Tom Moeller

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060314a.jpg" width="353">
US retail sales fell 1.3% last month but several factors suggest the decline hardly indicates consumer spending weakness, even though it exceeded Consensus expectations for a 0.8% drop. 1) January&#39;s warm weather surge in spending was revised higher to 2.9%. 2) Retail sales during January and February were 2.8% above 4Q05. 3) The 0.4% decline in nonauto sales was less than Consensus expectations for a 0.5% drop.
Lower nonauto retail sales followed a January surge revised up to 2.6% and the two month strength in sales left the 1Q average so far 2.3% above 4Q which rose 1.9% from 3Q.
Motor vehicle &amp; parts dealers sales fell 4.6% (-0.9% y/y) after an upwardly revised 4.2% January spurt. The decline was in line with the 5.8% m/m drop in unit auto sales during February.
Lower apparel store sales reflected the brunt of the warm-weather give back from January strength. A 3.3% (+1.6% y/y) drop followed the downwardly revised 2.4% gain. Elsewhere, discretionary spending looked respectable. General merchandise store sales slipped just 0.3% (5.3% y/y) after a little revised 1.8% January rise. Sales of furniture, electronics &amp; appliances fell 3.1% (+5.6% y/y) after a 5.6% January spurt that was much stronger than the 2.9% gain reported initially.
Building material sales rose another 1.5% (20.5% y/y) after a 7.3% jump in January that was double the rise initially estimated.
Sales at gasoline stations fell 1.6% (+17.7% y/y) as retail gasoline prices fell 1.5%. In March, gasoline prices at $2.35 per gallon are 3.0% higher than during February.
Less gasoline, nonauto retail sales fell 0.3% (+7.8% y/y) last month following a 2.4% January spike that revised up from 1.8% reported initially.
Sales of nonstore retailers (internet &amp; catalogue) surged 3.2% (13.3% y/y) after a little revised 2.7% January decline.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">&nbsp;</th>
<th scope="col">Feb</th>
<th scope="col">Jan</th>
<th scope="col">Y/Y</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
</tr>
</thead>
<tbody>
<tr>
<td class="firstcol"><a href="http://www.haverselect.com/dlx/usecon/@ED/@ED04/@ED0401/@ED0401.HTM">Retail Sales &amp; Food Services</a></td>
<td>-1.3%</td>
<td>2.9%</td>
<td>6.7%</td>
<td>7.5%</td>
<td>7.3%</td>
<td>4.3%</td>
</tr>
<tr>
<td class="firstcol">&nbsp; Excluding Autos</td>
<td>-0.4%</td>
<td>2.6%</td>
<td>8.9%</td>
<td>8.6%</td>
<td>8.2%</td>
<td>4.7%</td>
</tr>
</tbody>
</table>
</body>
</html>

US retail sales fell 1.3% last month but several factors suggest the decline hardly indicates consumer spending weakness, even though it exceeded Consensus expectations for a 0.8% drop. 1) January's warm weather surge in spending was [...]

U.S. Retail Sales Off, But ...

Louise Curley

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313c.jpg" width="353">
The diffusion index of Consumer confidence in Japan rose sharply in early 2004 and has shown little change up or down since then. However, the index in February, 2006 at 49.8 is the highest level since early 1990.
Monthly data on consumer confidence in Japan are available only from April, 2004 and are seasonally unadjusted. The data are published by the Cabinet Office which has engaged the market research firm, Shin Joho Center, Inc. to survey and analyze data from a sample of households that contains 5,040 two or more person households and 1,680 single person households. (Some problems with the data collection of the market research firm surfaced last August, but have subsequently been resolved to the satisfaction of the Cabinet Office.) To gain some historical perspective, the new monthly series is linked to the old quarterly Consumer Confidence Index, excluding the single person households. The result is shown in the attached chart where the quarterly data prior to April 2004, have been interpolated and linked with the new series.
Since September of last year, more Japanese consumers have been expecting prices to rise than those expecting prices to fall. We have aggregated the data shown in the Haver Data Base--Japan: Price Expectations. In the data base percentages are shown for up 2% or less, up between 2 and 5% and up over 5%, no change, down less than 2%, down between 2 and 5% and down over 5% and &quot;don&#39;t know&quot;. In the table below the total of percentages expecting rises, and the total of those expecting no change or a decline are shown with the percentage responding &#39;Don&#39;t know&quot; for the months since June 2005...

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/JAPAN/@J8/@J8.HTM">Japan</a></th>
<th scope="col">Feb 06</th>
<th scope="col">Jan 06</th>
<th scope="col">Feb 05</th>
<th scope="col">M/M %</th>
<th scope="col">Y/Y %</th>
<th scope="col">2005&nbsp; </th>
<th scope="col">2004&nbsp;</th>
<th scope="col">2003&nbsp;&nbsp;</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Consumer Confidence&nbsp;</td>
<td>49.8</td>
<td>49.5</td>
<td>47.4</td>
<td>0.61</td>
<td>4.62</td>
<td>47.3</td>
<td>45.6</td>
<td>37.3</td>
</tr>
<tr>
<td class="firstcol"></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td class="firstcol"> Price Expectations </td>
<td>Feb 06</td>
<td>Jan 06</td>
<td>Dec 05</td>
<td>Nov 05</td>
<td>Oct 05</td>
<td>Sep 05&nbsp; </td>
<td>Aug 05&nbsp;</td>
<td>Jul 05&nbsp;&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Percent Increase</td>
<td>50.9</td>
<td>53.2</td>
<td>51.4</td>
<td>55.6</td>
<td>53.9</td>
<td>55.7</td>
<td>44.6</td>
<td>43.5</td>
</tr>
<tr class="odd">
<td class="firstcol">Percent Decrease or Same</td>
<td>&nbsp;43.7</td>
<td>40.8&nbsp;</td>
<td>40.0</td>
<td>39.4</td>
<td>40.4</td>
<td>36.1&nbsp;</td>
<td>49.8</td>
<td>50.1&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Don&#39;t Know</td>
<td>5.6</td>
<td>6.0</td>
<td>8.7</td>
<td>5.0</td>
<td>5.6</td>
<td>8.1</td>
<td>5.7</td>
<td>6.4</td>
</tr>
</tbody>
</table>
</body>
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The diffusion index of Consumer confidence in Japan rose sharply in early 2004 and has shown little change up or down since then. However, the index in February, 2006 at 49.8 is the highest level since early 1990. Monthly data on [...]

Japanese Consumers Maintain Confidence: More Households Expect Prices to Rise Than to Fall

