Robert Brusca

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503a.jpg" width="353">Productivity mustered a larger gain than we had expected in Q1 but the trends still show productivity is on a deteriorating trend. 
Just as a refresher, recall that productivity is important because it governs the pace at which the economy can grow and it is an endogenous variable (one determined by the economic system not imposed upon it). Coupled with labor force growth, productivity sets the growth pace for the economy. Population growth is given to an economy. Labor force growth is the result of demographics (including population growth) tempered by economic decisions such as labor-leisure tradeoffs. Labor force growth can be augmented in small amounts by immigration. But the big variable that an economy controls that can alter its growth trends is productivity. All G-7 countries - indeed OECD countries and many developing nations - are seeing the same withering trend to population growth and advancing aging of the population. Slower population growth undercuts the base for growth in the labor force and therefore in the economy. Aging generally erodes labor force participation rates. So the key to keeping growth up is productivity. 
A fading pace of productivity growth is bad news for a nation like the US with huge needs to pay for its national medical insurance program, a burdened Social Security system, an ample stock of debt already on the books plus running large current fiscal deficits. Aging will place more burdens on younger workers. Low productivity growth will only make hard choices even harder.
The trend to productivity growth is shown in the chart above using annualized quarterly changes as the red line and with the blue line guiding your eye to the predominant year/year trend. Despite quarterly volatility, the trend is clearly moving lower.
This a tough policy issue for the Fed and one it did not face under Greenspan since inflation fell and productivity rose keeping growth strong in a rare double win for policymakers that made Greenspan look as if he could walk on water. And indeed he can, but only when it is frozen. The problem for Bernanke is that the lake is warming up and he&#146;s still in the middle. The Dilemma of Fed Policy 
With the Fed having abandoned the V-G (Volcker-Greenspan) mantra that there is no inflation-growth conflict in the Fed&#146;s mandate since low inflation boosts growth in the long run, the Fed is being forced into a bitter political dilemma. Should it to push for more growth as productivity fades or need it alter its inflation guideline? Congressman Frank continues to press the Fed to push for growth and to let wages rise. In dropping the old V-G approach to policy the Fed has fallen right into Frank&#146;s trap. 
This quarter&#146;s numbers give the Fed some unexpected respite. While the GDP growth number is not good, productivity did revive more than expected. More helpful was the low 0.6% (annualized) rise in unit labor costs, that had been expected to be much higher. Now the trend in wage costs is much more up in the air, instead of clearly accelerating as it was previously. At 3.4% y/y (last quarter), unit labor costs were real threat to an inflation ceiling of 2%. At 1.3% (this quarter) the Fed again seems to have some breathing room. But make no mistake about it. This was a break for the quarter. Unless something changes, productivity is on a path to cause the Fed trouble. And evidence suggests that labor cost are still simmering. This quarter&#146;s 2.3% rise in compensation costs comes after Q4&#146;s rise of 8.5% making it hard to judge the trend. The Fed&#146;s own recent Beige Book assessment of regional trends saw rather widespread pressure in the labor market despite this quarter&#146;s beneficial reading in the productivity report. Quarterly numbers are volatile but the trends are telling.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
NONFARM PRODUCTIVITY
</tr>
</thead>
<tbody>
<tr class="odd">
<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>
<td class="firstcol">Nonfarm Unit Labor Cost</td>
<td>1.3%</td>
<td>3.4%</td>
<td>2.6%</td>
<td>3.1%</td>
<td>3.6%</td>
<td>1.5%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Output/Hour</td>
<td>1.1%</td>
<td>1.6%</td>
<td>0.9%</td>
<td>1.9%</td>
<td>2.0%</td>
<td>2.1%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Comp/Hour</td>
<td>2.4%</td>
<td>5.0%</td>
<td>3.5%</td>
<td>5.1%</td>
<td>5.7%</td>
<td>3.7%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Real Comp/Hour</td>
<td>0.0%</td>
<td>2.9%</td>
<td>0.1%</td>
<td>1.0%</td>
<td>1.9%</td>
<td>0.0%</td>
</tr>
<tr class="odd">
<td colspan="7">Manufacturing</td>
</tr>
<tr>
<td class="firstcol">MFG Unit Labor Cost</td>
<td>-2.0%</td>
<td>-0.5%</td>
<td>-2.3%</td>
<td>0.1%</td>
<td>2.0%</td>
<td>-1.2%</td>
</tr>
<tr>
<td class="firstcol">MFG Output/Hour</td>
<td>3.6%</td>
<td>3.9%</td>
<td>4.2%</td>
<td>3.6%</td>
<td>4.1%</td>
<td>4.6%</td>
</tr>
<tr>
<td class="firstcol">MFG Comp/Hour</td>
<td>1.5%</td>
<td>3.4%</td>
<td>1.8%</td>
<td>3.7%</td>
<td>6.1%</td>
<td>3.4%</td>
</tr>
<tr>
<td class="firstcol">MFG Real Comp/Hour</td>
<td>-0.9%</td>
<td>1.4%</td>
<td>-1.5%</td>
<td>-0.3%</td>
<td>2.3%</td>
<td>-0.4%</td>
</tr>
</tbody>
</table>
</body>
</html>

Productivity mustered a larger gain than we had expected in Q1 but the trends still show productivity is on a deteriorating trend. Just as a refresher, recall that productivity is important because it governs the pace at which the [...]

