-binding tunnel bearing two values representing averages for each month drawn from the period of recession and depressed growth as well as from the pre-recession times when layoffs were much lower. We add, as another reference line to the chart, the midpoint between these two cases. The chart reveals that the 2007 figures were regularly at or below the midpoint line until May when the level of layoffs is higher relative to that standard. It may be that the economy is throwing off more layoffs in May than what is normal either because of calendar quirks or because of a real deterioration that is setting in.
But the chart, even though it uses NSA data, flags May 2007 as a month of backtracking on reducing layoffs. 
The comprehensive table below provides even more comparisons. May ranks as the fifth highest layoff total in the past 14 years. April was also the fifth highest layoff month. March had ranked 9th and layoffs appeared as if they were diminishing. The three-month average ranks sixth over these same 14 years. The six-month average ranks eighth. The 12-month is displayed in the table and as of May that ranks 8th. So the ranking has been creeping up as we shorten the length to measure the moving average or to look at the month directly. The improving trend is not so clear any more, indeed it appears to have switched to one of deterioration. We can see that there has been some slippage compared to historic standards; standards that are free from the effects of seasonality. 
A slight bump up in the layoff pace is not an unequivocal message. 
But the steadiness of the slippage of the rankings on shorted moving averages is indicative of a true deterioration. A pick up in layoffs need not be a sign of economic weakness, however. At the moment both jobless claims and nonfarm job growth are indicating that the job market is solid &#150; as is the 4.5% rate of unemployment. Layoffs are another way to supply labor to an already tight labor market. We know that manufacturing firms continue to shed employees and have been doing so for decades. With the pick up in M&amp;A activity it is no surprise that layoffs step-up since that is one common result of mergers and their drive for greater efficiency. 
The gradual up turn in layoffs is a trend to be aware of, but is not yet a clear signal for policy. It may be constructive or it may be a sign of true erosion and of encroaching weakness. It bears watching.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col></colgroup>
<thead>
<tr>
Summary Of Announced Corporate Layoffs
<th scope="col">Rank of</th>
<th scope="col">&quot;13-Yr&quot;</th>
</tr>
</thead>
<tbody>
<tr class="grey8">
<td colspan="4">Challenger, Gray and Christmas:</td>
<td>3-Mo Avg</td>
<td>6-Mo Avg</td>
<td>12-Mo Avg</td>
<td>12-Mo</td>
<td>Rank Of</td>
</tr>
<tr class="grey7">
<td class="firstcol">&nbsp;</td>
<td>May</td>
<td>Apr</td>
<td>Mar</td>
<td>May</td>
<td>May</td>
<td>May</td>
<td>Average</td>
<td>May</td>
</tr>
<tr class="grey6">
<td class="firstcol">Announced Layoffs: 2007</td>
<td>71,115</td>
<td>70,672</td>
<td>48,997</td>
<td>63,595</td>
<td>65,736</td>
<td>67,523</td>
<td>8</td>
<td>5</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. Year ago (2006):</td>
<td>53,716</td>
<td>59,688</td>
<td>64,975</td>
<td>59,460</td>
<td>79,514</td>
<td>84,503</td>
<td>6</td>
<td>9</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. Year ago (2005):</td>
<td>82,283</td>
<td>57,861</td>
<td>86,396</td>
<td>75,513</td>
<td>89,387</td>
<td>88,218</td>
<td>5</td>
<td>2</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. 2-Years ago (2004):</td>
<td>73,368</td>
<td>72,184</td>
<td>68,034</td>
<td>71,195</td>
<td>83,569</td>
<td>89,500</td>
<td>4</td>
<td>4</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo. 3-Years ago (2003):</td>
<td>68,623</td>
<td>146,399</td>
<td>85,396</td>
<td>100,139</td>
<td>110,622</td>
<td>113,426</td>
<td>2</td>
<td>6</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo .4-Years ago (2002):</td>
<td>84,978</td>
<td>112,649</td>
<td>102,315</td>
<td>99,981</td>
<td>139,686</td>
<td>154,906</td>
<td>1</td>
<td>1</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.5-years ago (2001):</td>
<td>80,140</td>
<td>165,564</td>
<td>162,867</td>
<td>136,190</td>
<td>131,037</td>
<td>74,439</td>
<td>7</td>
<td>3</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.6-years ago (2000):</td>
<td>27,036</td>
<td>37,291</td>
<td>55,783</td>
<td>40,037</td>
<td>41,644</td>
<td>103,205</td>
<td>3</td>
<td>12</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.7-years ago (1999):</td>
<td>55,231</td>
<td>54,399</td>
<td>68,984</td>
<td>59,538</td>
<td>70,553</td>
<td>65,201</td>
<td>9</td>
<td>8</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.8-years ago (1998):</td>
<td>27,631</td>
<td>48,758</td>
<td>23,028</td>
<td>33,139</td>
<td>45,637</td>
<td>39,950</td>
<td>11</td>
<td>11</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.9-years ago (1997):</td>
<td>21,004</td>
<td>15,214</td>
<td>50,182</td>
<td>28,800</td>
<td>34,646</td>
<td>31,851</td>
<td>13</td>
<td>13</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.10-years ago (1996):</td>
<td>30,845</td>
<td>30,810</td>
<td>37,486</td>
<td>33,047</td>
<td>47,598</td>
<td>41,526</td>
<td>10</td>
<td>10</td>
</tr>
<tr class="grey5">
<td class="firstcol">Same Mo.11-years ago (1995):</td>
<td>58,530</td>
<td>15,678</td>
<td>27,809</td>
<td>34,006</td>
<td>33,240</td>
<td>35,253</td>
<td>12</td>
<td>7</td>
</tr>
<tr class="grey4">
<td class="firstcol">Comparative Data</td>
<td>May</td>
<td>Apr</td>
<td>Mar</td>