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313b.jpg" width="353">
The Leading Index of the Major 7 OECD economies increased 0.2% in January. For December, the index increased 0.3% but that was revised down from a 0.6% gain reported initially. While the latest increases represent a slight slowdown from the 0.4% and 0.5% advances of October and November, the deceleration reflects weaker figures for the U.S., not elsewhere
During the last ten years there has been a 66% correlation between the change in the leading index and the q/q change in the GDP Volume Index for the Big Seven countries in the OECD.
The U.S. leaders fell 0.1% during January and rose by a moderate 0.3% the prior month, a gain initially reported at 0.9%. The leaders&#39; six month growth slipped, as a result, to 3.2% from 3.7% during the prior month. The correlation between the leaders&#39; growth rate and real GDP growth has been a high 73% during the last ten years.
In Japan, the leading index rose 0.5% in January though the strong 0.5% gain initially reported for December was revised lower to 0.3%. Nevertheless, the index&#39;s six month growth rate improved to 2.8%, it&#39;s best in two years. The leaders&#39; correlation with real economic growth in Japan has been a meaningful 40% during the last ten years.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313a.jpg" width="353">
Leaders in the European Union (15 countries) rose 0.4% after a 0.2% December increase. The rise lifted the six month growth rate to 3.8%, the best since May &#39;04. During the last ten years there has been a 59% correlation between the change in the leading index and the quarterly change in the GDP volume index for the European Union.
TheGerman leading index increased 0.7% for the ninth consecutive monthly increase and improved series&#39; the six month growth rate to 7.0%, the best since February 2004. New orders have risen sharply and the business climate indicator has improved markedly.
A 0.2% increase in the January leading indicators for France represented an improvement from the 0.1% December gain (revised down from the initial estimate) and the 3.9% six month growth rate remained up from the negative growth rates of last Summer. Even the Italian leading index showed an improved no change from a 0.1% December decline and negative changes reported earlier were revised to slightly positive, all sufficient to lift the series&#39; six month growth rate to 0.04% versus negative growth from early 2004 through all of last year.
The UK leaders also improved to plus 0.2% from slight decline during the prior two months and the six month growth rate rose to a slightly positive 0.2% from slightly negative growth during 2005.
The Canadian leaders surged 0.7% though the 0.8% jump during December was half the gain initially estimated. The six month growth nevertheless improved to 2.3%, its most promising since Summer 2004 The correlation of the leaders&#39; growth with Canadian real GDP has been 49% during the last ten years.
The latest OECD Leading Indicator report is available <a href="http://www.oecd.org/dataoecd/2/28/36260134.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/OECDMEI/OECDMEI.HTM">OECD</a></th>
<th scope="col">Jan</th>
<th scope="col">Dec</th>
<th scope="col">Y/Y</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
</tr>
</thead>
<tbody>
<tr>
<td class="firstcol">Composite Leading Index&nbsp;</td>
<td>104.51</td>
<td>104.28</td>
<td>1.7%</td>
<td>102.78</td>
<td>102.41</td>
<td>97.90</td>
</tr>
<tr>
<td class="firstcol">&nbsp;6 Month Growth Rate</td>
<td>3.1%</td>
<td>3.0%</td>
<td>&nbsp;</td>
<td>0.6%</td>
<td>3.6%</td>
<td>2.8%</td>
</tr>
</tbody>
</table>
</body>
</html>

The Leading Index of the Major 7 OECD economies increased 0.2% in January. For December, the index increased 0.3% but that was revised down from a 0.6% gain reported initially. While the latest increases represent a slight slowdown [...]

OECD Leaders' Gains Slower but Suggest Economic Growth

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313b.jpg" width="353">
The Leading Index of the Major 7 OECD economies increased 0.2% in January. For December, the index increased 0.3% but that was revised down from a 0.6% gain reported initially. While the latest increases represent a slight slowdown from the 0.4% and 0.5% advances of October and November, the deceleration reflects weaker figures for the U.S., not elsewhere
During the last ten years there has been a 66% correlation between the change in the leading index and the q/q change in the GDP Volume Index for the Big Seven countries in the OECD.
The U.S. leaders fell 0.1% during January and rose by a moderate 0.3% the prior month, a gain initially reported at 0.9%. The leaders&#39; six month growth slipped, as a result, to 3.2% from 3.7% during the prior month. The correlation between the leaders&#39; growth rate and real GDP growth has been a high 73% during the last ten years.
In Japan, the leading index rose 0.5% in January though the strong 0.5% gain initially reported for December was revised lower to 0.3%. Nevertheless, the index&#39;s six month growth rate improved to 2.8%, it&#39;s best in two years. The leaders&#39; correlation with real economic growth in Japan has been a meaningful 40% during the last ten years.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313a.jpg" width="353">
Leaders in the European Union (15 countries) rose 0.4% after a 0.2% December increase. The rise lifted the six month growth rate to 3.8%, the best since May &#39;04. During the last ten years there has been a 59% correlation between the change in the leading index and the quarterly change in the GDP volume index for the European Union.
TheGerman leading index increased 0.7% for the ninth consecutive monthly increase and improved series&#39; the six month growth rate to 7.0%, the best since February 2004. New orders have risen sharply and the business climate indicator has improved markedly.
A 0.2% increase in the January leading indicators for France represented an improvement from the 0.1% December gain (revised down from the initial estimate) and the 3.9% six month growth rate remained up from the negative growth rates of last Summer. Even the Italian leading index showed an improved no change from a 0.1% December decline and negative changes reported earlier were revised to slightly positive, all sufficient to lift the series&#39; six month growth rate to 0.04% versus negative growth from early 2004 through all of last year.
The UK leaders also improved to plus 0.2% from slight decline during the prior two months and the six month growth rate rose to a slightly positive 0.2% from slightly negative growth during 2005.
The Canadian leaders surged 0.7% though the 0.8% jump during December was half the gain initially estimated. The six month growth nevertheless improved to 2.3%, its most promising since Summer 2004 The correlation of the leaders&#39; growth with Canadian real GDP has been 49% during the last ten years.
The latest OECD Leading Indicator report is available <a href="http://www.oecd.org/dataoecd/2/28/36260134.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/OECDMEI/OECDMEI.HTM">OECD</a></th>
<th scope="col">Jan</th>
<th scope="col">Dec</th>
<th scope="col">Y/Y</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
</tr>
</thead>
<tbody>
<tr>
<td class="firstcol">Composite Leading Index&nbsp;</td>
<td>104.51</td>
<td>104.28</td>
<td>1.7%</td>
<td>102.78</td>
<td>102.41</td>
<td>97.90</td>
</tr>
<tr>
<td class="firstcol">&nbsp;6 Month Growth Rate</td>
<td>3.1%</td>
<td>3.0%</td>
<td>&nbsp;</td>
<td>0.6%</td>
<td>3.6%</td>
<td>2.8%</td>
</tr>
</tbody>
</table>
 Japanese Consumers Maintain Confidence:  More Households Expect Prices to Rise Than to Fall  
by <a href="/comment/Curley.html">Louise Curley</a> March 13, 2006


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060313c.jpg" width="353">
The diffusion index of Consumer confidence in Japan rose sharply in early 2004 and has shown little change up or down since then. However, the index in February, 2006 at 49.8 is the highest level since early 1990.
Monthly data on consumer confidence in Japan are available only from April, 2004 and are seasonally unadjusted. The data are published by the Cabinet Office which has engaged the market research firm, Shin Joho Center, Inc. to survey and analyze data from a sample of households that contains 5,040 two or more person households and 1,680 single person households. (Some problems with the data collection of the market research firm surfaced last August, but have subsequently been resolved to the satisfaction of the Cabinet Office.) To gain some historical perspective, the new monthly series is linked to the old quarterly Consumer Confidence Index, excluding the single person households. The result is shown in the attached chart where the quarterly data prior to April 2004, have been interpolated and linked with the new series. T
Since September of last year, more Japanese consumers have been expecting prices to rise than those expecting prices to fall. We have aggregated the data shown in the Haver Data Base--Japan: Price Expectations. In the data base percentages are shown for up 2% or less, up between 2 and 5% and up over 5%, no change, down less than 2%, down between 2 and 5% and down over 5% and &quot;don&#39;t know&quot;. In the table below the total of percentages expecting rises, and the total of those expecting no change or a decline are shown with the percentage responding &#39;Don&#39;t know&quot; for the months since June 2005...

