Category: Economics

EmployStats at the Upcoming NELA Spring Seminar

EmployStats is honored to be attending and speaking at the upcoming National Employment Lawyers Association (NELA) Spring Seminar.  The seminar, titled Epic Advocacy: Protecting Wages in Litigation & Arbitration will take place in Denver, CO on April 12-13, 2019.  

 

EmployStats’ principal economist Dwight Steward, Ph.D., and Matt Rigling, MA, will be presenting alongside attorneys Michael A. Hodgson and Dan Getman.  The speaker’s session, Calculating Damages: Views from an Expert and Lawyers, will discuss all relevant aspects of calculating and proving liability and damages in wage and hour cases.

 

The panelists will present the options attorneys face when attempting to tabulate damages, discuss the best practices for obtaining and analyzing data, as well as discuss common wage and hour issues such as sampling and surveys.  EmployStats’ statistical experts will also provide statistical background as they relate to labor and employment class action lawsuits, such as a explaining statistical significance, confidence intervals, stratified sampling, and margin of error.

 

We hope to see you at the upcoming NELA Spring Seminar in Denver on April 13, we would love to meet and discuss how EmployStats can assist you with your wage and hour lawsuit.  To find out more about the seminar, please visit the NELA Website. For more on EmployStats, visit the EmployStats Website.

Data Analytics and the Law: Putting it Together

This series on data analytics in litigation emphasized how best practices help secure reliable, valid, and defensible results based off of “Big Data.” Whether it is inter-corporate litigation, class actions, or whistleblower cases, electronic data is a source of key insights. Courts hold wide discretion in admitting statistical evidence, which is why opposing expert witnesses scrutinize or defend results so rigorously. There is generally accepted knowledge on the techniques, models, and coding languages for generating analytical results from “Big Data.” However, the underlying assumptions of a data analysis are biased. These assumptions are largest potential source of error, leading parties to confuse, generalize, or even misrepresent their results. Litigants need to be aware of and challenge such underlying assumptions, especially in their own data-driven evidence.

 

When it comes to big data cases, the parties and their expert witnesses should be readily prepared with continuous probing questions. Where (and on what program) are the data stored, how they are interconnected, and how “clean” they are, directly impact the final analysis. These stages can be overlooked, leading parties to miss key variables or spend additional time cleaning up fragmented data sets. When the data are available, litigants should not miss on opportunities due to lack of preparation or foresight. When data do not exist or they do not support a given assertion, a party should readily examine its next best alternative.

 

When the proper analysis is compiled and presented, the litigating parties must remind the court of the big picture: how the analysis directly relates to the case. Do the results prove a consistent pattern of “deviation” from a given norm? In other instances, an analysis referencing monetary values can serve as a party’s anchor for calculating damages.

 

In Big Data cases, the data should be used to reveal facts, rather than be molded to fit assertions.

EmployStats is Expanding

The EmployStats team is thrilled to announce a new division of expertise that we can now provide to our clients.

 

Starting in January 2019, the new Wage and Hour Data consulting division began operation under the leadership of Consultant Matt Rigling.  Matt Rigling obtained his Master’s of Arts in Economics from the University of Texas at Austin, and has been providing EmployStats’ clients with database and data analytics consulting for the past three years.  Under this new division of EmployStats, the team will strive to provide our wage and hour clients with the expertise they need in the construction and tabulation of time and pay record databases, as well as providing wage and hour penalty calculations for our clients in states such as California and New York.  

 

This type of consultation is perfect for both plaintiff and defense attorneys seeking to have the best support for their client in order to efficiently reach a settlement at mediation, as well as both private and government entities simply seeking to perform internal audits of their labor practices.  EmployStats has the capability to swiftly handle large and cumbersome data sets that can sometimes bog down attorneys and paralegals attempting to handle the analysis in-house.

 

Follow this blog as we continue to post about tips for efficiently using data to bring your wage and hour cases to settlement, updates on upcoming events, and current events in the world of labor and employment law.  For more information on Matt Rigling and the EmployStats team, please check us out on our website and social media accounts!

EmployStats Website

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Employee Update: Matt Rigling

EmployStats is pleased to announce that employee Matt Rigling has been offered admission into UT Austin’s Masters Program and will begin taking classes in Summer 2017!  Matt will be completing the 18-month program to obtain his Masters Degree in Economics.  He looks forward to taking advanced analytical and econometric courses and bringing those skills to his work here at EmployStats.  Matt will be working full-time in his position of Research Associate at EmployStats while pursuing his advanced degree.

Matt Rigling began working for EmployStats in an Intern position in March 2015, and was promoted to Research Associate in May 2015 after graduating from the University of Texas at Austin with a Bachelors Degree in Economics.  When he’s not crunching numbers for EmployStats, Matt enjoys watching the San Antonio Spurs and going on hikes with his puppy Zella.

Who is Doug Berg, Ph.D.?

Doug Berg, Ph.D., is an expert in big data, and has been working with EmployStats and Principal Economist Dr. Dwight Steward for several years regarding class action and discrimination lawsuits.  Dr. Berg is currently a professor at Sam Houston State University in the Department of Economics.  He received his Bachelor’s degree in Accounting from the University of Minnesota, and his Ph.D. in Economics from Texas A&M University.  Dr. Berg will provide additional support and his expert insight into using big data in employment litigation.  Doug Berg, Ph.D., describes litigation as “living on data”, and the better the data, the better the argument.  EmployStats welcomes his insight into the underlying meaning behind the data our clients provide us!

Who is David Neumark, Ph.D.?

We are joining forces with David Neumark, Ph.D., an expert on labor market discrimination in California, to bring a new air of expertise to the EmployStats team.  Dr. Neumark is the Chancellor’s Professor of Economics at U.C. Irvine, and has previously taught at Michigan State after starting his career at the Federal Reserve.  His primary work has focused on age and race discrimination, researching into new theories, as well as offering expert consulting for these discrimination cases.  Our highly skilled researchers will be providing support for Dr. Neumark in many of his large, complex employment litigation cases.  We are excited to have him on board!

 

Employee Update: Susan Wirtanen

EmployStats Research Associate, Susan Wirtanen, recently visited New York, NY to attend a course in Stata.  Stata is a statistical software data analytics tool utilized by EmployStats analysts in almost all of our case work, especially wage and hour, and employment litigation.  The tools Susan learned in attending this training include data management, data manipulation, and tools used for complex analyses.  These skills will allow Susan to work quickly and efficiently through large data sets our clients may provide for analysis.   

Susan Wirtanen was hired at EmployStats in June 2016 as an Intern after graduating from the University of Texas in Austin with a Bachelor’s degree in Economics.  Susan recently began working full-time as a Research Associate at the beginning of 2017.  In addition to being a full-time employee, Susan coaches club volleyball here in Austin, and recently finished her first season of coaching.

Do employers transmit revenue changes to employee wages? What does BLS big data say about it?

This paper (ASSA 2016 link below) looks to study revenue and sales volatility at the firm level and how that relates to employee level of wages.  The main take away is that employee wages tend to be positively related to revunue shocks. That is, employers tend to keep employee wages steady and increasing over time regardless of the specific shocks that the firm may be experiencing at any given time. 

ASSA 2016 paper

Using Microlevel BLS data to study aggregate wage dispersion

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. 

Dr. Sandra Black’s work on lifetime earnings and school starting age.

Dr. Sandra Black, UT-Austin economics professor, looks at the impact of school starting age and family background on work earnings.   From her work:

We find that if you enter the labor market later, as a result you have less experience and so you get paid less than the people who are the same age who started earlier, but by age 30 you’ve caught up. – Dr. Sandra Black