Tom Moeller

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<p align="justify"><b>&bull; Labor market weakness gets underway in March.
</b></p>

<p align="justify"><b>&bull; Service-sector employment declines, particularly in small businesses.
</b></p>

<p align="justify">The ADP National Employment Report
indicated that nonfarm private payrolls during March fell 27,000 (+1.3% y/y)
following a 179,000 February increase, revised from 183,000. ADP conducts its
monthly survey during the week that includes the 12th of the month, so it
preceded the stronger layoff activity in recent weeks. The latest figure
compared to a 200,000 decline expected in the Action Economics Forecast Survey.</p>

<p align="justify">Small payrolls declined 90,000 (-0.3% y/y) following a fairly
steady 21,000 February gain. Medium-sized payrolls rose 7,000 (1.1% y/y) after a
27,000 rise, which was half the January rise. Large-sized payrolls improved 56,000
(2.2% y/y) after a fairly steady steady131,000 rise.</p>

<p align="justify">Within industry sectors, employment at goods-producing firms
eased 9,000 (+0.2% y/y) last month after a 12,000 rise, which also was half the
upwardly revised January increase. Construction sector payrolls fell 16,000 last
month (+1.3% y/y), the first decline in nine months. Factory sector employment
improved 6,000 (-0.3% y/y), the first increase in four months. Employment in the
natural resource &amp; mining sector edged 1,000 higher (-2.0% y/y), but was
down versus March 2019.</p>

<p align="justify">Employment growth in the private service sector declined 18,000
(+1.5% y/y) after a 167,000 February strengthening. Education &amp; health
services jobs improved a steady 48,000 (2.4% y/y). Financial activities payrolls
held steady (1.3% y/y). These figures were offset by a collapse of 37,000 (+0.7%
y/y) in trade, transportation &amp; utilities, the largest decline in ten years.
Leisure &amp; hospitality employment fell 11,000 (+2.1% y/y) after two monthly
increases of roughly 45,000. Employment in professional &amp; business services
weakened 3,000 (+1.8% y/y). Information sector payrolls declined 7,000 (-0.5% y/y).</p>

<p align="justify">The Automatic Data Processing Research Institute survey is
based on ADP's business payroll transaction system covering 411,000 companies
and nearly 24 million employees. The data are processed by Moody's Analytics
Inc., then calibrated and aligned with the BLS establishment survey data. The
ADP data cover private sector employment only.</p>

<p align="justify">The ADP National Employment Report data can be found in
Haver's <b>USECON</b> database. Historical figures date back to 2001 for private
employment and the industry breakdown, and 2005 for the business size breakout.
The expectation figure is available in Haver's <b>AS1REPNA</b> database.</p>

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      <table class="centered" width="100%" border="0" cellspacing="0">
	  	<colgroup><col><col><col><col><col><col><col><col></colgroup>

  <thead>
    <tr>
      <th class="firstcol" scope="col" >ADP/Moody's National
        Employment Report</th>
      <th scope="col" >Mar</th>
      <th scope="col" >Feb</th>
      <th scope="col" >Jan</th>
      <th scope="col" >Mar Y/Y</th>
      <th scope="col" >2019</th>
      <th scope="col" >2018</th>
      <th scope="col" >2017</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td class="firstcol" >Nonfarm Private Payroll Employment (m/m
        chg, 000s)</td>
      <td  >-27</td>
      <td  >179</td>
      <td  >205</td>
      <td  >1.3%</td>
      <td  >1.5%</td>
      <td  >1.8%</td>
      <td  >1.7%</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" >&nbsp;Small Payroll (1-49)</td>
      <td  >-90</td>
      <td  >21</td>
      <td  >22</td>
      <td  >-0.2</td>
      <td  >0.2</td>
      <td  >0.6</td>
      <td  >1.1</td>
    </tr>
    <tr>
      <td class="firstcol" >&nbsp;Medium Payroll (50-499)</td>
      <td  >7</td>
      <td  >27</td>
      <td  >54</td>
      <td  >1.1</td>
      <td  >2.0</td>
      <td  >2.0</td>
      <td  >1.9</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" >&nbsp;Large Payroll (&gt;500)</td>
      <td  >56</td>
      <td  >131</td>
      <td  >130</td>
      <td  >2.2</td>
      <td  >1.9</td>
      <td  >2.3</td>
      <td  >2.0</td>
    </tr>
    <tr>
      <td class="firstcol" >Goods-Producing</td>
      <td  >-9</td>
      <td  >12</td>
      <td  >24</td>
      <td  >0.2</td>
      <td  >1.6</td>
      <td  >2.9</td>
      <td  >1.8</td>
    </tr>
    <tr>
      <td class="firstcol" >&nbsp; Construction</td>
      <td  >-16</td>
      <td  >19</td>
      <td  >33</td>
      <td  >1.3</td>
      <td  >2.7</td>
      <td  >4.1</td>
      <td  >3.7</td>
    </tr>
    <tr>
      <td class="firstcol" >&nbsp; Manufacturing</td>
      <td  >6</td>
      <td  >-4</td>
      <td  >-5</td>
      <td  >-0.3</td>
      <td  >1.0</td>
      <td  >1.9</td>
      <td  >0.8</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" >Service-Producing</td>
      <td  >-18</td>
      <td  >167</td>
      <td  >181</td>
      <td  >1.5</td>
      <td  >1.5</td>
      <td  >1.6</td>
      <td  >1.7</td>
     </tr>
              </tbody>
            </table>
            </span>
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• Labor market weakness gets underway in March. • Service-sector employment declines, particularly in small businesses. The ADP National Employment Report indicated that nonfarm private payrolls during March fell 27,000 (+1.3% y/y) [...]