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol"><a href="http://www.haverselect.com/dlx/JAPAN/@J8/@J8.HTM">Japan</a></th>
<th scope="col">Feb 06</th>
<th scope="col">Jan 06</th>
<th scope="col">Feb 05</th>
<th scope="col">M/M %</th>
<th scope="col">Y/Y %</th>
<th scope="col">2005&nbsp; </th>
<th scope="col">2004&nbsp;</th>
<th scope="col">2003&nbsp;&nbsp;</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Consumer Confidence&nbsp;</td>
<td>49.8</td>
<td>49.5</td>
<td>47.4</td>
<td>0.61</td>
<td>4.62</td>
<td>47.3</td>
<td>45.6</td>
<td>37.3</td>
</tr>
<tr>
<td class="firstcol"></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td class="firstcol"> Price Expectations </td>
<td>Feb 06</td>
<td>Jan 06</td>
<td>Dec 05</td>
<td>Nov 05</td>
<td>Oct 05</td>
<td>Sep 05&nbsp; </td>
<td>Aug 05&nbsp;</td>
<td>Jul 05&nbsp;&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Percent Increase</td>
<td>50.9</td>
<td>53.2</td>
<td>51.4</td>
<td>55.6</td>
<td>53.9</td>
<td>55.7</td>
<td>44.6</td>
<td>43.5</td>
</tr>
<tr class="odd">
<td class="firstcol">Percent Decrease or Same</td>
<td>&nbsp;43.7</td>
<td>40.8&nbsp;</td>
<td>40.0</td>
<td>39.4</td>
<td>40.4</td>
<td>36.1&nbsp;</td>
<td>49.8</td>
<td>50.1&nbsp;</td>
</tr>
<tr>
<td class="firstcol">Don&#39;t Know</td>
<td>5.6</td>
<td>6.0</td>
<td>8.7</td>
<td>5.0</td>
<td>5.6</td>
<td>8.1</td>
<td>5.7</td>
<td>6.4</td>
</tr>
</tbody>
</table>
</body>
</html>

Carol Stone, CBE

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310e.jpg" width="353">
Yesterday here, Tom Moeller discussed the Q4 Flow-of-Funds data and highlighted the important role of consumer borrowing during 2005. The release of this enormous body of data permits examination of other parts of consumer balance sheets and those of other sectors of the economy.
Consumers own assets.When they spend, besides their flow of current income, consumers can use their assets to finance their spending. The simplest form of spending against assets is writing a check or using a debit card to access bank accounts. Some assets, such as stocks, can be sold to obtain spendable cash.
The vast majority of people own houses. In recent years, the prices of their houses have gone up dramatically. But it&#39;s impractical to sell this asset for spending money. Instead, a growing practice is that of borrowing against the value of the property. Lenders facilitate this through home equity lines of credit and quickly processed refinancing transactions. Low mortgage rates, usually tax deductible, have made such borrowing even more attractive. (See first and second graphs)
A month or so ago here, Tom Moeller also explained about one form of this borrowing, &quot;cash-out refinancing&quot;, in which consumers refinance their home mortgage and increase the principal amount of their debt. They can then spend this &quot;cash&quot; they have &quot;taken out&quot; of their home equity. He pointed out that historically such financial actions have come at times of economic and financial stress. Increasingly, though, people are apparently also using such borrowing in a discretionary way to pay for major outlays, such as college tuition, car purchases, major vacations, and so on. This borrowing against the value of one&#39;s home is frequently called &quot;mortgage equity withdrawal&quot;.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310f.jpg" width="353">
The term &quot;mortgage equity withdrawal (MEW)&quot; is an awkward phrase, but it&#39;s in wide use at present. It refers to the reduction of home equity by borrowing against it in the mortgage market. The first use of that term we&#39;re aware of comes from the Bank of England, which developed the concept in 2001. We prefer &quot;home equity withdrawal&quot; and some series compiled by Federal Reserve Board analysts use the phrase &quot;equity extraction&quot;. Since this is a source of spending money, analysts are anxious to calculate it to gauge any possible impact on consumer spending.
An important technicality arises. Some mortgage borrowing has the purpose of creating the housing asset in the first place. So total net new mortgage debt alone overstates the amount of funds available for consumer spending on ordinary goods and services. But published mortgage data are not clearly classified by details of use. So analysts must compile estimates of these amounts. The assumptions in the calculations can make MEW vary considerably.
In Haver&#39;s USECON database, we have recently added five series of &quot;Mortgage Equity Withdrawal&quot;. Two were devised by Alan Greenspan and James Kennedy of the Federal Reserve Board as part of an attempt to refine existing aggregate data on home mortgage originations and repayments. They compute the amount of borrowing that would be required to finance home purchases at lenders&#39; average loan-to-value ratios. For a detailed explanation see FEDS working paper 2005-41, <a href="http://www.federalreserve.gov/pubs/feds/2005/200541/200541pap.pdf"> &quot;Estimates of Home Mortgage Originations, Repayments, and Debt on One-to-Four-Family Residences&quot;</a> by Alan Greenspan and James Kennedy. We call these MEW4 and MEW5. The latter nets out closing costs on mortgage transactions. In this case and in another by economists at a leading investment bank, the value of new home sales is obtained by a simple multiplication of the number of sales by average prices. The Wall-Street devised measure is Haver&#39;s series MEW2. The Fed analysts also estimate the number of sales likely to be all-cash and net them out. The remaining value is multiplied by lenders&#39; average loan-to-value ratios to obtain the applicable amount of the mortgage loan that goes toward the house itself. Equity withdrawal is then total mortgage borrowing less the debt dedicated directly to the house. This remainder can be negative, indicating a net infusion of equity by the homeowner.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310c.jpg" width="353">
We believe the new-home-sales-based measures are not broad enough, however, to capture all of the initial property value. It&#39;s possible, in our view, that those versions of MEW understate the house-dedicated debt and overstate the amount available for consumer spending. New home sales are only a portion of new home construction; compare their number, 1.283 million in 2005, to single-family housing starts, 1.716 million. Further, homeowners can also borrow to remodel their existing home, and this borrowing adds value to their property. Indeed, &quot;residential improvements&quot; are not part of PCE, but are classified in &quot;residential investment&quot;; last year they totaled $158 billion, equal to about 37% of the investment in new single-family homes.
So we have calculated two simple, but more comprehensive measures. The simplest of all, our MEW3, is just home mortgage borrowing less the value of residential construction put-in-place. Since lenders would not lend the full value of the home construction, this subtracts too much from mortgage borrowing, and this measure of MEW is too low. But it can serve as a &quot;quick and dirty&quot; baseline approximation. MEW can be at least as large as this measure. Our series of choice, MEW1, is a variant of this construction-value approach; we use the value of residential investment by households [a few residential properties are owned by corporations and other organizations], a national income accounts series published in the Flow of Funds, Tables F.6 and F.100. We apply a loan-to-value ratio to that amount and subtract it from net new home mortgage borrowing.
In Q4, home mortgage borrowing was $1,110.5 billion (SAAR), down from $1,205.1 billion in Q3. Residential investment by households was $672.1 billion, up from Q3&#39;s $656.5 billion. At a 74.6% loan-to-value ratio, the implied borrowing on the construction amount is $501.6, leaving $608.9 billion of the mortgage borrowing available to be spent on other things, that is, a &quot;cash-out&quot; or &quot;withdrawal&quot; of equity, our series MEW1. Often this figure is compared to disposable income, and it was 6.6% of Q4 DPI. By this reckoning, the highest such ratio was 7.9%, just in Q3.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310d.jpg" width="353">
The new-home-sales based method, MEW2, yields a MEW value of $831.5 billion in Q4, down from $916.4 billion in Q3. The corresponding ratio to disposable income fell to 9.0% from 10.1%. The Federal Reserve&#39;s working paper series (which are NOT &quot;official&quot; statistical release data) will be reported for Q4 sometime over the next couple of weeks.
There is significant controversy presently over how much MEW might have spurred consumer spending the last couple of years. We do not take a stand in this debate, but try to provide you with some resources you can use to interpret others&#39; arguments or in fact draw your own conclusions. What is evident from our analysis is that the mortgage market has never been anywhere near as significant as it was during 2005 in providing funds to consumer borrowers beyond those needed for home construction. So we are in uncharted waters as we move forward with interest rates on the way up and the housing market showing signs of slowing down. Since these funds are consumer liabilities that carry an interest cost, regardless of how the funds have been used, and people&#39;s homes are pledged as collateral, we&#39;d see the heavy borrowing as a source of noteworthy vulnerability.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">SAAR, Bil.$</th>
<th scope="col">Q4 2005</th>
<th scope="col">Q3 2005</th>
<th scope="col">Q2 2005</th>
<th scope="col">Q1 2005</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2000</th>
<th scope="col">1990</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">MEW1*</td>
<td>608.9</td>
<td>709.4</td>
<td>595.4</td>
<td>407.5</td>
<td>580.3</td>
<td>463.7</td>
<td>70.3</td>
<td>-46.1</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>6.6</td>
<td>7.9</td>
<td>6.6</td>
<td>4.6</td>
<td>6.4</td>
<td>5.4</td>
<td>1.0</td>
<td>-0.9</td>
</tr>
<tr class="odd">
<td class="firstcol">MEW2**</td>
<td>831.5</td>
<td>916.4</td>
<td>803.9</td>
<td>601.0</td>
<td>788.2</td>
<td>651.1</td>
<td>220.1</td>
<td>71.2</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>9.0</td>
<td>10.1</td>
<td>9.0</td>
<td>6.8</td>
<td>8.7</td>
<td>7.5</td>
<td>3.1</td>
<td>1.3</td>
</tr>
<tr class="odd">
<td class="firstcol">MEW5**</td>
<td>--</td>
<td>744.4</td>
<td>664.7</td>
<td>550.4</td>
<td>--</td>
<td>632.6</td>
<td>198.9</td>
<td>64.0</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>--</td>
<td>8.2</td>
<td>7.4</td>
<td>6.2</td>
<td>--</td>
<td>7.3</td>
<td>2.8</td>
<td>1.2</td>
</tr>
</tbody>
</table>
</body>
</html>