Upward Surprise on U.S. Productivity

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503a.jpg" width="353">Productivity mustered a larger gain than we had expected in Q1 but the trends still show productivity is on a deteriorating trend. 
Just as a refresher, recall that productivity is important because it governs the pace at which the economy can grow and it is an endogenous variable (one determined by the economic system not imposed upon it). Coupled with labor force growth, productivity sets the growth pace for the economy. Population growth is given to an economy. Labor force growth is the result of demographics (including population growth) tempered by economic decisions such as labor-leisure tradeoffs. Labor force growth can be augmented in small amounts by immigration. But the big variable that an economy controls that can alter its growth trends is productivity. All G-7 countries - indeed OECD countries and many developing nations - are seeing the same withering trend to population growth and advancing aging of the population. Slower population growth undercuts the base for growth in the labor force and therefore in the economy. Aging generally erodes labor force participation rates. So the key to keeping growth up is productivity. 
A fading pace of productivity growth is bad news for a nation like the US with huge needs to pay for its national medical insurance program, a burdened Social Security system, an ample stock of debt already on the books plus running large current fiscal deficits. Aging will place more burdens on younger workers. Low productivity growth will only make hard choices even harder.
The trend to productivity growth is shown in the chart above using annualized quarterly changes as the red line and with the blue line guiding your eye to the predominant year/year trend. Despite quarterly volatility, the trend is clearly moving lower.
This a tough policy issue for the Fed and one it did not face under Greenspan since inflation fell and productivity rose keeping growth strong in a rare double win for policymakers that made Greenspan look as if he could walk on water. And indeed he can, but only when it is frozen. The problem for Bernanke is that the lake is warming up and he&#146;s still in the middle. The Dilemma of Fed Policy 
With the Fed having abandoned the V-G (Volcker-Greenspan) mantra that there is no inflation-growth conflict in the Fed&#146;s mandate since low inflation boosts growth in the long run, the Fed is being forced into a bitter political dilemma. Should it to push for more growth as productivity fades or need it alter its inflation guideline? Congressman Frank continues to press the Fed to push for growth and to let wages rise. In dropping the old V-G approach to policy the Fed has fallen right into Frank&#146;s trap. 
This quarter&#146;s numbers give the Fed some unexpected respite. While the GDP growth number is not good, productivity did revive more than expected. More helpful was the low 0.6% (annualized) rise in unit labor costs, that had been expected to be much higher. Now the trend in wage costs is much more up in the air, instead of clearly accelerating as it was previously. At 3.4% y/y (last quarter), unit labor costs were real threat to an inflation ceiling of 2%. At 1.3% (this quarter) the Fed again seems to have some breathing room. But make no mistake about it. This was a break for the quarter. Unless something changes, productivity is on a path to cause the Fed trouble. And evidence suggests that labor cost are still simmering. This quarter&#146;s 2.3% rise in compensation costs comes after Q4&#146;s rise of 8.5% making it hard to judge the trend. The Fed&#146;s own recent Beige Book assessment of regional trends saw rather widespread pressure in the labor market despite this quarter&#146;s beneficial reading in the productivity report. Quarterly numbers are volatile but the trends are telling.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
NONFARM PRODUCTIVITY
</tr>
</thead>
<tbody>
<tr class="odd">
<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>
<td class="firstcol">Nonfarm Unit Labor Cost</td>
<td>1.3%</td>
<td>3.4%</td>
<td>2.6%</td>
<td>3.1%</td>
<td>3.6%</td>
<td>1.5%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Output/Hour</td>
<td>1.1%</td>
<td>1.6%</td>
<td>0.9%</td>
<td>1.9%</td>
<td>2.0%</td>
<td>2.1%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Comp/Hour</td>
<td>2.4%</td>
<td>5.0%</td>
<td>3.5%</td>
<td>5.1%</td>
<td>5.7%</td>
<td>3.7%</td>
</tr>
<tr>
<td class="firstcol">Nonfarm Real Comp/Hour</td>
<td>0.0%</td>
<td>2.9%</td>
<td>0.1%</td>
<td>1.0%</td>
<td>1.9%</td>
<td>0.0%</td>
</tr>
<tr class="odd">
<td colspan="7">Manufacturing</td>
</tr>
<tr>
<td class="firstcol">MFG Unit Labor Cost</td>
<td>-2.0%</td>
<td>-0.5%</td>
<td>-2.3%</td>
<td>0.1%</td>
<td>2.0%</td>
<td>-1.2%</td>
</tr>
<tr>
<td class="firstcol">MFG Output/Hour</td>
<td>3.6%</td>
<td>3.9%</td>
<td>4.2%</td>
<td>3.6%</td>
<td>4.1%</td>
<td>4.6%</td>
</tr>
<tr>
<td class="firstcol">MFG Comp/Hour</td>
<td>1.5%</td>
<td>3.4%</td>
<td>1.8%</td>
<td>3.7%</td>
<td>6.1%</td>
<td>3.4%</td>
</tr>
<tr>
<td class="firstcol">MFG Real Comp/Hour</td>
<td>-0.9%</td>
<td>1.4%</td>
<td>-1.5%</td>
<td>-0.3%</td>
<td>2.3%</td>
<td>-0.4%</td>
</tr>
</tbody>
</table>
Nonmanufacturing ISM Shows Some Life 
by <a href="/comment/Brusca.html">Robert Brusca</a> May 3, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503b.jpg" width="353">The Nonmanufacturing ISM rose smartly to 56 from 52.4. Its employment gauge rose to 51.9 from 50.8. Prices continue to be under upward pressures. 
The details of the ISM report shows that the main measures of the survey are just below their period averages. The nonmanufacturing sector is dominated by services but also contains construction and mining. Apparently construction did pick up in the month. But despite the jump in activity, overall orders and backlogs were more restrained. Both showed growth or neutrality but each was below its customary reading (see relative calculations relative to the mean in the far right of the table). The readings that score lowest as a percentage of their range of values (percentiles) are supplier deliveries, inventory sentiment and import orders. Low supplier deliveries tell us there is still plenty of slack. The inventory reading tells us that inventories are more under control than they usually are and that could be a good sign for future ordering especially since growth in this sector has been strong. A weaker import reading could be a bad sign about activity or a sign that the weaker dollar has taken some toll on imports 
During the period nonmanufacturing jobs averaged gains of 134K per month. The current ISM jobs barometer is just above the average for this period. Jobs: the outlook 
Of course the &#145;wild card&#146; in the nonmanufacturing jobs forecast is what happens with construction jobs. Construction spending in the month rose. And the ISM survey sees some increased construction activity. But those still might not be the right barometer for jobs. For consumer services, spending slowed in March, but again that may not be the right barometer for April, plus consumer service spending is strong apart from the unusual weak March result, having had a very brisk Q1 2007. 
The service portion of the nonmanufacturing report has probably remained pretty firm. Construction is still a big question mark for any forecast. AND recent construction job growth has been volatile month to month. Still jobless claims have remained low and dipped further after the sample period for nonfarm employment passed. Claims do not act like a rash of construction job cuts have hit the street - or any others for that matter. That claims figure suggests that the job market is still probably pretty strong. 
Overall the ISM nonmanufacturing index has been slowing despite the rebound this month. Still the ADP forecast seems far too weak at 64K overall. The ISM manufacturing survey showed a strong rise in the month for its jobs index. That should auger well for manufacturing job gains. April tends to be a strong month for job gains overall. The ISM nonmanufacturing reading was firm. We think a number like +120K or higher is sensible for private nonfarm jobs and government could boost things even beyond that. This month we part ways with the ADP Survey. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">&nbsp;</th>
ISM Nonmanufacturing Statistics from Jan. 1998 to Date
<th scope="col">&nbsp;</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">ISM-NMFG</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>56.0</td>
<td>52.4</td>
<td>4.7</td>
<td>57.5</td>
<td>8.2</td>
<td>67.9</td>
<td>40.5</td>
<td>27.4</td>
<td>56.6</td>
<td>97</td>
</tr>
<tr>
<td class="firstcol">New Orders</td>
<td>55.5</td>
<td>53.8</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>55.5</td>
<td>97</td>
</tr>
<tr>
<td class="firstcol">Backlogs</td>
<td>50.0</td>
<td>52.5</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>57.6</td>
<td>98</td>
</tr>
<tr>
<td class="firstcol">Supplier Deliveries</td>
