Rising inequality: Industries and mega firms

In a new paperwe document an important determinant of how much an employer pays: the industry. An employer’s industry is determined by its production processes or its products. Pay differentials across industries are large and have widened over time, leading to increases in labour earnings inequality. For example, restaurants tend to be low-paying employers. Our data indicate that in recent decades in the US, about one-tenth of the rise in labour earnings inequality can be attributed to restaurants employing more people and paying them less. We use matched employer-employee data for 18 US states to study labour earnings inequality (hereafter, simply ‘inequality’; note that this excludes self-employment and capital income). Thirty industries (out of a total of 301) can account for nearly all of the rise in inequality from the late 1990s to the late 2010s. In these 30 industries, ‘mega firms’ (which employ 10,000 or more) have seen a massive surge in employment. This column describes some of our main findings. Industries drive increasing inequality. Figure 1 reports our measure of inequality, which is the variance of log (annual) labour earnings. The contributions of different industries to between-industry inequality are shown in Figure 2. Recall from Figure 1 that between-industry inequality (the green region of Figure 1) accounts for 61.9% of the total increase in inequality. The 30 industries that contribute most to increasing inequality explain nearly all (98.1%) of the between-industry contribution to inequality - despite employing less than 40% of the workforce. Of these 30 industries, 19 are high-paying and account for 54.0% of the increase in between-industry inequality; 11 are low-paying and account for 44.1% of this increase. The other 271 industries account for only 1.9% of rising inequality. Is increasing inequality driven by changes in employment or earnings? Figure 3 shows that there are sizeable differences in the answer to this question depending on whether the industry is high- versus low-paying. Among high-paying industries, 83.9% of the contribution to inequality is due to strong increases in earnings, while any employment increases in these industries only account for only 16.1% of this rise. In contrast, the employment among the 11 most important low-paying industries surged, accounting for 68.3% of their contribution to between-industry inequality. A much more modest decline in earnings in these low-paying industries explains the remaining 31.7%. Industries drive recent changes in inequality in the US. Thirty out of the 301 industries in our classification can explain nearly all of the rise in between-industry inequality. Continued study of these industries can help shed light on the mechanisms by which inequality continues to increase.

We now address the question of how much of increasing inequality is due to employment versus earnings. Note that changes in either employment or earnings can contribute to earnings inequality. For example, restaurants tend to be among the lowest-paying employers. When (relatively) more workers are employed by restaurants, inequality will increase. A decline in the pay of this industry would also increase inequality.

Is increasing inequality driven by changes in employment or earnings? Figure 3 shows that there are sizeable differences in the answer to this question depending on whether the industry is high- versus low-paying. Among high-paying industries, 83.9% of the contribution to inequality is due to strong increases in earnings, while any employment increases in these industries only account for only 16.1% of this rise. In contrast, the employment among the 11 most important low-paying industries surged, accounting for 68.3% of their contribution to between-industry inequality. A much more modest decline in earnings in these low-paying industries explains the remaining 31.7%.

Following the pathbreaking work of Abowd et al. (1999), Card et al. (2013), and Song et al. (2019), we consider the question of the extent to which changes in inequality are driven by workers or firms, which is especially important for understanding the contribution of high-paying firms and industries to inequality. Do high-paying firms offer larger premia? Or are they hiring highly paid (i.e. more costly) workers? As Song et al. (2019) demonstrate, there are three channels through which differences among employers contribute to inequality. These are:

1. Pay premia: some firms offer greater earnings to any worker

2. Sorting: high-paying firms employ more highly paid workers

3. Segregation: more highly paid workers concentrate among each other

We explore the relative contributions of these three phenomena to between-industry inequality in Figure 4. Sorting has the greatest role in increasing inequality, and its contribution to the variance of log annual labour earnings increased from 0.078 to 0.112 from 1996-2002 to 2012-2018. In other words, high-paying industries increasingly employ highly paid workers. Highly paid workers tend to be employed in the same industries (to the exclusion of workers with low earnings), and this rises from 0.059 to 0.089. Industry-level pay premia have also widened somewhat over time. This latter channel has had a smaller contribution to the variance of log earnings and rose from 0.033 to 0.044.

‘Mega firm’ employment has surged in the 30 industries that drive increasing inequality

We now explore the role of ‘mega firms’ in increasing inequality. By mega firms we mean those that employ at least 10,000 workers. Mega firms have been increasing as a share of employment, as documented by Bloom et al. (2018) and Autor et al. (2020). In Figure 5, we break this increase down according to our four industry groups.