<td colspan="3">Values for previous months</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="grey3">
<td class="firstcol">Recession &amp; Post Recession</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>3-Mo</td>
<td>6-Mo</td>
<td>12-Mo</td>
<td>Month of</td>
<td>May</td>
</tr>
<tr class="grey3">
<td class="firstcol">&nbsp; Median (3-Yrs)</td>
<td>80,140</td>
<td>146,399</td>
<td>102,315</td>
<td>100,139</td>
<td>131,037</td>
<td>113,426</td>
<td>tends to be</td>
<td>lower than</td>
</tr>
<tr class="grey2">
<td class="firstcol">Pre-Recession (1995-2000)</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>Apr</td>
<td>60.0%</td>
</tr>
<tr class="grey2">
<td class="firstcol">&nbsp; Median (6-Yrs)</td>
<td>29,238</td>
<td>83,524</td>
<td>77,190</td>
<td>79,759</td>
<td>90,588</td>
<td>88,822</td>
<td>of the</td>
<td>time</td>
</tr>
<tr class="grey1">
<td class="firstcol">MIDPOINT-Median</td>
<td>54,689</td>
<td>114,962</td>
<td>89,753</td>
<td>89,949</td>
<td>110,812</td>
<td>101,124</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="grey1">
<td class="firstcol">% of Pre &amp; Post Gap</td>
<td>82.3%</td>
<td>-20.4%</td>
<td>-112.2%</td>
<td>-79.3%</td>
<td>-61.4%</td>
<td>-86.6%</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
</tbody>
</table>
Australia GDP Up 1.6% in Q1; Best Quarter in 3 Years  
by <a href="/comment/Stone.html">Carol Stone</a> June 6, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606c.jpg" width="353">
Australian GDP grew 1.6% in Q1, up from 1.1% in Q4 and the strongest quarter since Q4 2003. This compared with 1.3% expected in one major forecast survey. Year-to-year growth was 4.0%. Data for Australia are contained in Haver&#39;s ANZ database and in G10+ as well as numerous international databases from the OECD, IMF and others.
The pick-up resulted from positive inputs in several demand areas. Private consumption was up 1.5% compared to 1.2% the quarter before. Exports expanded 1.4%, up from 1.0%, while growth in imports was lower, 2.1% from 6.5%. This latter, of course, helps raise the total growth rate since imports enter the GDP calculation negatively. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606d.jpg" width="353">
Fixed capital formation grew nicely as well, although the Q1 rise of 2.0% was less than Q4&#39;s 2.6%. It is important to note here the impact of the privatization of the telephone and telecommunications utility in Australia, Telstra. The government sold this company to private owners in November and it enters the GDP accounts in the private investment category for the first time in this report. Thus, the 5.8% surge in private fixed investment and the 16.9% plunge in public investment exaggerate the underlying movements. The Australian Bureau of Statistics reports that private investment would still have looked pretty good, at 4.8% growth in Q1, if the telephone company had been in the private sector all during Q4 as well. Public investment would still have fallen in Q1, but by &quot;only&quot; 7.5%. These latter growth rates are recorded in a footnote in our ANZ menu.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070606c.jpg" width="353">
Interestingly, among the various industrial sectors, manufacturing output declined, despite the gain in overall GDP. Gross value added in manufacturing eased by 0.5%, although that did follow two very good quarters of 1.7% and 2.0%. Agricultural output also declined, but only 0.3% and far less than in the prior two quarters. So agriculture actually contributed to the increase in GDP growth by subtracting less. Construction activity gained 2.5%, a reputable figure, but less than Q4&#39;s 3.9%. The best performances came in retail trade, up 2.4%, and finance, up 2.3%, with both at least a percentage point stronger than the quarter before. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">AUSTRALIA, % Chg,&nbsp; Chn A$, Q3/2004-Q2/2005</th>
<th scope="col">Q1 2007*</th>
<th scope="col">Q4 2006*</th>
<th scope="col">Q3 2006*</th>
<th scope="col">Year Ago</th>
<th scope="col">2006</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Real GDP</td>
<td>1.6</td>
<td>1.1</td>
<td>0.5</td>
<td>4.0</td>
<td>2.7</td>
<td>2.7</td>
<td>3.7</td>
</tr>
<tr class="odd">
<td class="firstcol">Private Consumption</td>
<td>1.5</td>
<td>1.2</td>
<td>0.7</td>
<td>4.2</td>
<td>3.1</td>
<td>3.0</td>
<td>5.7</td>
</tr>
<tr class="odd">
<td class="firstcol">Gross Fixed Capital Formation</td>
<td>2.0</td>
<td>2.6</td>
<td>-0.5</td>
<td>5.8</td>
<td>6.3</td>
<td>7.8</td>
<td>7.5</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp; Private</td>
<td>5.8**</td>
<td>0.9</td>
<td>-1.5</td>
<td>7.1</td>
<td>5.4</td>
<td>7.6</td>
<td>7.1</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp; Public</td>
<td>-16.9**</td>
<td>-11.3</td>
<td>5.2</td>
<td>-2.1</td>
<td>11.9</td>
<td>8.7</td>
<td>9.9</td>
</tr>
<tr class="odd">
<td class="firstcol">Exports</td>
<td>1.4</td>
<td>1.0</td>
<td>0.2</td>
<td>4.6</td>
<td>3.4</td>
<td>2.4</td>
<td>4.6</td>
</tr>
<tr class="odd">
<td class="firstcol">Imports</td>
<td>2.1</td>
<td>6.5</td>
<td>-0.5</td>
<td>11.4</td>
<td>7.7</td>
<td>8.5</td>
<td>15.3</td>
</tr>
<tr>
<td class="firstcol">&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="odd">
<td class="firstcol">Manufacturing</td>
<td>-0.5</td>
<td>2.0</td>
<td>1.8</td>
<td>3.3</td>
<td>-1.3</td>
<td>0.2</td>
<td>0.0</td>
</tr>
<tr class="odd">
<td class="firstcol">Finance &amp; Insurance</td>
<td>2.3</td>
<td>1.0</td>
<td>0.9</td>
<td>5.9</td>
<td>6.1</td>
<td>2.5</td>
<td>3.7</td>
</tr>
</tbody>
</table>
</body>
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Productivity is Down and Unit Labor Costs are Up