<td>51.0</td>
<td>50.0</td>
<td>2.1</td>
<td>53.6</td>
<td>4.0</td>
<td>60.5</td>
<td>48.0</td>
<td>12.5</td>
<td>24.0</td>
<td>95</td>
</tr>
<tr>
<td class="firstcol">Inventory Sentiment*</td>
<td>60.5</td>
<td>63.0</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>39.3</td>
<td>96</td>
</tr>
<tr>
<td class="firstcol">Inventories</td>
<td>52.0</td>
<td>52.0</td>
<td>3.2</td>
<td>50.5</td>
<td>6.3</td>
<td>59.0</td>
<td>43.5</td>
<td>15.5</td>
<td>54.8</td>
<td>103</td>
</tr>
<tr>
<td class="firstcol">Prices</td>
<td>63.5</td>
<td>63.3</td>
<td>8.2</td>
<td>59.9</td>
<td>13.7</td>
<td>80.5</td>
<td>41.3</td>
<td>39.2</td>
<td>56.6</td>
<td>106</td>
</tr>
<tr>
<td class="firstcol">Employment</td>
<td>51.9</td>
<td>50.8</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>50.0</td>
<td>100</td>
</tr>
<tr>
<td class="firstcol">Export Orders</td>
<td>55.5</td>
<td>48.5</td>
<td>4.5</td>
<td>54.8</td>
<td>8.3</td>
<td>64.0</td>
<td>44.5</td>
<td>19.5</td>
<td>56.4</td>
<td>101</td>
</tr>
<tr>
<td class="firstcol">Import Orders</td>
<td>52.5</td>
<td>50.0</td>
<td>4.1</td>
<td>54.7</td>
<td>7.4</td>
<td>63.5</td>
<td>45.5</td>
<td>18.0</td>
<td>38.9</td>
<td>96</td>
</tr>
</tbody>
</table>
Driving Productivity Increases 
by <a href="/comment/Stone.html">Carol Stone</a> May 3, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503c.jpg" width="353">
A recently popular book on writing and grammar is titled &quot;Eats, Shoots and Leaves&quot;. The title is ambiguous because the intent of the original writer of the phrase was to describes the diet of a particular animal: it &quot;eats shoots and leaves&quot;. But the addition of the comma alters the meaning dramatically.
A somewhat parallel situation derives from our title above, &quot;Driving Productivity Increases&quot;. Punctuation has no role here, but the meaning is just as ambiguous. On a day when productivity data are reported for Q1, a reader of this website might well expect this discussion to concern factors that generated the rise in Q1 productivity. But Mr. Brusca has done that elsewhere here. Our subject is, instead, driving. Today, the Federal Highway Administration reported miles driven in March for the total US and the 50 states. After a simple description of these mileage figures, we will discuss &quot;driving productivity&quot;, that is, the amount of output (GDP) per mile driven. It, like labor productivity, is rising. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503d.jpg" width="353">
As seen in the first graph, total miles driven have flattened out. The 255.8 billion miles in March 2007 are a mere 0.3% above March 2006, and the 12-month moving average has declined outright by 0.2%. So people in the nation as a whole have restrained their driving.
The pattern around the nation varies widely, however. We looked at the top four states for miles driven, California, Texas, Florida and New York. The individual state data only began in 2003, so there&#39;s no much history to go on. Miles driven continue to increase in California, but more slowly than at this time last year. The March 2007 figure is 1.4% above the year-earlier and averaged across 12 months to smooth the seasonality, it is up 0.6%. The 12 months through March 2006, in turn, had been up 1.8% on the year before. In New York, a similar pattern of slowing growth had been in place. But February and March each had a marked decline from year-ago amounts, 2.8% and 3.0%. And the 12-month moving average now shows a non-trivial decline as well, 0.7%, for the period ending in March. People are driving less in New York State. <img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070503e.jpg" width="353">
They are also driving less in Texas, somewhat unexpectedly. In Florida, miles driven are still increasing, but at a slower rate than before the run-up in gasoline prices. In both of these states, the March figure is a new monthly record, though. For the brief history we have, March seems to be a peak driving month during the year, although Texas has seen larger figures in the summer months of some years.
So what about &quot;driving productivity&quot;. We compared GDP to mileage driven, calculating GDP per mile. As energy gets more expensive and people may be driving less, would that necessarily translate into weaker GDP. Is the US such a vehicle-dependent economy that it would suffer visibly by having to drive less? Encouragingly, over the last couple of years, this has not been the case. While some slowing may well result from this circumstance, it appears that more economical use of vehicles can offset at least some of the reduced driving volume. &quot;Driving productivity increases&quot; seems to be a statement of fact, not a misuse of words.
Total miles driven are contained in Haver&#39;s main USECON database. The state data are in REGIONAL. The graphs illustrate the new multiple series features of the upcoming version of DLXVG3 along with the manipulation of &quot;Styles &amp; Colors&quot; to alter the colors of series from the &quot;default&quot; arrangement.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">Miles Traveled (Billions)</th>
<th scope="col">Mar 2007</th>
<th scope="col">Feb 2007</th>
<th scope="col">Jan 2007</th>
<th scope="col">Year Ago</th>
<th scope="col">2006</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2000</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">US</td>
<td>255.8</td>
<td>215.0</td>
<td>229.1</td>
<td>255.0</td>
<td>--</td>
<td>--</td>
<td>--</td>
<td>--</td>
</tr>
<tr>
<td class="firstcol">12-mo Moving Average</td>
<td>248.1</td>
<td>248.0</td>
<td>248.4</td>
<td>248.6</td>
<td>248.5</td>
<td>247.4</td>
<td>244.8</td>
<td>228.9</td>
</tr>
<tr class="odd">
<td class="firstcol">California</td>
<td>27.7</td>
<td>23.5</td>
<td>22.4</td>
<td>27.4</td>
<td>28.0</td>
<td>27.7</td>
<td>27.3</td>
<td>--</td>
</tr>
<tr>
<td class="firstcol">Texas</td>
<td>21.3</td>
<td>17.9</td>
<td>18.4</td>
<td>21.0</td>
<td>19.6</td>
<td>19.5</td>
<td>19.0</td>
<td>--</td>
</tr>
<tr class="odd">
<td class="firstcol">Florida</td>
<td>18.9</td>
<td>15.9</td>
<td>17.5</td>
<td>18.7</td>
<td>16.7</td>
<td>16.6</td>
<td>15.8</td>
<td>--</td>
</tr>
<tr>
<td class="firstcol">New York</td>
<td>11.8</td>
<td>9.7</td>
<td>10.8</td>
<td>12.1</td>
<td>11.5</td>
<td>11.5</td>
<td>11.4</td>
<td>--</td>
</tr>
<tr class="odd">
<td class="firstcol">Memo: GDP/Mile</td>
<td>--</td>
<td>3.85(Q1)</td>
<td>--</td>
<td>3.74(Q1)</td>
<td>3.83</td>
<td>3.72</td>
<td>3.64</td>
<td>3.57</td>
</tr>
</tbody>
</table>
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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/070502a.jpg" width="353">
Employment in Germany rose 52,000 in March, following gains of 46,000 and 76,000 in February and January, respectively. This was the 13th consecutive monthly increase in employment, bringing it up 1.5% (annualized) from February 2006. By comparison over the same period, US employment rose 1.9% (comparable &quot;household&quot; survey) but 0.5% in the UK and -- through Q4 2006 -- 0.9% in France. So German employment growth is quite vigorous by its neighbors&#39; standards. Separate data on job vacancies shows some decline in most recent months, but these openings are more plentiful than a year ago, suggesting that employment might go up still further. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502b.jpg" width="353">
By the same token, unemployment is falling markedly. The ILO definition, used throughout the Eurozone, puts the rate at 6.8% in March, down 1.5 points from the year-ago level and the lowest since April 2001. The locally preferred &quot;registered&quot; unemployment rate was 9.2% in April, sharply lower than 11.3% in April 2006. The latest figure is the lowest since the same in May 2001 and was last lower in March 1995.
By the &quot;registered&quot; measure, the Germans appear distinctive in keeping unemployment down among their youth. The rate, shown in the third graph, for people under 25, was only 8.4% (not seasonally adjusted). The &quot;registered&quot; status means that people are indeed registered with a local employment agency and taking action to find work, at least partially through the placement service of the employment agency. So this is not the same thing as simply &quot;wanting&quot; to work, the concept used in the ILO definition of unemployment. Even so, it is still impressive that young people who look for work according to the registration procedures in Germany do seem to find jobs, keeping their unemployment down. The ILO &quot;labor force&quot; definition, by contrast, does remain considerably higher, at 13.9% in March, not seasonally adjusted, than overall unemployment, 7.2%. There is some good news, though, in recent historical comparison: March 2006 saw 15.2% and March 2005, 17.1%. So the firmer German economy is helping reduce youth unemployment by either definition. <img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502c.jpg" width="353"><img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502d.jpg" width="353">