U.S. ADP Private Payrolls Decline as Coronavirus Effects Begin

Sandy Batten

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<p align="justify">Led by a sharp increase in refinancing applications, the Mortgage Bankers Association's Mortgage Loan Application Index rebounded in the week ended March 27, rising 15.3% w/w (73.7% y/y) after having fallen 29.4% w/w in the previous week and 8.4% w/w in the week ended March 13. Purchase applications remained weak (-10.8% w/w and -23.5% y/y) as the first signs of the devastating hit to employment from the spreading coronavirus likely caused potential homebuyers to pull back. In contrast, with mortgage interest rates falling to series lows for some rates, applications for refinancing jumped up 25.5% w/w (167.7% y/y) after having declined 40.7% in the previous two weeks. The refinance share of mortgage activity increased to 75.9% of total applications from 69.3% the previous week. The adjustable-rate mortgage share of activity decreased to 3.2% of total applications.
</p><p align="justify">
The effective interest rate on a 15-year fixed-rate mortgage fell markedly to 3.12% in the week ended March 27 from 3.38% the previous week. The effective interest rate on the 30-year fixed-rate mortgage slumped to 3.57%, the lowest rate in the history of the series, from 3.93%. In contrast, the effective rate on a 30-year Jumbo mortgage only edged down 2 basis points to 3.93% after having risen 31 basis points in the previous two weeks. The rate on the 5-year adjustable rate mortgage fell to 3.34% from 3.48%.
</p><p align="justify">
The average mortgage loan size fell to $323,700 in the week ended March 27 from $337,000 the previous week. The average loan size of refinancings declined to $322,800 from $337,500. The average loan size for purchases fell to $326,500 from $336,000.
</p><p align="justify">
Applications for fixed-rate loans were up 85.8% y/y, while applications for adjustable rate loans fell 41.9% y/y.
</p><p align="justify">
The survey covers over 75% of all U.S. retail residential mortgage applications and
has been conducted weekly since 1990. Respondents include mortgage bankers, commercial
banks and thrifts. The base period and value for each index is March 16, 1990=100.
The figures for weekly mortgage applications and interest rates are available in
Haver's SURVEYW database.</p>

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	<colgroup><col><col><col><col><col><col><col><col></colgroup>

  <thead>
    <tr>
      <th class="firstcol" scope="col" >MBA Mortgage Applications (%,
        SA)</th>
      <th>03/27/20</th>
      <th>03/20/20</th>
      <th>03/13/20</th>
      <th>Y/Y</th>
      <th>2019</th>
      <th>2018</th>
      <th>2017</th>
    </tr>
  </thead>
  <tbody>
    <tr class="odd">
      <td class="firstcol" >Total Market Index</td>
<td  >15.3</td>
<td  >-29.4</td>
<td  >-8.4</td>
<td  >73.7</td>
<td  >32.4</td>
<td  >-10.4</td>
<td  >-17.8</td>
    </tr>
    <tr>
      <td class="firstcol" >&nbsp;&nbsp;Purchase</td>
<td  >-10.8</td>
<td  >-14.6</td>
<td  >-0.9</td>
<td  >-23.5</td>
<td  >6.6</td>
<td  >2.1</td>
<td  >5.6</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" >&nbsp;&nbsp;Refinancing</td>
<td  >25.5</td>
<td  >-33.8</td>
<td  >-10.4</td>
<td  >167.7</td>
<td  >71.1</td>
<td  >-24.3</td>
<td  >-34.0</td>
    </tr>
    <tr>
      <td class="firstcol" >15-Year Effective Mortgage Interest Rate
        (%)</td>
<td  >3.12</td>
<td  >3.38</td>
<td  >3.20</td>
<td  >3.88</td>
<td  >3.71</td>
<td  >4.35</td>
<td  >3.59</td>
    </tr>
    <tr>
      <td class="firstcol" >30-Year Effective Mortgage Interest Rate
        (%)</td>
<td  >3.57</td>
<td  >3.93</td>
<td  >3.85</td>
<td  >4.49</td>
<td  >4.34</td>
<td  >4.94</td>
<td  >4.32</td>
   </tr>
              </tbody>
            </table>
            </span>
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Led by a sharp increase in refinancing applications, the Mortgage Bankers Association's Mortgage Loan Application Index rebounded in the week ended March 27, rising 15.3% w/w (73.7% y/y) after having fallen 29.4% w/w in the previous [...]