Louise Curley

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070605c.jpg" width="353">
Eurostat released preliminary data for April retail trade today for the aggregates of the 13 countries in the Euro Area and the 27 countries in the European Union. The preliminary data are based on reports by countries representing at least 60% of the weight of the total. As a result data for all countries are not available at this time.
Eurostat does not publish, nor is it possible to derive, an index for total retail trade of the &quot;Fourteen&quot; non Euro Area countries included in the total. However, the fact that retail trade in the Euro Area increased 0.18% in April from March while trade in the entire Union declined, albeit slightly, 0.05%, suggests that retail trade in the &quot;Fourteen&quot; declined in April. The first chart shows the indexes of retail trade in the Euro Area and the European Union. The widening gap between the two series suggests that the greater growth in the retail trade of the European Union has been due largely to the &quot;Fourteen&quot;.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070605d.jpg" width="353">
The &quot;Fourteen&quot; non Euro Area countries includes three developed countries--the United Kingdom, Sweden and Denmark and eleven emerging countries of central and eastern Europe. Retail trade in the three developed countries has shown more strength than the total of the Euro Area as can be seen in the second chart. This growth, however, falls short of the dramatic growth of retail trade in the central and eastern European countries, as shown in the third chart where the paths of retail trade in Latvia, Estonia and Bulgaria are taken as illustrative of the group of emerging countries. It should however be kept in mind that these countries began to grow only after the fall of the Berlin Wall hence their growth has been from a very low base compared with that of the developed countries.
Growth of retail trade within the Euro Area has varied widely with Germany being the laggard. The fourth chart compares retail trade in Germany with that of France, Finland, and Spain among those with good growth. It appears that retail trade in Germany may finally be showing signs of growth.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070605e.jpg" width="353"><img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070605f.jpg" width="353">

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">VOLUME OF RETAIL TRADE EX AUTOS&nbsp; (SA, 2000=100)&nbsp;</th>
<th scope="col">Apr&nbsp;&nbsp; 07</th>
<th scope="col">Mar&nbsp; 07&nbsp;</th>
<th scope="col">Apr&nbsp;&nbsp; 06</th>
<th scope="col">M/M %</th>
<th scope="col">Y/Y %</th>
<th scope="col">2006</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">European Area 13</td>
<td>110.22</td>
<td>110.02</td>
<td>108.41</td>
<td>0.18</td>
<td>1.67</td>
<td>108.84</td>
<td>106.72</td>
<td>105.32</td>
</tr>
<tr>
<td class="firstcol">European Union 27</td>
<td>118.01</td>
<td>118.07</td>
<td>114.84</td>
<td>-0.05</td>
<td>2.76</td>
<td>115.46</td>
<td>112.14</td>
<td>109.97</td>
</tr>
<tr class="odd">
<td class="firstcol">France</td>
<td>120.6</td>
<td>119.5</td>
<td>116.1</td>
<td>0.92</td>
<td>3.88</td>
<td>116.9</td>
<td>114.7</td>
<td>113.2</td>
</tr>
<tr>
<td class="firstcol"> Germany </td>
<td>104.0</td>
<td>101.3</td>
<td>103.3</td>
<td>2.67</td>
<td>0.68</td>
<td>103.5</td>
<td>101.7</td>
<td>100.2</td>
</tr>
<tr class="odd">
<td class="firstcol">Spain</td>
<td>122.22</td>
<td>124.40</td>
<td>119.69</td>
<td>-1.75</td>
<td>2.11</td>
<td>120.38</td>
<td>118.02</td>
<td>116.27</td>
</tr>
<tr>
<td class="firstcol">Finland</td>
<td>132.0</td>
<td>136.1</td>
<td>128.7</td>
<td>-3.01</td>
<td>2.56</td>
<td>129.0</td>
<td>122.2</td>
<td>116.5</td>
</tr>
<tr class="odd">
<td class="firstcol">United Kingdom</td>
<td>133.14</td>
<td>133.09</td>
<td>127.45</td>
<td>0.04</td>
<td>4.46</td>
<td>128.65</td>
<td>124.65</td>
<td>122.28</td>
</tr>
<tr>
<td class="firstcol">Sweden</td>
<td>145.6</td>
<td>145.5</td>
<td>136.6</td>
<td>0.07</td>
<td>6.59</td>
<td>138.3</td>
<td>126.7</td>
<td>118.1</td>
</tr>
<tr class="odd">
<td class="firstcol">Denmark</td>
<td>132.0</td>
<td>134.0</td>
<td>130.0</td>
<td>-1.49</td>
<td>1.54</td>
<td>130.7</td>
<td>126.4</td>
<td>116.8</td>
</tr>
<tr>
<td class="firstcol">Latvia</td>
<td>249.98</td>
<td>251.69</td>
<td>202.48</td>
<td>-0.68</td>
<td>23.46</td>
<td>213.49</td>
<td>178.03</td>
<td>146.91</td>
</tr>
<tr class="odd">
<td class="firstcol">Bulgaria</td>
<td>232.14</td>
<td>232.71</td>
<td>210.84</td>
<td>-0.24</td>
<td>10.10</td>
<td>215.48</td>
<td>190.29</td>
<td>102.49</td>
</tr>
<tr>
<td class="firstcol">Estonia</td>
<td>233.51</td>
<td>242.72</td>
<td>205.19</td>
<td>-3.79</td>
<td>13.80</td>
<td>211.88</td>
<td>181.86</td>
<td>158.98</td>
</tr>
</tbody>
</table>
</body>
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Eurostat released preliminary data for April retail trade today for the aggregates of the 13 countries in the Euro Area and the 27 countries in the European Union. The preliminary data are based on reports by countries representing at [...]