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">GERMANY (Seas Adj, ex as noted)</th>
<th scope="col">Apr 2007</th>
<th scope="col">Mar 2007</th>
<th scope="col">Feb 2007</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">LFS Employment (mil)</td>
<td>--</td>
<td>39.50</td>
<td>39.45</td>
<td>38.89</td>
<td>39.09</td>
<td>38.82</td>
<td>38.88</td>
</tr>
<tr>
<td class="firstcol">Change (thous)</td>
<td>--</td>
<td>52</td>
<td>46</td>
<td>601</td>
<td>271</td>
<td>-52</td>
<td>151</td>
</tr>
<tr class="odd">
<td class="firstcol">Yr/Yr % Change, NSA</td>
<td>--</td>
<td>1.6</td>
<td>1.5</td>
<td>--</td>
<td>0.7</td>
<td>-0.1</td>
<td>0.4</td>
</tr>
<tr>
<td class="firstcol">Unemployment Rate (%, ILO Def.)</td>
<td>--</td>
<td>6.8</td>
<td>6.9</td>
<td>8.3</td>
<td>8.1</td>
<td>9.1</td>
<td>9.2</td>
</tr>
<tr class="odd">
<td class="firstcol">Registered Unemployment Rate (%)</td>
<td>9.2</td>
<td>9.2</td>
<td>9.3</td>
<td>11.3</td>
<td>10.8</td>
<td>11.7</td>
<td>10.6</td>
</tr>
<tr>
<td class="firstcol">Job Vacancies (thous)</td>
<td>610</td>
<td>621</td>
<td>642</td>
<td>503</td>
<td>564.2</td>
<td>413.1</td>
<td>284.3</td>
</tr>
</tbody>
</table>
</body>
</html>

