Tom Moeller

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051121a.jpg" width="353">
The Conference Board reported that the Composite Index of Leading Economic Indicators recovered 0.9% in October. The rise recouped virtually all of the index&#39;s declines since June.
The breadth of one month gain amongst the 10 components of the leading index improved to 70% and was the broadest since June. Lower claims for unemployment insurance and longer hours worked in the factory sector had the largest positive effects on the leaders&#39; one month change and offset large negative influences from lower stock prices and lower building permits.
The method of calculating the contribution to the index from the interest rate yield spread has been revised. A negative contribution will now occur only when the spread inverts rather than when declining as in the past. More details can be found <a href="http://www.conference-board.org/pdf_free/economics/bci/lei0705.pdf">here</a>.
The leading index is based on eight previously reported economic data series. Two series, orders for consumer goods and orders for capital goods, are estimated.
The coincident indicators rose 0.1% following an upwardly revised 0.3% rise during September. During the last ten years there has been a 64% correlation between the change in the coincident indicators and real GDP.
The lagging indicators rose 0.8%. Higher C&amp;I loans and a higher services CPI growth rate contributed greatly to the October increase. The ratio of coincident to lagging indicators, a measure of actual economic performance versus excess, fell after an upwardly revised September gain to its lowest level since late 2003.
Visit the Conference Board&#39;s <a href="http://www.conference-board.org">site</a> for coverage of leading indicator series from around the world. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/BCI/BCI.HTM">Business Cycle Indicators</a></th>
<th scope="col">Oct</th>
<th scope="col">Sept</th>
<th scope="col">6 Month Chg., AR</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Leading</td>
<td>0.9%</td>
<td>-0.8%</td>
<td>2.4%</td>
<td>7.7%</td>
<td>5.1%</td>
<td>5.0%</td>
</tr>
<tr>
<td class="firstcol">Coincident</td>
<td>0.1%</td>
<td>0.3%</td>
<td>1.2%</td>
<td>2.7%</td>
<td>0.4%</td>
<td>-0.6%</td>
</tr>
<tr class="odd">
<td class="firstcol">Lagging</td>
<td>0.8%</td>
<td>-0.2%</td>
<td>3.4%</td>
<td>-0.1%</td>
<td>-0.1%</td>
<td>-0.7%</td>
</tr>
</tbody>
</table>
</body>
</html>

The Conference Board reported that the Composite Index of Leading Economic Indicators recovered 0.9% in October. The rise recouped virtually all of the index's declines since June. The breadth of one month gain amongst the 10 [...]

Leading Economic Indicators Recovered

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051121a.jpg" width="353">
The Conference Board reported that the Composite Index of Leading Economic Indicators recovered 0.9% in October. The rise recouped virtually all of the index&#39;s declines since June.
The breadth of one month gain amongst the 10 components of the leading index improved to 70% and was the broadest since June. Lower claims for unemployment insurance and longer hours worked in the factory sector had the largest positive effects on the leaders&#39; one month change and offset large negative influences from lower stock prices and lower building permits.
The method of calculating the contribution to the index from the interest rate yield spread has been revised. A negative contribution will now occur only when the spread inverts rather than when declining as in the past. More details can be found <a href="http://www.conference-board.org/pdf_free/economics/bci/lei0705.pdf">here</a>.
The leading index is based on eight previously reported economic data series. Two series, orders for consumer goods and orders for capital goods, are estimated.
The coincident indicators rose 0.1% following an upwardly revised 0.3% rise during September. During the last ten years there has been a 64% correlation between the change in the coincident indicators and real GDP.
The lagging indicators rose 0.8%. Higher C&amp;I loans and a higher services CPI growth rate contributed greatly to the October increase. The ratio of coincident to lagging indicators, a measure of actual economic performance versus excess, fell after an upwardly revised September gain to its lowest level since late 2003.
Visit the Conference Board&#39;s <a href="http://www.conference-board.org">site</a> for coverage of leading indicator series from around the world. 

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/BCI/BCI.HTM">Business Cycle Indicators</a></th>
<th scope="col">Oct</th>
<th scope="col">Sept</th>
<th scope="col">6 Month Chg., AR</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Leading</td>
<td>0.9%</td>
<td>-0.8%</td>
<td>2.4%</td>
<td>7.7%</td>
<td>5.1%</td>
<td>5.0%</td>
</tr>
<tr>
<td class="firstcol">Coincident</td>
<td>0.1%</td>
<td>0.3%</td>
<td>1.2%</td>
<td>2.7%</td>
<td>0.4%</td>
<td>-0.6%</td>
</tr>
<tr class="odd">
<td class="firstcol">Lagging</td>
<td>0.8%</td>
<td>-0.2%</td>
<td>3.4%</td>
<td>-0.1%</td>
<td>-0.1%</td>
<td>-0.7%</td>
</tr>
</tbody>
</table>
Declines in the Euro and the Price of Oil Improve the  Euro Zone Balance of Trade in Goods  
by <a href="/comment/Curley.html">Louise Curley</a> November 21, 2005


