The top three occupations with the most new job openings in Texas for the month of December were Elementary and Middle School Teachers with 404 new openings, Registered Nurses with 267 new openings, and Nursing, Psychiatric, and home Health Aides with 212 new openings.
December 2014
| Occupation | Total_Openings | New_Openings |
| Nursing, Psychiatric, and Home Health Aides | 2,332 | 212 |
| Registered Nurses | 2,508 | 267 |
| Elementary and Middle School Teachers | 3,452 | 404 |
Source: BLS
The number of job openings in California for nurses, therapists, and physician assistants increased from 14,866 in November 2014 to 16,429 in December 2014. The searcher-to-job opening ratio decreased from 1.54 to 1.20 in the same span.
Source: BLS
Image source: http://pediatric-nurse-practitioners.blogspot.com/2012/12/top-5-cardiac-care-nursing-jobs-for-we.html
Big Data. Bureau of Labor Statistics. Survey data. Employment Big Data. Those are all things that calculating worklife expectancy for U.S. workers requires. Worklife expectancy is similar to life expectancy and indicates how long a person can be expected to be active in the workforce over their working life. The worklife expectancy figure takes into account the anticipated to time out of the market due to unemployment, voluntary leaves, attrition, etc.
Overall the goal of our recent work is to update the Millimet et al (2002) worklife expectancy paper and account for more recent CPS data.
The data for all years is shown below. Ultimately there were over 590,000 data points used in the analysis.
| Table 2. Matched CPS Sample Sizes 1993-2013 | |||||||||
| Female | Male | ||||||||
| Year | Less than High School | High School | Some College | College | Less than High School | High School | Some College | College | Total |
| 1993 | 3,766 | 7,326 | 4,898 | 3,452 | 3,376 | 5,619 | 4,280 | 3,935 | 36,652 |
| 1994 | 3,539 | 7,019 | 5,357 | 3,619 | 3,097 | 5,477 | 4,411 | 4,013 | 36,532 |
| 1995 | 3,082 | 6,161 | 5,086 | 3,545 | 2,664 | 4,815 | 4,086 | 3,938 | 33,377 |
| 1997 | 3,079 | 6,172 | 4,771 | 3,488 | 2,723 | 4,857 | 3,926 | 3,723 | 32,739 |
| 1998 | 2,839 | 6,113 | 4,873 | 3,672 | 2,694 | 4,952 | 3,995 | 3,834 | 32,972 |
| 1999 | 2,709 | 6,027 | 4,987 | 3,770 | 2,513 | 4,830 | 4,134 | 3,923 | 32,893 |
| 2000 | 2,692 | 5,930 | 5,009 | 3,915 | 2,463 | 4,899 | 4,052 | 4,204 | 33,164 |
| 2001 | 2,545 | 5,806 | 4,971 | 3,901 | 2,458 | 4,919 | 4,232 | 4,016 | 32,848 |
| 2003 | 1,096 | 3,218 | 2,579 | 2,411 | 1,019 | 2,701 | 2,122 | 2,470 | 17,616 |
| 2004 | 2,579 | 6,372 | 5,803 | 5,009 | 2,394 | 5,307 | 4,745 | 4,819 | 37,028 |
| 2005 | 2,039 | 5,378 | 5,146 | 4,673 | 1,867 | 4,632 | 4,270 | 4,285 | 32,290 |
| 2006 | 2,297 | 5,500 | 5,608 | 4,657 | 2,131 | 4,953 | 4,263 | 4,389 | 33,798 |
| 2007 | 2,147 | 5,730 | 5,466 | 5,060 | 2,076 | 5,133 | 4,344 | 4,592 | 34,548 |
| 2008 | 2,159 | 5,659 | 5,787 | 5,281 | 2,040 | 5,212 | 4,593 | 4,826 | 35,557 |
| 2009 | 2,027 | 5,637 | 5,780 | 5,556 | 2,023 | 5,062 | 4,776 | 4,976 | 35,837 |
| 2011 | 1,845 | 4,844 | 5,106 | 5,136 | 1,786 | 4,603 | 4,176 | 4,432 | 31,928 |
| 2012 | 1,733 | 4,849 | 4,930 | 4,956 | 1,779 | 4,693 | 4,151 | 4,616 | 31,707 |
| 2013 | 1,658 | 4,542 | 5,061 | 5,109 | 1,668 | 4,579 | 4,271 | 4,650 | 31,538 |
| Total | 43,831 | 102,283 | 91,218 | 77,210 | 40,771 | 87,243 | 74,827 | 75,641 | 593,024 |
Notes:
The CPS data was matched using the algorithm similar to Millimet et al (2002) and Peracchi and Welch (1995). Households in rotation 1-4 were matched using the household identifier number to the same household in rotations 5-8 of the following year. Individuals had to have the same sex, race and be a year older in rotation 5-8 to be determined a match.
The number of job openings in California for “Innovation Type Jobs” decreased from 24,404 in November 2014 to 23,218 in December 2014. The searcher-to-job opening ratio also decreased from 0.86 to 0.79 in the same span.
Innovation jobs definition: http://www.employstats.com/blog/2014/09/26/1233/
Image source: http://www.bizjournals.com/sacramento/news/2013/09/23/symposium-innovation-ecosystems-jobs-wea.html
The number of job openings in California for STEM (science, technology, engineering, math) jobs increased from 66,268 in November 2014 to 67,091 in December 2014. The searcher-to-job opening ratio decreased from 1.27 to 1.12 in the same span.
