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You are viewing Micro News from Friday, Mar 7, 2014 - View all recent Micro News
  • 3/7/14
    What does all that "Weather Stuff" mean in the Payrolls Data?

    You're not alone if connecting these dots is a bit confusing.  Hopefully this will be somewhat of a roadmap for the significance of the weather-related data in this morning's payrolls report.

    Background facts:

    - There are two surveys in the Employment Situation: Establishment and Household.  NFP comes from Establishment, Unemployment rate from Household. 

    - In order to NOT count in NFP, a worker would have to be absent for the entire pay period.

    - Just over 20% of workers have 1-week pay periods

    - The Household survey asks workers if they had a job, but missed the whole week due to weather!  (These people would be counted as employed in the Household survey, but not in the establishment survey).

    From there, let's look at what happened last report vs current...

    In January's data (reported early Feb), 262,000 workers said they missed the whole week due to weather.  That's historically low, and no big deal (although on an unrelated note, that does lend some credence to how some economic data was surprisingly strong in January vs December).

    The jump up in February's data (today) was big.  There are now 601,000 workers saying they didn't work for the whole week due to weather. 

    In both cases, 20% of these workers can be assumed to be 'missing' from the NFP figure (because 20% of workers have 1-week pay periods and NFP only counts you if you worked during that pay period).

    Such absences will ALWAYS detract from NFP (i.e. the fact that we can assume they're 'missing' isn't some scandalous revelation... it's always like that), but what we're interested in is the DIFFERENCE from the last report, and more importantly from the average/median February data.

    So, from the last report where 262k workers didn't work that week to 601k claiming the same this week, we have a difference of 

    601k - 262k = 339k

    20% of those have one week pay periods and therefore are not likely counted in NFP.

    339k*20% = 67.8k

    More important is the difference in this February vs the average past February (helps us assess "how many more jobs would we have seen without the weather?"  The $64k question...)

    The average number of workers reporting no work during the survey period for the past 10 Februaries is 356.8k (tally the Feb column on this page and divide by 11). 

    601k (this report) - 356.8k (average report) = 244.2k

    So the difference between this report and the average is 244.2k.  In other words, 244.2k fewer people than normal worked during the survey week.  And 20% of those folks only have 1-week pay periods, meaning they wouldn't be counted in NFP. So.......

    244.2k*20% = 48.84k

    CONCLUSION: It's strongly possible that payrolls would be at least 48k higher if the weather effect had been in the middle of it's historical range (one of those months spiked to over 1000k, so using the historical median as opposed to the average makes this figure jump to over 70k).

    Category: MBS, UPDATE
    Share:   
  • 3/7/14
    The Weather was Such a Big Deal, BLS Spent a lot of Time Talking About it

    In the accompanying FAQ found HERE

    How can unusually severe weather affect employment and hours estimates?  

    In the establishment survey, the reference period is the pay period that includes   the 12th of the month. Unusually severe weather is more likely to have an impact on   average weekly hours than on employment. Average weekly hours are estimated for paid   time during the pay period, including pay for holidays, sick leave, or other time off.   The impact of severe weather on hours estimates typically, but not always, results in   a reduction in average weekly hours. For example, some employees may be off work for   part of the pay period and not receive pay for the time missed, while some workers,   such as those dealing with cleanup or repair, may work extra hours.  

    In order for severe weather conditions to reduce the estimate of payroll employment,   employees have to be off work without pay for the entire pay period. Slightly more   than 20 percent of all employees in the payroll survey sample have a weekly pay   period. Employees who receive pay for any part of the pay period, even 1 hour, are counted in the payroll employment figures. It is not possible to quantify the effect of extreme weather on estimates of over-the-month change in employment.  

    In the household survey, the reference period is generally the calendar week that  includes the 12th of the month. Persons who miss the entire week's work for weather-related events are counted as employed whether or not they are paid for the time   off. The household survey collects data on the number of persons who had a job but were not at work due to bad weather. It also provides a measure of the number of   persons who usually work full time but had reduced hours due to bad weather.    Current and historical data are available on the  household survey's most   requested statistics page at http://data.bls.gov/cgi-bin/surveymost?

    Section: "Employed - Nonagriculture industries, Bad weather, With a job not at work"

    2014-3-7 weather

    Here's the kicker... From the heading: "Employment Level - Persons At Work 1-34 Hours, Noneconomic Reasons - Bad Weather, Nonagricultural Industries, Usually Work Fulltime"  (so these are folks who usually work full time, but didn't due to weather).

    2014-3-7 weather2

    Biggest weather-related disruption on labor market in this 10-yrs of record-keeping.