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051121b.jpg" width="353">
The Euro Zone&#39;s surplus on trade in goods rose in September to 1,239.5 million euros from 190.0 million euros in August. This was only the third month this year in which a rise in the trade balance took place. For the nine months through September, the trade surplus is 57% below the corresponding period of 2004. The deterioration in the trade surplus is shown in the first chart.
The main factors in the deterioration of the trade surplus have been the rise in the euro which tended to dampen export demand and the rise in the price of oil which increased imports. The second chart shows the year-to-year increases in total imports and imports of mineral fuels and lubricants. Since early 2004 the year-to-year increase in imports of mineral fuels and lubricants has ranged between 25 and 50%. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051121c.jpg" width="353">
The euro has been declining for most of this year and the price of crude has recently eased suggesting that the outlook for the balance of trade in goods is improving. The Euro has declined about 14% from the peak reached on December 30, 2004.Just two months ago the Brent Crude oil was $64.49 a barrel. It is now 18% lower at $52.66. The dollar value of the euro and the price of Brent Crude oil are shown in the third chart on a daily basis.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051121d.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">Euro Zone Trade in Goods (Millions of Euros)</th>
<th scope="col">Sep 05&nbsp;</th>
<th scope="col">Aug 05</th>
<th scope="col">Sep 04</th>
<th scope="col">M/M %&nbsp;</th>
<th scope="col">Y/Y&nbsp;&nbsp;&nbsp; %</th>
<th scope="col">2004 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;</th>
<th scope="col">2003 &nbsp;</th>
<th scope="col">2002&nbsp;&nbsp;</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Trade Balance</td>
<td>1,239</td>
<td>190</td>
<td>2,673</td>
<td>1,049*</td>
<td>-1,434*</td>
<td>71,827</td>
<td>70,027</td>
<td>99,097</td>
</tr>
<tr>
<td class="firstcol">&nbsp;&nbsp; Exports</td>
<td>107,019</td>
<td>106,672</td>
<td>95,492</td>
<td>0.33</td>
<td>12.07</td>
<td>1,144,937</td>
<td>1,059,880</td>
<td>1,083,611</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp;&nbsp; Imports</td>
<td>105,779</td>
<td>106,482</td>
<td>92,818</td>
<td>-0.66</td>
<td>13.96</td>
<td>1,073,110</td>
<td>989,853</td>
<td>984,514</td>
</tr>
<tr>
<td class="firstcol">&nbsp;&nbsp;&nbsp;&nbsp; Mineral Fuels &amp; Lubricants</td>
<td>22,285</td>
<td>23,126</td>
<td>15,545</td>
<td>-3.66</td>
<td>43.36</td>
<td>164,390</td>
<td>143,620</td>
<td>137,521</td>
</tr>
<tr class="odd">
<td class="firstcol"></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td class="firstcol"></td>
<td>Peak&nbsp;</td>
<td>Date</td>
<td>Current</td>
<td>Date</td>
<td>Pct Chg</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td class="firstcol">Euro&nbsp; ($)</td>
<td>1.3623&nbsp;</td>
<td>12/30/04&nbsp;</td>
<td>1.1741&nbsp;</td>
<td>11/18/05&nbsp;</td>
<td>-13.8&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Brent Crude Oil&nbsp; ($/bbl)</td>
<td>64.49&nbsp;</td>
<td>9/21/05&nbsp;</td>
<td>52.66&nbsp;</td>
<td>11/18/05&nbsp;</td>
<td>-18.3&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr class="odd">
<td class="firstcol"></td>
<td>&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">&nbsp;*Difference</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
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<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>
<td>&nbsp;</td>
</tr>
</tbody>
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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/051118a.jpg" width="353">
As readers are no doubt aware, among its many offerings, Haver Analytics carries a large number of regional databases. These cover such concepts as gross state product, county personal income, rental vacancy rates for all 50 states and 75 metropolitan areas. A client query the other day called our attention to a very simple set of data we have had in the general REGIONAL database for the last couple of years, the Philadelphia Fed&#39;s &quot;Coincident Economic Activity Indexes&quot; for all 50 states. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051118b.jpg" width="353">
These indexes are simple, handy, and available promptly compared with much regional information. Data on all 50 states were published on November 1 for September. October data will be out December 1. History goes back to 1979. They are calculated from four indicators:nonfarm payrolls, the unemployment rate, the workweek in manufacturing and real wage and salary income. All four of these are available in comparable form for all 50 states. Based in a Stock &amp; Watson framework, log changes are used in compiling each month&#39;s figure, and the index trend is tied to gross state product, an annual figure. A full and authoritative description of the calculation appears in a Philadelphia Fed working paper, &quot;Consistent Indexes for the 50 States&quot; by Theodore Crone, circulated in June 2003. The paper can be accessed <a href="http://www.phil.frb.org/files/wps/2002/wp02-7r.pdf"> here</a> .<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051118c.jpg" width="353">
We know intuitively that regional and local economies behave differently and these indexes show that in a quick summary number. In the table below, we show five arbitrarily selected states, plus two national coincident indexes calculated by private institutions. These five state index levels through August vary from 124.2 to 158.0 on a base of July 1992=100, indicating widely varying degrees of overall vitality. Four of these states and most of the rest had gains through early summer. We see, though, that Louisiana had already had two down months in July and August. Its index then fell 14.5% in September, when Katrina hit. The index for Mississippi was off 4.0% that month. A few of the varying patterns among states are shown in our accompanying graphs. In the first graph, the tech boom and bust is evident in the comparison of Washington State with New York. The second graph shows the impact of Hurricane Katrina. Notice that states even right next to each other can show differing paths of economic activity; for example, North and South Dakota vary with ups and downs in many months, and South Dakota&#39;s index stood at 154.7 in September, while North Dakota&#39;s was only 133.1.
The Philadelphia Fed explains that it has compiled and maintains these indexes to facilitate research and analysis of just such cross-state and state/national economic interactions. According to the conclusion of the paper cited above, &quot;Possible issues include the study of state business cycles, the effect of national economic forces on individual states, and the effect of the state&#146;s overall economic activity on state fiscal conditions, poverty, or in-migration.&quot; 