Yesterday here, Tom Moeller discussed the Q4 Flow-of-Funds data and highlighted the important role of consumer borrowing during 2005. The release of this enormous body of data permits examination of other parts of consumer balance [...]

What Is MEW? How Is It Calculated? Is It a Source of Free Money for Consumers?

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310a.jpg" width="353">
Non-farm payrolls rose 243,000 last month following a downwardly revised 170,000 increase during January that was initially reported at 193,000. Consensus expectations had been for a 210,000 increase during February.
From the household survey the unemployment rate rose modestly to 4.8% but remained near the five year low. Employment rose 183,000 (2.1% y/y) while the labor force rose 335,000 (1.5% y/y). An unchanged 4.7% unemployment rate had been the Consensus expectation for February.
Service producing payrolls surged 198,000 (1.5% y/y), the strongest gain since November, goosed by a 38,000 (0.7% y/y) rise in government employment which more than reversed the decline during January.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310b.jpg" width="353">
Jobs in private service-producing industries rose 160,000 (1.8% y/y) on the strength of a 22,000 (2.1% y/y) gain in financial activities employment and a 39,000 (2.8% y/y) worker rise in professional &amp; business services. Job gains in education &amp; health also rose a strong 47,000 (2.4% y/y) while jobs in leisure &amp; hospitality jobs rose 25,000 (1.9% y/y).
Warm weather continued to bolster construction employment which added 41,000 (4.8% y/y) to an upwardly revised 55,000 gain during January.
Factory sector payrolls slipped during February. The 1,000 worker decline (-0.3% y/y) was the first drop since September and reflected fewer managers. The number of production workers on the job rose 3,000 (1.4% y/y) with durable goods industries adding 2,000 (2.3% y/y). Employment in the motor vehicles &amp; parts industries fell 10,600 (-2.5% y/y). The breadth of gain in factory payrolls over the last three months slipped to a still firm 56.0%.
Average hourly earnings rose an expected 0.3% though factory sector earnings fell 0.1% (+1.8% y/y) and private service producing wages rose 0.4% (3.9% y/y).
Business employment dynamics: tabulations by employer size from the Bureau of Labor Statistics can be found <a href="http://www.bls.gov/opub/mlr/2006/02/art1full.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/USECON/@EB/@EB01/@EB01.HTM">Employment</a></th>
<th scope="col">Feb</th>
<th scope="col">Jan</th>
<th scope="col">Y/Y</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Payroll Employment</td>
<td>243,000</td>
<td>170,000</td>
<td>1.5%</td>
<td>1.5%</td>
<td>1.1%</td>
<td>-0.3%</td>
</tr>
<tr>
<td class="firstcol">&nbsp; Manufacturing</td>
<td>-1,000</td>
<td>7,000</td>
<td>-0.3%</td>
<td>-0.6%</td>
<td>-1.3%</td>
<td>-4.9%</td>
</tr>
<tr class="odd">
<td class="firstcol">Average Weekly Hours</td>
<td>33.7</td>
<td>33.8</td>
<td>33.7 (Feb &#39;05)</td>
<td>33.8</td>
<td>33.7</td>
<td>33.7</td>
</tr>
<tr>
<td class="firstcol">Average Hourly Earnings</td>
<td>0.3%</td>
<td>0.4%</td>
<td>3.5%</td>
<td>2.8%</td>
<td>2.1%</td>
<td>2.7%</td>
</tr>
<tr class="odd">
<td class="firstcol">Unemployment Rate</td>
<td>4.8%</td>
<td>4.7%</td>
<td>5.4% (Feb &#39;05)</td>
<td>5.1%</td>
<td>5.5%</td>
<td>6.0%</td>
</tr>
</tbody>
</table>
</body>
</html>

Non-farm payrolls rose 243,000 last month following a downwardly revised 170,000 increase during January that was initially reported at 193,000. Consensus expectations had been for a 210,000 increase during February. From the [...]

U.S. Payrolls Advance

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<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310a.jpg" width="353">
Non-farm payrolls rose 243,000 last month following a downwardly revised 170,000 increase during January that was initially reported at 193,000. Consensus expectations had been for a 210,000 increase during February.
From the household survey the unemployment rate rose modestly to 4.8% but remained near the five year low. Employment rose 183,000 (2.1% y/y) while the labor force rose 335,000 (1.5% y/y). An unchanged 4.7% unemployment rate had been the Consensus expectation for February.
Service producing payrolls surged 198,000 (1.5% y/y), the strongest gain since November, goosed by a 38,000 (0.7% y/y) rise in government employment which more than reversed the decline during January.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310b.jpg" width="353">
Jobs in private service-producing industries rose 160,000 (1.8% y/y) on the strength of a 22,000 (2.1% y/y) gain in financial activities employment and a 39,000 (2.8% y/y) worker rise in professional &amp; business services. Job gains in education &amp; health also rose a strong 47,000 (2.4% y/y) while jobs in leisure &amp; hospitality jobs rose 25,000 (1.9% y/y).
Warm weather continued to bolster construction employment which added 41,000 (4.8% y/y) to an upwardly revised 55,000 gain during January.
Factory sector payrolls slipped during February. The 1,000 worker decline (-0.3% y/y) was the first drop since September and reflected fewer managers. The number of production workers on the job rose 3,000 (1.4% y/y) with durable goods industries adding 2,000 (2.3% y/y). Employment in the motor vehicles &amp; parts industries fell 10,600 (-2.5% y/y). The breadth of gain in factory payrolls over the last three months slipped to a still firm 56.0%.
Average hourly earnings rose an expected 0.3% though factory sector earnings fell 0.1% (+1.8% y/y) and private service producing wages rose 0.4% (3.9% y/y).
Business employment dynamics: tabulations by employer size from the Bureau of Labor Statistics can be found <a href="http://www.bls.gov/opub/mlr/2006/02/art1full.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/USECON/@EB/@EB01/@EB01.HTM">Employment</a></th>
<th scope="col">Feb</th>
<th scope="col">Jan</th>
<th scope="col">Y/Y</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2003</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">Payroll Employment</td>
<td>243,000</td>
<td>170,000</td>
<td>1.5%</td>
<td>1.5%</td>
<td>1.1%</td>
<td>-0.3%</td>
</tr>
<tr>
<td class="firstcol">&nbsp; Manufacturing</td>
<td>-1,000</td>
<td>7,000</td>
<td>-0.3%</td>
<td>-0.6%</td>
<td>-1.3%</td>
<td>-4.9%</td>
</tr>
<tr class="odd">
<td class="firstcol">Average Weekly Hours</td>
<td>33.7</td>
<td>33.8</td>
<td>33.7 (Feb &#39;05)</td>
<td>33.8</td>
<td>33.7</td>
<td>33.7</td>
</tr>
<tr>
<td class="firstcol">Average Hourly Earnings</td>
<td>0.3%</td>
<td>0.4%</td>
<td>3.5%</td>
<td>2.8%</td>
<td>2.1%</td>
<td>2.7%</td>
</tr>
<tr class="odd">
<td class="firstcol">Unemployment Rate</td>
<td>4.8%</td>
<td>4.7%</td>
<td>5.4% (Feb &#39;05)</td>
<td>5.1%</td>
<td>5.5%</td>
<td>6.0%</td>
</tr>
</tbody>
</table>
What Is MEW?  How Is It Calculated? Is It a Source of Free Money for Consumers? 
by <a href="/comment/Stone.html">Carol Stone</a> March 10, 2006