U.S. Mortgage Applications Rebound, Led by Refinancing

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<title>Texas Factory Activity Improvement Led by Production by Tom Moeller&nbsp;
March 30</title>
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<br>
<span id="byline">April 1, 2020</span>
<p align="justify"><b>• Labor market weakness gets underway in March.</b></p>
<p align="justify"><b>• Service-sector employment declines, particularly in
small businesses</b>.</p>
<p align="justify"><span id="articletext">The ADP National Employment Report
indicated that nonfarm private payrolls during March fell 27,000 (+1.3% y/y)
following a 179,000 February increase, revised from 183,000. ADP conducts its
monthly survey during the week that includes the 12th of the month, so it
preceded the stronger layoff activity in recent weeks. The latest figure
compared to a 200,000 decline expected in the Action Economics Forecast Survey. 
<p align="justify">Small payrolls declined 90,000 (-0.3% y/y) following a fairly
steady 21,000 February gain. Medium-sized payrolls rose 7,000 (1.1% y/y) after a
27,000 rise, which was half the January rise. Large-sized payrolls improved 56,000
(2.2% y/y) after a fairly steady steady131,000 rise.</p>
<p align="justify">Within industry sectors, employment at goods-producing firms
eased 9,000 (+0.2% y/y) last month after a 12,000 rise, which also was half the
upwardly revised January increase. Construction sector payrolls fell 16,000 last
month (+1.3% y/y), the first decline in nine months. Factory sector employment
improved 6,000 (-0.3% y/y), the first increase in four months. Employment in the
natural resource &amp; mining sector edged 1,000 higher (-2.0% y/y), but was
down versus March 2019.</p>
<p align="justify">Employment growth in the private service sector declined 18,000
(+1.5% y/y) after a 167,000 February strengthening. Education &amp; health
services jobs improved a steady 48,000 (2.4% y/y). Financial activities payrolls
held steady (1.3% y/y). These figures were offset by a collapse of 37,000 (+0.7%
y/y) in trade, transportation &amp; utilities, the largest decline in ten years.
Leisure &amp; hospitality employment fell 11,000 (+2.1% y/y) after two monthly
increases of roughly 45,000. Employment in professional &amp; business services
weakened 3,000 (+1.8% y/y). Information sector payrolls declined 7,000 (-0.5%
y/y).</p>
<p align="justify">The Automatic Data Processing Research Institute survey is
based on ADP's business payroll transaction system covering 411,000 companies
and nearly 24 million employees. The data are processed by Moody's Analytics
Inc., then calibrated and aligned with the BLS establishment survey data. The
ADP data cover private sector employment only.</p>
<p align="justify">The ADP National Employment Report data can be found in
Haver's <b>USECON</b> database. Historical figures date back to 2001 for private
employment and the industry breakdown, and 2005 for the business size breakout.
The expectation figure is available in Haver's <b>AS1REPNA</b> database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="1068">ADP/Moody's National
        Employment Report</th>
      <th scope="col" width="114">Mar</th>
      <th scope="col" width="114">Feb</th>
      <th scope="col" width="114">Jan</th>
      <th scope="col" width="114">Mar Y/Y</th>
      <th scope="col" width="114">2019</th>
      <th scope="col" width="114">2018</th>
      <th scope="col" width="115">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td class="firstcol" width="1068">Nonfarm Private Payroll Employment (m/m
        chg, 000s)</td>
      <td align="center" width="114">-27</td>
      <td align="center" width="114">179</td>
      <td align="center" width="114">205</td>
      <td align="center" width="114">1.3%</td>
      <td align="center" width="114">1.5%</td>
      <td align="center" width="114">1.8%</td>
      <td align="center" width="115">1.7%</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">&nbsp;Small Payroll (1-49)</td>
      <td align="center" width="114">-90</td>
      <td align="center" width="114">21</td>
      <td align="center" width="114">22</td>
      <td align="center" width="114">-0.2</td>
      <td align="center" width="114">0.2</td>
      <td align="center" width="114">0.6</td>
      <td align="center" width="115">1.1</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp;Medium Payroll (50-499)</td>
      <td align="center" width="114">7</td>
      <td align="center" width="114">27</td>
      <td align="center" width="114">54</td>
      <td align="center" width="114">1.1</td>
      <td align="center" width="114">2.0</td>
      <td align="center" width="114">2.0</td>
      <td align="center" width="115">1.9</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">&nbsp;Large Payroll (&gt;500)</td>
      <td align="center" width="114">56</td>
      <td align="center" width="114">131</td>
      <td align="center" width="114">130</td>
      <td align="center" width="114">2.2</td>
      <td align="center" width="114">1.9</td>
      <td align="center" width="114">2.3</td>
      <td align="center" width="115">2.0</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">Goods-Producing</td>
      <td align="center" width="114">-9</td>
      <td align="center" width="114">12</td>
      <td align="center" width="114">24</td>
      <td align="center" width="114">0.2</td>
      <td align="center" width="114">1.6</td>
      <td align="center" width="114">2.9</td>
      <td align="center" width="115">1.8</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp; Construction</td>
      <td align="center" width="114">-16</td>
      <td align="center" width="114">19</td>
      <td align="center" width="114">33</td>
      <td align="center" width="114">1.3</td>
      <td align="center" width="114">2.7</td>
      <td align="center" width="114">4.1</td>
      <td align="center" width="115">3.7</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp; Manufacturing</td>
      <td align="center" width="114">6</td>
      <td align="center" width="114">-4</td>
      <td align="center" width="114">-5</td>
      <td align="center" width="114">-0.3</td>
      <td align="center" width="114">1.0</td>
      <td align="center" width="114">1.9</td>
      <td align="center" width="115">0.8</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">Service-Producing</td>
      <td align="center" width="114">-18</td>
      <td align="center" width="114">167</td>
      <td align="center" width="114">181</td>
      <td align="center" width="114">1.5</td>
      <td align="center" width="114">1.5</td>
      <td align="center" width="114">1.6</td>
      <td align="center" width="115">1.7</td>
    </tr>
  </tbody>
</table>
</span>
</p><p>&nbsp;</p>
<span id="articletitle">ISM Manufacturing Index Weakens Slightly; Prices Decline</span><br>
<span id="byline">by <a href="http://www.haver.com/comment/Moeller.html">Tom
Moeller</a>&nbsp;&nbsp;April 1, 2020</span><span id="articletext">
<p align="justify"><b>• Production &amp; new orders weakness offset by slower
product delivery speeds.</b></p>
<p align="justify"><b>• Pricing power eases.</b></p>
<p align="justify">Activity in the factory slowed last month. The Institute for
Supply Management (ISM) reported that its composite index of manufacturing
sector activity for February declined to 50.1 after rising to 50.9 in January.
These figures nevertheless remained above the dividing line between expansion
and contraction in the manufacturing sector. A reading of 50.5 had been expected
in the Action Economics Forecast Survey. During the last 15 years, there has
been a 68% correlation between the composite index and the quarterly change in
real GDP.</p>
<p align="justify">The easing in the composite index reflected declines in the
new orders and production components, although at 50.3 the production series
remained significantly improved from 44.8 in December. The jump in the supplier
deliveries reading to 57.3 from 52.9 suggested the slowest speed of product
deliveries since November 2018. The inventories component fell to the low end of
its recent range.</p>
<p align="justify">The slight rise in the employment figure to 46.9,
nevertheless, continued to reflect a decline in factory sector payrolls. Twelve
percent (NSA) of factory sector payrolls increased while 19% declined. During
the last 15 years, there has been an 80% correlation between the index and the
m/m change in factory sector payrolls.</p>
<p align="justify">The prices paid series fell sharply to 45.9, its lowest level