<table border="0" cellspacing="0" width="100%">

</table>
<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">Index Levels/% Changes</th>
<th scope="col">Sep 2005</th>
<th scope="col">Aug 2005</th>
<th scope="col">Jul 2005</th>
<th scope="col">Sep 2004</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Conference Board Coincident Indicators (rebased to 1992=100)</td>
<td>136.0</td>
<td>136.1</td>
<td>136.2</td>
<td>132.8</td>
<td>132.5</td>
<td>129.0</td>
<td>128.5</td>
</tr>
<tr>
<td class="firstcol">-0.1</td>
<td>-0.1</td>
<td>0.2</td>
<td>2.4</td>
<td>2.7</td>
<td>0.4</td>
<td>-0.6</td>
</tr>
<tr class="odd">
<td class="firstcol">ECRI Coincident Index (1992=100)</td>
<td>146.9</td>
<td>147.2</td>
<td>147.2</td>
<td>142.8</td>
<td>142.2</td>
<td>137.2</td>
<td>135.7</td>
</tr>
<tr>
<td class="firstcol">-0.2</td>
<td>0.0</td>
<td>0.3</td>
<td>2.9</td>
<td>3.7</td>
<td>1.1</td>
<td>-0.2</td>
</tr>
<tr class="odd">
<td colspan="4">Philly Fed State Indexes (July 1992=100)</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr>
<td class="firstcol">New York</td>
<td>140.0</td>
<td>139.9</td>
<td>139.5</td>
<td>136.1</td>
<td>135.2</td>
<td>132.0</td>
<td>131.0</td>
</tr>
<tr class="odd">
<td class="firstcol">0.1</td>
<td>0.3</td>
<td>0.2</td>
<td>2.9</td>
<td>2.4</td>
<td>0.7</td>
<td>-0.9</td>
</tr>
<tr>
<td class="firstcol">California</td>
<td>154.5</td>
<td>154.0</td>
<td>153.5</td>
<td>149.2</td>
<td>148.0</td>
<td>144.0</td>
<td>142.8</td>
</tr>
<tr class="odd">
<td class="firstcol">0.4</td>
<td>0.3</td>
<td>0.4</td>
<td>3.5</td>
<td>2.8</td>
<td>0.8</td>
<td>-0.1</td>
</tr>
<tr>
<td class="firstcol">Texas</td>
<td>158.2</td>
<td>158.0</td>
<td>157.7</td>
<td>154.1</td>
<td>153.2</td>
<td>149.6</td>
<td>149.3</td>
</tr>
<tr class="odd">
<td class="firstcol">0.1</td>
<td>0.2</td>
<td>0.2</td>
<td>2.7</td>
<td>2.4</td>
<td>0.2</td>
<td>-0.8</td>
</tr>
<tr>
<td class="firstcol">Iowa</td>
<td>143.0</td>
<td>142.6</td>
<td>142.2</td>
<td>138.3</td>
<td>137.7</td>
<td>134.5</td>
<td>133.9</td>
</tr>
<tr class="odd">
<td class="firstcol">0.2</td>
<td>0.3</td>
<td>0.3</td>
<td>3.3</td>
<td>2.4</td>
<td>0.4</td>
<td>-0.8</td>
</tr>
<tr>
<td class="firstcol">Louisiana</td>
<td>106.2</td>
<td>124.2</td>
<td>125.3</td>
<td>124.5</td>
<td>124.5</td>
<td>123.3</td>
<td>122.6</td>
</tr>
<tr class="odd">
<td class="firstcol">-14.5</td>
<td>-0.6</td>
<td>-0.4</td>
<td>-14.7</td>
<td>1.0</td>
<td>0.5</td>
<td>-1.0</td>
</tr>
</tbody>
</table>
</body>
</html>

As readers are no doubt aware, among its many offerings, Haver Analytics carries a large number of regional databases. These cover such concepts as gross state product, county personal income, rental vacancy rates for all 50 states [...]