Employment in Germany rose 52,000 in March, following gains of 46,000 and 76,000 in February and January, respectively. This was the 13th consecutive monthly increase in employment, bringing it up 1.5% (annualized) from February 2006. [...]

Employment Continues to Expand in Germany; Unemployment Lowest in 6 Years

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502e.jpg" width="353">
Factory orders struck back in March with an upward revision to durable goods orders and more strength in nondurables than anyone expected. While the three-month growth rate for orders is still severely negative, the outturn for the past two months makes it clear that such a result is temporary. Get December out of the base calculation and three month growth rates will soar....and if we look at durable goods orders alone, the source of most of the movement in factory orders, we find that seasonal adjustment has left us with some curiously consistent patterns in orders that have tended to skew the first quarter into weakness. 
The chart on the left shows the results. 
To create this chart I have taken a five-year quarterly moving average of each quarter&#146;s orders. This is NOT a five-quarter moving average as one is normally constructed. Rather it is a five-quarter moving average of five years worth of Q1, then of Q2 then of Q3 and so on, by quarter. Q/Q percentage changes are calculated off this base of five year average values, and are extended back in time as well. What emerges is a picture of the average seasonality over the past five years. By comparing each successive &#145;four quarter&#146; pattern, we can see how stable seasonality has been in recent years. Backward moving comparisons drop the recent quarter and add one from farther down the line for each quarter of the year. What the calculations show is that Q1 has tended to be the weak quarter even as the comparisons have shifted their patterns back in time. 
What is constant is that Q1 is weak and is therefore NOT representative of the true trend in durable goods orders. Growth rates calculated in Q1 will tend to distort growth downward in the short term. 
This result is not an artifact of a few very weak quarters occurring in Q1 due to bad weather or some other spurious factor. If we look at raw Q/Q percentage change data, over the 11 years we can perform this calculation, the first quarter emerges as the weakest in 6 out of 11 years. Since there are four quarters in the year we would expect out of sheer randomness to find Q1 is the weakest of the four quarters about 3 times out of twelve, not six out of eleven. It is emerging as weakest more than twice as often as expected. 
Certainly there have been other weak reports in the economy as well as durable goods. But durable goods stick out as something that has been very worrisome and extremely weak not just modestly soft like the ISM readings. And its readings may have biased other measures. Some selected components of orders filter into the index of leading economic indicators. So there is plenty of room for this distortion to have crept into other measures including consumer confidence to say nothing of being fodder for economists looking for something to support their pessimism. 
Machinery has been one persistently weak category. But its string of weakness is giving way to some upward momentum. While three month growth rates are weak for machinery across the board, that owes to another distortion, that December tends to be a machinery order high point. That of course will bias lower the three-month growth rate for machinery since December is the base for the three-month calculation in March. 
If we look at some machinery categories to see why capital spending has lagged, we find that in March there is a sharp reversal in monthly trends. In Construction machinery, despite ongoing concerns about weakness in US housing, strength is emerging. Engines and turbines, a previously weak category, is also up very sharply in March. Mining and oil field equipment is solidly back in the balance. And, despite ongoing inventory liquidation in the US, material handling equipment more than reversed February&#146;s decline. 
On balance we can sift though some of the more detailed data and find a lot of good stories in durable goods. 
But if we look &#145;top down&#146; at the seasonal factors we also find a bad story - bad in the sense that it is a story of how we have been mislead by persistently pessimistic orders results early in the year. 
With Q1 behind us the orders picture should continue to improve both for statistical reasons and because I think that the economy is doing better. Moreover the weakness in the dollar should be helping US equipment manufactures and exports. For a lot of these equipment makers the question is not just what is the demand in the US but what is global demand. And global demand is still looking pretty solid. We know that US manufacturing has been through a tough patch. But we expect it to pull out, helped by foreign demand and also by the fact that it wasn&#146;t in as big a hole as it seemed.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
Factory Orders
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Factory Orders</td>
<td>3Mo</td>
<td>6Mo</td>
<td>9Mo</td>
<td>12Mo</td>
<td>YearAgo</td>
</tr>
<tr>
<td class="firstcol">Shipments</td>
<td>-2.9%</td>
<td>1.8%</td>
<td>-3.6%</td>
<td>-0.5%</td>
<td>5.7%</td>
</tr>
<tr>
<td class="firstcol">New Orders</td>
<td>-5.6%</td>
<td>-4.5%</td>
<td>-2.4%</td>
<td>-1.3%</td>
<td>10.7%</td>
</tr>
<tr>
<td class="firstcol">Unfilled Orders</td>
<td>13.7%</td>
<td>18.7%</td>
<td>20.9%</td>
<td>19.8%</td>
<td>20.9%</td>
</tr>
<tr>
<td class="firstcol">Inventories</td>
<td>0.9%</td>
<td>2.0%</td>
<td>4.0%</td>
<td>5.7%</td>
<td>2.9%</td>
</tr>
</tbody>
</table>
</body>
</html>

Factory orders struck back in March with an upward revision to durable goods orders and more strength in nondurables than anyone expected. While the three-month growth rate for orders is still severely negative, the outturn for the [...]