since October. Seventeen percent (NSA) of survey respondents reported higher
prices while 25% reported declines.</p>
<p align="justify">Amongst other series in the survey, the imports figure
plummeted to an expansion low. The export reading slipped to 51.2 (NSA), but
remained up from 47.3 in December. The order backlog index surged to 50.3, its
highest level since last March.</p>
<p align="justify">The ISM figures are diffusion indexes where a reading above
50 indicates expansion. The figures from the Institute for Supply Management can
be found in Haver's <b>USECON</b> database; further detail is found in the <b>SURVEYS</b>
database. The expectations number is available in Haver's <b>AS1REPNA</b>
database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="724">ISM Mfg (SA)</th>
      <th width="163">Mar</th>
      <th width="163">Feb</th>
      <th width="163">Jan</th>
      <th width="163">Mar'19</th>
      <th width="163">2019</th>
      <th width="164">2018</th>
      <th width="164">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr class="odd">
      <td class="firstcol" width="724">Headline Index</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">50.1</td>
      <td align="center" width="163">50.9</td>
      <td align="center" width="163">54.1</td>
      <td align="center" width="163">51.2</td>
      <td align="center" width="164">58.9</td>
      <td align="center" width="164">57.4</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;New Orders</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">49.8</td>
      <td align="center" width="163">52.0</td>
      <td align="center" width="163">54.9</td>
      <td align="center" width="163">51.1</td>
      <td align="center" width="164">61.6</td>
      <td align="center" width="164">62.1</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">&nbsp;Production</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">50.3</td>
      <td align="center" width="163">54.3</td>
      <td align="center" width="163">55.4</td>
      <td align="center" width="163">51.2</td>
      <td align="center" width="164">60.9</td>
      <td align="center" width="164">60.9</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;Employment</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">46.9</td>
      <td align="center" width="163">46.6</td>
      <td align="center" width="163">53.2</td>
      <td align="center" width="163">50.9</td>
      <td align="center" width="164">56.9</td>
      <td align="center" width="164">56.8</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">&nbsp;Supplier Deliveries</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">57.3</td>
      <td align="center" width="163">52.9</td>
      <td align="center" width="163">55.3</td>
      <td align="center" width="163">52.9</td>
      <td align="center" width="164">62.0</td>
      <td align="center" width="164">56.8</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;Inventories</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">46.5</td>
      <td align="center" width="163">48.8</td>
      <td align="center" width="163">51.6</td>
      <td align="center" width="163">49.8</td>
      <td align="center" width="164">52.9</td>
      <td align="center" width="164">50.4</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">Prices Paid Index (NSA)</td>
      <td align="center" width="163"></td>
      <td align="center" width="163">45.9</td>
      <td align="center" width="163">53.3</td>
      <td align="center" width="163">49.4</td>
      <td align="center" width="163">49.1</td>
      <td align="center" width="164">71.7</td>
      <td align="center" width="164">65.0</td>
    </tr>
  </tbody>
</table>
</span>
<p>&nbsp;</p>
<span id="articletitle">U.S. Light Vehicle Sales Hold Steady in February</span><br>
<span id="byline">by <a href="http://www.haver.com/comment/Moeller.html">Tom
Moeller</a>&nbsp;&nbsp;April 1, 2020</span><span id="articletext">
<p align="justify">The Autodata Corporation reported that sales of light
vehicles during February eased 0.2% (+2.0% y/y) to 17.04 million (SAAR) from
17.07 million in January, revised from 17.05 million. During the last three
months, sales averaged 17.00 million units. Sales have been easing since the
2016 sales peak of 17.55 million units.</p>
<p align="justify">Sales of light trucks were off 0.1% (+6.6% y/y) at 12.56
million units. Purchases of domestically-made light trucks fell 0.8% (+7.2% y/y)
to 9.92 million units following January's 4.4% rise. Sales of imported light
trucks improved 2.7% (4.3% y/y) to 2.64 million units after January's 0.4%
improvement.</p>
<p align="justify">Trucks' share of the U.S. light vehicle market reached a
record 73.7%, up from a low of 48.8% during all of 2012.</p>
<p align="justify">Auto sales weakened 0.2% (-8.9% y/y) to 4.48 million units.
That remained below a peak level of 7.71 million unit sales during all of 2014.
Purchases of domestically-produced cars fell 3.3% (-12.7% y/y) to 3.22 million
units and added to January's decline. Sales of imported cars strengthened 7.7%
(2.4% y/y) to 1.26 million units after rising 0.9% in January.</p>
<p align="justify">Imports' share of the U.S. vehicle market rose last month to
22.9% and has been moving sideways for two years. Imports' share of the
passenger car market jumped to 28.1%, its highest level in four months. Imports
share of the light truck market edged higher to 21.0% and remained up from the
12.0% low in January 2015.</p>
<p align="justify">U.S. vehicle sales figures can be found in Haver's <b>USECON</b>
database. Additional detail by manufacturer is in the <b>INDUSTRY</b> database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="974">Light Weight Vehicle Sales
        (SAAR, Million Units)</th>
      <th width="127">Mar</th>
      <th width="127">Feb</th>
      <th width="127">Jan</th>
      <th width="128">Mar Y/Y %</th>
      <th width="128">2019</th>
      <th width="128">2018</th>
      <th width="128">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr class="odd">
      <td class="firstcol" width="974">Total</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">17.04</td>
      <td align="center" width="127">17.07</td>
      <td align="center" width="128">2.0</td>
      <td align="center" width="128">16.99</td>
      <td align="center" width="128">17.27</td>
      <td align="center" width="128">17.23</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;Autos</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">4.48</td>
      <td align="center" width="127">4.49</td>
      <td align="center" width="128">-8.9</td>
      <td align="center" width="128">4.80</td>
      <td align="center" width="128">5.36</td>
      <td align="center" width="128">6.16</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;&nbsp;Domestic</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">3.22</td>
      <td align="center" width="127">3.33</td>
      <td align="center" width="128">-12.7</td>
      <td align="center" width="128">3.52</td>
      <td align="center" width="128">4.00</td>
      <td align="center" width="128">4.58</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;&nbsp;Imported</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">1.26</td>
      <td align="center" width="127">1.17</td>
      <td align="center" width="128">2.4</td>
      <td align="center" width="128">1.28</td>
      <td align="center" width="128">1.36</td>
      <td align="center" width="128">1.59</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;Light Trucks</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">12.56</td>
      <td align="center" width="127">12.57</td>
      <td align="center" width="128">6.6</td>
      <td align="center" width="128">12.18</td>
      <td align="center" width="128">11.92</td>
      <td align="center" width="128">11.07</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;&nbsp;Domestic</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">9.92</td>
      <td align="center" width="127">10.00</td>
      <td align="center" width="128">7.2</td>
      <td align="center" width="128">9.65</td>
      <td align="center" width="128">9.44</td>
      <td align="center" width="128">9.00</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;&nbsp;Imported</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">2.64</td>
      <td align="center" width="127">2.57</td>
      <td align="center" width="128">4.3</td>
      <td align="center" width="128">2.53</td>
      <td align="center" width="128">2.48</td>
      <td align="center" width="128">2.07</td>
    </tr>
  </tbody>
</table>
</span>