State Coincident Indexes Highlight Regional Differences in Economic Activity

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051118a.jpg" width="353">
As readers are no doubt aware, among its many offerings, Haver Analytics carries a large number of regional databases. These cover such concepts as gross state product, county personal income, rental vacancy rates for all 50 states and 75 metropolitan areas. A client query the other day called our attention to a very simple set of data we have had in the general REGIONAL database for the last couple of years, the Philadelphia Fed&#39;s &quot;Coincident Economic Activity Indexes&quot; for all 50 states.
These indexes are simple, handy, and available promptly compared with much regional information. Data on all 50 states were published on November 1 for September. October data will be out December 1. History goes back to 1979. They are calculated from four indicators:nonfarm payrolls, the unemployment rate, the workweek in manufacturing and real wage and salary income. All four of these are available in comparable form for all 50 states. Based in a Stock &amp; Watson framework, log changes are used in compiling each month&#39;s figure, and the index trend is tied to gross state product, an annual figure. A full and authoritative description of the calculation appears in a Philadelphia Fed working paper, &quot;Consistent Indexes for the 50 States&quot; by Theodore Crone, circulated in June 2003. The paper can be accessed <a href="http://www.phil.frb.org/files/wps/2002/wp02-7r.pdf"> here</a> . <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051118a.jpg" width="353">
We know intuitively that regional and local economies behave differently and these indexes show that in a quick summary number. In the table below, we show five arbitrarily selected states, plus two national coincident indexes calculated by private institutions. These five state index levels through August vary from 124.2 to 158.0 on a base of July 1992=100, indicating widely varying degrees of overall vitality. Four of these states and most of the rest had gains through early summer. We see, though, that Louisiana had already had two down months in July and August. Its index then fell 14.5% in September, when Katrina hit. The index for Mississippi was off 4.0% that month. A few of the varying patterns among states are shown in our accompanying graphs. In the first graph, the tech boom and bust is evident in the comparison of Washington State with New York. The second graph shows the impact of Hurricane Katrina. Notice that states even right next to each other can show differing paths of economic activity; for example, North and South Dakota vary with ups and downs in many months, and South Dakota&#39;s index stood at 154.7 in September, while North Dakota&#39;s was only 133.1.
The Philadelphia Fed explains that it has compiled and maintains these indexes to facilitate research and analysis of just such cross-state and state/national economic interactions. According to the conclusion of the paper cited above, &quot;Possible issues include the study of state business cycles, the effect of national economic forces on individual states, and the effect of the state&#146;s overall economic activity on state fiscal conditions, poverty, or in-migration.&quot; 

<table border="0" cellspacing="0" width="100%">

</table>
<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">Index Levels/% Changes</th>
<th scope="col">Sep 2005</th>
<th scope="col">Aug 2005</th>
<th scope="col">Jul 2005</th>
<th scope="col">Sep 2004</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Conference Board Coincident Indicators (rebased to 1992=100)</td>
<td>136.0</td>
<td>136.1</td>
<td>136.2</td>
<td>132.8</td>
<td>132.5</td>
<td>129.0</td>
<td>128.5</td>
</tr>
<tr>
<td class="firstcol">-0.1</td>
<td>-0.1</td>
<td>0.2</td>
<td>2.4</td>
<td>2.7</td>
<td>0.4</td>
<td>-0.6</td>
</tr>
<tr class="odd">
<td class="firstcol">ECRI Coincident Index (1992=100)</td>
<td>146.9</td>
<td>147.2</td>
<td>147.2</td>
<td>142.8</td>
<td>142.2</td>
<td>137.2</td>
<td>135.7</td>
</tr>
<tr>
<td class="firstcol">-0.2</td>
<td>0.0</td>
<td>0.3</td>
<td>2.9</td>
<td>3.7</td>
<td>1.1</td>
<td>-0.2</td>
</tr>
<tr class="odd">
<td colspan="4">Philly Fed State Indexes (July 1992=100)</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
<td>&nbsp;</td>
</tr>
<tr>
<td class="firstcol">New York</td>
<td>140.0</td>
<td>139.9</td>
<td>139.5</td>
<td>136.1</td>
<td>135.2</td>
<td>132.0</td>
<td>131.0</td>
</tr>
<tr class="odd">
<td class="firstcol">0.1</td>
<td>0.3</td>
<td>0.2</td>
<td>2.9</td>
<td>2.4</td>
<td>0.7</td>
<td>-0.9</td>
</tr>
<tr>
<td class="firstcol">California</td>
<td>154.5</td>
<td>154.0</td>
<td>153.5</td>
<td>149.2</td>
<td>148.0</td>
<td>144.0</td>
<td>142.8</td>
</tr>
<tr class="odd">
<td class="firstcol">0.4</td>
<td>0.3</td>
<td>0.4</td>
<td>3.5</td>
<td>2.8</td>
<td>0.8</td>
<td>-0.1</td>
</tr>
<tr>
<td class="firstcol">Texas</td>
<td>158.2</td>
<td>158.0</td>
<td>157.7</td>
<td>154.1</td>
<td>153.2</td>
<td>149.6</td>
<td>149.3</td>
</tr>
<tr class="odd">
<td class="firstcol">0.1</td>
<td>0.2</td>
<td>0.2</td>
<td>2.7</td>
<td>2.4</td>
<td>0.2</td>
<td>-0.8</td>
</tr>
<tr>
<td class="firstcol">Iowa</td>
<td>143.0</td>
<td>142.6</td>
<td>142.2</td>
<td>138.3</td>
<td>137.7</td>
<td>134.5</td>
<td>133.9</td>
</tr>
<tr class="odd">
<td class="firstcol">0.2</td>
<td>0.3</td>
<td>0.3</td>
<td>3.3</td>
<td>2.4</td>
<td>0.4</td>
<td>-0.8</td>
</tr>
<tr>
<td class="firstcol">Louisiana</td>
<td>106.2</td>
<td>124.2</td>
<td>125.3</td>
<td>124.5</td>
<td>124.5</td>
<td>123.3</td>
<td>122.6</td>
</tr>
<tr class="odd">
<td class="firstcol">-14.5</td>
<td>-0.6</td>
<td>-0.4</td>
<td>-14.7</td>
<td>1.0</td>
<td>0.5</td>
<td>-1.0</td>
</tr>
</tbody>
</table>
</body>
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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117f.jpg" width="353">
Mexico&#39;s GDP was either strong or weak in Q3, according to who you listen to and which comparisons you make. The data were reported yesterday afternoon by INEGI, Mexico&#39;s statistical agency. The year-on-year gain of 3.3% was less than a government forecast, Reuters explained, but slightly larger than private market forecasts. Seasonally adjusted, the quarter saw a 2.1% increase (quarterly rate) after a basically flat performance in Q1 (+0.2%) and Q2 (-0.3%). It was this pattern that Dow Jones highlighted, with a headline in the Wall Street Journal that read &quot;Mexico Growth Picks Up...&quot;. <img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117g.jpg" width="353">
A further divergence of interpretation concerns manufacturing. This important sector has experienced considerable variability in recent years. From Q3 2004, this latest period&#39;s value added rose a mere 0.2%, less than Q2&#39;s 2.6% yearly increase. The retreat was led by metals and metal products. Based on seasonal adjustment of the industry data by Haver Analytics, these, along with &quot;other manufacturing&quot;, showed considerable quarter-to-quarter declines. Some attribute this to weakness in the US motor vehicle industry, although collateral data, such as unit vehicle imports into the US as published by the US Commerce Department, don&#39;t indicate any decline. At the same time, for the entire factory sector, some analysts apparently feared a decrease from a year earlier, so the 0.2% rise, modest as it is, was of some comfort.
Other notable sectors of the Mexican economy contributed to the mixed reading on its health. Agriculture, constituting a relatively small proportion of total GDP, had a substantial increase in Q3, 10.6% year-to-year after outright declines in the first half of 2005. Finance also strengthened, with a 6.2% increase; this industry group has been expanding consistently over the last couple of years. The largest sector of the Mexican economy is domestic trade and tourism, contributing just under 20% of GDP last year. This year, it continues to expand, but more slowly, with a 3.1% yearly increase in Q3, notably less than the 4.9% in 2004. As we face Q4, cross-currents will continue to raise questions for the nation: the storms in October, continuing uncertainty in the big US vehicle market, and volatile energy markets. Stay tuned.