April Retail Trade in the Euro Area Picks Up, Trade in Other EU Countries Slows

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070605b.jpg" width="353">
The NonMFG ISM shows that its components are indeed cycling higher. Prices are up strongly. Backlogs while below the neutral value of 50 are nonetheless rising strongly from their six month average. Still, they edged lower in the month of May. Orders also are edging higher. And activity is firming but not yet stronger on a three-month vs six month comparison. 
In May the Non MFG ISM activity index moved up sharply. Orders also rose briskly. The report generated exactly the sort of strength we thought we would see after seeing employment strength in May. 
The percentile positions of the various ISM components show a great deal of variation in the various ISM components (see table below). For the most part the readings are strong but not all are. The supplier deliveries reading, for example is in the bottom 12 percentile of its range and shows the same sort of slack or absence of tension on deliveries as the ISM MFG and other regional reports. Even as activity has ramped up slack has increased. Contrarily exports and inventories are at the top of their respective ranges going back to 1998. Activity is high in its range. Orders, prices and employment are at firm relative readings (Percentiles). While prices are 10 % above their average value, they has such large variation (std dev= 8.2) that they are still at a moderate position within their range of values. 
Private non MFG jobs statistics are at the bottom of this table. Readings (monthly changes in non MFG jobs) are in the 65th percentile of their range since 1998 close to the 68.8 percentile for the Non Mfg ISM job diffusion reading. We appear to be getting consistent signals about the growing strength and firmness of the economy. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">&nbsp;</th>
ISM Non Manufacturing Statistics from Jan 1998 to Date
<th scope="col">&nbsp;</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">ISM-Non MFG</td>
<td>Current</td>
<td>Last Mo</td>
<td>Std Dev</td>
<td>Average</td>
<td>SD% Avg</td>
<td>MAX</td>
<td>MIN</td>
<td>Range</td>
<td>Percentile</td>
<td>% of AVG</td>
</tr>
<tr>
<td class="firstcol">PM Activity</td>
<td>59.7</td>
<td>56.0</td>
<td>4.7</td>
<td>57.6</td>
<td>8.2</td>
<td>67.9</td>
<td>40.5</td>
<td>27.4</td>
<td>70.1</td>
<td>104</td>
</tr>
<tr>
<td class="firstcol">New Orders</td>
<td>57.4</td>
<td>55.5</td>
<td>4.7</td>
<td>57.2</td>
<td>8.2</td>
<td>66.9</td>
<td>41.3</td>
<td>25.6</td>
<td>62.9</td>
<td>100</td>
</tr>
<tr>
<td class="firstcol">Backlogs</td>
<td>48.0</td>
<td>50.0</td>
<td>3.7</td>
<td>51.0</td>
<td>7.2</td>
<td>57.0</td>
<td>40.5</td>
<td>16.5</td>
<td>45.5</td>
<td>94</td>
</tr>
<tr>
<td class="firstcol">Supplier Deliveries</td>
<td>49.5</td>
<td>51.0</td>
<td>2.2</td>
<td>53.6</td>
<td>4.1</td>
<td>60.5</td>
<td>48.0</td>
<td>12.5</td>
<td>12.0</td>
<td>92</td>
</tr>
<tr>
<td class="firstcol">Inventory Sentiment*</td>
<td>61.0</td>
<td>60.5</td>
<td>2.7</td>
<td>63.0</td>
<td>4.3</td>
<td>69.0</td>
<td>55.0</td>
<td>14.0</td>
<td>42.9</td>
<td>97</td>
</tr>
<tr>
<td class="firstcol">Inventories</td>
<td>61.0</td>
<td>52.0</td>
<td>3.3</td>
<td>50.6</td>
<td>6.6</td>
<td>61.0</td>
<td>43.5</td>
<td>17.5</td>
<td>100.0</td>
<td>121</td>
</tr>
<tr>
<td class="firstcol">Prices</td>
<td>66.4</td>
<td>63.5</td>
<td>8.2</td>
<td>60.1</td>
<td>13.6</td>
<td>80.5</td>
<td>41.3</td>
<td>39.2</td>
<td>64.0</td>
<td>110</td>
</tr>
<tr>
<td class="firstcol">Employment</td>
<td>54.9</td>
<td>51.9</td>
<td>3.7</td>
<td>51.7</td>
<td>7.1</td>
<td>59.9</td>
<td>43.9</td>
<td>16.0</td>
<td>68.8</td>
<td>106</td>
</tr>
<tr>
<td class="firstcol">Export Orders</td>
<td>66.0</td>
<td>55.5</td>
<td>4.6</td>
<td>55.0</td>
<td>8.4</td>
<td>66.0</td>
<td>44.5</td>
<td>21.5</td>
<td>100.0</td>
<td>120</td>
</tr>
<tr>
<td class="firstcol">Import Orders</td>
<td>55.5</td>
<td>52.5</td>
<td>4.0</td>
<td>54.8</td>
<td>7.3</td>
<td>63.5</td>
<td>45.5</td>
<td>18.0</td>
<td>55.6</td>
<td>101</td>
</tr>
<tr>
<td class="firstcol">Private Non MFG jobs</td>
<td>154.0</td>
<td>98.0</td>
<td>112.5</td>
<td>99.6</td>
<td>113.0</td>
<td>346.0</td>
<td>-202.0</td>
<td>548.0</td>
<td>65.0</td>
<td>155</td>
</tr>
</tbody>
</table>
</body>
</html>