US Factory Orders Strike Back with Strength...and Against a Statistical Anomaly

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502e.jpg" width="353">
Factory orders struck back in March with an upward revision to durable goods orders and more strength in nondurables than anyone expected. While the three-month growth rate for orders is still severely negative, the outturn for the past two months makes it clear that such a result is temporary. Get December out of the base calculation and three month growth rates will soar....and if we look at durable goods orders alone, the source of most of the movement in factory orders, we find that seasonal adjustment has left us with some curiously consistent patterns in orders that have tended to skew the first quarter into weakness. 
The chart on the left shows the results. 
To create this chart I have taken a five-year quarterly moving average of each quarter&#146;s orders. This is NOT a five-quarter moving average as one is normally constructed. Rather it is a five-quarter moving average of five years worth of Q1, then of Q2 then of Q3 and so on, by quarter. Q/Q percentage changes are calculated off this base of five year average values, and are extended back in time as well. What emerges is a picture of the average seasonality over the past five years. By comparing each successive &#145;four quarter&#146; pattern, we can see how stable seasonality has been in recent years. Backward moving comparisons drop the recent quarter and add one from farther down the line for each quarter of the year. What the calculations show is that Q1 has tended to be the weak quarter even as the comparisons have shifted their patterns back in time. 
What is constant is that Q1 is weak and is therefore NOT representative of the true trend in durable goods orders. Growth rates calculated in Q1 will tend to distort growth downward in the short term. 
This result is not an artifact of a few very weak quarters occurring in Q1 due to bad weather or some other spurious factor. If we look at raw Q/Q percentage change data, over the 11 years we can perform this calculation, the first quarter emerges as the weakest in 6 out of 11 years. Since there are four quarters in the year we would expect out of sheer randomness to find Q1 is the weakest of the four quarters about 3 times out of twelve, not six out of eleven. It is emerging as weakest more than twice as often as expected. 
Certainly there have been other weak reports in the economy as well as durable goods. But durable goods stick out as something that has been very worrisome and extremely weak not just modestly soft like the ISM readings. And its readings may have biased other measures. Some selected components of orders filter into the index of leading economic indicators. So there is plenty of room for this distortion to have crept into other measures including consumer confidence to say nothing of being fodder for economists looking for something to support their pessimism. 
Machinery has been one persistently weak category. But its string of weakness is giving way to some upward momentum. While three month growth rates are weak for machinery across the board, that owes to another distortion, that December tends to be a machinery order high point. That of course will bias lower the three-month growth rate for machinery since December is the base for the three-month calculation in March. 
If we look at some machinery categories to see why capital spending has lagged, we find that in March there is a sharp reversal in monthly trends. In Construction machinery, despite ongoing concerns about weakness in US housing, strength is emerging. Engines and turbines, a previously weak category, is also up very sharply in March. Mining and oil field equipment is solidly back in the balance. And, despite ongoing inventory liquidation in the US, material handling equipment more than reversed February&#146;s decline. 
On balance we can sift though some of the more detailed data and find a lot of good stories in durable goods. 
But if we look &#145;top down&#146; at the seasonal factors we also find a bad story - bad in the sense that it is a story of how we have been mislead by persistently pessimistic orders results early in the year. 
With Q1 behind us the orders picture should continue to improve both for statistical reasons and because I think that the economy is doing better. Moreover the weakness in the dollar should be helping US equipment manufactures and exports. For a lot of these equipment makers the question is not just what is the demand in the US but what is global demand. And global demand is still looking pretty solid. We know that US manufacturing has been through a tough patch. But we expect it to pull out, helped by foreign demand and also by the fact that it wasn&#146;t in as big a hole as it seemed.

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
Factory Orders
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Factory Orders</td>
<td>3Mo</td>
<td>6Mo</td>
<td>9Mo</td>
<td>12Mo</td>
<td>YearAgo</td>
</tr>
<tr>
<td class="firstcol">Shipments</td>
<td>-2.9%</td>
<td>1.8%</td>
<td>-3.6%</td>
<td>-0.5%</td>
<td>5.7%</td>
</tr>
<tr>
<td class="firstcol">New Orders</td>
<td>-5.6%</td>
<td>-4.5%</td>
<td>-2.4%</td>
<td>-1.3%</td>
<td>10.7%</td>
</tr>
<tr>
<td class="firstcol">Unfilled Orders</td>
<td>13.7%</td>
<td>18.7%</td>
<td>20.9%</td>
<td>19.8%</td>
<td>20.9%</td>
</tr>
<tr>
<td class="firstcol">Inventories</td>
<td>0.9%</td>
<td>2.0%</td>
<td>4.0%</td>
<td>5.7%</td>
<td>2.9%</td>
</tr>
</tbody>
</table>
Employment Continues to Expand in Germany; Unemployment Lowest in 6 Years 
by <a href="/comment/Stone.html">Carol Stone</a> May 2, 2007


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502a.jpg" width="353">
Employment in Germany rose 52,000 in March, following gains of 46,000 and 76,000 in February and January, respectively. This was the 13th consecutive monthly increase in employment, bringing it up 1.5% (annualized) from February 2006. By comparison over the same period, US employment rose 1.9% (comparable &quot;household&quot; survey) but 0.5% in the UK and -- through Q4 2006 -- 0.9% in France. So German employment growth is quite vigorous by its neighbors&#39; standards. Separate data on job vacancies shows some decline in most recent months, but these openings are more plentiful than a year ago, suggesting that employment might go up still further. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502b.jpg" width="353">
By the same token, unemployment is falling markedly. The ILO definition, used throughout the Eurozone, puts the rate at 6.8% in March, down 1.5 points from the year-ago level and the lowest since April 2001. The locally preferred &quot;registered&quot; unemployment rate was 9.2% in April, sharply lower than 11.3% in April 2006. The latest figure is the lowest since the same in May 2001 and was last lower in March 1995.
By the &quot;registered&quot; measure, the Germans appear distinctive in keeping unemployment down among their youth. The rate, shown in the third graph, for people under 25, was only 8.4% (not seasonally adjusted). The &quot;registered&quot; status means that people are indeed registered with a local employment agency and taking action to find work, at least partially through the placement service of the employment agency. So this is not the same thing as simply &quot;wanting&quot; to work, the concept used in the ILO definition of unemployment. Even so, it is still impressive that young people who look for work according to the registration procedures in Germany do seem to find jobs, keeping their unemployment down. The ILO &quot;labor force&quot; definition, by contrast, does remain considerably higher, at 13.9% in March, not seasonally adjusted, than overall unemployment, 7.2%. There is some good news, though, in recent historical comparison: March 2006 saw 15.2% and March 2005, 17.1%. So the firmer German economy is helping reduce youth unemployment by either definition. <img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502c.jpg" width="353"><img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070502d.jpg" width="353">

