Tom Moeller

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      The Chicago Federal Reserve indicated that its National Activity Index
      (CFNAI) remained negative last month. The figure improved, however, to
      -0.30 from a little-revised -0.52 in April. The three-month moving average
      deteriorated -0.43, its lowest reading since October. During the last ten
      years, there has been a 79% correlation between the Chicago Fed Index and
      the q/q change in real GDP.</p>
      <p>The Production &amp; Income component showed the greatest m/m
      improvement with a recovery to -0.10. The Employment, Unemployment &amp;
      Hours series improved to 0.01 and also recovered its April decline. The Personal
      Consumption &amp; Housing reading was stable at -0.17. Sales, Inventories
      &amp; Inventories deteriorated to -0.04. The Chicago Fed reported that
      during May, 33 of the 85 individual indicators made positive contributions
      to the overall index while 52 made negative contributions.</p>
      <p>The CFNAI is a weighted average of 85 indicators of national economic
      activity. It is constructed to have an average value of zero and a
      standard deviation of one. Since economic activity tends toward trend
      growth rate over time, a positive index reading corresponds to growth
      above trend and a negative index reading corresponds to growth below
      trend.</p>
      <p>The Chicago Federal Reserve figures are available in Haver's <b>SURVEYS</b>
      database.&nbsp;</p>
      <p><b>Managing Economic Development in Times of Fiscal Uncertainty</b>
      from the Federal Reserve Bank of Chicago can be found <a href="http://chicagofed.org/digital_assets/publications/chicago_fed_letter/2013/cfljuly2013_312a.pdf">here</a>.</p>
      
      
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      <p>&nbsp;</p>


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       <thead>
          <tr>
            <th class="firstcol" scope="col">Chicago Federal Reserve
              Bank</th>
            <th  scope="col">May</th>
            <th  scope="col">Apr</th>
            <th  scope="col">Mar</th>
            <th  scope="col">May'12</th>
            <th  scope="col">2012</th>
            <th  scope="col">2011</th>
            <th  scope="col">2010</th>
          </tr>
        </thead>
        <tbody>
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            <td class="firstcol">CFNAI</td>
            <td>-0.30</td>
            <td>-0.52</td>
            <td>-0.48</td>
            <td>-0.12</td>
            <td>-0.08</td>
            <td>-0.08</td>
            <td>0.02</td>
          </tr>
          <tr class="odd">
            <td class="firstcol">&nbsp;3-Month Moving Average</td>
            <td>-0.43</td>
            <td>-0.13</td>
            <td>-0.14</td>
            <td>-0.23</td>
            <td>--</td>
            <td>--</td>
            <td>--</td>
          </tr>
          <tr>
            <td class="firstcol">&nbsp;&nbsp;Personal Consumption
              &amp; Housing</td>
            <td>-0.17</td>
            <td>-0.17</td>
            <td>-0.16</td>
            <td>-0.25</td>
            <td>-0.22</td>
            <td>-0.30</td>
            <td>-0.30</td>
          </tr>
          <tr class="odd">
            <td class="firstcol">&nbsp;&nbsp;Employment,
              Unemployment &amp; Hours</td>
            <td>0.01</td>
            <td>-0.06</td>
            <td>0.01</td>
            <td>0.09</td>
            <td>0.10</td>
            <td>0.14</td>
            <td>0.03</td>
          </tr>
          <tr>
            <td class="firstcol">&nbsp;&nbsp;Production &amp; Income</td>
            <td>-0.10</td>
            <td>-0.33</td>
            <td>-0.10</td>
            <td>-0.03</td>
            <td>0.04</td>
            <td>0.05</td>
            <td>0.20</td>
          </tr>
          <tr class="odd">
            <td class="firstcol">&nbsp;&nbsp;Sales, Orders &amp;
              Inventories</td>
            <td>-0.04</td>
            <td>0.03</td>
            <td>-0.24</td>
            <td>0.01</td>
            <td>-0.01</td>
            <td>0.04</td>
            <td>0.09</td>
          </tr>
        </tbody>
      </table>
      </span>
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The Chicago Federal Reserve indicated that its National Activity Index (CFNAI) remained negative last month. The figure improved, however, to -0.30 from a little-revised -0.52 in April. The three-month moving average deteriorated [...]

U.S. Chicago Fed National Activity Index Remains Negative

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            <p>Improvement in the overall labor market is evident in May's 7.6%
      unemployment rate. That compares to 7.8% at the end of last year and 8.1%
      during all of 2012. Notable has been the rate's recent decline in states
      where it previously was sticky. Great improvement has been in California
      where May's 8.6% rate of unemployment is two percentage below last year's
      average. Washington also saw great improvement. May's 6.8% unemployment
      rate compared to 8.2% during all of last year. In New York, May's rate of
      7.6% was roughly one full percentage point below last year's average.</p>
      
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      <p>The rate of labor market improvement has lagged in many large states.
      In Texas, for example, while the 6.5% jobless rate is low relative to the
      rest of the country, it's down just slightly from last year's 6.8%
      average. In Illinois, 9.1% joblessness differs little from the 8.9%
      averaged last year. In Tennessee, the current 8.3% unemployment rate is
      actually above last year's 8.0% average. In smaller states, the rate of
      job market improvement also varies. Nevada's 9.5% unemployment rate is
      well below last year's 11.1% average but in neighboring Arizona, 7.8%
      unemployment is down just modestly from last year's 8.3%.</p>
      <p>The household employment survey also produces data on individual
      metropolitan areas. These figures, in a few circumstances, differ widely
      from the state numbers. Florida's 7.1% unemployment rate, for example, is
      a far cry from the 9.3% in the Miami metro area. Michigan's 8.4% rate also
      is under the 9.5% rate around Detroit. New York state's 7.6% rate lags the
      8.3% in New York City while California's 8.6% rate is under 9.6% around
      Los Angeles. Running close to one another are the Illinois unemployment
      rate of 9.1% and the 9.3% rate around Chicago. Also, Ohio's 7.0%
      unemployment rate is near Cleveland's of 6.9%. Working the other way,
      Washington state's 6.8% jobless rate by far exceeds Seattle's 4.7%.</p>
      <p>State unemployment figures are available in Haver's <b>EMPLR</b>
      database.
            </p>

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      <p>&nbsp;</p>


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        <thead>
          <tr>
            <th class="firstcol" scope="col" >State Unemployment
              Rate</th>
            <th scope="col" ><b>May</b></th>
            <th scope="col" ><b>April</b></th>
            <th scope="col" ><b>2012</b></th>
            <th scope="col" ><b>2011</b></th>
            <th scope="col" ><b>2010</b></th>
            <th scope="col" ><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol" ><b>Total U.S.</b></td>
            <td  >7.6%</td>
            <td  >7.5%</td>
            <td  >8.1%</td>
            <td  >8.9%</td>
            <td  >9.6%</td>
            <td  >155.7 mil.</td>
          </tr>
          <tr class="grey3">
            <td class="firstcol" ><b>Ten States With Highest
              Jobless Rate</b></td>
            <td  ></td>
            <td  ></td>
            <td  ></td>
            <td  ></td>
            <td  ></td>
            <td  ></td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Nevada</td>
            <td  >9.5</td>
            <td  >9.6</td>
            <td  >11.1</td>
            <td  >13.2</td>
            <td  >13.8</td>
            <td  >1.4</td>
          </tr>
          <tr class="odd">
            <td class="firstcol"  >&nbsp;&nbsp;Illinois</td>
            <td  >9.1</td>
            <td  >9.3</td>
            <td  >8.9</td>
            <td  >9.7</td>
            <td  >10.4</td>
            <td  >9.6</td>
          </tr>
          <tr>
            <td class="firstcol"  >&nbsp;&nbsp;Mississippi</td>
            <td  >9.1</td>
            <td  >9.1</td>
            <td  >9.1</td>
            <td  >10.5</td>
            <td  >10.5</td>
            <td  >1.3</td>
            
          </tr>
          <tr class="odd">
            <td class="firstcol"  >&nbsp;&nbsp;North Carolina</td>
            <td  >8.8</td>
            <td  >8.9</td>
            <td  >9.5</td>
            <td  >10.3</td>
            <td  >10.8</td>
            <td  >4.7</td>
            
