The Widening Gap Between High- and Low-Paying Companies in North Carolina

<p>How can we explain increasing wage inequality in North Carolina? This article shows that the inequality trend is being driven not by disparities between you and your boss, but rather between you and workers at other companies.&nbsp;</p>

Author: Andrew Berger-Gross

Income inequality remains an urgent concern among most Americans six years into the economic recovery. North Carolina’s income trends have looked much like those of the nation at large, with the top one percent of earners taking home an ever-larger share of total earnings in the state. However, determining the appropriate strategy for boosting the wages of our lowest earners requires clearly identifying the causes of the problem. What are the particular factors driving inequality in North Carolina?

Some researchers have asserted that surging CEO pay is responsible for much of the dispersion in wages seen in recent decades. This argument has an intuitive appeal to it; the difference between a person’s salary and that of their boss is probably the most visible expression of inequality encountered by a typical worker. However, what if overall wage inequality is being driven not by widening disparities between you and your boss, but rather between you and workers at other companies?  

In this article we examine restricted-access, firm-level wage data from the Quarterly Census of Employment and Wages program in order to track earnings trends at individual companies. These data clearly show that a great deal of earnings inequality in North Carolina is manifested in disparities between firms. For example, while a typical firm in North Carolina (paying average wages at the 50th percentile) has seen inflation adjusted wages increase 20 percent since the first quarter of 1990, a top-paying firm (with average wages at the 99th percentile) saw a 91 percent increase. In dollars, the annual wage gap between an average worker at a typical vs. top-paying firm increased in real terms from $65,000 to $145,000 during this period.

We can see a similar pattern emerging when comparing wages in individual industries (as defined by detailed NAICS sectors) in North Carolina. While the average inflation adjusted wage in a top-paying industry has increased 56 percent since the first quarter of 1990, average wages in a typical industry have increased by only 25 percent.1

The National Bureau of Economic Research recently published a working paper in which researchers, using a richer source of earnings data, demonstrate that widening wage inequality in the U.S. has been driven almost entirely by this difference between companies rather than disparities within companies (e.g., between you and your boss.) Although the causes of wage inequality between companies are not fully understood, the authors suggest that firms may have become more specialized, or that changes in production technology may have caused some firms to grow more productive than others, thus attracting higher (or lower) skill workers with more (or less) generous compensation packages. While economists usually look to differences between individuals (e.g., their education levels or job experience) in explaining earnings outcomes, these findings suggest that differences between firms (e.g., in productivity or occupational composition) might provide another framework for understanding wage inequality.   

These findings have several implications for economic and workforce developers. For economic developers, this means that targeting high-wage firms (and industries) is more important than ever in an era when lower-paying firms are seeing relatively low rates of wage growth. One potential implication for workforce developers is that workers who are looking to climb the pay ladder might be better served by preparing for employment at a different company (and/or a different industry) rather than seeking growth within their own organization.

General Disclaimers:

Data from the Quarterly Census of Employment and Wages (QCEW) are based on administrative records and are subject to nonsampling error. Any mistakes in data management, analysis, or presentation are the author’s.

 


1 Note that industry wage percentiles are computed here for each calendar period. This means that the particular industries constituting the 1st, 50th, 75th, 90th, and 99th wage percentiles change over time.

 

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