Our definition of STEM jobs: http://www.employstats.com/blog/2014/09/19/growing-national-interest-in-stem-fields-has-focused-our-research/
Source: BLS
Image source: http://fairmountinc.com/help-wanted-1-2-million-good-paying-jobs-available/
The number of job openings in Texas for “Innovation Type Jobs” decreased from 12,748 in November 2014 to 12,021 in December 2014. The searcher-to-job opening ratio also decreased from 0.66 to 0.58 in the same span.
Innovation jobs definition: http://www.employstats.com/blog/2014/09/26/1233/
Source: BLS
Image source: http://www.americas.gecapital.com/insight-and-ideas/capital-perspectives/innovation-secrets-of-steve-jobs
In this post, we look at the weekly overtime (OT) hours typically worked by those who work in automotive body and related repair occupations.
Many of the employees that work in these jobs are not exempt from FLSA overtime pay and earn 1.5 times pay for hours worked over 40 in a given week.
The tabulations below are based on U.S. BLS survey data. The BLS job title groups are insightful, generally containing more specific job titles with similar knowledge, skills, and abilities (KSA), but can be more broad than a particular company’s job title listing. Also, some companies may have the job title listed here as exempt from FLSA or state OT due to their specific job assignments. The BLS does not make a distinction as to if the job title is exempt or non-exempt from OT.
| Occupational Group Title | Percent of OT Workers | Average Hours of OT | 1 out of every 4 (25%) OT workers works at least |
| Automotive Body and Related Repairers | 26.92% | 13.3 hours | 60 hours |
U.S. BLS data inddicates that approximately 26.92% of automotive body and related repairers work overtime hours in a given week. On average, these workers that have FLSA overtime work approximately 13.3 hours a week in OT. The average regular or straight time pay rate of theise workers in the U.S. is approximately 18.77 an hour. The average FLSA OT rate, not including supplemental pay such as non-discretionary bonus pay is 28.16 an hour.
Source: BLS (CPS March)
The number of job openings in Texas for STEM (science, technology, engineering, math) jobs decreased from 39,659 in November to 39,570 in December 2014. The searcher-to-job opening ratio also decreased from 0.81 to 0.68 in the same span.
Our definition of STEM jobs: http://www.employstats.com/blog/2014/09/19/growing-national-interest-in-stem-fields-has-focused-our-research/
Source: BLS
Image source: http://projecttomorrowblog.blogspot.com/2013/11/i-am-scientist.html
A pension band is a figure that is used when calculating the monthly benefit for a defined benefit pension program. A pension band figure, which is typically changes each year, is generally a dollar amount that the person will receive monthly for each year of service with the employer when they retire.. The pension band generally varies by job title/grade level/occupation covered by a pension plan.. Once assigned, the job title, grade level and occupation will generally remain in that band unless the job title, grade level and occupation (by location) are later reclassified to a different pension band.
Example of Basic Monthly Benefit Calculation.
The following hypothetical example shows how a basic monthly benefit is calculated assuming: •
You are in pension band 115.
The monthly benefit for pension band 115 is $55.49
In this example, the monthly benefit for a person with 30 years of credited service would be
Monthly benefit for pension band 115 ($ 55.49 Multiplied by 30 years of net credited service x 30 Basic monthly benefit = $1,664.70
Big Data. Bureau of Labor Statistics. Survey data. Employment Big Data. Those are all things that calculating worklife expectancy for U.S. workers requires. Worklife expectancy is similar to life expectancy and indicates how long a person can be expected to be active in the workforce over their working life. The worklife expectancy figure takes into account the anticipated to time out of the market due to unemployment, voluntary leaves, attrition, etc.
Overall the goal of our recent work is to update the Millimet et al (2002) worklife expectancy paper and account for more recent CPS data. Their paper uses data from the 1992 to 2000 time period. Our goal is to update that paper using data from 2000 to 2013. The main goal of the paper is to see if estimating the Millimet et al (2002) econometric worklife models with more recent data changes the results in the 2002 paper in any substantive way.
Our approach is two fold. First we matched the BLS data cohorts based on the Millimet et al. (2002) and Peracchi and Welch (1995) papers. In a nutshell the CPS matching routine involves matching incoming and outgoing cohorts across a given year. Once the data is matched, we then look at the work status of the individuals to determine if they were active or in active across the year that they were interviewed by the BLS. . We were able to create a match CPS data set of 201,797 individuals where as the Millimet et al. (2002) found 200,916 matched individuals.
| Table 1. Comparsion of CPS cohort matched data sets | ||
| Year | Millimet et al. (2002) | Steward and Gaylor (2015) |
| 1992/93 | 37,709 | 36,652 |
| 1994/95 | 34,418 | 33,377 |
| 1996/97 | 31,691 | 32,739 |
| 1997/98 | 32,276 | 32,972 |
| 1998/99 | 32,083 | 32,893 |
| 1999/2000 | 32,739 | 33,164 |
| Total | 200,916 | 201,797 |
Notes:
The CPS data was matched using the algorithm similar to Millimet et al (2002) and Peracchi and Welch (1995). Households in rotation 1-4 were matched using the household identifier number to the same household in rotations 5-8 of the following year. Individuals had to have the same sex, race and be a year older in rotation 5-8 to be determined a match.