<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310e.jpg" width="353">
Yesterday here, Tom Moeller discussed the Q4 Flow-of-Funds data and highlighted the important role of consumer borrowing during 2005. The release of this enormous body of data permits examination of other parts of consumer balance sheets and those of other sectors of the economy.
Consumers own assets. When they spend, besides their flow of current income, consumers can use their assets to finance their spending. The simplest form of spending against assets is writing a check or using a debit card to access bank accounts. Some assets, such as stocks, can be sold to obtain spendable cash.
The vast majority of people own houses. In recent years, the prices of their houses have gone up dramatically. But it&#39;s impractical to sell this asset for spending money. Instead, a growing practice is that of borrowing against the value of the property. Lenders facilitate this through home equity lines of credit and quickly processed refinancing transactions. Low mortgage rates, usually tax deductible, have made such borrowing even more attractive. (See first and second graphs)
A month or so ago here, Tom Moeller also explained about one form of this borrowing, &quot;cash-out refinancing&quot;, in which consumers refinance their home mortgage and increase the principal amount of their debt. They can then spend this &quot;cash&quot; they have &quot;taken out&quot; of their home equity. He pointed out that historically such financial actions have come at times of economic and financial stress. Increasingly, though, people are apparently also using such borrowing in a discretionary way to pay for major outlays, such as college tuition, car purchases, major vacations, and so on. This borrowing against the value of one&#39;s home is frequently called &quot;mortgage equity withdrawal&quot;.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310f.jpg" width="353">
The term &quot;mortgage equity withdrawal (MEW)&quot; is an awkward phrase, but it&#39;s in wide use at present. It refers to the reduction of home equity by borrowing against it in the mortgage market. The first use of that term we&#39;re aware of comes from the Bank of England, which developed the concept in 2001. We prefer &quot;home equity withdrawal&quot; and some series compiled by Federal Reserve Board analysts use the phrase &quot;equity extraction&quot;. Since this is a source of spending money, analysts are anxious to calculate it to gauge any possible impact on consumer spending.
An important technicality arises. Some mortgage borrowing has the purpose of creating the housing asset in the first place. So total net new mortgage debt alone overstates the amount of funds available for consumer spending on ordinary goods and services. But published mortgage data are not clearly classified by details of use. So analysts must compile estimates of these amounts. The assumptions in the calculations can make MEW vary considerably.
In Haver&#39;s USECON database, we have recently added five series of &quot;Mortgage Equity Withdrawal&quot;. Two were devised by Alan Greenspan and James Kennedy of the Federal Reserve Board as part of an attempt to refine existing aggregate data on home mortgage originations and repayments. They compute the amount of borrowing that would be required to finance home purchases at lenders&#39; average loan-to-value ratios. For a detailed explanation see FEDS working paper 2005-41, &quot;Estimates of Home Mortgage Originations, Repayments, and Debt on One-to-Four-Family Residences&quot; by Alan Greenspan and James Kennedy on <a href="http://www.federalreserve.gov">www.federalreserve.gov</a>. We call these MEW4 and MEW5. The latter nets out closing costs on mortgage transactions. In this case and in another by economists at a leading investment bank, the value of new home sales is obtained by a simple multiplication of the number of sales by average prices. The Wall-Street devised measure is Haver&#39;s series MEW2. The Fed analysts also estimate the number of sales likely to be all-cash and net them out. The remaining value is multiplied by lenders&#39; average loan-to-value ratios to obtain the applicable amount of the mortgage loan that goes toward the house itself. Equity withdrawal is then total mortgage borrowing less the debt dedicated directly to the house. This remainder can be negative, indicating a net infusion of equity by the homeowner.<img align="left" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310c.jpg" width="353">
We believe the new-home-sales-based measures are not broad enough, however, to capture all of the initial property value. It&#39;s possible, in our view, that those versions of MEW understate the house-dedicated debt and overstate the amount available for consumer spending. New home sales are only a portion of new home construction; compare their number, 1.283 million in 2005, to single-family housing starts, 1.716 million. Further, homeowners can also borrow to remodel their existing home, and this borrowing adds value to their property. Indeed, &quot;residential improvements&quot; are not part of PCE, but are classified in &quot;residential investment&quot;; last year they totaled $158 billion, equal to about 37% of the investment in new single-family homes.
So we have calculated two simple, but more comprehensive measures. The simplest of all, our MEW3, is just home mortgage borrowing less the value of residential construction put-in-place. Since lenders would not lend the full value of the home construction, this subtracts too much from mortgage borrowing, and this measure of MEW is too low. But it can serve as a &quot;quick and dirty&quot; baseline approximation. MEW can be at least as large as this measure. Our series of choice, MEW1, is a variant of this construction-value approach; we use the value of residential investment by households [a few residential properties are owned by corporations and other organizations], a national income accounts series published in the Flow of Funds, Tables F.6 and F.100. We apply a loan-to-value ratio to that amount and subtract it from net new home mortgage borrowing.
In Q4, home mortgage borrowing was $1,110.5 billion (SAAR), down from $1,205.1 billion in Q3. Residential investment by households was $672.1 billion, up from Q3&#39;s $656.5 billion. At a 74.6% loan-to-value ratio, the implied borrowing on the construction amount is $501.6, leaving $608.9 billion of the mortgage borrowing available to be spent on other things, that is, a &quot;cash-out&quot; or &quot;withdrawal&quot; of equity, our series MEW1. Often this figure is compared to disposable income, and it was 6.6% of Q4 DPI. By this reckoning, the highest such ratio was 7.9%, just in Q3.<img align="right" border="0" height="265" src="https://haver-commentaries.s3.eu-west-1.amazonaws.com/comments/060310d.jpg" width="353">
The new-home-sales based method, MEW2, yields a MEW value of $831.5 billion in Q4, down from $916.4 billion in Q3. The corresponding ratio to disposable income fell to 9.0% from 10.1%. The Federal Reserve&#39;s working paper series (which are NOT &quot;official&quot; statistical release data) will be reported for Q4 sometime over the next couple of weeks.
There is significant controversy presently over how much MEW might have spurred consumer spending the last couple of years. We do not take a stand in this debate, but try to provide you with some resources you can use to interpret others&#39; arguments or in fact draw your own conclusions. What is evident from our analysis is that the mortgage market has never been anywhere near as significant as it was during 2005 in providing funds to consumer borrowers beyond those needed for home construction. So we are in uncharted waters as we move forward with interest rates on the way up and the housing market showing signs of slowing down. Since these funds are consumer liabilities that carry an interest cost, regardless of how the funds have been used, and people&#39;s homes are pledged as collateral, we&#39;d see the heavy borrowing as a source of noteworthy vulnerability.

