AmazonTania
02-13-2014, 08:05 PM
The non farm payroll numbers in December were pretty abysmal, adding only 74,000 jobs to the market place. Well below the 190,000 consensus the street was forecasting. Being that this was the last month in the year, given the extreme cold weather of the month, the market — more importantly, economist Mark Zandi — is choosing to ignore it, as he feels these numbers are invalid due to the overall trend in 2013.
From CNBC (http://video.cnbc.com/gallery/?video=3000234878&play=1#eyJ2aWQiOiIzMDAwMjM0ODc4IiwiZW5jVmlkIjoieTl ENlVDaE9mM0JDWXgyMjdHTzZRZz09IiwidlRhYiI6InRyYW5zY 3JpcHQiLCJ2UGFnZSI6MSwiZ05hdiI6WyLCoExhdGVzdCBWaWR lbyJdLCJnU2VjdCI6IkFMTCIsImdQYWdlIjoiMSIsInN5bSI6I iIsInNlYXJjaCI6IiJ9):
Mark Zandi: I wouldn’t pay any attention at all to these numbers. They’re not consistent with anything. Next month this will be – we’ll get the benchmark revisions and they’ll be revised up and away. This is not consistent with anything.
So an entire month passes and we get the get the non farm payroll numbers for the month of January, and the same exact thing happens. The number of jobs created — 113,00 — was well below the market estimates of 180,000. And lucky for Mark Zandi, December’s numbers were revised away: from 74,000 to 75,000. His response: ignore it. Oh, and blame the weather.
Mark Zandi: It was still really cold in January, and early February. I think the weather is all over these numbers. I don’t think anything fundamental has changed.
There are a few things wrong with the ‘blame the weather’ excuse, which I will address here:
The Weather Is an Obvious Excuse
Of course everyone knows that the weather is an obvious excuse. But if the weather is such an obvious catalysis for the drop in payroll prints, then why were so many market analyst and economist so surprised by these numbers, and why were they expecting such a big increase in payroll prints? Citigroup expected 165K, Barclay expected 175K, HSBC expected 195K, while Goldman Sachs, JP Morgan, Bank of America and Deutsche Bank expected 200K or more.
You would also think that these experts would understand the seasonal trends and learn from their errors, but no! Some of these banks made the same forecast for January as they did for December 2013, such as Goldman Sachs, JP Morgan and Barclay, while banks like Citigroup increased their non-farm payroll forecast from 165K to 185K. While Deutsche Bank downgraded their forecast from 250K to 200K and Bank of America revised theirs from 220K to 180K. All of which still missed the headline number of 113K for January.
How the BLS Captures Employment
The excuse totally ignores how the Bureau Labour of Statistics (BLS) captures employment. The Current Employment Survey (CES), the statistics what covers the nonfarm payroll numbers, is released monthly, however, the survey only covers one week of the entire referenced month. More importantly, the week of the 12th is usually the period that is referenced for these payroll prints. While anyone can look at records of the type of weather forecast for the week of the 12th on their free time, it is quite a stretch to suggest so many people were missing work during the same week of the same month.
Not At Work Due To Weather
The BLS, for our convenience, already complies statistics of people who have missed out on work due to the weather (http://beta.bls.gov/dataViewer/view/timeseries/LNU02007327;jsessionid=A25E996BA69FC88F5FC24A62704 23D8D.tc_instance6). Using these statistics, we can gauge the significant of the impact. What you’ll find is interesting, there were more people who missed out on work due to the weather in the weather of 2010 and 2011. Keep in mind, the recovery officially started in 2009, so the state of the economy cannot be used as an excuse here.
In fact, there were less people who missed out on work during the winter of 2014, than any other winter within the last 6 years.
http://imagizer.imageshack.us/v2/640x480q90/197/9ov5.png
I’m sure this information will be overlooked. After all, it’s not going to be cold forever, which means Zandi will not be able to use this excuse forever.
From CNBC (http://video.cnbc.com/gallery/?video=3000234878&play=1#eyJ2aWQiOiIzMDAwMjM0ODc4IiwiZW5jVmlkIjoieTl ENlVDaE9mM0JDWXgyMjdHTzZRZz09IiwidlRhYiI6InRyYW5zY 3JpcHQiLCJ2UGFnZSI6MSwiZ05hdiI6WyLCoExhdGVzdCBWaWR lbyJdLCJnU2VjdCI6IkFMTCIsImdQYWdlIjoiMSIsInN5bSI6I iIsInNlYXJjaCI6IiJ9):
Mark Zandi: I wouldn’t pay any attention at all to these numbers. They’re not consistent with anything. Next month this will be – we’ll get the benchmark revisions and they’ll be revised up and away. This is not consistent with anything.
So an entire month passes and we get the get the non farm payroll numbers for the month of January, and the same exact thing happens. The number of jobs created — 113,00 — was well below the market estimates of 180,000. And lucky for Mark Zandi, December’s numbers were revised away: from 74,000 to 75,000. His response: ignore it. Oh, and blame the weather.
Mark Zandi: It was still really cold in January, and early February. I think the weather is all over these numbers. I don’t think anything fundamental has changed.
There are a few things wrong with the ‘blame the weather’ excuse, which I will address here:
The Weather Is an Obvious Excuse
Of course everyone knows that the weather is an obvious excuse. But if the weather is such an obvious catalysis for the drop in payroll prints, then why were so many market analyst and economist so surprised by these numbers, and why were they expecting such a big increase in payroll prints? Citigroup expected 165K, Barclay expected 175K, HSBC expected 195K, while Goldman Sachs, JP Morgan, Bank of America and Deutsche Bank expected 200K or more.
You would also think that these experts would understand the seasonal trends and learn from their errors, but no! Some of these banks made the same forecast for January as they did for December 2013, such as Goldman Sachs, JP Morgan and Barclay, while banks like Citigroup increased their non-farm payroll forecast from 165K to 185K. While Deutsche Bank downgraded their forecast from 250K to 200K and Bank of America revised theirs from 220K to 180K. All of which still missed the headline number of 113K for January.
How the BLS Captures Employment
The excuse totally ignores how the Bureau Labour of Statistics (BLS) captures employment. The Current Employment Survey (CES), the statistics what covers the nonfarm payroll numbers, is released monthly, however, the survey only covers one week of the entire referenced month. More importantly, the week of the 12th is usually the period that is referenced for these payroll prints. While anyone can look at records of the type of weather forecast for the week of the 12th on their free time, it is quite a stretch to suggest so many people were missing work during the same week of the same month.
Not At Work Due To Weather
The BLS, for our convenience, already complies statistics of people who have missed out on work due to the weather (http://beta.bls.gov/dataViewer/view/timeseries/LNU02007327;jsessionid=A25E996BA69FC88F5FC24A62704 23D8D.tc_instance6). Using these statistics, we can gauge the significant of the impact. What you’ll find is interesting, there were more people who missed out on work due to the weather in the weather of 2010 and 2011. Keep in mind, the recovery officially started in 2009, so the state of the economy cannot be used as an excuse here.
In fact, there were less people who missed out on work during the winter of 2014, than any other winter within the last 6 years.
http://imagizer.imageshack.us/v2/640x480q90/197/9ov5.png
I’m sure this information will be overlooked. After all, it’s not going to be cold forever, which means Zandi will not be able to use this excuse forever.