The NonMFG ISM shows that its components are indeed cycling higher. Prices are up strongly. Backlogs while below the neutral value of 50 are nonetheless rising strongly from their six month average. Still, they edged lower in the [...]

Non MFG ISM strength is cycling higher—so are prices

USD/EUR exchange rate uncoupling from interest rate differential

Widespread downgrading of 2025 GDP outlook

Trade and fiscal policy uncertainty has exploded with the new administration

Much lower US electricity costs gives it a competitive advantage

Wage growth slowing in the US and Euro area; elevated and sticky in the UK

Stagflation-lite: Blue Chip forecasts below-trend growth and elevated inflation

US policy gyrations boosting policy uncertainty worldwide

Expected tariff hikes have boosted inflation expectations

US and Japan ended 2024 on solid ground in contrast to Europe

US economy expected to outperform other major economies in 2025

Only modest evidence of AI-related surge in US productivity growth

Previous Trump tariffs fading. A boost from new tariffs ahead?

Heavy US manufacturing states underperforming while Sun Belt states outperforming

Rising long-term yields a global phenomenon

US financial market concerns shifting from growth to inflation

Economic activity is picking up in the US but remains lackluster abroad

Policy uncertainty has surged since the US national elections.

Recent turnaround in US economic surprises leading to increases in rate-cut expectations

The outlook has brightened in the US, while it has dimmed for other major economies

Headline US PCE inflation elevated by sticky services prices

US and global equity prices have recently diverged

US leading global upturn in economic surprises

Blue Chip forecasters look for further significant monetary easing apart from Japan

Recent rise in global supply chain pressures could augur a pickup in global inflation pressures

Underperforming German economy generating increased policy uncertainty relative to Europe and the US

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Tom Moeller

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Nonfarm payrolls increased 177,000 (1.2% y/y) during April after rising 185,000 in March, revised from 228,000, and 102,000 in February, revised from 117,000. Expectations had been for a 130,000 rise in the Action Economics Forecast Survey. The latest figure left the three-month average change at 155,000 in April, down from 232,000 in January.

Average hourly earnings rose 0.2% during April after unrevised increases of 0.3% in March and 0.2% in February. Earnings growth of 3.8% y/y was below the 5.9% high in March 2022.

The unemployment rate, measured in the household survey, held m/m at an expected 4.2% in April, and compared to 4.1% in February and 4.0% in January. It reached a low of 3.4% in April 2023. The unemployment rate, including employees working part-time for economic reasons plus all marginally-attached workers, eased to 7.8% in April from 7.9% in March.

In the **establishment survey**, private-sector employment rose 167,000 (1.2% y/y) after a 170,000 March increase. Factory sector jobs edged 1,000 lower (-0.7% y/y) following a 3,000 gain. Construction sector employment increased 11,000 (1.7% y/y), after rising 7,000 in March.

Private service-producing sector employment increased 156,000 (1.4% y/y) in April after improving 161,000 in March. Increases varied greatly amongst service sector categories. Private education & health sector employment rose 70,000 (3.4% y/y) last month following a 74,000 March increase. Leisure & hospitality employment rose 24,000 (1.3% y/y) after a 38,000 gain. Trade, transportation & utilities rose 32,000 (0.9% y/y) in April following a 25,000 March increase. Professional & business services employment rose 17,000 (-0.1% y/y) following a 3,000 rise while temporary help employment rose 3,600 (-3.9% y/y) following a 2,700 decline. Financial activities employment improved 14,000 (1.2% y/y) after a 6,000 gain. The number of information sector jobs held steady (-0.4% y/y) last month after falling 2,000 in March.

Government sector payrolls rose 10,000 (1.3% y/y) last month after increasing 15,000 in March. The number of local government jobs increased 13,000 (1.4% y/y) following a 17,000 gain. State government employment rose 6,000 (1.8% y/y) following a 2,000 March increase but federal government payrolls fell 9,000 (-0.3% y/y), the third consecutive monthly decline.