          </tr>
          <tr>
            <td class="firstcol"  >&nbsp;&nbsp;California</td>
            <td  >8.6</td>
            <td  >9.0</td>
            <td  >10.5</td>
            <td  >11.8</td>
            <td  >12.3</td>
            <td  >18.6</td>
          </tr>
          <tr class="odd">
            <td class="firstcol"  >&nbsp;&nbsp;New Jersey</td>
            <td  >8.6</td>
            <td  >8.7</td>
            <td  >9.5</td>
            <td  >9.3</td>
            <td  >9.6</td>
            <td  >4.6</td>
          </tr>
          <tr>
            <td class="firstcol"  >&nbsp;&nbsp;Georgia</td>
            <td  >8.3</td>
            <td  >8.2</td>
            <td  >9.0</td>
            <td  >9.9</td>
            <td  >10.2</td>
            <td  >4.8</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Indiana</td>
            <td  >8.3</td>
            <td  >8.5</td>
            <td  >8.4</td>
            <td  >9.0</td>
            <td  >10.1</td>
            <td  >3.2</td>
            
          </tr>
          <tr>
            <td class="firstcol" >&nbsp; Tennessee</td>
            <td  >8.3</td>
            <td  >8.0</td>
            <td  >8.0</td>
            <td  >9.3</td>
            <td  >9.8</td>
            <td  >3.1</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;South Carolina</td>
            <td  >8.0</td>
            <td  >8.0</td>
            <td  >9.1</td>
            <td  >10.4</td>
            <td  >11.2</td>
            <td  >2.2</td>
            
          </tr>
        </tbody>
      </table>
      <br>
<table class="centered" width="100%" border="0" cellspacing="0">
        <thead>
          <tr>
            <th class="firstcol" scope="col" >States With Lowest
              Jobless Rate</th>
            <th scope="col" ><b>May</b></th>
            <th scope="col" ><b>April</b></th>
            <th scope="col" ><b>2012</b></th>
            <th scope="col" ><b>2011</b></th>
            <th scope="col" ><b>2010</b></th>
            <th scope="col" ><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;New Hampshire</td>
            <td  >5.3%</td>
            <td  >5.5%</td>
            <td  >5.5%</td>
            <td  >5.5%</td>
            <td  >6.1%</td>
            <td  >0.7 mil.</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Minnesota</td>
            <td  >5.3</td>
            <td  >5.3</td>
            <td  >5.6</td>
            <td  >6.5</td>
            <td  >7.3</td>
            <td  >3.0</td>
           </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Virginia</td>
            <td  >5.3</td>
            <td  >5.2</td>
            <td  >5.9</td>
            <td  >6.5</td>
            <td  >7.1</td>
            <td  >4.2</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Wyoming</td>
            <td  >4.6</td>
            <td  >4.8</td>
            <td  >5.4</td>
            <td  >6.1</td>
            <td  >7.0</td>
            <td  >0.3</td>
           </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Utah</td>
            <td  >4.6</td>
            <td  >4.7</td>
            <td  >5.7</td>
            <td  >6.9</td>
            <td  >8.1</td>
            <td  >1.4</td>
          </tr>
          <tr class="odd">
             <td class="firstcol" >&nbsp;&nbsp;Iowa</td>
            <td  >4.6</td>
            <td  >4.7</td>
            <td  >5.2</td>
            <td  >5.9</td>
            <td  >6.3</td>
            <td  >1.6</td>
            
          </tr>
          <tr>
             <td class="firstcol" >&nbsp;&nbsp;Vermont</td>
            <td  >4.1</td>
            <td  >4.0</td>
            <td  >5.0</td>
            <td  >5.6</td>
            <td  >6.4</td>
            <td  >0.4</td>
            
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;South Dakota</td>
            <td  >4.0</td>
            <td  >4.1</td>
            <td  >4.4</td>
            <td  >4.8</td>
            <td  >5.1</td>
            <td  >0.4</td>
            
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Nebraska</td>
            <td  >3.8</td>
            <td  >3.7</td>
            <td  >3.9</td>
            <td  >4.5</td>
            <td  >4.7</td>
            <td  >1.0</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;North Dakota</td>
            <td  >3.2</td>
            <td  >3.3</td>
            <td  >3.1</td>
            <td  >3.5</td>
            <td  >3.8</td>
            <td  >0.4</td>
          </tr>
        </tbody>
      </table>
      <br>
<table class="centered" width="100%" border="0" cellspacing="0">
        <thead>
          <tr>
            <td class="firstcol" ><b>Jobless Rate In Other Selected
              Large States</b>
            </td><th scope="col" ><b>May</b></th>
            <th scope="col" ><b>April</b></th>
            <th scope="col" ><b>2012</b></th>
            <th scope="col" ><b>2011</b></th>
            <th scope="col" ><b>2010</b></th>
            <th scope="col" ><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol"  >&nbsp;&nbsp;Connecticut</td>
            <td  >8.0%</td>
            <td  >8.0%</td>
            <td  >8.3%</td>
            <td  >8.9%</td>
            <td  >9.3%</td>
            <td  >1.8 mil.</td>
            
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Arizona</td>
            <td  >7.8</td>
            <td  >7.9</td>
            <td  >8.3</td>
            <td  >9.4</td>
            <td  >10.4</td>
            <td  >3.0</td>
            
          </tr>
          <tr>
            <td class="firstcol"  >&nbsp;&nbsp;New York</td>
            <td  >7.6</td>
            <td  >7.8</td>
            <td  >8.5</td>
            <td  >8.3</td>
            <td  >8.6</td>
            <td  >9.6</td>
            
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Florida</td>
            <td  >7.1</td>
            <td  >7.2</td>
            <td  >8.6</td>
            <td  >10.3</td>
            <td  >11.3</td>
            <td  >9.4</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Wisconsin</td>
            <td  >7.0</td>
            <td  >7.1</td>
            <td  >6.9</td>
            <td  >7.6</td>
            <td  >8.4</td>
            <td  >3.1</td>
            
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Ohio</td>
            <td  >7.0</td>
            <td  >7.0</td>
            <td  >7.2</td>
            <td  >8.6</td>
            <td  >10.0</td>
            <td  >5.7</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Colorado</td>
            <td  >6.9</td>
            <td  >6.9</td>
            <td  >8.0</td>
            <td  >8.6</td>
            <td  >9.0</td>
            <td  >2.8</td>
            
          </tr>
          <tr class="odd">
              <td class="firstcol" >&nbsp;&nbsp;Washington</td>
            <td  >6.8</td>
            <td  >7.0</td>
            <td  >8.2</td>
            <td  >9.2</td>
            <td  >9.9</td>
            <td  >3.5</td>
            
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Maryland</td>
            <td  >6.7</td>
            <td  >6.5</td>
            <td  >6.8</td>
            <td  >7.3</td>
            <td  >7.8</td>
            <td  >3.1</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Texas</td>
            <td  >6.5</td>
            <td  >6.4</td>
            <td  >6.8</td>
            <td  >8.0</td>
            <td  >8.2</td>
            <td  >12.8</td>
          </tr>
        </tbody>
      </table>
      


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Improvement in the overall labor market is evident in May's 7.6% unemployment rate. That compares to 7.8% at the end of last year and 8.1% during all of 2012. Notable has been the rate's recent decline in states where it previously [...]