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<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">Mexico GDP &amp; Select Industries, &nbsp;% Changes, NSA unless noted</th>
<th scope="col">Q3 2005</th>
<th scope="col">Q2 2005</th>
<th scope="col">Q1 2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Real GDP, SA (100%*)</td>
<td>2.1</td>
<td>-0.3</td>
<td>0.2</td>
<td>--</td>
<td>--</td>
<td>--</td>
</tr>
<tr>
<td class="firstcol">&nbsp; Yr/Yr, NSA</td>
<td>3.3</td>
<td>3.1</td>
<td>2.4</td>
<td>4.4</td>
<td>1.4</td>
<td>0.8</td>
</tr>
<tr class="odd">
<td class="firstcol">Agriculture (5.3%*)</td>
<td>10.6</td>
<td>-3.3</td>
<td>-1.5</td>
<td>4.0</td>
<td>3.5</td>
<td>0.1</td>
</tr>
<tr>
<td class="firstcol">Manufacturing (18.2%*)</td>
<td>0.2</td>
<td>2.6</td>
<td>-0.2</td>
<td>3.8</td>
<td>-1.3</td>
<td>-0.7</td>
</tr>
<tr class="odd">
<td class="firstcol">Wholesale &amp; Retail Trade/Restaurants &amp; Hotels &nbsp; (19.8%*)</td>
<td>3.1</td>
<td>3.5</td>
<td>3.3</td>
<td>4.9</td>
<td>1.6</td>
<td>0.0</td>
</tr>
<tr>
<td class="firstcol">Finance/Insurance/ Banking &nbsp; (15.9%*)</td>
<td>6.2</td>
<td>5.5</td>
<td>5.1</td>
<td>4.6</td>
<td>3.9</td>
<td>4.2</td>
</tr>
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Mexico's GDP was either strong or weak in Q3, according to who you listen to and which comparisons you make. The data were reported yesterday afternoon by INEGI, Mexico's statistical agency. The year-on-year gain of 3.3% was less than [...]

Mexico's GDP Expands 3.3% in Q3: Is This Good or Bad?

