Month: January 2016

Employment and Wage & Hour Statistics Focus: National Longitudinal Survey of Youth

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.

Employment and Wage & Hour Statistics Focus: Consumer Expenditure Survey

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

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.