The scope of Wage and Hour cases can extend beyond traditional claims on overtime or off-the-clock work. The same analytical principles can extend, for example, to cases involving employee reimbursements. EmployStats has recently worked on a case in California where the Plaintiffs allege they were not reimbursed for routine miles traveled in personal vehicles between job sites, despite the Defendant’s stated policy.

The EmployStats team assessed the Plantiffs’ theory of liability and estimated unreimbursed expenses based off of the available case data on mileage, parking, and toll charges. The analysis presented to the court showed a significant difference between stated and actual reimbursements for miles traveled by the Plantiffs. Based off of the analysis and other evidence at trial, the court certified the Plaintiff class.

The EmployStats Wage and Hour Consulting team’s trial plan is as follows:

  1. First, the EmployStats team would survey a statistically representative sample of class members about the existence of unreimbursed miles, using a random sampling methodology to eliminate potential bias.
  2. Next, the team would use a similar statistical sampling methodology to determine the typical miles traveled by the class members, and combining this resulting data with mapping platforms (ex. Google Maps API) to calculate distances in miles traveled between job locations.
  3. Finally, Employstats would tabulate damages based off of these results, using publicly available data on reimbursement rates for miles traveled in personal vehicles.
A copy of the court’s order can be found though the link here: McLeod v Bank of America Court Order – Dwight Steward PhD Statistical Sampling Plan
To see how EmployStats can assist you with similar employment or statistics cases, please visit www.EmployStats.com or give us a call at 512-476-3711.  Follow our blog and find us on social media! @employstatsnews

In determining if a Plaintiff made extensive efforts in their job search following their alleged wrongful termination, economic experts should look into several key factors.  Lawyer’s should be very familiar with these factors in order to best represent their client, whether Plaintiff or Defense.

  1. How many jobs has your client applied to and are they similar to the position they were terminated from?  A major point of attack experts should address in their reports will examine if the Plaintiff has performed a sufficiently diligent replacement job search. In Texas, individuals are granted unemployment benefits provided they apply for a minimum of three jobs per week.  This number can be used as the threshold for determining if a Plaintiff has done his or her due diligence in finding replacement employment after the alleged wrongful termination.
  2. How long has the Plaintiff been unemployed?  Widely accepted labor market data from the U.S. Bureau of Labor Statistics can be utilized to determine the average range an individual with a similar job position, in the same job market, would expect to be unemployed.  If the Plaintiff has been unable to find replacement employment within the typical unemployment duration, it is not likely they have performed a sufficient job search.
  3. How many job openings were available in the Plaintiff’s job market at the time of their termination?  Again, data from the U.S. Bureau of Labor Statistics can be utilized to determine job openings per month that the Plaintiff would have been qualified to hold.  In many cases, there are a significant number of job openings in the area the Plaintiff is searching.  Occasionally, a Plaintiff’s job search records will reveal that they have applied to jobs in multiple job markets, sometimes spanning across several states.  To a defense attorney requesting a mitigation analysis, this is music to their ears.  The more markets a Plaintiff makes themselves available to, the more markets experts can include when determining a number of job openings.  This only increases the number of jobs the Plaintiff could have held had they performed a sufficient job search and strengthens the argument that they have not performed such as search.

The National Longitudinal Survey of Youth (NLSY) is a Bureau of Labor Statistics longitudinal study that repeatedly surveys approximately 12,000 individuals every two years.  These individuals, who were selected at the beginning of the survey, are followed over time and surveyed on issues such as the individual’s educational and employment experiences.

Ordered probit regressions and the NLSY can be used to estimate the probability of different levels of educational attainment.  The probability of an individual obtaining a high school or college degree can be calculated based on demographic characteristics, such as race and gender, and household characteristics, such as family structure or parental educational attainment levels.

Regression analysis on NLSY data has also been used to estimate the length of time it takes for an individual’s salary to catch up after an employment termination.  This data can be used to determine the appropriate length of damages in wrongful termination cases.

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