State Unemployment Rates Continue Lower but Vary Greatly

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      <br>
      <span id="articletext">
      <p>Improvement in the overall labor market is evident in May's 7.6%
      unemployment rate. That compares to 7.8% at the end of last year and 8.1%
      during all of 2012. Notable has been the rate's recent decline in states
      where it previously was sticky. Great improvement has been in California
      where May's 8.6% rate of unemployment is two percentage below last year's
      average. Washington also saw great improvement. May's 6.8% unemployment
      rate compared to 8.2% during all of last year. In New York, May's rate of
      7.6% was roughly one full percentage point below last year's average.</p>
      </span>
      <p>The rate of labor market improvement has lagged in many large states.<span id="articletext">
      In Texas, for example, while the 6.5% jobless rate is low relative to the
      rest of the country, it's down just slightly from last year's 6.8%
      average. In Illinois, 9.1% joblessness differs little from the 8.9%
      averaged last year. In Tennessee, the current 8.3% unemployment rate is
      actually above last year's 8.0% average. In smaller states, the rate of
      job market improvement also varies. Nevada's 9.5% unemployment rate is
      well below last year's 11.1% average but in neighboring Arizona, 7.8%
      unemployment is down just modestly from last year's 8.3%.
      <p>The household employment survey also produces data on individual
      metropolitan areas. These figures, in a few circumstances, differ widely
      from the state numbers. Florida's 7.1% unemployment rate, for example, is
      a far cry from the 9.3% in the Miami metro area. Michigan's 8.4% rate also
      is under the 9.5% rate around Detroit. New York state's 7.6% rate lags the
      8.3% in New York City while California's 8.6% rate is under 9.6% around
      Los Angeles. Running close to one another are the Illinois unemployment
      rate of 9.1% and the 9.3% rate around Chicago. Also, Ohio's 7.0%
      unemployment rate is near Cleveland's of 6.9%. Working the other way,
      Washington state's 6.8% jobless rate by far exceeds Seattle's 4.7%.</p>
      <p>State unemployment figures are available in Haver's <b>EMPLR</b>
      database. </p>
      <table class="centered" border="0" cellSpacing="0" width="1231">
        <colgroup>
          <col>
          <col>
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          <col>
          <col>
          <col>
          <col>
          <col>
        </colgroup>
        <thead>
          <tr>
            <th class="firstcol" scope="col" ? width="527">State Unemployment
              Rate</th>
            <th scope="col" width="116"><b>May</b></th>
            <th scope="col" width="116"><b>April</b></th>
            <th scope="col" width="117"><b>2012</b></th>
            <th scope="col" width="117"><b>2011</b></th>
            <th scope="col" width="117"><b>2010</b></th>
            <th scope="col" width="117"><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol" ? width="527"><b>Total U.S.</b></td>
            <td align="center" width="116">7.6%</td>
            <td align="center" width="116">7.5%</td>
            <td align="center" width="117">8.1%</td>
            <td align="center" width="117">8.9%</td>
            <td align="center" width="117">9.6%</td>
            <td align="center" width="117">155.7 mil.</td>
          </tr>
          <tr class="grey3">
            <td class="firstcol" ? width="527"><b>Ten States With Highest
              Jobless Rate</b></td>
            <td align="center" width="116"></td>
            <td align="center" width="116"></td>
            <td align="center" width="117"></td>
            <td align="center" width="117"></td>
            <td align="center" width="117"></td>
            <td align="center" width="117"></td>
          </tr>
          <tr>
            <td class="firstcol" ? width="527">&nbsp;&nbsp;Nevada</td>
            <td align="center" width="116">9.5</td>
            <td align="center" width="116">9.6</td>
            <td align="center" width="117">11.1</td>
            <td align="center" width="117">13.2</td>
            <td align="center" width="117">13.8</td>
            <td align="center" width="117">1.4</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;Illinois</td>
            <td align="center" width="116">9.1</td>
            <td align="center" width="116">9.3</td>
            <td align="center" width="117">8.9</td>
            <td align="center" width="117">9.7</td>
            <td align="center" width="117">10.4</td>
            <td align="center" width="117">9.6</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;Mississippi</td>
            <td align="center" width="116">9.1</td>
            <td align="center" width="116">9.1</td>
            <td align="center" width="117">9.1</td>
            <td align="center" width="117">10.5</td>
            <td align="center" width="117">10.5</td>
            <td align="center" width="117">1.3</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;North Carolina</td>
            <td align="center" width="116">8.8</td>
            <td align="center" width="116">8.9</td>
            <td align="center" width="117">9.5</td>
            <td align="center" width="117">10.3</td>
            <td align="center" width="117">10.8</td>
            <td align="center" width="117">4.7</td>
            </span>
          </tr>
          <tr>
            <td class="firstcol" ? width="527">&nbsp;&nbsp;California</td>
            <td align="center" width="116">8.6</td>
            <td align="center" width="116">9.0</td>
            <td align="center" width="117">10.5</td>
            <td align="center" width="117">11.8</td>
            <td align="center" width="117">12.3</td>
            <td align="center" width="117">18.6</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;New Jersey</td>
            <td align="center" width="116">8.6</td>
            <td align="center" width="116">8.7</td>
            <td align="center" width="117">9.5</td>
            <td align="center" width="117">9.3</td>
            <td align="center" width="117">9.6</td>
            <td align="center" width="117">4.6</td>
          </tr>
          <tr>
            <td class="firstcol" ? width="527">&nbsp;&nbsp;Georgia</td>
            <td align="center" width="116">8.3</td>
            <td align="center" width="116">8.2</td>
            <td align="center" width="117">9.0</td>
            <td align="center" width="117">9.9</td>
            <td align="center" width="117">10.2</td>
            <td align="center" width="117">4.8</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;Indiana</td>
            <td width="122" align="center">8.3</td>
            <td width="129" align="center">8.5</td>
            <td width="117" align="center">8.4</td>
            <td width="118" align="center">9.0</td>
            <td width="118" align="center">10.1</td>
            <td width="118" align="center">3.2</td>
            </span>
          </tr>
          <tr>
            <td class="firstcol" width="518">&nbsp; Tennessee</td>
            <td width="122" align="center">8.3</td>
            <td width="129" align="center">8.0</td>
            <td width="117" align="center">8.0</td>
            <td width="118" align="center">9.3</td>
            <td width="118" align="center">9.8</td>
            <td width="118" align="center">3.1</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;South Carolina</td>
            <td width="122" align="center">8.0</td>
            <td width="129" align="center">8.0</td>
            <td width="117" align="center">9.1</td>
            <td width="118" align="center">10.4</td>
            <td width="118" align="center">11.2</td>
            <td width="118" align="center">2.2</td>
            </span>
          </tr>
        </tbody>
      </table>
      <br>
      <table class="centered" border="0" cellSpacing="0" width="1240">
        <thead>
          <tr>
            <th class="firstcol" scope="col" width="524">States With Lowest
              Jobless Rate</th>
            <th scope="col" width="121"><b>May</b></th>
            <th scope="col" width="121"><b>April</b></th>
            <th scope="col" width="121"><b>2012</b></th>
            <th scope="col" width="121"><b>2011</b></th>
            <th scope="col" width="122"><b>2010</b></th>
            <th scope="col" width="122"><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;New Hampshire</td>
            <td width="121" align="center">5.3%</td>
            <td width="121" align="center">5.5%</td>
            <td width="121" align="center">5.5%</td>
            <td width="121" align="center">5.5%</td>
            <td width="122" align="center">6.1%</td>
            <td width="122" align="center">0.7 mil.</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;Minnesota</td>
            <td width="121" align="center">5.3</td>
            <td width="121" align="center">5.3</td>
            <td width="121" align="center">5.6</td>
            <td width="121" align="center">6.5</td>
            <td width="122" align="center">7.3</td>
            <td width="122" align="center">3.0</td>
            </span>
          </tr>
          <tr class="odd">
            <td class="firstcol" width="524">&nbsp;&nbsp;Virginia</td>
            <td width="121" align="center">5.3</td>
            <td width="121" align="center">5.2</td>
            <td width="121" align="center">5.9</td>
            <td width="121" align="center">6.5</td>
            <td width="122" align="center">7.1</td>
            <td width="122" align="center">4.2</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;Wyoming</td>
            <td width="121" align="center">4.6</td>
            <td width="121" align="center">4.8</td>
            <td width="121" align="center">5.4</td>
            <td width="121" align="center">6.1</td>
            <td width="122" align="center">7.0</td>
            <td width="122" align="center">0.3</td>
            </span>
          </tr>
          <tr>
            <td class="firstcol" width="524">&nbsp;&nbsp;Utah</td>
            <td width="121" align="center">4.6</td>
            <td width="121" align="center">4.7</td>
            <td width="121" align="center">5.7</td>
            <td width="121" align="center">6.9</td>
            <td width="122" align="center">8.1</td>
            <td width="122" align="center">1.4</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;Iowa</td>
            <td width="121" align="center">4.6</td>
            <td width="121" align="center">4.7</td>
            <td width="121" align="center">5.2</td>
            <td width="121" align="center">5.9</td>
            <td width="122" align="center">6.3</td>
            <td width="122" align="center">1.6</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;Vermont</td>
            <td width="121" align="center">4.1</td>
            <td width="121" align="center">4.0</td>
            <td width="121" align="center">5.0</td>
            <td width="121" align="center">5.6</td>
            <td width="122" align="center">6.4</td>
            <td width="122" align="center">0.4</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="524">&nbsp;&nbsp;South Dakota</td>
            <td width="121" align="center">4.0</td>
            <td width="121" align="center">4.1</td>
            <td width="121" align="center">4.4</td>
            <td width="121" align="center">4.8</td>
            <td width="122" align="center">5.1</td>
            <td width="122" align="center">0.4</td>
            </span>
          </tr>
          <tr class="odd">
            <td class="firstcol" width="524">&nbsp;&nbsp;Nebraska</td>
            <td width="121" align="center">3.8</td>
            <td width="121" align="center">3.7</td>
            <td width="121" align="center">3.9</td>
            <td width="121" align="center">4.5</td>
            <td width="122" align="center">4.7</td>
            <td width="122" align="center">1.0</td>
          </tr>
          <tr>
            <td class="firstcol" width="524">&nbsp;&nbsp;North Dakota</td>
            <td width="121" align="center">3.2</td>
            <td width="121" align="center">3.3</td>
            <td width="121" align="center">3.1</td>
            <td width="121" align="center">3.5</td>
            <td width="122" align="center">3.8</td>
            <td width="122" align="center">0.4</td>
          </tr>
        </tbody>
      </table>
      <br>
      <table class="centered" border="0" cellSpacing="0" width="1231">
        <thead>
          <tr>
            <td class="firstcol" width="518"><b>Jobless Rate In Other Selected
              Large States</b>
            </td><th scope="col" width="122"><b>May</b></th>
            <th scope="col" width="129"><b>April</b></th>
            <th scope="col" width="117"><b>2012</b></th>
            <th scope="col" width="118"><b>2011</b></th>
            <th scope="col" width="118"><b>2010</b></th>
            <th scope="col" width="118"><b>Labor Force</b></th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <span id="articletext">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;Connecticut</td>
            <td align="center" width="116">8.0%</td>
            <td align="center" width="116">8.0%</td>
            <td align="center" width="117">8.3%</td>
            <td align="center" width="117">8.9%</td>
            <td align="center" width="117">9.3%</td>
            <td align="center" width="117">1.8 mil.</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;Arizona</td>
            <td width="122" align="center">7.8</td>
            <td width="129" align="center">7.9</td>
            <td width="117" align="center">8.3</td>
            <td width="118" align="center">9.4</td>
            <td width="118" align="center">10.4</td>
            <td width="118" align="center">3.0</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" ? width="527">&nbsp;&nbsp;New York</td>
            <td align="center" width="116">7.6</td>
            <td align="center" width="116">7.8</td>
            <td align="center" width="117">8.5</td>
            <td align="center" width="117">8.3</td>
            <td align="center" width="117">8.6</td>
            <td align="center" width="117">9.6</td>
            </span>
          </tr>
          <tr class="odd">
            <td class="firstcol" width="518">&nbsp;&nbsp;Florida</td>
            <td width="122" align="center">7.1</td>
            <td width="129" align="center">7.2</td>
            <td width="117" align="center">8.6</td>
            <td width="118" align="center">10.3</td>
            <td width="118" align="center">11.3</td>
            <td width="118" align="center">9.4</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;Wisconsin</td>
            <td width="122" align="center">7.0</td>
            <td width="129" align="center">7.1</td>
            <td width="117" align="center">6.9</td>
            <td width="118" align="center">7.6</td>
            <td width="118" align="center">8.4</td>
            <td width="118" align="center">3.1</td>
            </span>
          </tr>
          <tr>
            <td class="firstcol" width="518">&nbsp;&nbsp;Ohio</td>
            <td width="122" align="center">7.0</td>
            <td width="129" align="center">7.0</td>
            <td width="117" align="center">7.2</td>
            <td width="118" align="center">8.6</td>
            <td width="118" align="center">10.0</td>
            <td width="118" align="center">5.7</td>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;Colorado</td>
            <td width="122" align="center">6.9</td>
            <td width="129" align="center">6.9</td>
            <td width="117" align="center">8.0</td>
            <td width="118" align="center">8.6</td>
            <td width="118" align="center">9.0</td>
            <td width="118" align="center">2.8</td>
            </span>
          </tr>
          <tr>
            <span id="articletext">
            <td class="firstcol" width="518">&nbsp;&nbsp;Washington</td>
            <td width="122" align="center">6.8</td>
            <td width="129" align="center">7.0</td>
            <td width="117" align="center">8.2</td>
            <td width="118" align="center">9.2</td>
            <td width="118" align="center">9.9</td>
            <td width="118" align="center">3.5</td>
            </span>
          </tr>
          <tr>
            <td class="firstcol" width="518">&nbsp;&nbsp;Maryland</td>
            <td width="122" align="center">6.7</td>
            <td width="129" align="center">6.5</td>
            <td width="117" align="center">6.8</td>
            <td width="118" align="center">7.3</td>
            <td width="118" align="center">7.8</td>
            <td width="118" align="center">3.1</td>
          </tr>
          <tr>
            <td class="firstcol" width="518">&nbsp;&nbsp;Texas</td>
            <td width="122" align="center">6.5</td>
            <td width="129" align="center">6.4</td>
            <td width="117" align="center">6.8</td>
            <td width="118" align="center">8.0</td>
            <td width="118" align="center">8.2</td>
            <td width="118" align="center">12.8</td>
          </tr>
        </tbody>
      </table>
      </span>
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      <p>The index of Leading Economic Indicators, published by the Conference
      Board, ticked up 0.1% (2.0% y/y) during May to 95.2, another high for the
      economic recovery. The gain followed an upwardly revised 0.8% April
      increase, last month reported as 0.6%. A 0.2% rise had been expected for
      April. Just 45 percent of the component series had a positive influence on
      the index. A steeper interest rate yield curve, higher stock prices and
      the leading credit index increased the total. These were offset by a lower
      ISM new orders index, fewer building permits and higher initial claims for
      unemployment insurance.</p>
      <p>The index of coincident indicators gained 0.2% (1.5% y/y) after an
      unrevised 0.1% April uptick. Higher payroll employment, improved personal
      income less transfers and more manufacturing and trade sales had positive
      influences on the index. Industrial production was unchanged.</p>
      <p>The index of lagging economic indicators increased 0.3% (3.4% y/y)
      after a minimal 0.1% April rise. Roughly two-thirds of the component
      series rose paced by more commercial &amp; industrial loans outstanding.</p>
      <p>Another leading economic series is the ratio of coincident-to-lagging
      indicators. It measures how the economy is performing versus its excesses.
      The figure fell 0.2% (-1.9% y/y) last month to its lowest level of the
      economic expansion.</p>
      <p>The Conference Board figures are available in Haver's <b>BCI</b>
      database; the components are available there, and most are also in <b>USECON</b>.
      The forecast figures for the Consensus are in the <b>AS1REPNA</b>
      database. Visit the Conference Board's <a href="http://www.conference-board.org/">site</a>
      for coverage of leading indicator series from around the world.&nbsp;</p>
      <p>The <b>economic projections</b> which accompanied yesterday's FOMC
      meeting are available <a href="http://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20130619.pdf">here</a>.</p>
      