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">GERMANY (Seas Adj, ex as noted)</th>
<th scope="col">Apr 2007</th>
<th scope="col">Mar 2007</th>
<th scope="col">Feb 2007</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">LFS Employment (mil)</td>
<td>--</td>
<td>39.50</td>
<td>39.45</td>
<td>38.89</td>
<td>39.09</td>
<td>38.82</td>
<td>38.88</td>
</tr>
<tr>
<td class="firstcol">Change (thous)</td>
<td>--</td>
<td>52</td>
<td>46</td>
<td>601</td>
<td>271</td>
<td>-52</td>
<td>151</td>
</tr>
<tr class="odd">
<td class="firstcol">Yr/Yr % Change, NSA</td>
<td>--</td>
<td>1.6</td>
<td>1.5</td>
<td>--</td>
<td>0.7</td>
<td>-0.1</td>
<td>0.4</td>
</tr>
<tr>
<td class="firstcol">Unemployment Rate (%, ILO Def.)</td>
<td>--</td>
<td>6.8</td>
<td>6.9</td>
<td>8.3</td>
<td>8.1</td>
<td>9.1</td>
<td>9.2</td>
</tr>
<tr class="odd">
<td class="firstcol">Registered Unemployment Rate (%)</td>
<td>9.2</td>
<td>9.2</td>
<td>9.3</td>
<td>11.3</td>
<td>10.8</td>
<td>11.7</td>
<td>10.6</td>
</tr>
<tr>
<td class="firstcol">Job Vacancies (thous)</td>
<td>610</td>
<td>621</td>
<td>642</td>
<td>503</td>
<td>564.2</td>
<td>413.1</td>
<td>284.3</td>
</tr>
</tbody>
</table>
</body>
</html>

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070501b.jpg" width="353">
Periodically I run the table below just to see if people are awake. But seriously&#133; 
The table contains a wealth of data on the ISM and what it is doing. The &#145;percentile&#146; and &#145;% of average&#146; columns at the right of the table put the raw monthly readings (which are on the far left) in the perspective of their normal variation. Whatever you think of the ISM at 54.7, it is in the 62nd percentile of its range of values for actual experience since Mid-1999. New orders and order back logs are also in their 60th percentiles or more. Unfortunately, prices, at a reading of 73, are in the top 23 percentile of all readings for this period (percentile 77th). But employment has turned a corner in April with a diffusion reading of 53.1 that places it in the 71st percentile of its range. The ISM for April looks a lot stronger than anyone had expected - from the headline down through the components. And there is more good news&#133; the components that are mostly leading components such as orders, backlogs and prices are cycling higher with 3-month averages trending above 6-month averages. Still, supplier deliveries are lagging as we saw in some regional reports. Supplier deliveries are supposed to track with price pressures and recently delivery speeds have speeded up - a sign of more slack while prices have spurted - usually a sign of less slack. We might be tempted to chalk prices up to energy spurting but clear improvement in activity indexes discourages that conclusion.
Another anomaly in this report is the weakness in the PMI relative to the import reading. Both production and the PMI itself tend to score higher values than the import reading. But since 2005, imports have scored as high or higher and this is with a weakening dollar in the mix. It is hard to believe that import penetration has increased noticeably during this period, but maybe it has. Certainly Japan could be factor in that regard since the yen has been contrarily weak and we know Japanese automakers have taken advantage of the situation.
Finally I offer the chart below which does NOT plot data from the ISM. This plot draws from the HAVER database on regional PMI surveys and the lot is only up to date through March. But it makes a point I want to make and it is a point beyond just the April data. The chart above plots several different PMI data types by converting each survey to a reading that reflects the index&#146;s position in its range of values since April of 1995. So no matter what the index, we can plot it on one graph with the others in a consistent fashion. The indexes are the Chicago national activity index which is a broad index not just of MFG activity, the Chicago Mid-West MFG index, the Mid-America States index and the Mountain States index. I chose these from the available MFG and activity surveys because they are for different groupings of states. And the point right now that various blocks of states are doing very differently economically. For some it&#146;s hard to &#145;keep up with the Joneses&#146;; others &#145;are the Joneses&#146;.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/070501a.jpg" width="353">
The Mountain States, while the most volatile, are also the states with the strongest readings. Until mid-1996 the Chicago MFG index was heading steadily higher as well. In contrast, the Chicago national activity index and the Mid-America States index are each trending lower, since about 2004. Now, new trends are in the making, the Mountain States and Mid America States are showing rebound with national activity index and the Chicago Mid-West MFG index flat to slightly lower.
Different parts of the country are locked in different medium-term trends and are experiencing different short-term trends as well.
We have recently seen a revival of MFG orders from the durable goods report. The ISM is now up in April. Consumer confidence, while off peak, is not unraveling as we saw with the upward revision to the April U of M sentiment index. But energy prices are up again and sub-prime lending problems - that have been blown out of proportion - clearly weigh on the home-owning public.
But, by and large, what we can see seems to represent a creeping improvement in the MFG sector for an economy where the services sector has remained firm all along. There are hints of less weakness in construction to go along with all this. Income growth in March was strong. There is every reason to expect US manufacturers will be able to put problems behind them now that the dollar is lower and inventories have been reduced. Problems have causes and solutions. The fact of the past weakness in US MFG is that US firms have used the time to get better prepared to re-balance inventories with sales. With the special declines in sectors that sapped strength from GDP largely out of the way, we are prepared to see growth show though instead of the pessimism that is heralded by other economists who want to extrapolate trends instead of seeing the trappings of rebuilding or of turning points in the making.
The spottiness in the regional indexes reveals the mixed nature the economy. It also results in some instability in the national index depending on which region&#146;s tug is the greatest month-to-month. This unevenness is a sign of an economy in transition. I think this has been transition for the positive, not a preparation for an even greater negative ahead as some others think. Some slowdowns prove to be a pause that refreshes instead of a prelude to decline. The incoming data will help us decide which scenario is correct. 

