Author: Dwight Steward, Ph.D.

Dr. Steward regularly writes and speaks on topics involving business and individual economic damages, employment audits, and the analysis of payroll and time data in wage and hour investigations. Dr. Steward has also held teaching positions at The University of Texas-Austin in the Department of Economics and in the Red McCombs School of Business, The College of Business at Sam Houston State University, and at The University of Iowa. He has taught numerous courses in statistics, corporate finance, labor economics, business policies, managerial economics, and microeconomics.

California STEM job openings increased from Nov to Dec

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/

STEM_2014_12

Source: BLS

Image source: http://fairmountinc.com/help-wanted-1-2-million-good-paying-jobs-available/

FLSA OT report for individuals working in automotive body and related repair occupations

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)

What’s a pension band?

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

CPI falls faster than medical care commodities while medical services rise from Dec to Jan

The consumer price index (CPI) went down from 236.284 in December 2014 to 234.677 in January 2015, an annualized rate of 8.16%.

The price index for medical care commodities went down at an annualized rate of 3.37% from December 2014 to January 2015. During the same period, the price index increased for medical care services (0.98%), hospital and related services (0.59%), and professional services (2.09%).

Source: BLS

Image source: http://www.shutterstock.com/pic-54762670/stock-photo-background-concept-illustration-consumer-price-index.html

Worklife expectancy for U.S. workers – updating the Millimet et al. (2002) econometric model of worklife

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.

In addition we also wanted to supplement and expand on a few additional topics. The additional topics included looking at different definitions of educational attainment, adding in reported disability, and looking at occupational effects on worklife expectancy.

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.

Using this matched data we next replicated the work of Millimet et al. (2002) using the 1992 to 2000 CPS data as they did in their paper. In general the Millimet et al. (2002) econometric model uses a standard logistic regression framework to estimate transitional probabilities based on a two state labor market framework where a person is either active or in active in the workforce.

The methodology begins by estimating logistic regression using individuals who were active when first interviewed. Independent variables such as the occupation, gender, marital status and number of children are included in the logistic regression. A separate regression is estimated for individuals who are inactive at the start of the BLS interview. Separate active and inactive regressions are also estimated for certain factors of interest, such as education attainment level and reported disability status.

The logistic regression equations provide the probabilities that are conditional on the labor force attachment of the individual at the time of the interview. The conditional probabilities yield the transitional probabilities for initially active or in active individuals. For example, a person who is active at the start of a period could be either active or inactive in the next period. The transitional probabilities obtained from the logistic regression is used to calculate the probability that a person who is active at the start of a period could be either active or inactive in the next period in this example.

As described in the Millimet et al (2002) paper, the expected work life for each age is obtained recursively by working backwards from an assumed terminal year (T+ 1). The terminal year is the year in which after no one is assumed to be active. In the analysis a terminal age of 80 or 85 is used.

Using the model we began by replicating the Millimet et al. (2002) econometric model. After we replicated the model, we then performed some additional work and expanded logistic regression worklife equations. The results of our estimation are shown in the tables that are attached.

As for the results, overall there are several findings. First 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.

Overall we match their results very closely as well. For example Millimet et al. (2002) found that a male who was 26 years old with a less than a high school education had a 27.27 years WLE remaining while we found that person had 26.319 years remaining during our replication. They found that the same age person with a high school had 32.89 years remaining while we found 32.728 years remaining. The replication was particularly good for both less than high school and high school levels of educational attainment.

The WLE numbers are close but not quite as close for college and some college. This is primarily due to the fact that we use different definitions of some college and college then Millimet et al. (2002) did in their 2002 paper.

Overall, the worklife expectancy estimated using more recent data from 2000-2013 is shorter then in the earlier time period (1992-2000) data set. This is true for younger worker (18-early 40’s); younger workers from the more recent cohorts have a shorter expected work life then younger workers in the earlier cohorts. Conversely, while older workers in their 40s and 50s have a slightly longer worklife expectancy in the later time period data set. We are in the process of determining the statistical significance of these differences.

We also looked at the worklife expectancy for individuals with and without a reported disability. Disability was not covered in the Millimet et al. (2002) paper. As has been well reported, the disability measure in the BLS data is very general in nature. Accordingly the applicability of the BLS disability measure to litigation is somewhat limited. However it is interesting to note that there is a substantial reduction in worklife expectancy exhibited by individuals who reported have a disability. On average the difference is about 10 years of work life. This is consistent with other studies on disability that a relied on the BLS data. Other factors such as occupation and geographical region do not appear to have much impact on WLE estimates.

FLSA OT report for individuals working in grounds maintenance occupations

In this post, we look at the weekly overtime (OT) hours typically worked by those who work in grounds maintenance 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.

Occupational Group Title	Percent of OT Workers	Average Hours of OT	1 out of every 4 (25%) OT workers works at least:
Grounds Maintenance Workers	15.85%	11.2 hours	53.5 hours

U.S. BLS data inddicates that approximately 15.85% of grounds maintenance workers work overtime hours in a given week. On average, these workers that have FLSA overtime work approximately 11.2 hours a week in OT. The average regular or straight time pay rate of theise workers in the U.S. is approximately 11.90 an hour. The average FLSA OT rate, not including supplemental pay such as non-discretionary bonus pay is 16.35 an hour.

Source: BLS (CPS March)

Texas healthcare jobs increased by 0.3% from Nov to Dec

healthcare

The health care and social assistance industry gained 4,300 jobs from November 2014 to December 2014. Compared to December 2013, the cumulative number of jobs added in this industry is 57,000, an annual increase of 4.3%.

http://www.tracer2.com/admin/uploadedPublications/2127_TLMR-January_15.pdf

Image source: http://blogs.wsj.com/health/2012/01/06/health-care-sector-adds-jobs-as-overall-employment-picture-looks-healthier/

Texas oil and gas extraction jobs increased by 0.5% from Nov to Dec

The oil and gas extraction industry in Texas gained 600 jobs from November 2014 to December 2014. Compared to December 2013, the cumulative number of jobs added in this industry is 5,600, an increase of 5.2%.

Source: http://www.tracer2.com/admin/uploadedPublications/2127_TLMR-January_15.pdf

Image Source: http://www.eliteexploration.com/texas-oil-gas-companies/

Texas hydro-fracturing job openings decreased from Nov to Dec

petroleum engineer

The number of job openings in Texas for “petroleum engineers” and “geological and petroleum technicians” decreased from 632 in November 2014 to 595 in December 2014, while the searcher-to-job opening ratio also decreased from 0.89 to 0.78 in the same span.

The number of job openings in Texas for “derrick operators” and “roustabouts” decreased from 271 in November 2014 to 259 in December 2014, while the searcher-to-job opening ratio also decreased from 11.14 to 10.35 in the same span.

roustabout_2014_12

Source: BLS

Image source: http://wonderfulengineering.com/what-is-petroleum-engineering/

All four largest MSAs in Texas see annual increase in job openings for Dec

Compared to December of last year, all of the main MSAs (metropolitan statistical areas) in Texas saw an annual increase in the number of job openings and decrease in the searcher-to-job opening ratio.

Source: BLS