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	<colgroup><col><col><col><col><col><col><col><col></colgroup>
        
          <tr>
            <th class="firstcol" scope="col">Business Cycle
              Indicators (%)</th>
            <th scope="col">May</th>
            <th scope="col">Apr</th>
            <th scope="col">Mar</th>
            <th scope="col">Y/Y</th>
            <th scope="col">2012</th>
            <th scope="col">2011</th>
            <th scope="col">2010</th>
          </tr>
        <tbody>
          <tr>
            <td class="firstcol">Leading</td>
            <td>0.1</td>
            <td>0.8</td>
            <td>-0.3</td>
            <td>2.0</td>
            <td>2.0</td>
            <td>5.1</td>
            <td>8.0</td>
          </tr>
          <tr class="odd">
            <td class="firstcol">Coincident</td>
            <td>0.2</td>
            <td>0.1</td>
            <td>0.1</td>
            <td>1.5</td>
            <td>2.1</td>
            <td>2.4</td>
            <td>1.2</td>
          </tr>
          <tr>
            <td class="firstcol">Lagging</td>
            <td>0.3</td>
            <td>0.1</td>
            <td>0.3</td>
            <td>3.4</td>
            <td>3.6</td>
            <td>2.7</td>
            <td>-3.1</td>
                            </tr>
              </tbody>
            
            

            
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The index of Leading Economic Indicators, published by the Conference Board, ticked up 0.1% (2.0% y/y) during May to 95.2, another high for the economic recovery. The gain followed an upwardly revised 0.8% April increase, last month [...]