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117c.jpg" width="353">
A 25,000 decline last week in initial claims for unemployment insurance to 303,000 followed a little revised 3,000 increase the prior week and dropped claims to the lowest level since mid-April. Consensus expectations had been for a lesser decline 320,000 claims.
The latest figure covers the survey period for November nonfarm payrolls and claims were down 54,000 (15.1%) from the October period.
The Labor Department indicated that roughly 10,000 new claims last week were related to hurricanes Katrina and Rita, bringing the total since Sept. 3 linked to the Gulf Coast storms to an unadjusted 545,000 claims. Hurricane Wilma, which struck Florida late last month, led to roughly 9,000 claims bringing the total to 16,400 related claims since that storm hit.
The four-week moving average of initial claims fell sharply to 321,500 (-4.2% y/y), the lowest level since early September.
Continuing claims for unemployment insurance rose 3,000 following a downwardly revised 5,000 drop during the prior week.
The insured rate of unemployment remained at 2.2% for the eighth week.
Spendthrift Nation from the Federal Reserve Bank of San Francisco can be found <a href="http://www.frbsf.org/publications/economics/letter/2005/el2005-30.pdf"> here</a>.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/WEEKLY/@W5/@W507/@W507.HTM">Unemployment Insurance (000s)</a></th>
<th scope="col">11/12/05</th>
<th scope="col">11/05/05</th>
<th scope="col">Y/Y</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr>
<td class="firstcol">Initial Claims</td>
<td>303</td>
<td>328</td>
<td>-9.8%</td>
<td>343</td>
<td>402</td>
<td>404</td>
</tr>
<tr>
<td class="firstcol">Continuing Claims</td>
<td>--</td>
<td>2,793</td>
<td>0.3%</td>
<td>2,926</td>
<td>3,531</td>
<td>3,570</td>
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A 25,000 decline last week in initial claims for unemployment insurance to 303,000 followed a little revised 3,000 increase the prior week and dropped claims to the lowest level since mid-April. Consensus expectations had been for a [...]

Initial Claims for Jobless Insurance Lowest Since April

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117b.jpg" width="353">
The National Association of Home Builders&#39; (NAHB) Composite Housing Market Index fell a hard 11.8% in November to 60, the lowest level since May 2003.
During the last twenty years the y/y change in the annual composite index has had an 85% correlation with the change in single family housing starts and there has been a 75% correlation between the current sales index and new single family home sales.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117d.jpg" width="353">
The m/m drop reflected sharp declines throughout the country.
The index for current sales of single family homes in November fell sharply to the lowest level since May 2003. The index for sales in six months also fell hard the lowest in over two years.
The NAHB index is a diffusion index based on a survey of builders. Readings above 50 signal that more builders view conditions as good than poor.
Visit the <a href="http://www.nahb.org">National Association of Home Builders</a>.

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<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/SURVEYS/@S4/@S4.HTM">Nat&#39;l Association of Home Builders</a> </th>
<th scope="col">Nov</th>
<th scope="col">Oct</th>
<th scope="col">Nov &#39;04</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr>
<td class="firstcol">Composite Housing Market Index</td>
<td>60</td>
<td>68</td>
<td>70</td>
<td>68</td>
<td>64</td>
<td>61</td>
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The National Association of Home Builders' (NAHB) Composite Housing Market Index fell a hard 11.8% in November to 60, the lowest level since May 2003. During the last twenty years the y/y change in the annual composite index has had [...]

NAHB Housing Market Index Fell Hard

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/051117a.jpg" width="353">
Housing starts in October fell 5.6% m/m to 2.014M units following an upwardly revised gain in September.The drop was to the lowest level since March and compared to Consensus expectations for a lesser decline to 2.06M starts.
The 3.7% decline in single-family starts reversed all of an upwardly revised 3.0% increase in September. Single family starts fell hard throughout the country. A 6.7% decline (-7.1% y/y) in the West was accompanied by a 7.2% drop (-6.6% y/y) in the Midwest. In the Northeast, single family starts were notably weak and fell 8.5% (+3.2% y/y) to the lowest level since April. Only an unchanged reading (11.6% y/y) in the South tempered the declines..
Multi family starts cratered 14.8% m/m after a downwardly revised 0.6% increase in September.
Building permits fell a hard 6.7% m/m to the lowest level since April as single family permits fell 4.9% (+4.9% y/y).
China: An Evolving Housing Market from the Federal Reserve Bank of San Francisco is available <a href="http://www.frbsf.org/publications/banking/asiafocus/2005/AsiaFocus-Jun05.pdf"> here</a>.

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<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/USECON/@E9/@E901/@E90101/@E90101.HTM">Housing Starts (000s, AR)</a> </th>
<th scope="col">Oct</th>
<th scope="col">Sept</th>
<th scope="col">Y/Y</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
<th scope="col">2002</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Total</td>
<td>2,014</td>
<td>2,134</td>
<td>-2.3%</td>
<td>1,950</td>
<td>1,854</td>
<td>1,7 10</td>
</tr>
<tr>
<td class="firstcol">&nbsp; Single-family</td>
<td>1,704</td>
<td>1,770</td>
<td>2.3%</td>
<td>1,604</td>
<td>1,505</td>
<td>1,363</td>
</tr>
<tr class="odd">
<td class="firstcol">&nbsp; Multi-family</td>
<td>310</td>
<td>364</td>
<td>-21.7%</td>
<td>345</td>
<td>349</td>
<td>347</td>
</tr>
<tr>
<td class="firstcol">Building Permits</td>
<td>2,071</td>
<td>2,219</td>
<td>-1.1%</td>
<td>2,058</td>
<td>1,8 88</td>
<td>1,749</td>
</tr>
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Housing starts in October fell 5.6% m/m to 2.014M units following an upwardly revised gain in September.The drop was to the lowest level since March and compared to Consensus expectations for a lesser decline to 2.06M starts. The 3.7% [...]

Housing Starts Down

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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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.

