I purposed this ^ question for my Python Data Visualization project.
According to the BLS (Bureau Labor of Statistics), and JOLTS (Job Opening and Labor Turnover Survey), 2016 estimates,
7,738,000 people were unemployed. Among them, 2,185,500 people did not have an open position available to work.
This is less than 2015 estimates, when 2,981,834 unemployed people did not have a job available.
Check out the regional breakdown of the BLS stats and job scarcity.
BLS datasets note an age restriction of 16 and older, however, it does not specify if it includes retirees.
To identify if retirees are included in the BLS stats, (and to include everyone, such as non-resident population) the Census population estimates are included. These stats are organized by age and state.
Removing the BLS Employed and Institutionalized population from the Census estimates reveals a much larger portion of the population without a job available to them.
According to the combined Census, BLS, and JOLTS data estimates, approximately 32,913,191 people were unemployed.
Among them, 27,360,691 people did not have an open position available to them in 2016.
Estimates for whether or not stay-at-home parents are considered employed or unemployed vary by state.
According to Scott Galloway, Professor of Marketing at the NYU Stern School of Business, the job scarcity estimates revealed by this analysis may be attributed to Amazon reducing jobs in retail and other industries. Source: The Four
Nevertheless, to-date I do not have an official answer as to how fast automation is reducing available jobs.
For more information about the project click here.