<table border="0" cellspacing="0" width="100%">
<colgroup><col><col><col><col><col><col><col><col></colgroup>
<thead>
<tr>
<th scope="col" class="firstcol">SAAR, Bil.$</th>
<th scope="col">Q4 2005</th>
<th scope="col">Q3 2005</th>
<th scope="col">Q2 2005</th>
<th scope="col">Q1 2005</th>
<th scope="col">2005</th>
<th scope="col">2004</th>
<th scope="col">2000</th>
<th scope="col">1990</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td class="firstcol">MEW1*</td>
<td>608.9</td>
<td>709.4</td>
<td>595.4</td>
<td>407.5</td>
<td>580.3</td>
<td>463.7</td>
<td>70.3</td>
<td>-46.1</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>6.6</td>
<td>7.9</td>
<td>6.6</td>
<td>4.6</td>
<td>6.4</td>
<td>5.4</td>
<td>1.0</td>
<td>-0.9</td>
</tr>
<tr class="odd">
<td class="firstcol">MEW2**</td>
<td>831.5</td>
<td>916.4</td>
<td>803.9</td>
<td>601.0</td>
<td>788.2</td>
<td>651.1</td>
<td>220.1</td>
<td>71.2</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>9.0</td>
<td>10.1</td>
<td>9.0</td>
<td>6.8</td>
<td>8.7</td>
<td>7.5</td>
<td>3.1</td>
<td>1.3</td>
</tr>
<tr class="odd">
<td class="firstcol">MEW5**</td>
<td>--</td>
<td>744.4</td>
<td>664.7</td>
<td>550.4</td>
<td>--</td>
<td>632.6</td>
<td>198.9</td>
<td>64.0</td>
</tr>
<tr>
<td class="firstcol">&nbsp; % of DPI</td>
<td>--</td>
<td>8.2</td>
<td>7.4</td>
<td>6.2</td>
<td>--</td>
<td>7.3</td>
<td>2.8</td>
<td>1.2</td>
</tr>
</tbody>
</table>
</body>
</html>

US is big leader in global surge in private AI investment

Larger-than-usual income tax refunds this year are supporting consumer spending

Sharply rising share of AI-related jobs

Inflationary impact of surge in oil prices larger in Europe than in the US

Futures market thinks the price of oil will recede significantly over the next six months

Recent pickup in US defense orders could help support overall growth ahead

Cost of transporting crude oil has soared to series high

Market-based inflation expectations have not yet reflected recent surge in oil prices

Global equity markets are fearing a major economic disruption from soaring oil prices

Is recent drop in sentiment signaling softer growth ahead?

With the Iran conflict, geopolitical risk has soared to alarming levels

Soaring AI-related investment in US underpinning strong contribution of business spending to overall growth

AI-related outperformance of IP in Advanced Asia ex Japan

Resilient US economy pushing up Blue Chip 2026 outlook

US and China big leaders in adoption of AI models

Robust US demand for advanced technology products

China's export growth rotating away from the US

More pronounced upward revisions in countries more exposed to AI investment

Stable job openings and hiring rates point to cautious hiring

Global freight costs are on the rise while supply chain pressures are contained

Accelerating positive economic surprises in the G10 are boosting the global economy

Considerably more monetary ease expected from US and UK as Japan tightens

Tighter US immigration enforcement adversely impacting labor force

Economic policy uncertainty, while still elevated, is declining

Gradual disinflation and easier monetary policies across advanced economies

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Sandy Batten

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Industrial production (IP) rose a much larger-than-expected 0.7% m/m in April, rebounding from an upwardly revised 0.3% m/m decline in March (previously -0.5% m/m), according to data released by the Federal Reserve Board. The Action Economics Survey looked for a 0.2% monthly gain. The y/y rate also rebounded in April, rising to 1.4% y/y after having fallen to 0.7% in March. IP has clearly trended up since late last year. Since November 2025, it has grown at a 3.6% annual rate. The current level of output is the highest since August 2019 but is still 1.5% below the November 2018 series peak.

Manufacturing output led the April rebound, rising 0.6% m/m (1.3% y/y) following an upwardly revised 0.1% monthly increase in March (previously -0.1% m/m). Mining output fell in April for the second consecutive month, edging down 0.1% m/m (+0.2% y/y) after a 1.6% monthly drop in March (revised down from -1.2% m/m). Utilities production rebounded in April, jumping 1.6% m/m (2.7% y/y) and more than offsetting a 1.4% monthly decline in March (revised up from -2.3% previously). The rebound in utilities output reflected a 1.1% rise in electricity production and a 7.3% monthly jump in natural gas distribution, the first monthly gain in four months.

Within manufacturing, durable goods production jumped 1.2% m/m (3.2% y/y) in April after having been unchanged in March. A 3.7% m/m rebound in motor vehicles and parts production, the largest monthly gain since May 2025, led the April increase. Motor vehicles and parts production had fallen 2.4% m/m in March. Production of computers and electronic products increased 1.5% m/m, the fourth consecutive monthly rise. Aerospace output rose 1.6% m/m in April, the third consecutive monthly gain and the largest since July 2025. By contrast, furniture production fell 1.8% m/m, the third consecutive monthly decline. 

Output of nondurable manufactured goods edged down 0.1% m/m (-0.6% y/y) in April, the first monthly decline in four months. Production of apparel and leather goods slumped 2.2% m/m on top of a 2.0% monthly fall in March. Chemical output fell 0.9% m/m in April, its first monthly decline in four months. Output of plastics and rubber products fell 0.9% m/m, the first monthly fall in four months. By contrast, production of petroleum and coal products rose 1.0% m/m in April, the same monthly increase as in March.

By market group, output of consumer goods rebounded in April, increasing 0.9% m/m (-0.2% y/y) following a 0.8% m/m decline in March. Production of business equipment surged 1.5% m/m (+6.0% y/y) in April, the largest monthly gain since March 2025. Output of construction supplies was unchanged in April from March (+1.2% y/y) following a 0.9% m/m gain in March. Materials production rebounded in April, rising 0.5% m/m (1.2% y/y) after a 0.4% m/m decline in March.

In special classifications, output of selected high-tech industries increased 1.0% m/m (+9.2% y/y) in April following a 0.5% monthly gain in March. The rebound in motor vehicles and parts production reflected a 5.3% monthly surge in vehicle output, the largest monthly gain since May 2025. Manufacturing output excluding selected high-tech industries rose 0.6% m/m in April, the largest increase since February 2025, following a 0.1% m/m increase in March. Manufacturing output excluding both selected high-tech industries and motor vehicles and parts advanced 0.3% m/m in April, the same monthly gain as in March.

Capacity utilization rose to 76.1% in April from 75.7% in March. The April reading was the highest since last August but was still 3.3%-points below its long-term (1972-2025) average. Manufacturing capacity utilization increased to 75.8% in April from 75.4% in March, 2.4%-points below its long-term average.

Industrial production and capacity data are in Haver’s **USECON** database. Additional detail on production and capacity utilization can be found in the **IP** database. The expectations figures come from the **AS1REPNA** database.



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- Total industrial output increased a much larger-than-expected 0.7% m/m in April with a small upward revision to March.
- Manufacturing output increased 0.6% m/m, led by a 5.3% m/m rebound in vehicle production.
- Mining output edged down 0.1% m/m, while utilities production rose 1.9% m/m.
- The headline rate of capacity utilization rose to 76.1% in April, its highest reading since last August but still well below its long-term average.


U.S. Industrial Production Jumped in April

Robert Brusca

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Industrial orders in Canada are back on an expansion path with orders growing 4.7% in March on top of a 6.9% gain in February. These statistics chronicle Canadian orders digging out from a hole they fell into early in 2026. Now the data show emerging sequential growth in Canadian orders, which are advancing 3.6% over 12 months at a 14.9% annual rate over six-months, and a 26.7% annual rate over three-months. Still, on the chart that plots the year-over-year growth rates these recent accelerated rates of growth appear as mere recoveries from what had been earlier weakness. It remains to be seen how much acceleration the Canadian economy will actually undergo.

Unfilled orders expanded in March for the second month in a row, growing 2.4% after growing 1.4% in February once again following the recovery theme.

