from Liberty Street Economics
— this post authored by Jason Bram, Fatih Karahan, and Brendan Moore
The federal minimum wage, currently set at $7.25 per hour, has remained unchanged for the longest stretch of time since its 1938 inception under the Fair Labor Standards Act. With the real purchasing power of the federal minimum wage eroded by inflation, many states and municipalities have raised their local minimum wages.
As of July 2019, fourteen states plus the District of Columbia – home to 35 percent of Americans – have minimum wages above $10 per hour, as do numerous localities scattered across other states. New York is among a handful of states – along with California, Connecticut, Illinois, Maryland, Massachusetts, and New Jersey – that have passed legislation to eventually increase minimum wages to $15 per hour. While New York began raising its minimum wage from $7.25 per hour in 2014, neighboring Pennsylvania has left its minimum wage unchanged at the federal floor. The minimum-wage variation between contiguous states has allowed researchers to evaluate the respective impacts on employment and average earnings. In this post, we gauge the effect of New York’s recent minimum-wage hikes by comparing low-wage sectors in counties along the New York-Pennsylvania border.
A “Border County” Analysis
One technique used to gauge local effects of minimum wage changes involves comparing trends in employment and wages across adjacent counties with diverging minimum wage levels, as highlighted in various research studies from 2000.
Specifically, we evaluate the effects on both employment and average weekly earnings in two industries with lots of lower-wage workers: retail trade and leisure & hospitality. We use data from the Quarterly Census of Employment and Wages, which provides quarterly payroll information at a detailed industry level for each county along the Pennsylvania-New York border (see the map below).
In the next sections, we provide a visual analysis of total employment and average earnings trends in these two low-wage industries along the Pennsylvania-New York border. For each industry, we index the level of employment and average weekly earnings to equal 100 in 2013:Q4, just before New York’s first minimum-wage increase.
Leisure and Hospitality
Leisure and hospitality employment followed similar trends in New York and Pennsylvania before the Empire State’s minimum-wage increases (see the left panel in the chart below). Employment at New York leisure and hospitality businesses along the border seems to be unaffected by the phasing in of the minimum wage increases. By the fourth quarter of 2017, leisure and hospitality employment in both Pennsylvania and New York border counties had increased by 5 percent over their 2013:Q4 levels. As the minimum wage was raised to levels above $10 per hour, leisure and hospitality employment in New York counties, if anything, increased relative to businesses over the Pennsylvania state line. Concerns of diminished employment growth in New York’s leisure and hospitality industry as a result of the rising minimum wage seem not to have been borne out.
Average weekly earnings also followed very similar trends on both sides of the border before the beginning of 2014 (see the right panel in the chart below). Even after the first two minimum-wage increases, there was no discernible difference in average weekly earnings between employees in the two states. However, around the start of 2016, earnings for New York employees in leisure and hospitality began to increase substantially relative to workers in Pennsylvania. This divergence in average weekly earnings has widened as the minimum wage has risen higher. By the end of 2018, leisure and hospitality workers in New York border counties earned 33 percent more, on average, than they did in late 2013, while workers in Pennsylvania border counties only received a pay increase of 15 percent over the same period. These trends suggest that the minimum-wage increases had the intended effect of boosting worker pay in low-wage industries, without negatively affecting jobs.
Retail Trade
Next, we look at retail trade, an industry in which employment has contracted along the New York-Pennsylvania border in recent years. In the chart below, we detect a pattern similar to that for leisure and hospitality: there appears to be a positive divergence in average wages between the states but no discernible divergence in employment trends (see the next chart). Without the minimum-wage increases beginning in 2014, the data seem to suggest that New York’s average weekly earnings for retail trade workers would have followed a somewhat weaker upward trend exhibited in the pre-hike period.
Conclusion
In gauging the effects of New York’s escalating minimum wage on two sizable low-wage industry sectors, one growing and the other shrinking, we find that it appears to have had a positive effect on average wages but no discernible effect on employment. It is possible that there was some negative effect on weekly hours worked, though that would imply an even stronger upward effect on hourly wages. However, longer-term effects, if any, remain to be seen. It is certainly conceivable that minimum-wage differentials may affect decisions on firm location, business investment, lease renewal, and the like over a longer time horizon. Moreover, as currently scheduled, the phasing in of the higher minimum wage across upstate New York still has a long way to go. Thus, we will continue to monitor local trends in both employment and wages – particularly in these lower-wage sectors.
Source
Disclaimer
The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.
About the Authors
Jason Bram is a research officer in the Federal Reserve Bank of New York’s Research and Statistics Group.
Fatih Karahan is a senior economist in Bank’s Research and Statistics Group.
Brendan Moore is a senior research analyst in the Bank’s Research and Statistics Group.