    Category: MBS, UPDATE
    Share:   
  • 3/7/14
    Payrolls came in 175k vs 149k forecast. Last month...
    MBS Updates are a service provided to MBS Live! subscribers only.
    Learn More | Start a Free Trial | View MBS Prices
    Category: MBS, alert
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  • 3/7/14

    You're not alone if connecting these dots is a bit confusing.  Hopefully this will be somewhat of a roadmap for the significance of the weather-related data in this morning's payrolls report.

    Background facts:

    - There are two surveys in the Employment Situation: Establishment and Household.  NFP comes from Establishment, Unemployment rate from Household. 

    - In order to NOT count in NFP, a worker would have to be absent for the entire pay period.

    - Just over 20% of workers have 1-week pay periods

    - The Household survey asks workers if they had a job, but missed the whole week due to weather!  (These people would be counted as employed in the Household survey, but not in the establishment survey).

    From there, let's look at what happened last report vs current...

    In January's data (reported early Feb), 262,000 workers said they missed the whole week due to weather.  That's historically low, and no big deal (although on an unrelated note, that does lend some credence to how some economic data was surprisingly strong in January vs December).

    The jump up in February's data (today) was big.  There are now 601,000 workers saying they didn't work for the whole week due to weather. 

    In both cases, 20% of these workers can be assumed to be 'missing' from the NFP figure (because 20% of workers have 1-week pay periods and NFP only counts you if you worked during that pay period).

    Such absences will ALWAYS detract from NFP (i.e. the fact that we can assume they're 'missing' isn't some scandalous revelation... it's always like that), but what we're interested in is the DIFFERENCE from the last report, and more importantly from the average/median February data.

    So, from the last report where 262k workers didn't work that week to 601k claiming the same this week, we have a difference of 

    601k - 262k = 339k

    20% of those have one week pay periods and therefore are not likely counted in NFP.

    339k*20% = 67.8k

    More important is the difference in this February vs the average past February (helps us assess "how many more jobs would we have seen without the weather?"  The $64k question...)

    The average number of workers reporting no work during the survey period for the past 10 Februaries is 356.8k (tally the Feb column on this page and divide by 11). 

    601k (this report) - 356.8k (average report) = 244.2k

    So the difference between this report and the average is 244.2k.  In other words, 244.2k fewer people than normal worked during the survey week.  And 20% of those folks only have 1-week pay periods, meaning they wouldn't be counted in NFP. So.......

    244.2k*20% = 48.84k

    CONCLUSION: It's strongly possible that payrolls would be at least 48k higher if the weather effect had been in the middle of it's historical range (one of those months spiked to over 1000k, so using the historical median as opposed to the average makes this figure jump to over 70k).

    Category: MBS, UPDATE
    Share:   
  • 3/7/14

    In the accompanying FAQ found HERE

    How can unusually severe weather affect employment and hours estimates?  

    In the establishment survey, the reference period is the pay period that includes   the 12th of the month. Unusually severe weather is more likely to have an impact on   average weekly hours than on employment. Average weekly hours are estimated for paid   time during the pay period, including pay for holidays, sick leave, or other time off.   The impact of severe weather on hours estimates typically, but not always, results in   a reduction in average weekly hours. For example, some employees may be off work for   part of the pay period and not receive pay for the time missed, while some workers,   such as those dealing with cleanup or repair, may work extra hours.  

    In order for severe weather conditions to reduce the estimate of payroll employment,   employees have to be off work without pay for the entire pay period. Slightly more   than 20 percent of all employees in the payroll survey sample have a weekly pay   period. Employees who receive pay for any part of the pay period, even 1 hour, are counted in the payroll employment figures. It is not possible to quantify the effect of extreme weather on estimates of over-the-month change in employment.  

    In the household survey, the reference period is generally the calendar week that  includes the 12th of the month. Persons who miss the entire week's work for weather-related events are counted as employed whether or not they are paid for the time   off. The household survey collects data on the number of persons who had a job but were not at work due to bad weather. It also provides a measure of the number of   persons who usually work full time but had reduced hours due to bad weather.    Current and historical data are available on the  household survey's most   requested statistics page at http://data.bls.gov/cgi-bin/surveymost?

    Section: "Employed - Nonagriculture industries, Bad weather, With a job not at work"

    2014-3-7 weather

    Here's the kicker... From the heading: "Employment Level - Persons At Work 1-34 Hours, Noneconomic Reasons - Bad Weather, Nonagricultural Industries, Usually Work Fulltime"  (so these are folks who usually work full time, but didn't due to weather).

    2014-3-7 weather2

    Biggest weather-related disruption on labor market in this 10-yrs of record-keeping.

    Category: MBS, UPDATE
    Share:   
  • 3/7/14
    Payrolls came in 175k vs 149k forecast. Last month...
    MBS Updates are a service provided to MBS Live! subscribers only.
    Learn More | Start a Free Trial | View MBS Prices
    Category: MBS, alert
    Share:   
 
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