The rise in mega firm employment is quite dramatic in the 30 industries that drive increasing inequality. It is especially apparent in the low-paying firms that drive inequality through increasing employment. The employment share of mega firms in the 11 low-paying industries that drive between-industry inequality increased by 2.5 percentage points, from 3.1% to 5.6%. Note that this implies that millions of additional workers were employed in mega firms in low-paying industries: the total number of people employed in the US in 2018 was more than 150 million (Bureau of Labor Statistics 2019). The employment share of mega firms in the 19 high-paying industries increased by 1.4 percentage points, from 3.2% to 4.5%. The employment share of mega firms in the other 271 industries fell.

Industries drive recent changes in inequality in the US. Thirty out of the 301 industries in our classification can explain nearly all of the rise in between-industry inequality. Continued study of these industries can help shed light on the mechanisms by which inequality continues to increase.

References

Abowd, J, F Kramarz and D Margolis (1999), “High Wage Workers and High Wage Firms”, Econometrica 67(2): 251-333.

Autor, D, D Dorn, L F Katz, C C Patterson, and J Van Reenen (2020), “The Fall of the Labor Share and the Rise of Superstar Firms”, Quarterly Journal of Economics 135(2): 645-709.

Berlingieri, G, P Blanchenay, C Criscuolo (2017), “Great Divergences: The growing dispersion of wages and productivity in OECD countries”, VoxEU.org, 15 May.

Bloom, N, F Guvenen, B S Smith, J Song and T von Wachter (2018), “The Disappearing Large-Firm Premium”, AEA Papers and Proceedings 108: 317-322.

Bloom, N, T Hassan, A Kalyani, J Lerner and A Tahoun (2021), “How disruptive technologies diffuse”, VoxEU.org, 10 August.

Card, D, A Cardoso and P Kline (2016), “Bargaining, Sorting, and the Gender Wage Gap: Quantifying the Effect of Firms on the Relative Pay of Women”, Quarterly Journal of Economics 131(2): 633-686.

Card, D, J Heining and P Kline (2013), “Workplace Heterogeneity and the Rise of West German Wage Inequality”, Quarterly Journal of Economics 128(3): 967-1015.

Cooper, Z, S Craig, M Gaynor and J Van Reenen (2019), “The Price Ain’t Right? Hospital Prices and Health Spending on the Privately Insured”, Quarterly Journal of Economics 134(1): 51-107.

Decker, R A, A Flaaen and M D Tito (2016), “Unraveling the Oil Conundrum: Productivity Improvements and Cost Declines in the U.S. Shale Oil Industry”, FEDS Notes.

Dey, M, S Houseman and A E Polivka (2006), “Manufacturers’ Outsourcing to Employment Services”, Working paper.

Dey, M, S Houseman and A Polivka (2010), “What Do We Know About Contracting Out in the United States? Evidence from Household and Establishment Surveys” in K G Abraham, J R Spletzer and M Harper (eds), Labor in the New Economy, Chicago: University of Chicago Press.

Dorn, D, J Schmieder and J Spletzer (2018), “Domestic Outsourcing in the United States”, Unpublished.

Fernald, J (2014), “Productivity and Potential Output before, during, and after the Great Recession”, NBER Macroeconomics Annual 29(1): 1-51.

Foster, L, J Haltiwanger and C J Krizan (2006), “Market Selection, Reallocation, and Restructuring in the U.S. Retail Trade Sector in the 1990s”, Review of Economics and Statistics 88(4): 748-758.

Foster, L, J Haltiwanger, S Klimek and C J Krizan (2016), “The Evolution of National Retail Chains: How We Got Here”, in E Basker (ed), Handbook on the Economics of Retailing and Distribution, Northampton, MA: Edward Elgar Publishing.

Fulton, B (2017), “Health care market concentration trends in the United States: Evidence and policy responses”, Health Affairs 36(9): 1530-1538.

Goldschlag, N and J Miranda (2016), “Business Dynamics Statistics of High Tech Industries”, US Census Bureau Center for Economic Studies.

Hecker, D (2005), “High-technology employment: a NAICS-based update”, Monthly Labor Review 128(7).

Kroszner, R and P Strahan (2014), “Regulation and Deregulation of the US Banking Industry: Causes, Consequences, and Implications for the Future”, in N L Rose (ed), Economic Regulation and Its Reform: What Have We Learned?, Chicago: University of Chicago Press.

Luo, T, A Mann and R Holden (2010), “The expanding role of temporary help services from 1990 to 2008”, Monthly Labor Review 133(8): 3-16.

Marin, D (2016), “Inequality in Germany: How it differs from the US”, VoxEU.org, 23 June.

Mion, G, L D Opromolla and G Ottaviano (2020), “Dream jobs: A comparison of career prospects in Portuguese firms”, VoxEU.org, 28 August.

Song, J, D Price, F Guvenen, N Bloom, and T von Wachter (2019), “Firming Up Inequality”, Quarterly Journal of Economics 134(1): 1-50.