U.S. Leading Economic Indicators Rise on Financial Series' Strength

Robert Brusca

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The flash readings for Markit's manufacturing and service sector PMIs both rose in June, indicating the least amount of contraction since March of 2012 for the service sector (compared to finalized data) and since February of 2012 for the manufacturing sector. 

</p><p>
The downdraft in Europe seems to be slowly dissipating. The chart shows a relatively stronger and longer-lived rise for the manufacturing index compared to the services index. Indeed, the manufacturing PMI stands in the lower 29th percentile of its historic queue compared to a 19% standing for the services sector. Both of these are still extremely low readings. Viewed another way, the manufacturing index is at 95% of its historic average compared to services which is at the 91st percentile of its historic average.

</p><p>
Both indicators are below the mark of '50' indicating ongoing contraction; both of them are below their historic mean indicating weaker than normal activity. And both of them are on an improving trend of some sort.

</p><p></p>
The manufacturing index has been moving up relatively strongly since about August 2012. During that move, there was a decline in October 2012 and two recent declines in March and in April 2013. The increases in May and June 2013, however, have now brought manufacturing back up to a local cycle high reading, its best since February 2012.

<p>
The services index shows a much flatter profile. It has now risen for three months in a row after falling for two months in a row in February and March; it has generally been increasing since October 2012.

</p><p>
Other Euro area data continue to be mixed. The economy in Europe is still not doing well, but the PMI data are speaking to the issue of the degree of decline and that is letting up. Europe has great internal differences in terms of the PMI values for individual country members. We will get more on that when the final figures are released. For now, we will note that France's PMI index for manufacturing jumped in June to 48.3 from 46.4 in May- even so that measures a decline in the French MFG sector. France's services PMI rose by more than two points on the month as well. In Germany the two sector PMI gauges translated into a net gain in its private sector in June for the second month in a row. Even so, the German MFG sector took a step back to 48.7 in June from 49.4 in May.  

</p><p>
Conditions in the Zone remain somewhat unpredictable in spite of the month's overall improvement. The news today from China of a weakening in the MFG PMI there is an offsetting bit of disturbing global news. Early data in the US seem to be better than expected for housing and for a regional MFG report on manufacturing from the Philadelphia Fed region. 

</p><p>
Still, markets are wary about the Fed down-shifting its support. Data have blown hot and cold. While Europe seems to have a trend improvement in train (less weakness) markets and central banks remain wary, The Fed, in its zeal to end QE, still is using language of a very hedged nature. Meanwhile, many inflation-sensitive indicators are very weak with silver looking especially weak in today's trading. The global economy is in flux if not in play. Many Fed watchers are trying to square the Fed's newest policy choice and bond market reactions with the ongoing weak -and weakening- inflation picture globally and in the US itself.

</p><p>
The picture is perplexing. The outlook while possibly better and stronger is also still with a good deal of risk even as the Fed says it sees less risk. The recent drop in inflation has caught some attention but not yet headlines and is the focus of at least one Fed member, St Louis Fed President, James Bullard. There are still a lot of interesting international twists and turns in the data that merit our full attention. We are not yet 'off to the races' despite what some of today's data might suggest. 
</p>

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The flash readings for Markit's manufacturing and service sector PMIs both rose in June, indicating the least amount of contraction since March of 2012 for the service sector (compared to finalized data) and since February of 2012 for [...]

EMU Down-Draft Abates

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            <p> Economic recovery is
      taking hold. The Philadelphia Federal
      Reserve Bank reported that its General Business Conditions Index for June
      jumped to 12.5. This figure was the highest level since April 2011 and it
      followed an unrevised -5.2 in May. Another negative reading (-2.0) had
      been expected. <b>Haver Analytics constructs a seasonally adjusted figure
      comparable to the ISM index. It also rose but more moderately to 49.6, its
      highest level since December. </b>During the last ten years there has been
      a 71% correlation between the adjusted Philadelphia Fed index and real GDP
      growth.</p>
      <p>Improvement in the Composite Index was driven by a surge in new orders
      to its highest level (16.6) since March 2011. The shipments series also
      recovered handsomely to its highest level this year (4.1). Lesser
      improvement was logged by unfilled orders and employment. During the last
      ten year there has been a 79% correlation between the employment index and
      the m/m change in nonfarm payrolls. To the downside, the delivery times
      and inventories indexes slipped. </p>
      <p>Pricing power recovered sharply m/m to its highest level since December.
      A sharply higher 28.2% of firms paid higher prices while a reduced 5.7%
      paid less. During the last ten years there has been a 71% correlation
      between the prices paid index and three-month growth in the intermediate
      goods PPI.</p>
      <p>The separate index of expected business conditions in six months
      advanced to 33.7, the highest level in nine months. The employment figure
      surged to its highest reading since April 2011. The readings for new
      orders, shipments, unfilled orders also improved significantly.</p>
      <p>The survey panel consists of 150 manufacturing companies in Federal
      Reserve District III (consisting of southeastern PA, southern NJ and
      Delaware.) The diffusion indexes represent the percentage of respondents
      indicating an increase minus the percentage indicating a decrease in
      activity. The figures from the Philadelphia Federal Reserve can be found
      in Haver's <b>SURVEYS</b> database. The Consensus expectations figure is
      available in <b>AS1REPNA</b>.&nbsp; 
            </p>

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      <p>&nbsp;</p>


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	<colgroup><col><col><col><col><col><col><col><col></colgroup>
        <thead>
          <tr>
            <th class="firstcol" >Philadelphia Fed (%, SA)</th>
            <th scope="col">Jun</th>
            <th scope="col" >May</th>
            <th scope="col" >Apr</th>
            <th scope="col" >Jun'12</th>
            <th scope="col" >2012</th>
            <th scope="col" >2011</th>
            <th scope="col" >2010</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol" >ISM-Adjusted General Business
              Conditions</td>
            <td>49.6</td>
            <td  >45.8</td>
            <td  >46.1</td>
            <td  >44.7</td>
            <td  >47.7</td>
            <td  >51.9</td>
            <td  >50.7</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >General Business Conditions</td>
            <td>12.5</td>
            <td  >-5.2</td>
            <td  >1.3</td>
            <td  >-12.8</td>
            <td  >-0.2</td>
            <td  >7.7</td>
            <td  >12.1</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;New Orders</td>
            <td>16.6</td>
            <td  >-7.9</td>
            <td  >-1.0</td>
            <td  >-13.1</td>
            <td  >-0.1</td>
            <td  >7.2</td>
            <td  >5.5</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Shipments</td>
            <td>4.1</td>
            <td  >-8.5</td>
            <td  >9.1</td>
            <td  >-13.8</td>
            <td  >-1.4</td>
            <td  >9.9</td>
            <td  >8.3</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Unfilled Orders</td>
            <td>-7.9</td>
            <td  >-9.3</td>
            <td  >-8.7</td>
            <td  >-11.3</td>
            <td  >-6.5</td>
            <td  >-0.9</td>
            <td  >-3.0</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Delivery Time</td>
            <td>-9.3</td>
            <td  >-6.0</td>
            <td  >-13.8</td>
            <td  >-14.0</td>
            <td  >-9.1</td>
            <td  >-0.4</td>
            <td  >0.9</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Inventories</td>
            <td>-6.6</td>
            <td  >4.1</td>
            <td  >-22.2</td>
            <td  >-7.8</td>
            <td  >-6.0</td>
            <td  >-0.3</td>
            <td  >-4.9</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >&nbsp;&nbsp;Number of Employees</td>
            <td>-5.4</td>
            <td  >-8.7</td>
            <td  >-6.8</td>
            <td  >2.3</td>
            <td  >0.0</td>
            <td  >11.0</td>
            <td  >4.7</td>
          </tr>
          <tr>
            <td class="firstcol" >&nbsp;&nbsp;Prices Paid</td>
            <td>22.5</td>
            <td  >6.9</td>
            <td  >3.1</td>
            <td  >5.4</td>
            <td  >17.6</td>
            <td  >39.3</td>
            <td  >29.0</td>
          </tr>
        </tbody>
      </table>
      </span>
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Economic recovery is taking hold. The Philadelphia Federal Reserve Bank reported that its General Business Conditions Index for June jumped to 12.5. This figure was the highest level since April 2011 and it followed an unrevised -5.2 [...]