Manufacturing shipments grew by 3% in March after growing 3.4% in February and after dropping sharply in January - again echoing the recovery theme. Durable goods show two months of increases with the March increase weak after a very strong rise in February. Motor vehicle output recovered very strongly in February, after falling at a 37.1% annual rate in January; motor vehicle output is up by 15% in March, a hefty growth rate but short of what was posted in February. Once again, we see an echo of the theme of recovery. However, shipments of durable goods excluding motor vehicles are less robust, after dropping 1.8% in January output rose by 3.8% in February and has fallen back, dropping by 1.1% in March, a small fly in the ointment of this recovery theme for Canada. And nondurable goods shipments saw a small increase in January of 0.2%, a flat February, and now an extremely strong, 5.6% month-to-month gain in March.

Canada's sequential growth rates are on the verge of showing broad acceleration. Orders clearly do accelerate from 12-months to six-months to three-months. Unfilled orders, however, accelerate over six-months compared to 12-months and then take a small step back over three-months to an annualized growth rate of 13.4% - a very small step back that is still far above the 12-month growth pace. Manufacturing shipments, too, show a small flaw in acceleration as the 6-month pace dips ever so slightly before logging a very strong 3-month pace. Durable goods then are an exception to the acceleration theme; however, nondurable goods get back on board with the strong acceleration move.

**Rankings**
The rank standings for these categories are based on annual growth rates and comparison with data extend back approximately 25 years. Orders have a 58-percentile standing, unfilled orders have a 57-percentile standing, while manufacturing shipments have a 62-percentile standing. Shipments for durable goods durables excluding motor vehicles and from motor vehicles as a stand-alone have rankings in their 30th- to 40th-percentiles, below their historic medians. (medians occur at a ranking of 50). However, nondurables have an extremely strong 80.5 percentile standing. The data are consistent, the recovery and progress with the exception that durable goods shipments that are not fully on board and languish below their historic median results. Ranking the data over six-month growth rates improves the results somewhat and brings motor vehicles on board for a growth rate that is above its historic median.

**Signs of improvement**
Goods-based industry shows signs of picking up even in March as oil prices were rising and industry was facing greater challenges. The US industrial production report for April, similarly, shows acceleration across the board, even as the economy continued to deal with the difficulties of rising oil prices. Of course, the Canadian US economies are closely linked; we would expect the manufacturing sectors to be performing with some degree of synchronization. However, there's no reason to be complacent about the outlook. Oil prices have continued to rise, the challenge to consumers is strong and across all countries. In the US special tax cuts enacted last year, which went into effect earlier this year, have helped to deliver extra money to consumers that have helped them deal with the oil price shock. But these were funds that were supposed to help stimulate the economy to higher growth and were planned by the President to help him with midterm elections coming later in the year. The US economy still has to deal with those realities with sharply divided political reality as well.

**Outlook**
The US acrimony with Canada has taken a back burner for a while. And as that has happened the Canadian economy has come back to life. However, Canada still has some problems with inflation although it also has a broader inflation target to accommodate some flexibility. And the prospect for more inflation because of global oil prices continues to hang in the balance. The results for March are encouraging but certainly not definitive. Canada has mounted a nice recovery after a period of difficulty earlier in the year but it's still hard to say what comes next.



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Canada

Canadian Industry Perks Up

Andrew Cates

**A Tug of War Between AI Hope and Geopolitical Shock**
The latest Blue Chip Economic Indicators survey highlights a growing divergence between economies benefiting from AI-driven optimism and those more exposed to the inflationary consequences of renewed geopolitical instability. Taiwan stands out as the clearest AI beneficiary, with growth forecasts revised sharply higher while inflation expectations have risen only modestly, reflecting surging semiconductor demand and continued investment in global technology supply chains. China also remains relatively resilient, supported by ongoing AI-related capital spending and stronger technology sectors. By contrast, the euro area and UK have seen much larger upward revisions to inflation forecasts alongside weaker or declining growth expectations, underscoring their greater vulnerability to the recent Middle East shock and higher energy costs. Korea sits somewhere in between: benefiting from the AI hardware cycle but still exposed to trade and energy headwinds. Overall, the chart illustrates the increasingly important push-and-pull shaping the global outlook: AI optimism and productivity hopes on one side, and geopolitical fragmentation, energy insecurity and supply-side inflation pressures on the other.

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**Forecasters See Contained Pass-Through**
Against this backdrop, our latest Blue Chip special question sought to gauge whether economists believe the recent rise in energy prices will remain largely contained — or whether it risks spilling more meaningfully into underlying global inflation dynamics. The results suggest forecasters have become somewhat less concerned about a broad and persistent inflationary impulse since April. A larger share of respondents in the May survey now expect only a “limited and temporary” pass-through into core inflation, while the proportion anticipating “moderate and persistent” effects has declined noticeably. Very few panelists expect significant second-round effects, implying that most still believe inflation expectations and wage-setting behaviour remain relatively well anchored. In part, this reflects confidence in central bank credibility and the view that softer global demand conditions will constrain firms’ pricing power. Yet the persistence of a sizeable minority still expecting moderate pass-through underscores the uncomfortable tension facing policymakers. 

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**Energy Reawakens as a US Inflation Driver**
While survey respondents generally expect only limited pass-through from higher energy prices into broader inflation, the latest US CPI data provide a reminder that the process may already be underway at the margin. April’s CPI report showed core inflation coming in slightly firmer than expected, suggesting underlying price pressures remain more persistent than many policymakers had hoped. The decomposition of CPI inflation highlights that services continue to dominate overall inflation dynamics, reflecting still-elevated wage and labour-intensive price pressures across the economy. However, the more notable recent development has been the renewed contribution from energy prices, which had previously acted as a disinflationary force through much of 2025. Food inflation has also remained comparatively steady, while non-energy goods prices continue to exert only modest upward pressure despite ongoing tariff and supply-chain concerns. Taken together, the data reinforce the idea that the US economy is not facing a classic demand collapse, but rather a more uncomfortable supply-side environment in which geopolitical energy shocks risk colliding with still-resilient domestic demand, AI-related investment spending and sticky service-sector inflation.

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**AI: The Powerful Counterweight to Geopolitical Headwinds**
If rising energy prices and geopolitical instability represent one major force shaping the current macroeconomic outlook, the extraordinary surge in AI-related investment represents the other. The latest data from Our World in Data show global private investment in AI accelerating sharply again in 2025, reaching close to $300 billion — more than double the level seen just two years earlier. The United States continues to dominate the global AI landscape, accounting for the overwhelming majority of private investment spending, while China and Europe remain considerably smaller contributors despite continued growth. The scale and speed of the 2025 increase is particularly striking given the broader backdrop of elevated policy uncertainty, trade fragmentation and concerns about slowing global productivity growth. In effect, the global economy is now being pulled in two competing directions: on one side, geopolitical tensions, supply-chain fragilities and more recent energy shocks are weighing on confidence and raising supply-side costs; on the other, AI enthusiasm is driving an enormous wave of capital expenditure, infrastructure build-out and technology-related demand. This helps explain why growth expectations — particularly in the US and parts of Asia — have remained comparatively resilient despite an increasingly uncertain global environment.

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**Industrial Winners and Losers in a Fragmenting Global Economy**
The divergence in industrial performance across advanced economies has become increasingly striking. Taiwan has emerged as one of the clearest beneficiaries of the global AI boom, with industrial production surging as semiconductor demand, data-centre investment and advanced electronics exports continue to accelerate. Denmark has also significantly outperformed, though for very different reasons, with the extraordinary global success of its pharmaceutical sector — particularly weight-loss and diabetes drugs — driving a powerful expansion in manufacturing output. By contrast, the UK and Germany have experienced a far weaker industrial recovery. In both cases, elevated energy costs and greater dependence on imported energy have weighed heavily on industrial competitiveness since the post-pandemic energy shock. Germany’s large manufacturing sector has been particularly exposed to higher natural gas prices and weaker external demand, while the UK has continued to struggle with a combination of high energy costs, weak productivity growth and subdued business investment. The chart highlights an increasingly important feature of the global economy: countries exposed to powerful structural growth themes such as AI or pharmaceuticals are pulling away from those still burdened by energy dependence and deteriorating industrial competitiveness.

