His comments on selective perception, cognitive bias, the "recency effect" and the soft prejudice of low expectations apply well beyond the NFP example.
Let's begin with a quick word on cognitive bias. Humans are guilty of this -- selectively perceiving and recalling what agrees with their world view. We are all guilty of this, and while we cannot escape it, being aware of it at least allows some measure of recognition, and perhaps, adaptation to the phenomena.Unfortunately, the two trend chart he shows only go back three years (suffering themselves from the recency effect) so we can't compare the relatively weak current numbers to the NFP increases of the 1990s. The two charts shown in the Bureau of Labor Statistics Employment Situation Report also only go back 3 years.Let's use the NFP data as an example: Consider another bias, the Human tendency to overemphasize more recent data versus the totality of information and the overall trend. This is a cognitive bias known as the recency effect. Despite the overwhelming evidence showing this to be a generally weak jobs recovery (the worst since WWII), our primate brains interpret a single good data point as proof of something better. ...
Regardless, we also see some of the soft prejudice of low expectations in yesterday's data: 180k is hardly a rockin' strong number, relative to population growth,. Put that into the context of recent expansions such as the 1990s. Oh, and in that more recent period, there was no BLS Birth/Death adjustment, responsible for nearly a million fictitious jobs in 2006.
So, below I have posted a 15 year view showing year over year percentage change for the seasonally adjusted value of the growth in NonFarm Payroll. It's pretty clear from this longer term chart that our growth in non-farm employment during this latest expansion never got back to the steady, multi-year 2.5% growth rate of the late 1990's and appears to be declining again.
Of course, in a subject area as complex as employment, an equally important danger in my opinion is the almost universal tendency these days to stick with just a few headline factors. If we truly want to understand employment, I believe we have to make it easy to visualize and then examine a full range of factors over a substantial time period.
For example, the recent drop off shown above does not seem to square with the reported drop in the headline unemployment rate. Maybe some other factor of the thousands of factors recorded by Bureau of Labor Statistics (BLS) can help explain it.
Too often, really important factors aren't mentioned at all, and the ones that are mentioned are not accompanied by their corresponding trend charts.
Here's a link to a short list of the most popular BLS statistics which might be a useful starting point for a deeper analysis.
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