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• Labor market weakness gets underway in March. • Service-sector employment declines, particularly in small businesses

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<title>Texas Factory Activity Improvement Led by Production by Tom Moeller&nbsp;
March 30</title>
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<br>
<span id="byline">April 1, 2020</span>
<p align="justify"><b>• Labor market weakness gets underway in March.</b></p>
<p align="justify"><b>• Service-sector employment declines, particularly in
small businesses</b>.</p>
<p align="justify"><span id="articletext">The ADP National Employment Report
indicated that nonfarm private payrolls during March fell 27,000 (+1.3% y/y)
following a 179,000 February increase, revised from 183,000. ADP conducts its
monthly survey during the week that includes the 12th of the month, so it
preceded the stronger layoff activity in recent weeks. The latest figure
compared to a 200,000 decline expected in the Action Economics Forecast Survey. 
<p align="justify">Small payrolls declined 90,000 (-0.3% y/y) following a fairly
steady 21,000 February gain. Medium-sized payrolls rose 7,000 (1.1% y/y) after a
27,000 rise, which was half the January rise. Large-sized payrolls improved 56,000
(2.2% y/y) after a fairly steady steady131,000 rise.</p>
<p align="justify">Within industry sectors, employment at goods-producing firms
eased 9,000 (+0.2% y/y) last month after a 12,000 rise, which also was half the
upwardly revised January increase. Construction sector payrolls fell 16,000 last
month (+1.3% y/y), the first decline in nine months. Factory sector employment
improved 6,000 (-0.3% y/y), the first increase in four months. Employment in the
natural resource &amp; mining sector edged 1,000 higher (-2.0% y/y), but was
down versus March 2019.</p>
<p align="justify">Employment growth in the private service sector declined 18,000
(+1.5% y/y) after a 167,000 February strengthening. Education &amp; health
services jobs improved a steady 48,000 (2.4% y/y). Financial activities payrolls
held steady (1.3% y/y). These figures were offset by a collapse of 37,000 (+0.7%
y/y) in trade, transportation &amp; utilities, the largest decline in ten years.
Leisure &amp; hospitality employment fell 11,000 (+2.1% y/y) after two monthly
increases of roughly 45,000. Employment in professional &amp; business services
weakened 3,000 (+1.8% y/y). Information sector payrolls declined 7,000 (-0.5%
y/y).</p>
<p align="justify">The Automatic Data Processing Research Institute survey is
based on ADP's business payroll transaction system covering 411,000 companies
and nearly 24 million employees. The data are processed by Moody's Analytics
Inc., then calibrated and aligned with the BLS establishment survey data. The
ADP data cover private sector employment only.</p>
<p align="justify">The ADP National Employment Report data can be found in
Haver's <b>USECON</b> database. Historical figures date back to 2001 for private
employment and the industry breakdown, and 2005 for the business size breakout.
The expectation figure is available in Haver's <b>AS1REPNA</b> database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="1068">ADP/Moody's National
        Employment Report</th>
      <th scope="col" width="114">Mar</th>
      <th scope="col" width="114">Feb</th>
      <th scope="col" width="114">Jan</th>
      <th scope="col" width="114">Mar Y/Y</th>
      <th scope="col" width="114">2019</th>
      <th scope="col" width="114">2018</th>
      <th scope="col" width="115">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td class="firstcol" width="1068">Nonfarm Private Payroll Employment (m/m
        chg, 000s)</td>
      <td align="center" width="114">-27</td>
      <td align="center" width="114">179</td>
      <td align="center" width="114">205</td>
      <td align="center" width="114">1.3%</td>
      <td align="center" width="114">1.5%</td>
      <td align="center" width="114">1.8%</td>
      <td align="center" width="115">1.7%</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">&nbsp;Small Payroll (1-49)</td>
      <td align="center" width="114">-90</td>
      <td align="center" width="114">21</td>
      <td align="center" width="114">22</td>
      <td align="center" width="114">-0.2</td>
      <td align="center" width="114">0.2</td>
      <td align="center" width="114">0.6</td>
      <td align="center" width="115">1.1</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp;Medium Payroll (50-499)</td>
      <td align="center" width="114">7</td>
      <td align="center" width="114">27</td>
      <td align="center" width="114">54</td>
      <td align="center" width="114">1.1</td>
      <td align="center" width="114">2.0</td>
      <td align="center" width="114">2.0</td>
      <td align="center" width="115">1.9</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">&nbsp;Large Payroll (&gt;500)</td>
      <td align="center" width="114">56</td>
      <td align="center" width="114">131</td>
      <td align="center" width="114">130</td>
      <td align="center" width="114">2.2</td>
      <td align="center" width="114">1.9</td>
      <td align="center" width="114">2.3</td>
      <td align="center" width="115">2.0</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">Goods-Producing</td>
      <td align="center" width="114">-9</td>
      <td align="center" width="114">12</td>
      <td align="center" width="114">24</td>
      <td align="center" width="114">0.2</td>
      <td align="center" width="114">1.6</td>
      <td align="center" width="114">2.9</td>
      <td align="center" width="115">1.8</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp; Construction</td>
      <td align="center" width="114">-16</td>
      <td align="center" width="114">19</td>
      <td align="center" width="114">33</td>
      <td align="center" width="114">1.3</td>
      <td align="center" width="114">2.7</td>
      <td align="center" width="114">4.1</td>
      <td align="center" width="115">3.7</td>
    </tr>
    <tr>
      <td class="firstcol" width="1068">&nbsp; Manufacturing</td>
      <td align="center" width="114">6</td>
      <td align="center" width="114">-4</td>
      <td align="center" width="114">-5</td>
      <td align="center" width="114">-0.3</td>
      <td align="center" width="114">1.0</td>
      <td align="center" width="114">1.9</td>
      <td align="center" width="115">0.8</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="1068">Service-Producing</td>
      <td align="center" width="114">-18</td>
      <td align="center" width="114">167</td>
      <td align="center" width="114">181</td>
      <td align="center" width="114">1.5</td>
      <td align="center" width="114">1.5</td>
      <td align="center" width="114">1.6</td>
      <td align="center" width="115">1.7</td>
    </tr>
  </tbody>
</table>
</span>
</p><p>&nbsp;</p>
<span id="articletitle">ISM Manufacturing Index Weakens in March</span><br>
<span id="byline">by <a href="http://www.haver.com/comment/Moeller.html">Tom
Moeller</a>&nbsp;&nbsp;April 1, 2020</span><span id="articletext">
<p align="justify"><b>• Broad-based component declines led by fewer new orders.</b></p>
<p align="justify"><b>• Pricing power falls sharply.</b></p>
<p align="justify"><b>• Most readings move below the break-even level of 50.</b></p>
<p align="justify">Activity in the factory sector weakened just slightly last
month despite the onset of the coronavirus. The Institute for Supply Management
(ISM) reported that its composite index of manufacturing sector activity for
March fell to 49.1 after easing to 50.1 in February. A reading of 50.5 had been
expected in the Action Economics Forecast Survey. During the last 15 years,
there has been a 68% correlation between the composite index and the quarterly
change in real GDP.</p>
<p align="justify">The new orders index fell to 42.2, its lowest level since
March 2009. The production measure also fell sharply to 47.7, down versus the
cycle high of 64.2 in January 2018. </p>
<p align="justify">Also declining to its lowest point since May 2009 was the
employment measure to 43.8. Just nine percent (NSA) of respondents reported
higher payrolls while 21% reported a decline. During the last 15 years, there
has been 80% correlation between the employment index and the m/m change in
factory sector payrolls.</p>
<p align="justify">The supplier delivery measure surged to 65.0 from 57.3,
indicating the slowest product delivery speeds since June 2018. Holding fairly
steady m/m at 46.9 was the inventory index, but that was down from 53.9 in
August 2018.</p>
<p align="justify">The prices paid index declined sharply to 37.4 (NSA), its
lowest point since January 2016. Only 12% of respondents reported higher prices
while 37% reported a decline.&nbsp; </p>
<p align="justify">Other series in the ISM report indicated weakness. The export
