Employstats Employee Focus: Training in D.C.

Posted by Matt Rigling and Susie Wirtanen | Statistical Analysis

This past week, Employstats associate Matt Rigling visited Washinton D.C. for a training course led by StataCorp experts. The course was titled Using Stata Effectively: Data Management, Analysis, and Graphics Fundamentals, and was taught by instructor Bill Rising at the MicroTek Training Solutions facility, just a few blocks away from the White House.

Here at Employstats, our analysts utilize the statistical software package Stata for data management, as well as data analysis in all types of wage & hour, economic, and employment analyses. With Stata, all analyses can be reproduced and documented for publication and review.

The training course covered topics ranging from Stata’s syntax to data validation and generation, and even topics such as estimation and post-estimation. “I took away a lot of useful techniques from the Stata course, and I learned about some new features of Stata 14, such as tab auto-complete and the command to turn Stata Markup files into reproducible do-files. Most importantly, I learned data manipulation skills that will help me work more efficiently and accurately.” said associate Matt Rigling.


The Census of Fatal Occupational Injuries, conducted by the Bureau of Labor Statistics, provides data on the number of fatal on-the-job injuries by type, occupation, industry, or worker characteristics. This data is sometimes used to statistically value a life. Dangerous jobs tend to offer a wage premium in exchange for additional risk of death on the job. Some economists have attempted to quantify the value of life based on the additional wages that must be paid for a worker to accept an increased chance of a fatal accident.

For more information, visit www.bls.gov/iif/oshcfoi1.htm

Conducted every ten years, the Census is the largest survey in the United States. The 2010 Census represented the most massive participation movement ever witnessed in the US, with approximately 74% of households returning their census by mail. The Census Bureau hired about 635,000 employees to walk through neighborhoods throughout the United States to count the remaining households.

The 100% characteristics form was used with every person and housing unit in the United States. It includes information on sex, age, and race by geographic location. Census data is available at many geographic levels, including blocks, zip codes, county, and state.

The 2010 Census asked detailed questions that include information on educational attainment, marital status, labor-force status, and income. The Census is a very large database and hence has many uses ranging from racial profiling in police-stop baselines to wage data.

For more information, please go to www.census.gov/

The American Statistical Association released an important statement and supporting paper concerning the use and interpretation of statistical significance and p-values in statistical research.


The American Statistical Associations’ statement notes that the increased quantification of scientific research and a proliferation of large, complex data sets, often referred to as Big Data, has expanded the scope for statistics.  Accordingly, the importance of appropriately chosen techniques, properly conducted analyses, and correct interpretation has also increased.

This statement by the ASA furthers, and in some ways solidifies, the ground roots “counter-statistical significance” movement that many economists and statisticians, such as Steve Zillack and Diedre McCloskey, have been working on for decades.


According to the ASA statement “The p-value [and the concept of statistical significance] was never intended to be a substitute for scientific reasoning,” said Ron Wasserstein, the ASA’s executive director. In research analysts use the data to calculate a p-value which shows how consistent the data is with the research hypothesis.  A small p-value is typically interpreted as having a small likelihood of being consistent with the research hypothesis.   In research papers, small p-values are in essence viewed as a ‘good thing’ and according to the ASA statement, are more favored by journal editors for publication.

The ASA statement argues against this approach.  Instead, the ASA statement states that “Well-reasoned statistical arguments contain much more than the value of a single number and whether that number exceeds an arbitrary threshold.”


Ronald L. Wasserstein & Nicole A. Lazar (2016): The ASA’s statement on p-values: context, process, and purpose, The American Statistician, DOI: 10.1080/00031305.2016.1154108

Ziliak, S.T., and McCloskey, D.N. (2008), The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives, Ann Arbor: University of Michigan Press

Ziliak, S.T. (2010), “The Validus Medicus and a New Gold Standard,” The Lancet, 376, 9738, 324-325.



The Current Population Survey (CPS) is a monthly survey of approximately 50,000 households conducted by the Bureau of Labor Statistics (BLS) and the U.S. Census Bureau. The CPS collects a vast amount of data and is an excellent resource for information on labor-force characteristics.

The basic monthly CPS provides general demographic information as well as employment status, industry, and occupation. The monthly survey is often used to examine unemployment rates and the duration of unemployment. The BLS publishes tables reporting the unemployment rate and the average and median duration of unemployment by gender and age, race, or marital status. These tables are generally referenced in wrongful termination cases to show the expected length of time it will take the plaintiff to find a new job.

In addition to the basic monthly survey, the CPS includes monthly supplements. These supplements include displaced workers, job tenure, and mobility, and a demographic supplement (often referred to as the March supplement), just to name a few.

The job tenure supplement can be used to estimate the amount of time an individual would have likely remained at a job if the termination had not occurred. The demographic supplement is often used to determine average and median wages for particular education levels. Additionally, regression analysis can be used to estimate lifecycle earnings for individuals based on their age or years of experience, education, and other pertinent demographic factors.

For more information, please go to www.bls.gov/cps/

The Consumer Expenditure Survey (CE) is conducted for the US Census Bureau and the Bureau of Labor Statistics. The CE is important because it is the only Federal survey to provide information on the complete range of consumers’ expenditures and incomes, as well as the characteristics of those consumers.  It studies the expenditures, income, and household characteristics of American consumers.  The CE is often used in wrongful death cases to estimate a personal consumption factor.

The personal consumption factor is the amount of income the decedent would have spent on personal expenditures as opposed to income going to the household or other members of the household.  Personal consumption includes expenditures on food, clothing, alcohol, transportation, etc.  This factor is generally estimated using the expenditure data from CE and regression analysis.

2012 statsitcs about American spending

For more information, see http://www.bls.gov/cex.

Image Source: http://www.creditloan.com/media/uploads/sites/2/2014/12/paycheck-of-the-average-american-2013.png

Can Microlevel BLS data be used to study how and why employees are paid differently at US employers ?  This paper and the work ultimately looks to provide a method to use the Microlevel, i.e. individual level survey observations, to match dispersion measures like, the standard deviation, in big data BLS employment data. The first step for the researchers is to try and match the aggregate numbers to the micro numbers. 

In this post, we look at the weekly overtime (OT) hours typically worked by telemarketers. 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. Bureau of Labor Statistics (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:
Telemarketers 21.43% 11.67 hours 60 hours

U.S. BLS data indicates that approximately 21.43% of telemarketers work overtime hours in a given week.  On average, these workers that have FLSA overtime work approximately 11.67 hours a week in OT. The average regular or straight time pay rate of these workers in the U.S. is approximately $8.48 an hour.  The average FLSA OT rate, not including supplemental pay such as non-discretionary bonus pay, is $12.72 an hour.

Source: BLS (CPS March)


Crude oil prices decreased from $59.48 per barrel in June 2015 to $47.11 per barrel in July 2015. Natural gas prices also decreased from $2.80 per million BTU in June 2015 to $2.76 per million BTU in July 2015.


Texas crude oil production for July 2015 was 80,379 barrels, up from 79,556 barrels reported in June 2015. Texas natural gas production was 682,723 Mcf (thousand cubic feet) of gas in July 2015, up from the June 2015 natural gas production total of 671,691 Mcf.

Source: EIA, Texas RRC

healthcareThe health care and social assistance industry gained 9,200 jobs from August 2015 to September 2015. Compared to September 2014, the cumulative number of jobs added in this industry is 67,000, an annual increase of 5.0%.

Source: http://www.tracer2.com/admin/uploadedPublications/2138_TLMR-Current_Edition.pdf

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