Philadelphia Fed Business Conditions Index Recovers to a Two-Year High

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      <p><b>Initial unemployment insurance claims rose</b> to 354,000 (-8.3%
      y/y) during the week ended June 15 from a revised 336,000 during the week
      prior, initially reported as 334,000. Consensus expectations were for 340,000
      claims. The four week moving average of claims nudged up to 348,250. The
      latest claims figure covers the survey period for June nonfarm payrolls.
      There was a 10,000 increase (2.9%) from May. During the last ten years,
      there has been a 74% correlation between the level of claims and the m/m
      change in nonfarm payrolls.</p>
      <p>Continuing claims for unemployment insurance in the week ended June 8
      fell to 2.951 million (-11.1% y/y) from a revised 2.991 million. The four
      week moving average of continuing claims ticked up to 2.979 million. The
      insured rate of unemployment held at 2.3% where it's been for nine weeks.
      This particular count covers only &quot;regular&quot; programs and does
      not include all extended benefit and other specialized jobless insurance
      programs. In the week of June 1, the latest figure available, the grand
      total of all benefit recipients rose w/w to 4.534 million, (-22.1% y/y).
      That compares to a cycle peak of 12.060 million in January 2010. The
      number of individuals who are collecting emergency and extended payments
      fell to a cycle low of 1.684 million (-33.5% y/y).</p>
      <p><b>By state,</b> the insured unemployment rate continued to vary
      greatly with South Dakota (0.48%), Virginia (1.24%), Oklahoma (1.39%),
      Texas (1.56%),&nbsp; Indiana (1.57%), Ohio (1.60%), Tennessee (1.67%) and
      Georgia (1.67%) at the low end of the range. At the high end were Michigan
      (1.94%), New York (2.50%), Massachusetts (2.50%), Illinois (2.58%), Nevada
      (2.80%), California (2.89%), Pennsylvania (2.98%) and New Jersey (3.10%).</p>
      <p>Data on weekly unemployment insurance are contained in Haver's <b>WEEKLY</b>
      database and they are summarized monthly in <b>USECON</b>. Data for
      individual states are in <b>REGIONW</b>. The consensus estimates come from
      the Action Economics survey, carried in the <b>AS1REPNA</b> database.</p>
      <p><b>Estimating the Trend in Employment Growth </b>from the Federal
      Reserve Bank of Chicago is available <a href="http://www.chicagofed.org/digital_assets/publications/chicago_fed_letter/2013/cfljuly2013_312.pdf">here</a>.</p>

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      <p>&nbsp;</p>


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	<colgroup><col><col><col><col><col><col><col><col></colgroup>
	
        <thead>
          <tr>
            <th class="firstcol" scope="col" >Unemployment Insurance
              (000s)</th>
            <th scope="col" >06/15/13</th>
            <th scope="col" >06/08/13</th>
            <th scope="col" >06/01/13</th>
            <th scope="col" >Y/Y %</th>
            <th scope="col" >2012</th>
            <th scope="col" >2011</th>
            <th scope="col" >2010</th>
          </tr>
        </thead>
        <tbody>
          <tr>
            <td class="firstcol" >Initial Claims</td>
            <td  >354</td>
            <td  >336</td>
            <td  >346</td>
            <td  >-8.3</td>
            <td  >375</td>
            <td  >409</td>
            <td  >459</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >Continuing Claims</td>
            <td  >--</td>
            <td  >2,951</td>
            <td  >2,991</td>
            <td  >-11.1</td>
            <td  >3,318</td>
            <td  >3,744</td>
            <td  >4,544</td>
          </tr>
          <tr>
            <td class="firstcol" >Insured Unemployment Rate (%)</td>
            <td  >--</td>
            <td  >2.3</td>
            <td  >2.3</td>
            <td  >2.6<br>
              (6/12)</td>
            <td  >2.6</td>
            <td  >3.0</td>
            <td  >3.6</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >Total &quot;All Programs&quot;
              (NSA)</td>
            <td  >--</td>
            <td  >--</td>
            <td  >4.534</td>
            <td  >-22.5</td>
            <td  >6.047M</td>
            <td  >7.750M</td>
            <td  >9.850M</td>
          </tr>
        </tbody>
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Initial unemployment insurance claims rose to 354,000 (-8.3% y/y) during the week ended June 15 from a revised 336,000 during the week prior, initially reported as 334,000. Consensus expectations were for 340,000 claims. The four week [...]

U.S. Initial Jobless Insurance Claims Move Higher

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      <p>As expected, the Federal Open Market Committee today left the Federal
      funds rate in a range from 0 to 1/4 percent. The Fed funds rate has
      remained unchanged since late-2008 at its lowest level ever. The discount
      rate was left at 0.75%. Also unchanged were the Fed's comments on the
      economy. &quot;Economic activity has been expanding at a moderate pace.
      Labor market conditions have shown some improvement in recent months, on
      balance, but the unemployment rate remains elevated. Household spending
      and business fixed investment advanced, and the housing sector has
      strengthened further, but fiscal policy is restraining economic growth. Inflation
      has been running below the Committee's longer-run objective, but
      longer-term inflation expectations have remained stable.&quot;</p>
      <p>New was the statement that &quot;Risks to the economic outlook for the
      economy and labor markets have diminished since the fall.&quot; The
      Committee continues to &quot;anticipate that inflation over the medium
      term likely will run at or below its 2 percent objective.&quot;</p>
      <p>&quot;The Committee decided to continue purchasing additional agency
      mortgage-backed securities at a pace of $40 billion per month and
      longer-term Treasury securities at a pace of $45 billion per month. The
      Committee is maintaining its existing policy of reinvesting principal
      payments from its holdings of agency debt and agency mortgage-backed
      securities in agency mortgage-backed securities and of rolling over
      maturing Treasury securities at auction.&quot;</p>
      <p>The &quot;exceptionally low range for the federal funds rate will be
      appropriate at least as long as the unemployment rate remains above 6-1/2
      percent, inflation between one and two years ahead is projected to be no
      more than a half percentage point above the Committee's 2 percent
      longer-run goal, and longer-term inflation expectations continue to be
      well anchored.&quot;</p>
      <p>The press release for today's <b>FOMC meeting</b> can be found <a href="http://www.federalreserve.gov/newsevents/press/monetary/20130619a.htm">here</a>.</p>
      <p>Haver's <b>SURVEYS</b> database contains the projections from the
      Federal Reserve Board. The economic data can be found in Haver's <b>USECON
      </b>database. </p>
      <p><b>Low Inflation in a World of Securitization</b> from the Federal
      Reserve Bank of St. Louis can be found here <a href="http://research.stlouisfed.org/publications/es/article/9801">here</a>.</p>
 
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	<colgroup><col><col><col><col><col><col><col><col></colgroup>
        <thead>
          <tr>
            <th class="firstcol" scope="col" >&nbsp;</th>
            <th scope="col"><b>Current</b></th>
            <th scope="col"><b>Last</b></th>
            <th scope="col"><b>2012</b></th>
            <th scope="col"><b>2011</b></th>
            <th scope="col"><b>2010</b></th>
            <th scope="col"><b>2009</b></th>
          </tr>
        </thead>
        <tbody>
          <tr class="odd">
            <td class="firstcol" >Federal Funds Rate, % (Target</td>
            <td>0.00-0.25</td>
            <td>0.00-0.25</td>
            <td>0.14</td>
            <td>0.10</td>
            <td>0.17</td>
            <td>0.16</td>
          </tr>
          <tr class="odd">
            <td class="firstcol" >Discount Rate, %</td>
            <td>0.75</td>
            <td>0.75</td>
            <td>0.75</td>
            <td>0.75</td>
            <td>0.72</td>
            <td>0.50</td>
             </tr>
              </tbody>
            </table>
            </span>
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As expected, the Federal Open Market Committee today left the Federal funds rate in a range from 0 to 1/4 percent. The Fed funds rate has remained unchanged since late-2008 at its lowest level ever. The discount rate was left at [...]