order measure fell to 46.6, the lowest point in six months and down from a high
of 62.8 in February 2018. The import series fell to an expansion low of 42.1 and
the order backlog measure fell to 45.9 from 50.4 twelve months
earlier.&nbsp;&nbsp; </p>
<p align="justify">The ISM figures are diffusion indexes where a reading above
50 indicates expansion. The figures from the Institute for Supply Management can
be found in Haver's <b>USECON</b> database; further detail is found in the <b>SURVEYS</b>
database. The expectations number is available in Haver's <b>AS1REPNA</b>
database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="724">ISM Mfg (SA)</th>
      <th width="163">Mar</th>
      <th width="163">Feb</th>
      <th width="163">Jan</th>
      <th width="163">Mar'19</th>
      <th width="163">2019</th>
      <th width="164">2018</th>
      <th width="164">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr class="odd">
      <td class="firstcol" width="724">Composite Index</td>
      <td align="center" width="163">49.1</td>
      <td align="center" width="163">50.1</td>
      <td align="center" width="163">50.9</td>
      <td align="center" width="163">54.6</td>
      <td align="center" width="163">51.2</td>
      <td align="center" width="164">58.9</td>
      <td align="center" width="164">57.4</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;New Orders</td>
      <td align="center" width="163">42.2</td>
      <td align="center" width="163">49.8</td>
      <td align="center" width="163">52.0</td>
      <td align="center" width="163">55.5</td>
      <td align="center" width="163">51.1</td>
      <td align="center" width="164">61.6</td>
      <td align="center" width="164">62.1</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">&nbsp;Production</td>
      <td align="center" width="163">47.7</td>
      <td align="center" width="163">50.3</td>
      <td align="center" width="163">54.3</td>
      <td align="center" width="163">55.1</td>
      <td align="center" width="163">51.2</td>
      <td align="center" width="164">60.9</td>
      <td align="center" width="164">60.9</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;Employment</td>
      <td align="center" width="163">43.8</td>
      <td align="center" width="163">46.9</td>
      <td align="center" width="163">&nbsp;46.6</td>
      <td align="center" width="163">57.1</td>
      <td align="center" width="163">50.9</td>
      <td align="center" width="164">56.9</td>
      <td align="center" width="164">56.8</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">&nbsp;Supplier Deliveries</td>
      <td align="center" width="163">65.0</td>
      <td align="center" width="163">57.3</td>
      <td align="center" width="163">52.9</td>
      <td align="center" width="163">54.9</td>
      <td align="center" width="163">52.9</td>
      <td align="center" width="164">62.0</td>
      <td align="center" width="164">56.8</td>
    </tr>
    <tr>
      <td class="firstcol" width="724">&nbsp;Inventories</td>
      <td align="center" width="163">46.9</td>
      <td align="center" width="163">46.5</td>
      <td align="center" width="163">48.8</td>
      <td align="center" width="163">50.6</td>
      <td align="center" width="163">49.8</td>
      <td align="center" width="164">52.9</td>
      <td align="center" width="164">50.4</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="724">Prices Paid Index (NSA)</td>
      <td align="center" width="163">37.4</td>
      <td align="center" width="163">45.9</td>
      <td align="center" width="163">53.3</td>
      <td align="center" width="163">54.3</td>
      <td align="center" width="163">49.1</td>
      <td align="center" width="164">71.7</td>
      <td align="center" width="164">65.0</td>
    </tr>
  </tbody>
</table>
</span>
<p>&nbsp;</p>
<span id="articletitle">U.S. Light Vehicle Sales Hold Steady in February</span><br>
<span id="byline">by <a href="http://www.haver.com/comment/Moeller.html">Tom
Moeller</a>&nbsp;&nbsp;April 1, 2020</span><span id="articletext">
<p align="justify">The Autodata Corporation reported that sales of light
vehicles during February eased 0.2% (+2.0% y/y) to 17.04 million (SAAR) from
17.07 million in January, revised from 17.05 million. During the last three
months, sales averaged 17.00 million units. Sales have been easing since the
2016 sales peak of 17.55 million units.</p>
<p align="justify">Sales of light trucks were off 0.1% (+6.6% y/y) at 12.56
million units. Purchases of domestically-made light trucks fell 0.8% (+7.2% y/y)
to 9.92 million units following January's 4.4% rise. Sales of imported light
trucks improved 2.7% (4.3% y/y) to 2.64 million units after January's 0.4%
improvement.</p>
<p align="justify">Trucks' share of the U.S. light vehicle market reached a
record 73.7%, up from a low of 48.8% during all of 2012.</p>
<p align="justify">Auto sales weakened 0.2% (-8.9% y/y) to 4.48 million units.
That remained below a peak level of 7.71 million unit sales during all of 2014.
Purchases of domestically-produced cars fell 3.3% (-12.7% y/y) to 3.22 million
units and added to January's decline. Sales of imported cars strengthened 7.7%
(2.4% y/y) to 1.26 million units after rising 0.9% in January.</p>
<p align="justify">Imports' share of the U.S. vehicle market rose last month to
22.9% and has been moving sideways for two years. Imports' share of the
passenger car market jumped to 28.1%, its highest level in four months. Imports
share of the light truck market edged higher to 21.0% and remained up from the
12.0% low in January 2015.</p>
<p align="justify">U.S. vehicle sales figures can be found in Haver's <b>USECON</b>
database. Additional detail by manufacturer is in the <b>INDUSTRY</b> database.</p>
<table width="1871" class="centered" border="0" cellSpacing="0">
  <thead>
    <tr>
      <th class="firstcol" scope="col" width="974">Light Weight Vehicle Sales
        (SAAR, Million Units)</th>
      <th width="127">Mar</th>
      <th width="127">Feb</th>
      <th width="127">Jan</th>
      <th width="128">Mar Y/Y %</th>
      <th width="128">2019</th>
      <th width="128">2018</th>
      <th width="128">2017</th>
    </tr>
  </thead>
  <tbody>
    <tr class="odd">
      <td class="firstcol" width="974">Total</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">17.04</td>
      <td align="center" width="127">17.07</td>
      <td align="center" width="128">2.0</td>
      <td align="center" width="128">16.99</td>
      <td align="center" width="128">17.27</td>
      <td align="center" width="128">17.23</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;Autos</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">4.48</td>
      <td align="center" width="127">4.49</td>
      <td align="center" width="128">-8.9</td>
      <td align="center" width="128">4.80</td>
      <td align="center" width="128">5.36</td>
      <td align="center" width="128">6.16</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;&nbsp;Domestic</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">3.22</td>
      <td align="center" width="127">3.33</td>
      <td align="center" width="128">-12.7</td>
      <td align="center" width="128">3.52</td>
      <td align="center" width="128">4.00</td>
      <td align="center" width="128">4.58</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;&nbsp;Imported</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">1.26</td>
      <td align="center" width="127">1.17</td>
      <td align="center" width="128">2.4</td>
      <td align="center" width="128">1.28</td>
      <td align="center" width="128">1.36</td>
      <td align="center" width="128">1.59</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;Light Trucks</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">12.56</td>
      <td align="center" width="127">12.57</td>
      <td align="center" width="128">6.6</td>
      <td align="center" width="128">12.18</td>
      <td align="center" width="128">11.92</td>
      <td align="center" width="128">11.07</td>
    </tr>
    <tr>
      <td class="firstcol" width="974">&nbsp;&nbsp;Domestic</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">9.92</td>
      <td align="center" width="127">10.00</td>
      <td align="center" width="128">7.2</td>
      <td align="center" width="128">9.65</td>
      <td align="center" width="128">9.44</td>
      <td align="center" width="128">9.00</td>
    </tr>
    <tr class="odd">
      <td class="firstcol" width="974">&nbsp;&nbsp;Imported</td>
      <td align="center" width="127"></td>
      <td align="center" width="127">2.64</td>
      <td align="center" width="127">2.57</td>
      <td align="center" width="128">4.3</td>
      <td align="center" width="128">2.53</td>
      <td align="center" width="128">2.48</td>
      <td align="center" width="128">2.07</td>
    </tr>
  </tbody>
</table>
</span>