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**China’s Pulse Is Picking Up Again**
China’s economic backdrop has shown clearer signs of improvement in recent months, with both the Citigroup Economic Surprise Index and the Yicai High Frequency Economic Activity Index moving higher. The rebound suggests that incoming data have begun consistently outperforming expectations after a prolonged period of disappointment. Part of the recent improvement likely reflects the cumulative effects of policy easing, including targeted fiscal support, infrastructure spending and further efforts to stabilise the property sector. Export demand has also remained more resilient than many expected, helped in part by the continued strength of global technology and AI-related supply chains. At the same time, improving domestic mobility and energy usage indicators point to firmer underlying activity momentum. The Yicai index itself is designed to provide a near real-time pulse of the Chinese economy using a basket of high-frequency indicators including subway usage, air pollution, coal consumption, freight activity, unemployment and bankruptcy trends. While China still faces significant structural headwinds — including weak household confidence, property-sector fragilities and deflationary pressures — the recent pickup suggests that growth momentum may be stabilising at a time when several other major economies are becoming more vulnerable to geopolitical and energy-related shocks.

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The global economy is still caught between two powerful and competing forces. On one side, the AI investment boom continues to support growth, industrial activity and equity markets, particularly in the US and parts of Asia. On the other, renewed Middle East tensions and higher energy prices are adding to inflation risks and broader policy uncertainty. The latest Blue Chip survey reflects this divide clearly: growth expectations have generally held up best in economies tied to AI-related investment and technology supply chains, while inflation forecasts have risen more sharply in more energy-exposed economies such as the UK and euro area (chart 1). Forecasters still largely expect only limited pass-through from higher energy prices into core inflation, although recent US CPI data suggest underlying price pressures remain somewhat sticky (charts 2 and 3). At the same time, the extraordinary continued surge in global AI investment — now approaching $300 billion annually — highlights the sheer scale of capital being deployed into semiconductors, data centres and digital infrastructure, particularly in the United States (chart 4). The divergence in industrial production trends also reinforces the growing gap between economies benefiting from structural growth drivers — such as Taiwan’s semiconductor sector and Denmark’s pharmaceutical industry — and those struggling with higher energy costs and weaker competitiveness, notably Germany and the UK (chart 5). Meanwhile, improving Chinese activity indicators suggest policy support and stronger technology demand may finally be helping to stabilise growth (chart 6). Overall, the world economy remains resilient, but increasingly uneven, with AI-related investment continuing to offset — though not eliminate — the drag from geopolitical fragmentation and rising energy insecurity.

Charts of the Week: The Tug of War

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Total retail sales rose a solid 0.5% m/m (4.9% y/y) in April on top of a slightly downwardly revised 1.6% monthly jump in March (previously 1.7%), according to data released by the U.S. Census Bureau. The Action Economics Forecast Survey looked for a 05% m/m gain. Excluding autos, other sales increased 0.7% m/m (6.3% y/y) in April following an unrevised 1.9% monthly jump in March. Expectations were for a 0.6% monthly increase. The strong performance in March and the additional solid gain in April put the April level up 7.8% at an annual rate from the Q1 average, providing a very solid start for Q2.

As expected, the continued rise in retail gasoline prices boosted gasoline sales further in April. Gasoline sales increased 2.8% m/m in April following a 13.7% m/m surge in March and accounted for more than 40% of the April increase in total sales. However, sales were solid even without gasoline sales. Total sales excluding gasoline rose 0.3% m/m in April versus a 0.7% monthly gain in March. Sales excluding both autos and gasoline increased 0.5% m/m in April following a 0.7% m/m rise in March.

The control group of sales (total sales excluding food services, autos, gasoline and building materials that the BEA uses to construct PCE in the national accounts) posted another solid increase in March, rising 0.5% m/m in April following an upwardly revised 0.8% m/m increase in March (previously (0.7% m/m). The solid performances of the control group sales in March and April provide a strong start to Q2. April control-group sales are 5.4% at an annual rate above the Q1 average, in line with the 5.7% annualized increase in Q1. Consumer spending remains surprisingly resilient notwithstanding the recent hit to disposable income from the marked increase in energy prices.

Sales across major sectors were varied in April. Consumers clearly spent more on necessities, owing largely to higher prices. Food sales increased 0.8% m/m in April on top of a 1.0% m/m rise in March. And as already noted, gasoline sales posted another outsized monthly increase. By contrast, department store sales slumped 3.2% m/m, clothing sales fell 1.5% m/m, auto sales declined 0.4% m/m and furniture sales fell 2.0% m/m. More encouragingly, sales of nonstore retailers rose 1.1% m/m, their fourth consecutive solid monthly gain. And sales at restaurants increased 0.6% m/m in April, their third consecutive monthly rise. Analysts frequently use restaurant sales as a barometer of consumer attitudes, believing that consumers would not eat out regularly if they were under serious financial stress.

Retail sales data can be found in Haver’s **USECON** database. The expectations figures are from the Action Economics Forecast Survey in **AS1REPNA**.


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- Total sales increase 0.5% m/m in April after a 1.6% monthly jump in March.
- Gasoline sales rose 2.8% m/m in April on top of a 13.7% surge in March.
- Auto sales fell 0.4% m/m after a 0.6% m/m rise in March.
- Excluding auto and gasoline sales, remaining sales increased by a solid 0.5% m/m in April versus a 0.7% m/m rise in March.
- Sales of the retail control group that is used to construct PCE rose 0.5% m/m in April and are 5.4% annualized above the Q1 average, providing a good start to Q2.


U.S. Retail Sales Slowed in April But Remained Solid

Kathleen Stephansen, CBE

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Initial claims for unemployment insurance rose by 12,000 to 211,000 in the week ending May 9, from 199,000 in the week ending May 2, revised from 200,000. The four-week average rose 750 to 203,750 in the week ending May 9, from 203,000 the May 2 week, revised from 203,250. The Action Economics/Haver Analytics Survey looked for 205,000 claims to have been filed. 

The total number of unemployment insurance beneficiaries—also known as “continuing claims”—rose by 24,000 to 1.782 million in the week ending May 2, from 1.758 million in the week ending April 25, revised from 1.766 million. The four-week moving average declined to 1.781 million in the latest week from 1.788 million in the April 25 week. The four-week moving average reached the lowest level since May 2024. The insured unemployment rate rose back to 1.2% in the week of May 2 from the one-week dip to 1.1% in the April 25 week. It had been at 1.2% since the week of November 29, 2025.

The insured unemployment rate varied greatly across individual states and territories. In the week ending April 25, the highest unemployment rates were in Rhode Island (2.29%), New Jersey and Massachusetts (both 2.20%), and Washington (2.15%). The lowest rates were in Florida and Louisiana (both 0.31%), South Dakota (0.32%), Alabama and Arkansas (both 0.36%), North Carolina (0.38%), Tennessee (0.47%) and Iowa, Kansas and Virginia (all 0.48%). Rates in other notable states include California (1.99%), New York (1.66%), Illinois (1.56%), Pennsylvania (1.28%), and Texas (1.03%). These state data are not seasonally adjusted.

Data on weekly unemployment claims are from the Department of Labor itself, not the Bureau of Labor Statistics. They begin in 1967 and are contained in Haver’s **WEEKLY** database and summarized monthly in **USECON**. Data for individual states are in **REGIONW** back to December 1986.


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- New claims rose by 12,000 to 211,000.
- Continuing claims rose by 24,000 to 1.782 million.
- The insured unemployment rate was back up to 1.2% in the week of May 2, from the one-week dip to 1.1% the prior week.

Economy in Brief: 2006

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