Private-sector average hourly earnings rose 0.2% (3.8% y/y) in April after increasing 0.3% in March. Earnings in the goods-producing sector eased 0.1% (+4.0% y/y) following a 0.6% gain. Earnings in construction rose 0.3% (3.6% y/y), after a 0.2% rise but factory sector earnings declined 0.3% (+4.3% y/y) after surging 0.8% in March. In the private services-sector, earnings rose 0.2% (3.7% y/y) in April for the third straight month. Information sector pay increased 1.0% (5.2% y/y) last month after easing 0.1%, and financial activities earnings rose 0.5% (4.3% y/y) for the second straight month. Trade, transportation & utilities sector pay increased 0.4% (3.4% y/y) after 0.6%. Professional & business sector earnings increased 0.1% (4.4% y/y) after 0.2% in March. Leisure & hospitality earnings held steady (+3.8% y/y) following a 0.6% March increase.

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The length of the average workweek held steady at 34.3 hours in April. The workweek in the goods-producing sector eased to 39.8 hours from 40.0 hours. The construction sector average workweek eased to 39.0 hours from 39.3 hours while the factory sector workweek moved lower to 40.0 hours from 40.2. The average workweek in the private service sector held at 33.2 hours. Professional & business service hours fell to 36.3 hours from 36.4 while trade, transportation & utilities hours improved to 34.3 from 34.0 hours. Private education hours rose slightly to 32.8, but leisure & hospitality held steady at 25.5 hours.

In the **household survey**, the unemployment rate held at 4.2% in April as employment rose 436,000 and the size of the labor force increased 518,000. The labor force participation rate edged up to 62.6% last month from 62.5% in March. It remained below the high of 63.3% early in 2020. The rate for teenagers declined to 36.9%. For workers aged 20-24, the rate held steady at 72.1%, up from 71.8% six months earlier. For workers aged 25-54 the rate rose to 83.6%, a five-month high. For individuals 55 and over, the rate improved to 38.4% in April.

The employment/population ratio for all workers in April rose to 60.0%. It remained below the peak reading of 61.1% in February, 2020 just prior to the pandemic.

The employment and earnings data are collected from surveys taken each month during the week containing the 12th day of the month. The labor market data are contained in Haver's **USECON** database. Detailed figures are in the **EMPL** and **LABOR** databases. The expectations figures are in the **AS1REPNA** database.

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- Job growth spreads across most sectors.
- Earnings growth trend decelerates.
- Jobless rate holds steady.

U.S. Job Growth Is Firm in April but March Gain Is Lessened

Winnie Tapasanun

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Total factory orders rose a slightly less-than-expected 4.3% m/m in March after rises of 0.5% in February and 1.8% in January, data from the U.S. Census Bureau showed. A 4.5% m/m March increase had been expected in the Action Economics Forecast Survey. The March reading was the third successive monthly rise and the largest since July 2024. The year-on-year rate accelerated to 6.0% in March, the highest since November 2022, from 2.3% in February. Notably, orders for nondefense aircraft & parts soared 139.0% in March following a 7.4% drop in February and a 92.9% surge in January. Factory orders excluding defense rose 4.8% (5.9% y/y), the largest of three straight m/m/ rises, after a 0.4% February increase. Factory orders excluding the transportation sector fell 0.2% (+1.1% y/y), the first m/m fall since August, after rising 0.3% in February, January and December.

Durable goods orders jumped 9.2% (11.9% y/y) in March, the third consecutive m/m gain and the biggest since July 2024, on top of a 0.8% increase in February (matching +9.2% m/m in the advance report on April 24). The March jump reflected m/m orders increases of 27.1% (the largest m/m surge since July 2024; 31.2% y/y) in transportation equipment, 1.1% (4.9% y/y) in primary metals, 0.5% (-0.4% y/y) in furniture & related products, 0.1% (2.5% y/y) in fabricated metal products, and 0.1% (0.9% y/y) in machinery. To the downside, durable goods orders for computers & electronic products (-1.3%; +2.7% y/y) and electrical equipment, appliances & components (-1.0%; +4.2% y/y) declined m/m in March.

Nondurable goods orders, which equal nondurable goods shipments, fell 0.3% (+0.4% y/y) in March, the first m/m fall since September, after a 0.1% uptick in February. The March fall reflected m/m drops of 2.4% (-9.3% y/y) in petroleum & coal products and 0.9% (-1.2% y/y) in apparel. To the upside, the following nondurable goods shipments rose m/m in March: leather & allied products (1.5%; 8.6% y/y), beverage & tobacco products (0.7%; 5.8% y/y), paper products (0.6%; 2.3% y/y), printing (0.3%; 3.8% y/y), textile mills (0.3%; 0.8% y/y), chemical products (0.2%; 5.4% y/y), plastics & rubber products (0.2%; 0.4% y/y), food products (0.1%; 1.8% y/y), and textile products (0.1%; 2.1% y/y).

Total shipments slipped 0.1% (+2.0% y/y) in March, the first m/m easing since October, after a 0.7% increase in February. Excluding transportation, shipments were virtually unchanged m/m (+1.1% y/y) in March following six straight m/m gains. Shipments of durable goods industries inched up 0.1% (3.8% y/y) in March, the smallest of four consecutive m/m increases, after a 1.3% advance in February. This reflected m/m durable goods shipments rises of 1.2% (5.6% y/y) in primary metals, 0.9% (0.1% y/y) in furniture & related products, 0.8% (-0.2% y/y) in nonmetallic mineral products, 0.4% (0.0% y/y) in machinery, 0.3% (1.8% y/y) in fabricated metal products, 0.2% (4.5% y/y) in computers & electronic products, 0.2% (-2.1% y/y) in wood products, and 0.1% (3.0% y/y) in electrical equipment, appliances & components. In contrast, durable goods shipments for transportation equipment (-0.5%; +7.3% y/y) and miscellaneous durable goods (-0.1%; +2.9% y/y) fell m/m in March following three successive m/m increases.