</html>

Even with expected tariff-induced increases in inflation, BCFF forecasters look for a more aggressive round of monetary easing

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

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Nonfarm labor productivity fell 0.8% (SAAR) during Q1’25 after increasing 1.7% in Q4’24, revised from 1.5%. A 0.6% decline had been expected in the Action Economics Forecast Survey. It was the first productivity decline since Q2’22. The y/y increase during Q1 fell to 1.4% from 2.1% in Q4. It was below a 3.3% high in the first quarter of last year. Productivity fell as real value-added output dropped 0.3% last quarter (+2.2% y/y) after increasing 2.5% in Q4, and hours worked lengthened 0.6% (0.8% y/y) following a 0.8% gain.

Compensation per hour increased 4.8% last quarter following a 3.7% Q4 rise. Despite the strength of these last two increases, y/y growth decelerated to 2.7% from a 6.8% high one year earlier. Nevertheless, the productivity decline raised unit labor costs by 5.7% (1.3% y/y) in Q1 versus expectations for a 5.2% increase. It followed a 2.0% gain during Q4 and was the strongest quarterly increase in a year.

Factory sector productivity surged 4.5% (1.5% y/y) during Q1’25 following three consecutive increases of roughly 0.5%. This strength was accompanied by a 6.2% rise (2.2% y/y) in hourly compensation which came after two consecutive increases of approximately 4.1%. The strength in productivity lowered the rise in unit labor costs to 1.6% from 3.8% in Q4. The y/y gain fell to 0.7% from 2.0% in Q4 and stood below the 6.2% y/y increase in Q1’24.

The productivity and labor cost data are available in Haver’s **USECON** database. The Action Economics expectations figures are in the **AS1REPNA** database.

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- Productivity declines with lower output.
- Compensation surge exacerbates labor market stress.
- Factory sector productivity surge lessens cost pressure.

U.S. Productivity Declines in Q1’25; Unit Labor Costs Surge

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The National Association of Realtors' Fixed Rate Mortgage Housing Affordability Index (HAI) rose 0.6% (3.2% y/y) in March to 103.2 after rising 0.9% to 102.6 in February and rising 0.8% in January to 101.7. The level of home affordability has risen 14.8% from its low of 89.9 in October 2023. It remains 42.4% below the high of 179.2 in April 2020.

The rise in affordability in March occurred as the median price of an existing single-family home rose 1.8% (2.9% y/y) to $408,000 which was offset by a decline in mortgage rates to 6.73% from 6.92% in February. The price compared to the record $432,900 in June 2024. The decline in mortgage rates compared to a recent low of 6.26% in September of last year and a 7.70% high during October of 2023. It remained well above a December 2020 low of 2.73%. These changes lowered the principal & interest payment by 0.2% (+1.1% y/y) to $2,113 per month. That was well above the most recent low of $984 in February 2020. Monthly mortgage payments averaged a lessened 24.2% of income during March. They remained up from a low of 14.0% of income in April 2020.

The rise in housing costs in March was accompanied by improvement in median family income. It increased 0.4% (4.4% y/y) to a record $104,705 after rising 0.4% in February and 0.7% in January.

Housing affordability improved m/m across the country in March. The index edged 0.1% higher (2.8% y/y) to 134.5 in the Midwest. It remains the most affordable region of the country. In the South, the index 0.9% (5.4% y/y) to 106.6 and the affordability index in the Northeast increased 2.1% (-2.6% y/y) to 95.7. In the West, where homes are the least affordable, the index rose 0.8% (3.3% y/y) to 71.8 in March.

The Housing Affordability Index (HAI) equals 100 when a median-income borrower qualifies for an 80% mortgage on a median-priced existing single-family home. The HAI had exceeded 100 in each month since July 1990 and reached its all-time high of 213.3 in January 2013; since then, it fell below 100 for the first time in June 2022.

Data on Housing Affordability can be found in Haver’s **REALTOR** database. Median home sales prices are also available in **USECON**. Higher frequency interest rate data are found in **SURVEYS**, **WEEKLY**, and **DAILY**.

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- Home prices rise but mortgage rates decline.
- Median income improves.
- Affordability increases across the country.

U.S. Housing Affordability Improves Slightly in March

Carol Stone, CBE

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Initial claims for unemployment insurance were 228,000 seasonally adjusted in the week ended May 3, down from 241,000 in the previous week, which was unrevised. For the latest week, the Action Economics Forecast Survey had expected a smaller decline to 233,000.

In the week ended April 26, the total number of unemployment insurance beneficiaries – also known as “continuing claims” – was 1.879 million, down from 1.908 million in the April 19 week.

The insured unemployment rate, that is, the number of beneficiaries as a percentage of covered employment, returned to its longstanding rate of 1.2% in the April 26 week; this rate has held that amount since continuously since the week of January 6, 2024, except for the prior week’s 1.3%.

As we do highlight in every week’s discussion, economic conditions vary widely across individual states and territories. In the week ended April 19, the highest unemployment rates were in New Jersey and Rhode Island (both at 2.48%), California (2.26%), Washington (2.14%) and New York (1.85%). The lowest were in Florida (0.36%), South Dakota (0.37%), Alabama (0.41%), Virginia (0.45%) and Nebraska (0.47%). Rates in other notable states include Illinois (1.78%), Pennsylvania (1.53%) and Texas (1.14%). 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. The expectations figure is from the Action Economics Forecast Survey in the **AS1REPNA** database.

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- Continued claims for unemployment insurance decreased 29, 000 in the week ended April 26.
- Insured unemployment rate returns to longstanding 1.2%.
- Across the states, the insured unemployment rate ranges from 0.36% to 2.48%.

U.S. Initial Unemployment Insurance Claims Ease 13,000 in the May 3 Week

Andrew Cates

**The global business cycle** 
The recent sharp decline in the Future Output Balance in the global composite PMI survey reflects a sudden deterioration in global business expectations. The sweeping tariffs, introduced in April 2025, have generated heightened uncertainty around trade policy and sparked fears of retaliatory actions from key trading partners. As a result, businesses worldwide are scaling back their expectations for future output, wary of rising costs, disrupted demand flows, and a broader shift toward protectionism that could undermine global economic momentum.