250501Z1.jpg

**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.

250501Z2.jpg

**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.

250501Z3.jpg

**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.

250501Z4.jpg

**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.

250501Z5.jpg

**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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Real GDP eased 0.3% SAAR (+2.1% y/y) during the first quarter of 2025 after increasing 2.4% in Q4’24 and 3.1% in Q3’24. A 0.4% increase had been expected in the Action Economics Forecast Survey. It was the first decline since Q1 2022.

Foreign trade subtracted 4.83 percentage points from growth last quarter as imports surged 41.3% (13.4% y/y) ahead of tariffs, which began to come into effect in the first quarter. The rise followed a 1.9% decline in Q4’24. Exports rose 1.8% (3.0% y/y) after easing 0.2% in Q4. Inventories added 2.25 percentage points to growth after subtracting 0.84 percentage point from Q4 growth.

Real final sales to domestic purchasers grew 2.3% (2.9% y/y) in Q1 after rising 3.0% in Q4. Personal consumption expenditures rose 1.8% (3.1% y/y) following a 4.0% gain. Durable goods spending fell 3.4% (+5.3% y/y) after surging 12.4% in Q4. Motor vehicle purchases declined 11.1% (+5.5% y/y) after strengthening 19.7% in Q4. Spending on home furnishings & appliances gained 1.5% (6.1% y/y) following a 5.4% rise. Recreational goods & vehicle outlays rose 2.5% (7.0% y/y) last quarter after a 13.9% Q4 increase.

Nondurable goods outlays rose 2.7% (3.0% y/y) following 3.1% growth in Q4. Apparel spending increased 6.7% (2.5% y/y) following a 5.0% rise. Food & beverage buying gained 2.5% (2.3% y/y) after a 1.8% increase. Gasoline & fuel oil purchases increased 4.6% (3.4% y/y) after falling 2.0% in Q4.

Spending on services increased 2.4% last quarter (2.7% y/y) after a 3.0% gain. Outlays on housing & utilities increased 3.4% (1.8% y/y) after rising 1.1% in Q4. Health care expenditures rose 4.0% (4.8% y/y) following a 4.7% strengthening. Transportation outlays increased 5.3% (4.6% y/y) after a 3.7% rise while recreation spending rose 4.7% (2.8% y/y) following a 4.5% rise. Restaurant & hotel expenditures declined 2.1% (+0.5% y/y) following a 2.8% rise. Financial services expenditures rose 1.9% (2.0% y/y) after a 3.1% Q4 increase.

Business fixed investment increased 9.8% (3.6% y/y) following a 3.0% decline in Q4. Expenditures on structures rose 0.4% (-0.4% y/y) after a 2.9% increase. Expenditures on producers’ durable equipment jumped 22.5% (8.0% y/y) after falling 8.7%.  Outlays on information processing equipment soared 69.3% (18.9% y/y) following a 7.3% decline. Industrial equipment investment fell 1.4% (-0.3% y/y) after easing 0.9%. Intellectual property product spending rose 4.1% (1.8% y/y) following a 0.5% decline. 

Residential structures investment increased 1.3% (-0.1% y/y) in Q1 after a 5.5% Q4 rise.

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Government spending fell 1.5% (+2.4% y/y) after a 3.1% Q4 rise. Federal government expenditures declined 5.1% (+2.9% y/y) after rising 4.0% in Q4. National defense expenditures declined 8.0% (+4.0% y/y) after increasing 4.8% in Q4. State & local government spending rose 0.8% (2.1% y/y) following a 2.5% rise.

The GDP price index rose 3.7% (2.6% y/y) after increasing 2.3% in Q4. It was the largest increase since Q4’22. A 2.4% increase had been expected. The PCE chain price index increased 3.6% (2.5% y/y) following a 2.4% rise. The PCE price index excluding food and energy rose 3.5% (2.8% y/y) after increasing 2.6% in Q4. The business fixed investment price index rose 0.4% (1.8% y/y) after 1.5% rise. The residential price index strengthened 3.9% (3.2% y/y) after a 1.9% rise while the government price index increased 4.7% (2.8% y/y) following a 2.1% rise.

The GDP data can be found in Haver’s **USECON** and **USNA** databases. **USNA** contains virtually all of the Bureau of Economic Analysis detail in the national accounts. The Action Economics consensus estimates can be found in **AS1REPNA**.

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- Decline in GDP is first in three years.
- Foreign trade subtracts substantially ahead of tariffs.
- Domestic final demand growth weakens.
- Price index strengthens with higher core PCE prices.

U.S. GDP Unexpectedly Declines in Q1’25; Prices Strengthen

Michael J. Moran

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High-side readings on the price indexes for personal consumption expenditures in January and February caused some concern about emerging price pressure, especially with some policies of the Trump administration possibly adding to the upward force. However, March brought notable relief, with the headline price index falling slightly (-0.04%). A marked decline in energy prices was helpful (-2.7%), but core prices also were subdued, increasing less than 0.1%.  Year-over-year changes were still above the Fed’s target of 2%, but only barely so for the headline measure (2.3%). The core index backed away from the reading of 3.0% in February, but the latest reading of 2.7% was in line with observations in the past year, and still uncomfortably above target.