Unfilled orders rose 2.0% (2.3% y/y) in March, up for the eighth month in nine, after a 0.1% uptick in February. Excluding transportation, unfilled orders dipped 0.1% (+0.7% y/y) in March, the first m/m easing since May 2024, after holding steady in February. Backlogs of durable goods rose 2.0% (2.3% y/y) in March, reflecting m/m rises of 3.1% (3.1% y/y) in transportation equipment and 0.2% (2.4% y/y) in electrical equipment, appliances & components.

Inventories edged up 0.1% (0.9% y/y) in March, the fifth straight m/m increase, after rising at the same pace in the prior two months. Excluding transportation, inventories were up 0.1% (0.5% y/y) in March, the fifth consecutive m/m rise. Durable goods inventories ticked up 0.1% (1.0% y/y) in March after holding steady in February and January; nondurable goods inventories edged up 0.1% (0.8% y/y), the fifth successive m/m increase.

The factory sector data are available in Haver’s **USECON** database. The Action Economics Forecast Survey is in the **AS1REPNA** database.

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- March manufacturers’ new orders +4.3% m/m; +6.0% y/y, highest since Nov. ’22.
- Durable goods orders (+9.2%) jump m/m, while nondurable goods orders (-0.3%) and shipments (-0.1%) decline m/m.
- Transportation equipt. orders +27.1% m/m, w/ a 139.0% m/m surge in nondefense aircraft & parts orders.
- Unfilled orders +2.0%, the eighth m/m rise in nine months.
- Inventories +0.1%, the fifth consecutive m/m increase.

U.S. Factory Orders Increase for the Third Straight Month in March

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The global manufacturing data showed broad weakening in April as conditions weakened across more than half of the contributing early reporters in the S&P survey of manufacturing. Of the 18 early reporting countries, more than half of them showed deceleration over six months and 12 months. Over three months, only 8 of 18 showed deterioration and that's about as good as it got in this report. In the current month, month-to-month changes showed more than half of the survey contributors showing weaker results than the month before. In the S&P framework, manufacturing improved month-to-month for the U.S.; however, looking at sequential averages for the U.S., U.K., European monetary union, Canada, and Japan, we see a steady weakening and results over 12 months, over six months versus 12 months, and for three months versus 6 months. The highly developed countries are not doing particularly well.

Asian economies are also showing slight deterioration but doing a little better than the developed countries in general.

Only five of the 18 reporting countries have queue percentile standings in their data back to January 2021 that are above their medians. Readings at or above the 50% mark are at or above the median standing. Canada is showing the weakest manufacturing result on record over this span, in terms of its queue percentile standing which is at 0 in the current month.

I showed the graphic for the Baltic dry goods index in this report rather than statistics on the manufacturing PMI data because the Baltic data, which reflect shipping volume for dry goods - that is excluding things like oil - is weak but it's only in the neighborhood where it's been for some time. There has been a great deal of talk about how tariffs may have impacted trade flows, expected trade flows, shipping, shipping rates, and the like. However, according to the Baltic dry goods index, there isn't much evidence that this is occurring right now and affecting the current data. That may still lie ahead but for now it's not baked in the cake.

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Globally Manufacturing Weakens

Andrew Cates

**China-US shipping activity** 
The economic fallout from escalating US-China trade tensions is becoming increasingly visible in the data. A clear example is the chart below, which highlights a sharp drop in vessel arrivals at the ports of Los Angeles and Long Beach, along with a notable decline in ships waiting offshore. These trends point to a tangible weakening in bilateral trade flows, as the effects of tit-for-tat tariffs imposed by both countries begin to bite. Given the outsized role the US and China play in global commerce, this slowdown is likely to reverberate through global supply chains, weighing on trade volumes, dampening demand, and curbing economic growth worldwide.

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**GDP growth in Q1**
Data this week showed that the US economy contracted, albeit modestly, in Q1 even as the euro area recorded a modest expansion—an unusual divergence. The contraction in US GDP can be largely attributed to a sharp increase in imports, as firms rushed to front-load purchases ahead of anticipated tariff hikes. In addition, domestic demand was subdued, with weaker contributions from both consumer spending and government consumption. This decoupling between the US and euro area economies is particularly striking given the current global focus on the US dollar. While the euro area has shown unexpected signs of resilience, the US downturn raises important questions about its underlying momentum, especially as trade dynamics and policy uncertainty continue to cloud the outlook.

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**The US dollar versus yield differentials**
Chart 3 below illustrates a sharp breakdown in the correlation between the US-Germany 10-year yield differential and the EUR/USD exchange rate. Historically, the dollar has moved closely with interest rate spreads, as yield-seeking capital flowed into US assets. But since early 2025—and more acutely following the April tariff actions—the dollar has weakened markedly even as the yield spread has narrowed only modestly. This decoupling underscores a critical shift: capital markets are reacting not just to monetary policy, but to rising trade and geopolitical uncertainty. In other words, the exchange rate is now being driven as much by risk sentiment as by interest rate arbitrage.