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Note: The extreme declines in the Future Output Balance that were recorded in the early months of 2020 (at the height of the COVID pandemic) have been removed from this chart.

**Global supply chain pressures**
Still, despite the marked deterioration in global business expectations, this second chart below provides a reassuring counterpoint: as of now, there is little evidence that global supply chain pressures have materially intensified. Both the New York Fed’s Global Supply Chain Pressure Index and the Baltic Exchange Dry Index remain relatively subdued, especially compared to the pandemic-era spikes of 2020–2022. While there has been heightened concern following the April 2025 US tariff announcements, these trade policy shifts have yet to translate into measurable physical disruption in logistics or freight rates. The stability of these indices suggests that although sentiment has taken a hit, global shipping networks and supply flows are, for now, absorbing the shock. However, this calm may prove fragile if the policy environment hardens further or retaliatory trade actions begin to compound the strain.

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**Expectations for central banks’ policy rates** 
Adding to the picture of mounting economic caution, the latest Blue Chip Financial Forecasts survey reveals that expectations for policy easing over the next 12 months have become even more pronounced than in previous months. While earlier surveys had already pointed to a further extension of the global rate-cutting cycle, the latest results suggest forecasters now anticipate a deeper and more aggressive round of monetary easing—most notably from the US Federal Reserve, which is now expected to deliver nearly a full percentage point in rate cuts over the next 12 months. The sharp deterioration in business sentiment is reshaping the macro narrative: central banks are no longer simply guiding inflation lower, but are instead preparing to confront the risk of a deeper, demand-driven slowdown.

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**Energy prices and inflation** 
Adding further context to the growing expectations for policy easing, oil prices have dropped sharply in recent weeks—driven by mounting concerns over global growth, as reflected in weakening business sentiment and softer demand indicators. The chart below provides a longer-run perspective on why this matters: energy prices have historically played a central role in shaping the global inflation trajectory. The strong positive correlation (r = 0.83) between median world energy price inflation and median core consumer price inflation underscores the powerful pass-through effects energy costs can have on broader price dynamics. While core inflation tends to be stickier, this historical relationship makes clear that sustained declines in energy prices often foreshadow broader disinflationary trends.

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**Intangibles versus tangibles** 
Shifting focus from short-term cyclical risks to longer-term structural dynamics, the next chart below underscores a fundamental transformation in the composition of US investment: the economy has increasingly been built on intangibles. Over the past several decades, investment in intangible assets—such as software, intellectual property, R&D, and brand equity—has steadily climbed and, since the mid-2010s, has overtaken investment in both structures and equipment as a share of GDP. This shift reflects the rise of a knowledge-based, innovation-driven economy, but it also introduces new forms of vulnerability. Unlike physical capital, intangible assets rely heavily on trust, reputation, legal protections, and global openness. In this context, escalating trade frictions and a more confrontational US economic stance—as signalled by the recent tariff wave—risk eroding the goodwill and institutional credibility that underpin much of the value created by intangibles. If geopolitical uncertainty undermines the perceived reliability of US intellectual property protections or weakens global collaboration, it could pose a deeper structural challenge to future growth than any immediate cyclical downturn.

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**Investment in Artificial Intelligence**
The centrality of intangibles to the US growth model is nowhere more evident than in the explosion of private investment in artificial intelligence. As this chart illustrates, global AI investment has surged over the past decade—reaching new highs in 2024—and the United States has consistently accounted for the lion’s share of that spending. This reflects not only America’s previous leadership in frontier technologies but also its dependence on intangible capital, from algorithms and data infrastructure to human expertise and institutional trust. However, this dominance also underscores the strategic stakes of current policy choices. In an environment of rising trade tensions and potential fragmentation, the foundations of US leadership in AI—cross-border collaboration, data openness, and global market access—could be at risk.

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Financial market sentiment has rebounded in recent weeks, buoyed by signs of de-escalation in the US-led trade war and growing confidence that central banks—particularly the Federal Reserve—will step in with more rate cuts to cushion any fallout. Yet beneath the surface, a more sobering picture of the global economy persists. For example, latest PMI surveys reveal that global business expectations have slumped to their lowest levels since the pandemic, reflecting widespread unease about the growth outlook (chart 1). While supply chain pressures have so far remained contained, suggesting no repeat of the logistical chaos seen during the pandemic (chart 2), the latest Blue Chip Financial Forecasts survey reveals that forecasters are now pencilling in deeper and more widespread monetary easing than previously anticipated—an acknowledgment that demand is faltering (chart 3). Falling oil prices further reinforce this view: they are both a symptom of weakening global demand and a potential source of disinflation, reducing the urgency for central banks to maintain tight policy (chart 4). At the structural level, the US economy's increasing reliance on intangible assets—ranging from intellectual property to reputation—has made it more vulnerable to geopolitical frictions and the erosion of global trust (chart 5). This risk is compounded by America's dominant role in AI investment, a sector symbolic of both its economic strengths and its exposure to international perceptions (chart 6). The longer-term challenge, then, is not just navigating the current downturn, but ensuring that the institutional goodwill and cross-border openness that support the modern US economy are not sacrificed in a more fragmented and uncertain global order.

Charts of the Week: Relief Rally Meets Recession Risk

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At today’s meeting of the Federal Open Market Committee, the target range for the Fed funds rate was left unchanged at 4.25% to 4.50%. This followed reductions at three consecutive meetings in the fall of 2024. Rates remain below the high of 5.25% to 5.50% in place in mid-September. Today’s target range matched expectations in the Action Economics Forecast Survey.

The statement following the meeting indicated that, “The Committee seeks to achieve maximum employment and inflation at the rate of 2 percent over the longer run. Uncertainty about the economic outlook has increased further. The Committee is attentive to the risks to both sides of its dual mandate and judges that the risks of higher unemployment and higher inflation have risen.”

“The Committee's assessments will take into account a wide range of information, including readings on labor market conditions, inflation pressures and inflation expectations, and financial and international developments.”

The Fed continued, “The Committee will continue reducing its holdings of Treasury securities and agency debt and agency mortgage backed securities.”

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- FOMC holds funds rate target at late-December level.
- Risk assessments include higher unemployment & inflation.

Economy in Brief: April 2020

Jump to:

U.S. ADP Private Payrolls Decline as Coronavirus Effects Begin

U.S. Mortgage Applications Rebound, Led by Refinancing

U.S. ADP Private Payrolls Decline as Coronavirus Effects Begin

U.S. ADP Private Payrolls Decline as Coronavirus Effects Begin