<table border="0" cellspacing="0" width="100%">
<colgroup></colgroup>
<thead>
<tr>
Placing ISM Readings in their Respective Ranges
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">since Jun-99</td>
<td colspan="10">&nbsp;</td>
</tr>
<tr>
<td class="firstcol">ISM</td>
<td>Current</td>
<td>Last Month</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 Index</td>
<td>54.7</td>
<td>50.9</td>
<td>5.3</td>
<td>53.2</td>
<td>10.0</td>
<td>63.2</td>
<td>40.5</td>
<td>22.7</td>
<td>62.6</td>
<td>103</td>
</tr>
<tr>
<td class="firstcol">New Orders</td>
<td>58.5</td>
<td>51.6</td>
<td>6.7</td>
<td>55.8</td>
<td>12.0</td>
<td>71.3</td>
<td>38.4</td>
<td>32.9</td>
<td>61.1</td>
<td>105</td>
</tr>
<tr>
<td class="firstcol">Backlogs</td>
<td>54.5</td>
<td>47.0</td>
<td>6.6</td>
<td>50.7</td>
<td>13.0</td>
<td>66.5</td>
<td>36.0</td>
<td>30.5</td>
<td>60.7</td>
<td>108</td>
</tr>
<tr>
<td class="firstcol">Production</td>
<td>57.3</td>
<td>53.0</td>
<td>6.3</td>
<td>55.6</td>
<td>11.4</td>
<td>70.0</td>
<td>38.6</td>
<td>31.4</td>
<td>59.6</td>
<td>103</td>
</tr>
<tr>
<td class="firstcol">Supplier Deliveries</td>
<td>50.2</td>
<td>51.3</td>
<td>5.0</td>
<td>54.2</td>
<td>9.2</td>
<td>68.1</td>
<td>45.4</td>
<td>22.7</td>
<td>21.1</td>
<td>93</td>
</tr>
<tr>
<td class="firstcol">Inventories</td>
<td>46.3</td>
<td>47.5</td>
<td>3.9</td>
<td>45.8</td>
<td>8.6</td>
<td>53.6</td>
<td>37.1</td>
<td>16.5</td>
<td>55.8</td>
<td>101</td>
</tr>
<tr>
<td class="firstcol">Prices(Pd)</td>
<td>73.0</td>
<td>65.5</td>
<td>12.6</td>
<td>62.3</td>
<td>20.3</td>
<td>88.0</td>
<td>32.0</td>
<td>56.0</td>
<td>73.2</td>
<td>117</td>
</tr>
<tr>
<td class="firstcol">Employment</td>
<td>53.1</td>
<td>48.7</td>
<td>5.9</td>
<td>49.3</td>
<td>12.1</td>
<td>60.3</td>
<td>35.1</td>
<td>25.2</td>
<td>71.4</td>
<td>108</td>
</tr>
<tr>
<td class="firstcol">New Export Orders</td>
<td>57.0</td>
<td>55.5</td>
<td>3.5</td>
<td>53.7</td>
<td>6.6</td>
<td>60.2</td>
<td>44.3</td>
<td>15.9</td>
<td>79.9</td>
<td>106</td>
</tr>
<tr>
<td class="firstcol">Import Orders</td>
<td>58.0</td>
<td>57.5</td>
<td>3.6</td>
<td>54.7</td>
<td>6.7</td>
<td>61.5</td>
<td>46.9</td>
<td>14.6</td>
<td>76.0</td>
<td>106</td>
</tr>
<tr class="odd">
<td class="firstcol">Avg Days&nbsp; Lead For:</td>
<td colspan="10">&nbsp;Since&nbsp; Jun 1999 </td>
</tr>
<tr>
<td class="firstcol">Production Material</td>
<td>46.0</td>
<td>45.0</td>
<td>3.2</td>
<td>47.1</td>
<td>6.9</td>
<td>55.0</td>
<td>38.0</td>
<td>17.0</td>
<td>47.1</td>
<td>98</td>
</tr>
<tr>
<td class="firstcol">Capital Expenditure</td>
<td>115.0</td>
<td>110.0</td>
<td>8.6</td>
<td>107.0</td>
<td>8.1</td>
<td>120.0</td>
<td>86.0</td>
<td>34.0</td>
<td>85.3</td>
<td>107</td>
</tr>
<tr>
<td class="firstcol">Maint., Repair, &amp; Ops</td>
<td>25.0</td>
<td>22.0</td>
<td>2.1</td>
<td>22.5</td>
<td>9.5</td>
<td>29.0</td>
<td>17.0</td>
<td>12.0</td>
<td>66.7</td>
<td>111</td>
</tr>
<tr>
<td colspan="6">Note: From April 1991 to Date; except back logs since Jan 1993</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
</tbody>
</table>
</body>
</html>

Periodically I run the table below just to see if people are awake. But seriously The table contains a wealth of data on the ISM and what it is doing. The percentile and % of average columns at the right of the table put the raw [...]

ISM: Keeping up with the Joneses…

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: May 2007

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