Consumers roused from a winter slumber in March, with nominal outlays increasing 0.7%. With inflation restrained, real outlays also posted a gain of 0.7%. Spending on durable gods stood out, with real outlays advancing 3.2%. Real outlays for both nondurable goods and services rose 0.4%, a solid pace. Signs of life were certainly welcome after an average decline of 0.1% in January and February. The March rebound left growth of 1.8% (annual rate) in the first quarter.

The brisk increase in spending in March was supported by a solid gain in personal income (0.5% in both nominal and real terms). Growth in wage income was firm at 0.5%, while proprietors’ income was robust with a gain of 1.8% (not annualized!). The farm sector led the advance in proprietors’ income, but the nonfarm sector also was strong (0.6%).

The personal income and consumption figures are available in Haver’s **USECON** database with detail in the **USNA** database. The Action Economics forecasts are in **AS1REPNA**.

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- Price pressure eases.
- Spending rebounds after two soft months.

Personal Income, Consumption, and Prices in March

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The Pending Home Sales Index, a forward-looking home sales measure based on contract signings, from the National Association of Realtors rose 6.1% to 76.5 (-0.6% y/y) during March after rising a little-revised 2.1% in February. These changes followed a 4.6% January decline.

The rise in March sales occurred as the rate on a 30-year mortgage eased to an average 6.65% from 6.84% in February. This rate was well above a low of 2.68% averaged in December 2020.

Pending home sales were up in most regions of the country. Sales in the Midwest rose 4.9% (1.4% y/y) last month after rising 1.8% in February. Sales in the South increased 9.8% (-0.4% y/y) following a 5.8% February rise. Sales in the West improved 4.8% (-2.0% y/y) after falling 3.0% in February. Sales in the Northeast were off 0.5% (-3.0% y/y) in March after falling 0.9% in February.

The pending home sales index measures sales at the time the contract for the purchase of an existing home is signed, similar to the Census Bureau's new home sales data. In contrast, the National Association of Realtors' existing home sales data are recorded when the sale is closed, which is usually a couple of months after the sales contract has been signed. In developing the pending home sales index, the NAR found that the level of monthly sales contract activity leads the level of closed existing home sales by about two months.

The series dates back to 2001 and are available in Haver's **PREALTOR** database. Weekly mortgage interest rates from the Mortgage Bankers Association can be found in the **WEEKLY** database.

- Sales rise to highest level in four months.
- Strength is evident throughout most of country.

U.S. Pending Home Sales Surge in March

Sandy Batten

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The employment cost index (ECI) for civilian workers, arguably the most accurate measure of labor compensation in the United States, rose 0.9% q/q (3.6% y/y) in Q1, the same quarterly increase as in last year’s Q4, according to the Bureau of Labor Statistics. The quarterly gains have fluctuated between 0.8% and 1.0% for the past six quarters. The Action Economics Forecast Survey had expected a 0.9% q/q increase and a 3.5% y/y gain.

Wages and salaries for civilian workers rose 0.8% q/q (3.5% y/y) in Q1, down from 1.0% q/q in Q4. This tied the Q3 2024 quarterly rise as the smallest increase since Q2 2021. It was also the smallest y/y increase since Q2 2021. Benefits increased by an outsized 1.2% q/q (3.9% y/y) in Q1 versus 0.8% q/q in Q4. This is the largest quarterly gain since Q2 2022. In general, employment cost gains remain above the pace observed prior to the pandemic but are slowing gradually.

Private industry workers’ compensation rose 0.8% q/q (3.4% y/y) in Q1, down from 0.9% q/q (3.6% y/y) in Q4. Wages and salaries for private industry workers increased 0.8% q/q (3.4% y/y) in Q1 versus 0.8% q/q (3.7% y/y) in Q4. The quarterly gain in Q1 tied that in Q3 2024 as the smallest increase since Q4 2020. Benefits for private industry workers jumped 1.2% q/q (3.6% y/y). the largest quarterly gain since Q2 2022. The acceleration in benefits in Q1 was primarily in service-producing industries.

Compensation in private goods-producing industries increased 1.0% q/q (3.2% y/y) in Q1, the largest quarterly gain in five quarters, versus a 0.7% q/q increase in Q4. Compensation in construction jumped 1.3% q/q, its largest quarterly increase since Q2 2022, up from a 0.6% q/q gain in Q4. Manufacturing compensation growth slowed to 0.7% q/q, its slowest quarterly advance since Q4 2020, from 0.8% q/q in Q4. Compensation in private service-producing industries increased 0.8% q/q (3.5% y/y), down slightly from a 0.9% q/q gain in Q4. Compensation in education and health services jumped 1.3% q/q, its largest quarterly gain since Q3 2023. In contrast, compensation in other services edged up 0.1% q/q in Q1, its smallest quarterly advance since before the pandemic.

The employment cost index measures the change in the cost of labor, free from the influence of employment shifts across occupations and industries. It is provided by the Bureau of Labor Statistics and is available in Haver’s **USECON** database. Consensus estimates from the Action Economics Forecast Survey are in Haver’s **AS1REPNA** database.

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- Compensation grew 0.9 q/q in Q1, the same pace as in Q4.
- Wage growth slowed to 0.8% q/q while benefits surged 1.2% q/q, their largest quarterly increase since Q2 2022.

Economy in Brief: November 2005

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