John Haltiwanger, Henry Hyatt, Jim Spletzer, "Rising inequality: Industries and mega firms,"Center For Economic And Policy Research, May 30, 2022, https://voxeu.org/article/rising-inequality-industries-and-mega-firms

Rising inequality: Industries and mega firms

Why has earnings inequality been increasing? Evidence from an increasing number of countries indicates that where people work is of key importance (Card et al. 2013, 2016, Marin 2016, Berlingieri et al. 2017, Song et al. 2019, Mion et al. 2020). Some employers pay more than others, and these pay differentials have widened in recent decades. An important question is why employer-driven inequality has been rising over time.

In a new paper, we document an important determinant of how much an employer pays: the industry (Haltiwanger et al. 2022). An employer’s industry is determined by its production processes or its products. Pay differentials across industries are large and have widened over time, leading to increases in labour earnings inequality. For example, restaurants tend to be low-paying employers. Our data indicate that in recent decades in the US, about one-tenth of the rise in labour earnings inequality can be attributed to restaurants employing more people and paying them less.

We use matched employer-employee data for 18 US states to study labour earnings inequality (hereafter, simply ‘inequality’; note that this excludes self-employment and capital income). Thirty industries (out of a total of 301) can account for nearly all of the rise in inequality from the late 1990s to the late 2010s. In these 30 industries, ‘mega firms’ (which employ 10,000 or more) have seen a massive surge in employment. This column describes some of our main findings.

Industry-level differences drive increasing inequality

Industries drive increasing inequality. Figure 1 reports our measure of inequality, which is the variance of log (annual) labour earnings. We estimate inequality in three seven-year intervals: 1996-2002, 2004-2010, and 2012-2018. This is broken down into the inequality within firms and between firms. The between-firm component of inequality is further broken down into that which occurs between firms in the same industry versus that which occurs at the industry level.

Inequality in the US has risen over time. In Figure 1, we show that the variance of log earnings has increased from 0.794 in 1996-2002 to 0.916 in 2012-2018. The variance of log earnings is the sum of three components. Most inequality occurs within firms, and this dispersion increased from 0.512 to 0.531, accounting for 14.9% of the increase in inequality. Among firms in the same industry, dispersion increased from 0.112 to 0.140, accounting for 23.1% of the rise in inequality. Dispersion between industries increased from 0.170 to 0.245, accounting for 61.9% of the increase in inequality. Therefore, most of the rise in inequality has occurred across industries.

About 10% of industries account for all of the between-industry rise in inequality. We consider 301 industries defined using the North American Industrial Classification System (NAICS) at the 4-digit level. We classify industries based on whether they tend to pay more or less than the average, as well as their contribution to inequality. Thirty industries account for at least 1% (positive) of the rise in between-industry inequality. Another 271 industries each contribute less than 1% to between-industry inequality.

The contributions of different industries to between-industry inequality are shown in Figure 2. Recall from Figure 1 that between-industry inequality (the green region of Figure 1) accounts for 61.9% of the total increase in inequality. The 30 industries that contribute most to increasing inequality explain nearly all (98.1%) of the between-industry contribution to inequality - despite employing less than 40% of the workforce. Of these 30 industries, 19 are high-paying and account for 54.0% of the increase in between-industry inequality; 11 are low-paying and account for 44.1% of this increase. The other 271 industries account for only 1.9% of rising inequality.

We start with the 19 high-paying industries. At least ten of these industries have been defined as high-tech in terms STEM intensity according to the criteria of Hecker (2005) and Goldschlag and Miranda (2016). Two high-paying industries are in mining, including support activities such as drilling oil wells. The contribution of these industries is likely related to the shale oil boom (e.g. Decker et al. 2016) Five high-paying industries involve finance, insurance, or corporate headquarters. The outsized role of these industries may reflect restructuring and consolidation that have followed financial deregulation (e.g. Krozner and Strahan 2014).

Health care and social assistance includes both low-paying and high-paying industries. Two high-paying industries include physician offices and hospitals, in which considerable consolidation has occurred (e.g. Fulton 2017, Cooper et al. 2019). Of the three low-paying industries, two deal primarily with care for the elderly, including both in-home care (e.g. hospice) and retirement homes. The remaining low-paying industry, Individual and Family Services, includes adoption and foster care, services for persons with disabilities, and crisis hotlines.

The nine remaining low-paying industries can be divided into roughly two groups. First, there are two industries that provide support to businesses and facilities. This includes temporary help, where employment has increased (e.g. Luo et al. 2010), as well as Professional Employee Organisations (Dey et al. 2006). It also includes cleaning and other support services in which there has been a substantial amount of outsourcing (e.g. Dorn et al. 2018). The remaining six industries include restaurants, retail trade, and gyms, which have been transformed in recent decades with the rise of national chains (e.g. Foster et al. 2016).