FOMC Leaves Fed Funds, Economic Outlook and Securities Purchases Unchanged

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

Largest October layoffs since 2003, led by technology

Subdued global shipping costs not yet pointing to supply chain problems

PMIs show still-elevated but slowing US inflation

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Andrew Cates

**Energy shock lifts inflation, trims growth**
The IMF’s latest WEO revisions for 2026 broadly reflect the classic stagflationary impact of the recent Middle East energy shock, with growth downgraded and inflation revised higher across most major economies. Higher energy prices act as a tax on real incomes while simultaneously pushing up costs. That said, the picture is not uniform: a number of economies—notably the US, China and India—have seen growth upgrades, reflecting stronger-than-expected momentum so far in 2026. By contrast, the UK stands out at the stagflationary extreme, combining one of the largest growth downgrades with a relatively strong inflation uplift—consistent with its weaker underlying momentum, greater energy sensitivity and more persistent domestic inflation dynamics. More broadly, while the global revisions remain modest—pointing to resilience in activity—the message is that disinflation is no longer a smooth glide back to target but increasingly contingent on energy prices and geopolitical developments.

260423Z1.jpg

**Markets largely shrug off rising economic pessimism**
Notwithstanding a more downbeat assessment from economists—including the IMF’s stagflationary tilt to the outlook—there has been remarkably little follow-through into financial markets. Measures of systemic stress in both the US and UK remain low by historical standards, suggesting that investors are, for now, largely looking through the Middle East conflict. There are several possible explanations: corporate profits remain resilient, the AI-driven investment narrative continues to dominate market thinking, and markets may be assuming that any energy shock will be temporary and contained. In effect, investors appear to be pricing a benign baseline in which geopolitical risks do not materially disrupt growth, inflation expectations or policy. The UK is a partial exception, with a somewhat more visible uptick in stress, which aligns more closely with the IMF’s more challenging growth-inflation trade-off and the economy’s greater sensitivity to energy prices.

260423Z2.jpg

**Volatility falls despite deteriorating growth surprises**
Market optimism is also increasingly at odds with the incoming data flow. Typically, equity volatility declines when growth surprises are positive and inflation surprises are benign. However, the recent pattern has broken that relationship. Growth surprises across the G10 have turned increasingly negative (our series is inverted in the chart below), yet volatility has continued to fall. In other words, markets are becoming less sensitive to weakening macro data, continuing to price a benign outlook even as the data deteriorate. This divergence reinforces the broader theme: investors are, for now, looking through both geopolitical risks and softer economic momentum, placing greater weight on resilience in earnings, the AI-driven narrative and the assumption that policy will remain supportive.

260423Z3.jpg

**Inflation Nowcasts Have Jumped**
Incoming data suggest that headline inflation has moved higher in recent weeks, broadly in line with expectations given the rise in energy prices following the Middle East shock. Nowcasts for CPI across the major economies show a clear rebound in March and April from the lows seen at the start of 2026, with the move occurring in a relatively synchronised fashion. This reinforces the view that the recent pickup in inflation is being driven primarily by a common external factor—energy.

260423Z4.jpg

**Energy shock not yet feeding into underlying inflation**
However, the detailed breakdown of March inflation outcomes suggests that this remains, for now, a largely headline-driven phenomenon. While headline CPI prints were firm across most economies, core inflation—stripping out energy and food—was more subdued and in some cases weaker. This indicates that there has been very limited pass-through from higher energy prices into broader goods and services inflation at this early stage. In other words, the shock is still being absorbed rather than propagated. That distinction is critical for policy and markets alike: as long as second-round effects remain contained, central banks may be able to look through the near-term rise in inflation, even as headline rates move higher.

260423Z5.jpg

**Inflation Expectations Rising as Growth Sentiment Falters**
It remains early days, and much will hinge on how inflation expectations evolve from here. The latest ZEW survey for Germany already conveys the hallmarks of a classic stagflationary shock, with macroeconomic expectations weakening even as inflation expectations have ratcheted sharply higher. This shift is important: while the recent rise in headline inflation has so far shown limited pass-through into core, a sustained increase in expectations would raise the risk of second-round effects and make the inflation process more persistent. In that sense, the ZEW data highlight the key fault line in the current environment—whether the energy-driven shock remains contained, or begins to embed itself more broadly through expectations and pricing behaviour.

260423Z6.jpg

Financial markets have remained notably calm in recent weeks despite rising geopolitical tensions in the Middle East, a more downbeat macroeconomic narrative and elevated uncertainty. Measures of financial stress and volatility remain low, and equity markets continue to look through both the conflict and softer data. That resilience sits alongside a more nuanced macro backdrop. The IMF’s latest WEO revisions point to a classic stagflationary energy shock—growth downgraded and inflation revised higher—although the global impact remains modest and uneven, with some economies still benefiting from stronger momentum (chart 1). At the same time, market pricing appears increasingly detached from the data flow, with volatility declining even as growth surprises have turned more negative relative to inflation (charts 2 and 3). Incoming inflation data reinforce the idea of a largely headline-driven shock, with nowcasts rising in line with higher energy prices but only limited pass-through into core inflation so far (charts 4 and 5). However, it remains early days. Survey evidence, such as the latest ZEW release, suggests that inflation expectations may already be responding in a more concerning way, with a marked rise alongside weakening growth sentiment (chart 6). Taken together, the key question for markets is whether this remains a contained, energy-driven shock that can be looked through—or whether it begins to embed more persistently via expectations, forcing a reassessment of the currently benign outlook.

<iframe data-testid="embed-iframe" style="border-radius:12px" src="https://open.spotify.com/embed/episode/44A12ktUaoJGHZG7pEVcul?utm_source=generator" width="100%" height="152" frameBorder="0" allowfullscreen="" allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture" loading="lazy"></iframe>

Charts of the Week: Risks Build, Markets Shrug

260424E.jpg

The onset of the war in Iran appears to have hit the German economy extremely hard as the Ifo survey shows very substantial and broad-based decline across its survey in April. The Ifo survey features readings for five sectors as well as an aggregate reading, and it surveys them for climate, current conditions, and expectations. The decline in the Ifo survey is present for all three concepts and across all five sectors, marking the weakening in April as a highly significant and extremely disturbing development. Only manufacturing in the current conditions survey escapes a month-to-month decline.

**The Ifo sequences**: The **climate** reading fell both overall and across each of the five sectors. **Current conditions** declined for the overall and for four of the five sectors, with manufacturing the sole exception. **Expectations** declined for the overall and for all sectors. Several of the sector declines were for a very substantial magnitude, especially when compared to historic changes in these indexes.

**Monthly changes in readings—severe broad deterioration**
The month-to-month change in the climate reading has weakened more month-to-month 19% of the time. That overall result, however, is boosted by manufacturing where the monthly change has been weaker 35% of the time (on data back to 2011). However, all other sectors have seen climate weaker m/m only 2.3% to 6.3% of the time! The current situation readings weakened, with the headline weakening more m/m 11% of the time. This was boosted by manufacturing, the only sector that improved on the month; its ranking on change was in its 85th percentile—quite good and truly stand-alone good news. The other current changes by sector ranged from construction being weaker 1.7% of the time, to retailing that has been weaker about 30% of the time in terms of m/m changes. Expectation changes were uniformly terrible, with the headline drop weaker only 6.3% of the time and sector change month-to-month weaker between 9% and 1.7% of the time. The monthly weakening was uniform and substantial. I document it with these calculations, but you can also see it on the chart above.

**Climate**: The bottom line is that the all-sector index for climate fell to -20.3 in April from -18 in March, placing it at a 10.5 percentile standing on data since 1993. The sector ranking is the highest for construction with a 42.2 percentile standing and the weakness for services at a 1.1 percentile standing—weaker than the table reading nearly 99% of the time. In terms of percentile standing levels or monthly changes, conditions are closing in on grim.

**Current conditions**: Current conditions saw the all-sector index slip to -5.3 in April from -2.4 in March. The headline ranking stands at a 9.8 percentile mark, making it—like the climate reading—weaker than its current reading only about 10% of the time. The strongest reading under current conditions is for construction which has a 60.6 percentile standing; it is the only ranking in the table above its historic median. Manufacturing, the only sector in the survey that improved month-to-month, has a 22.5 percentile standing, while services record the weakest percentile standing under current conditions, at an 8.4 percentile standing.

**Expectations:** The all-sector index for expectations fell to -25.3 in April from -19.9 in March, placing it at a 6.3 percentile standing. The percentile standings across sectors range from a high of 9.5% for manufacturing to a low of 1.5% for retailing. Up until earlier this year, the Ifo was showing signs of improvement; however, all of that has simply collapsed in the last month. Weakness is across economic concepts and sectors, as documented above. For reference, the table also gives a separate set of rankings on where the various indexes stand since the invasion of Ukraine, since that was another marked event that drove the index, that had been improving after Covid, down to lower levels.  Ranked even on this reduced scale looking at conditions only since the invasion of Ukraine, when conditions have generally been weaker, the current rankings across the Ifo survey remained extremely weak. This is a very disturbing survey for the German economy.

