In October, voters in Albuquerque, New Mexico will decide on a minimum wage of $7.50 an hour for all employees in the city. If passed, Albuquerque will become the fourth city in America to institute a wage floor above the federal level . The first city to do so was neighboring Santa Fe, New Mexico which implemented an $8.50 minimum wage in June, 2004.
This study, by Dr. Aaron Yelowitz of the University of Kentucky, utilizes government collected data to examine the labor market effects of Santa Fe’s living wage increase. Dr. Yelowitz finds that the living wage in Santa Fe significantly increased unemployment and decreased hours worked for those who were able to keep their job. Even more troubling, this research found that almost the entire negative effect of the living wage was concentrated on the city’s least-skilled and least-educated employees. These are the very individuals the living wage is purportedly helping.
While supporters of the living wage in Albuquerque have pointed to Santa Fe as a “success” story, a closer look at these claims finds that they are based on aggregate time series data, which makes no attempt to control for even the most basic economic factors. For example, living wage advocates point to an increase in overall employment in Santa Fe since the ordinance as “evidence” of success. This a faulty analysis that fails to control for factors such as overall economic growth in the state or a growing population. The importance of controlling for these factors is the very basis of credible economic analysis and one of the first things taught in any rudimentary statistics course.
In this analysis, Dr. Yelowitz utilizes an economic model that controls for both fixed effects (factors such as Santa Fe’s traditionally low unemployment rate and more vibrant economy) as well as time varying effects (such as overall employment growth). By constructing this careful model, Dr. Yelowitz is able to isolate the effect of the living wage ordinance from the confounding effects of other factors in the economy.
Utilizing United States Bureau of Labor Statistics Current Population Survey (CPS) microdata, Dr. Yelowitz found that Santa Fe’s living wage ordinance is responsible for a 3.2 percentage point increase in the city’s unemployment rate. While the aggregate unemployment rate for Santa Fe remains lower than many surrounding areas, this is because other factors serve to counteract a portion of the living wage ordinance’s negative effect on the job market. Examining the data further, Dr. Yelowitz found that nearly the entire negative effect in terms of unemployment was felt by Santa Fe’s least educated residents. Those with 12 years of education or fewer suffered an extremely large and negative effect, while those with 13 years of education or more felt virtually no statistically or economically significant effect.
These results should not be surprising. Economic research into the minimum wage has long found that the economy’s least-skilled and most vulnerable populations suffer the most under a minimum wage increase. As employers react to the higher wage floor they look for more skilled and productive employees or attempt to switch to automation where possible. Simultaneously, more skilled employees are enticed into these jobs by the higher wage rate (65 percent higher in this case). The end result is that the least skilled—people these ordinances are purportedly attempting to help—end up left out of the labor force.
For those that do keep their jobs, Dr. Yelowitz found that they end up working fewer hours than before. On the whole, the living wage ordinance reduced hours worked by 1.6 hours per week. Similar to the unemployment results, these hours reductions were felt most by the least-educated employees. Those with 12 years or fewer of education saw their hours reduced by 3.5 hours per week.
While aggregate time series data often masks the underlying dynamics of the labor market—specifically the potential effects of policies such as the living wage—if properly controlled for they can serve as important support for microdata results. Dr. Yelowitz constructed an aggregate time series model that used populations in other areas of New Mexico as control groups to account for factors other than the living wage that may have affected employment. Dr. Yelowitz found that the minimum wage increased the overall unemployment rate in Santa Fe by nearly 0.7 percentage points. This result is both statistically and economically significant. This increase amounts to a roughly 16 percent increase in the unemployment rate and the loss of approximately 540 jobs. This analysis only serves to support Dr. Yelowitz’s microdata results.
Overall, the results of this complete economic analysis show that the living wage in Santa Fe had an indisputable negative effect on the labor market. As a result of the increase in the wage floor, unemployment is significantly increased in the city and individuals who were able to keep their jobs are being forced to work fewer hours. Most troubling, though, is the fact that the least skilled employees are those who are being most hurt by this ordinance. Voters in other areas considering an increase in the minimum wage must consider these unintended consequences that end up hurting those who the law is supposed to help.