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**The US economy’s structural outperformance and the dollar**
A second dynamic, captured in the next chart, reveals a tight correlation between the US real effective exchange rate and the potential GDP growth differential between the US and euro area over the past 50-60 years. This raises the question: has dollar strength (until recently) merely been a reflection of US growth leadership—or are capital inflows themselves helping to sustain this growth outperformance? In effect, the tail may be wagging the dog. Global investors have long allocated capital to the US, attracted by its macroeconomic resilience, technological leadership, and deep, liquid financial markets. The danger now is that the US trade war may disrupt this equilibrium. A sharp or sustained reduction in capital inflows could undermine growth, weaken the dollar, and trigger broader financial instability. Moreover, reversing this dynamic is not straightforward—barring a credible structural resurgence in European (or Asian) growth, the global investment landscape remains tilted toward the US.

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**US competitiveness versus Europe, China and Japan** 
The next chart below examines relative unit labour costs across major economies since 2011. The US and China have seen a broadly similar trajectory, with steady increases in relative cost structures, while the euro area has remained flat and Japan has seen dramatic improvement. This suggests that, from a cost competitiveness standpoint, the US is not uniquely disadvantaged vis-à-vis China. However, as we discuss further below, this parallel erosion of cost competitiveness is occurring at much higher nominal wage levels in the US, which blunts its ability to regain export share through tariff-related shifts alone. The trade war strategy—absent a corresponding improvement in productivity or structural reforms—risks imposing costs without delivering material competitiveness gains.

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**Average wages in selected developed and developing economies**
This point is reinforced by the final chart, which shows estimates for average monthly wages across countries in 2024. US labour remains much more expensive than in peer or emerging economies. So even if China’s costs rise in tandem with the US, the global supply chain has ample alternatives. 'China plus one' strategies are accelerating, and the US remains structurally misaligned with low-cost production hubs. Tariffs aimed at reshoring supply chains are unlikely to deliver sustained gains unless accompanied by deep supply-side reforms, and risk further disincentivizing foreign direct investment if global firms perceive US trade policy as erratic or punitive.

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Financial markets found a measure of calm this week, buoyed by some subtle shifts in tone from US policymakers. A softening in the administration’s rhetoric around trade tariffs coupled with a less confrontational stance toward Federal Reserve Chair Jerome Powell, helped ease tensions that had roiled markets earlier in the month. Equities rebounded modestly, and volatility indicators edged lower, reflecting cautious optimism that the worst of the policy shocks may be behind us. But beneath the surface, significant downside risks persist. New shipping data point to a pronounced slowdown in US-China trade flows (chart 1), suggesting the damage from recent tariff escalations is already rippling through global supply chains. Meanwhile, incoming data for the US revealed an unexpected contraction in the economy in Q1 and further signs of weakness in the labour market (chart 2). The US dollar, in the meantime, while long supported by superior growth and yield differentials, has begun to decouple from traditional drivers (charts 3 and 4) suggesting growing pressure on capital flows. At the same time, structural imbalances are drawing renewed scrutiny: unit labour cost comparisons show the US steadily losing competitiveness (chart 5), while nominal wage disparities remain stark versus China and other Asian economies, further complicating any effort to restore trade balance without broader reforms (chart 6). In short, while markets may be drawing temporary comfort from a pause in tariff brinkmanship, the deeper economic and financial vulnerabilities exposed this month remain unresolved—and increasingly central to the global macro narrative.

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Charts of the Week: Tariff Truce, Tenuous Trust

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U.S. light vehicle sales dropped 2.9% (+6.5% y/y) to 17.31 million units (SAAR) in April after surging 10.8% to 17.82 million units in March. The retreat in April vehicle sales accompanied a 1.7% y/y rise in real disposable income through March, which compared to 2.0% growth last year.

Sales declines were broad-based last month. Light truck sales fell 1.3% (+9.9% y/y) during April to 14.34 million units (SAAR), after rising 12.4% in March. Purchases of domestically-made light trucks declined 1.2% (+11.9% y/y) to 11.02 million units, after jumping 12.5% in March. Sales of imported light trucks fell 1.8% (+4.4% y/y) to 3.32 million units, following an 11.6% March surge.

Trucks’ record 82.8% share of the light vehicle market last month compared to 81.5% in March and 80.3% in April of last year. The share averaged 80.3% during all of 2024 versus 53.3% ten years earlier.

Auto sales also declined last month, down 9.5% (-7.5%) to 2.97 million units (SAAR) following a 3.5% March rise. The decline reversed all of the increase over the prior two months. Purchases of domestically-produced cars fell 9.8% (-4.3% y/y) last month to 2.22 million units, after rising 3.8% in March. Sales of imported autos declined 9.6% (-15.7% y/y) to 0.75 million units, following a 2.5% March increase.

Imports' 23.5% share of the U.S. light vehicle market was little changed from 23.6% in March and compared to a May 2023 low of 22.9% and a high of 26.3% in November of 2023. Imports' share of the passenger car market held steady at 25.3% last month and compared to 27.7% in April of last year. It reached a high of 38.7% in September 2021. Imports' share of the light truck market eased to 23.2% last month after falling to 23.3% in March.

U.S. vehicle sales figures can be found in Haver's **USECON** database. Additional detail by manufacturer is in the I**NDUSTRY** database.

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- Light truck sales pull back, while auto sales tumble.
- Both domestic and imported sales decline.
- Imports' market share slips further.

Economy in Brief: June 2007

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