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Germany

German Ifo Plunges Everywhere

Sandy Batten

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The National Activity Index published by the Federal Reserve Bank of Chicago (CFNAI) slipped to -0.20 in March from an upwardly revised +0.03 in February (previously (-0.11). This is the lowest monthly reading since last November. Smoothing out the monthly volatility, the index's three-month moving average (CFNAI-MA3) declined to -0.03 in March from an upwardly revised +0.03 in February (previously -0.01).

This index is expressed in standard deviation units from zero (with a value of zero defined as trend real GDP growth). Research at the FRB Chicago indicates that readings on the 3-month average of -0.70 or below are consistent with the economy being in a recession. Therefore, even though the March reading on the 3-month average was negative, it indicates that the US economy is still growing, just slightly slower than trend, and is well away from recessionary conditions. The 3-month average would be much deeper in negative territory if the economy was at risk of contracting.

The National Activity Index is a composite of 85 economic indicators, grouped into four major categories: production and income; employment, unemployment, and hours worked; personal consumption and housing; sales, orders, and inventories. Three of the four broad categories of indicators used to construct the index decreased from February, and three categories made negative contributions in March. Production-related indicators contributed –0.20 to the CFNAI in March, down from +0.13 in February. The sales, orders, and inventories category's contribution to the CFNAI was –0.01 in March, down from +0.05 in February. Employment-related indicators contributed +0.02 to the CFNAI in March, up from –0.15 in February. The personal consumption and housing category's contribution to the CFNAI was –0.01 in March, down from a neutral value in February.

The CFNAI Diffusion Index, which measures the breadth of the change in the component series and is also a three-month moving average, increased to –0.04 in March from –0.08 in February. This is the highest reading since February 2025. A reading of zero indicates that all of the indicators are growing at their long-term average. If all of the underlying indicators in a given month are below their long-run averages, the diffusion index will equal -1. If all of the indicators are above their long-run averages, it will equal +1. Thirty-four of the 85 individual indicators made positive contributions to the CFNAI in March, while 51 made negative contributions. Forty-three indicators improved from February to March, while 40 indicators deteriorated and two were unchanged. Of the indicators that improved, 16 made negative contributions.

These figures are available in Haver's **SURVEYS** database.

- The monthly reading fell to -0.20 in March from an upwardly revised +0.03 in February.
- The three-month average slipped from +0.03 to -0.03.
- Despite the slip in March, the index points to near-trend economic growth and is well above recession territory.

Chicago Fed National Activity Index Slipped in March

Kathleen Stephansen, CBE

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Initial claims for unemployment insurance rose by 6,000 to 214,000 in the week ending April 18, from 208,000 in the week ending April 11, revised from 207,000. The four-week average rose 750 to 210,750 in the week ending April 18, from 210,000 the April 11 week, revised from 209,750. The Action Economics/Haver Analytics Survey looked for 210,000 claims to have been filed.

The total number of unemployment insurance beneficiaries—also known as “continuing claims”—rose by 12,000 to 1.821 million in the week ending April 11, from 1.809 million in the week ending April 4. The four-week moving average rose to 1.812 million in the latest week from 1.811 million in the March 28 week. The insured unemployment rate remained at 1.2% in the week of April 11. It has remained at that level since the week of November 29, 2025.

The insured unemployment rate varied greatly across individual states and territories. In the week ending April 4, the highest unemployment rates were in New Jersey (2.51%), Massachusetts (2.37%), Rhode Island (2.31%), Washington (2.25%), Minnesota (2.11%), and California (2.02%). The lowest rates were in Florida (0.30%), Louisiana (0.31%), Arkansas (0.35%), Alabama (0.36%), North Carolina (0.39%), Tennessee (0.46%), South Dakota (0.47%), Kansas and Virginia (both 0.49%). Rates in other notable states include New York (1.92%), Illinois (1.82%), Pennsylvania (1.52%), and Texas (1.04%). 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 6,000 to 214,000.
- Continuing claims rose by 12,000 to 1.821 million.
- The insured unemployment rate remained at 1.2%.


U.S. Initial Unemployment Claims Rose in the Week of April 18

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**Manufacturing looks strong while service sectors weaken**
S&P's April flash PMI readings show some very mixed results. For the United States, India, Australia, and the United Kingdom, there is a strengthening in the readings month-to-month for services, manufacturing, and the composite.

For Japan, France, and the European Monetary Union as a whole, there is improvement in the manufacturing sector on the month but a weaker services reading and a weaker composite overall.

Germany is the only responding area in the table showing weakness all around—in all three sectors—a weaker composite, a weaker manufacturing sector, and a weaker services sector in April. For Germany, this follows a weaker composite and service sector in March as well.

Most reporters—France, the United Kingdom, Japan, Australia, and India—had weaker readings for all three metrics in March: the composite, services, and manufacturing. The March exceptions were the United States, Germany, and the European Monetary Union; in each case, the exception was that the manufacturing sector improved month-to-month, while the composite and services both weakened.

This has been a period of weakening—in March and April—since the war in Iran began. The 48 separate sector readings produced 30 readings that were weaker month-to-month in March and April. Among the 16 composite readings, 12 reported weaker conditions month-to-month. In March, the immediate aftermath of the outbreak of war brought instantaneous step backs across the PMI readings, while April, responding to at least a military success in the area, has shown a significant bounce back that is now more common than further weakness.

The sequential data over three months, six months, and 12 months are based only on completed data; therefore, they're up to date through March. On that basis, we have triple sector weakness in the U.S., India, and Australia, with only Japan and the United Kingdom showing triple-sector improvement over three months. However, if we look at six months compared to 12 months, we have triple sector strength in the Monetary Union, Germany, France, the United Kingdom, Japan, and Australia. India and the U.S. each show only one stronger sector over that comparison—services in India’s case and manufacturing in the U.S. case.

**Ranking Peculiarity**
The ranking data take the current flash data and compare them to the history of observations back to January 2022. What is quite surprising is that, on that timeline, the manufacturing sectors of all the countries in the table—except for Australia and India—show manufacturing standings in their respective 80th to 90th percentiles. Meanwhile, services standings are typically in the 30th percentile or lower.

**Odd Impact of War**
If the war in Iran has an impact on something, we would expect that to fall on the goods trade sector. We would expect this to have an impact on manufacturing although it's the opposite thing that's happening. Manufacturing is showing a revival, while services sectors are showing weaker performance across these countries generally. India is an interesting case, with manufacturing only in its 32nd percentile; however, India’s raw diffusion reading for manufacturing is the strongest raw diffusion reading in the table. What India's ranking is telling us is that India had been extremely strong over the period since 2022, and now compared to that past standard, it's relatively weaker. However, it's still strong in absolute terms, showing a great deal of strength based on its pure diffusion value, just not in comparison to historic performance.

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**Next?**
At this point, it's not clear to me at least what these PMI data are telling us since the strength in manufacturing is a curiosity as is the weakness in the services sector. You see these two phenomena displayed in the chart above, in the case of the European Monetary Union’s flash readings as well.

**War breeds negative effects**
It's not a surprise that war would take some toll on consumer confidence or that it would be reflected in the services sector. However, seeing the kind of weakness being portrayed now in services against the strength in manufacturing is simply a bit hard to rationalize and understand. So, I think we're going to have to keep an eye on these readings as well as other readings in the months ahead to try to discern how global events, the war, conditions in the Strait of Hormuz, inflation currency shifts, and central bank policy are playing out across these various countries. None of what is happening is obvious to me. Japan clearly continues to benefit from a weak yen as its manufacturing sector is flying high, at its best reading since January 2022.

Economy in Brief

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U.S. Chicago Fed National Activity Index Remains Negative

State Unemployment Rates Continue Lower but Vary Greatly

State Unemployment Rates Continue Lower but Vary Greatly

U.S. Leading Economic Indicators Rise on Financial Series' Strength

EMU Down-Draft Abates

Philadelphia Fed Business Conditions Index Recovers to a Two-Year High

U.S. Initial Jobless Insurance Claims Move Higher

FOMC Leaves Fed Funds, Economic Outlook and Securities Purchases Unchanged