Labor Market Concentration, Earnings, and Inequality

Kevin Rinz

doi:10.3368/jhr.monopsony.0219-10025R1

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Figure 1
Trends in Industrial Concentration, 1976–2015
Source: Longitudinal Business Database 1976–2015
Note: Figure plots the mean Herfindahl-Hirschman Index across national four-digit NAICS industries in Panel A and commuting zone-level four-digit NAICS industries in Panel B, with industries standardized according to Fort and Klimek (2018), for each year, 1976–2015. Means are calculated using total market employment as weights.
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Figure 2
Decomposition of Industrial Concentration Trends, 1976–2015
Source: Longitudinal Business Database 1976–2015
Note: Figure plots the mean Herfindahl–Hirschman Index across national or local four-digit NAICS industries as indicated. Solid gray lines plot the actual observed trend in industrial concentration. In Panels A and B, the solid black lines plot the trend that would have been observed if only industrial concentration varied, and the dark gray dashed lines plot the trend that would have been observed if only industrial composition varied. In Panel B, the light gray dashed line plots the trend that would have been observed if only the distribution of employment across commuting zones varied. Panel C plots counterfactual local concentration trends that would have been realized under various assumptions. See Section III for details.
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Figure 3
Large Firms and the Divergence between National and Local Concentration Trends
Source: Longitudinal Business Database 1976–2015
Notes: Panel A reports the number of markets (commuting zone-level four-digit NAICS industries) that contain at least one establishment belonging to at least one of the five largest firms by national employment within that four-digit NAICS industry. Panel B reports the share of markets (commuting zone-level four-digit NAICS industries) containing at least N top-five national firms, conditional on containing at least one such firm. Panels C and D report trends in national and local concentration, respectively, estimated with and without the top five firms by employment within each national industry.
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Figure 4
Distributional Trends in Local Industrial Concentration
Source: Longitudinal Business Database 1976–2015
Note: Figure plots trends in the mean and key percentiles of the local industrial concentration distribution, as measured using the Herfindahl-Hirschman Index. The unit of analysis is the commuting zone-level four-digit NAICS industry. The black circles represent the mean. The boundaries of the box in the box and whisker plots represent the 25th and 75th percentiles of the distribution, while the whiskers represent the 10th and 90th percentiles. Percentiles are approximated using the mean value of markets surrounding the actual percentile value. Percentile values are the mean value for markets within a given percentile. All values are calculated using total market employment as weights.
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Figure 5
Average Concentration across Industries within Commuting Zones
Source: Longitudinal Business Database 1976, 2005, and 2015
Note: Map plots the level of or change in the average HHI (represented by Δ in the legend) across four-digit NAICS industries within each commuting zone, as indicated. Each commuting zones has had random noise drawn from a Laplace distribution with parameter ε = 15 added to its true value before being categorized.
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Figure 6
Changes in Mean Earnings versus Changes in Log Mean Industrial Concentration
Source: Longitudinal Business Database and Form W-2 1976, 2005, and 2015
Notes: Figures plot changes in mean earnings against changes in local industrial concentration between the indicated years. Changes are calculated at the indicated level and then aggregated into 20 equal-sized bins, divided according the values of the change in industrial concentration. Earnings are obtained from the LBD in Panels A, B, and C and from Form W-2 in Panel D.
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Figure 7
Effects of Industrial Concentration on Key Percentiles of the Earnings Distribution
Source: Longitudinal Business Database and Form W-2 2005–2015
Notes: Figure plots regression coefficients and 95 percent confidence intervals from mean regressions of the log of the values of key percentiles of the earnings distribution within markets on the log of local industrial concentration as measured by the HHI. Regressions include market and commuting zone by year fixed effects. Regressions are employment-weighted. Coefficients represent elasticities.
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Figure 8
Effects of Industrial Concentration on Earnings Outcomes, by Demographic Group
Source: Longitudinal Business Database, Form W-2, and American Community Survey 2005–2015, decennial census 2000 and 2010, Census Numident.
Notes: Figure plots regression coefficients and 95 percent confidence intervals from mean regressions of the indicated outcome within markets on the log of local industrial concentration as measured by the HHI for demographic groups identified on the x-axis. Regressions include market and commuting zone by year fixed effects. Regressions are employment-weighted. Coefficients represent elasticities. The white and Black categories refer to non-Hispanic white and non-Hispanic Black. The “Hisp” category includes Hispanics of any race. The “LowEd” category includes individuals with a high school diploma or less, while the “HighEd” category includes individuals who have at least attended some college.

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Table 1

W-2 Match Counts

				Matched to Geography, Industry, and
Year	Forms	Matched to Geography	Matched to Geography and Industry	Gender	Age	Race/ethnicity	Education
2005	233,700,000	219,600,000	213,400,000	213,400,000	213,400,000	204,100,000	45,220,000
2006	239,100,000	224,400,000	218,100,000	218,100,000	218,100,000	208,500,000	44,740,000
2007	241,100,000	225,800,000	219,200,000	219,200,000	219,200,000	209,500,000	43,650,000
2008	232,900,000	219,100,000	212,300,000	212,300,000	212,300,000	203,200,000	41,660,000
2009	212,500,000	200,400,000	193,400,000	193,400,000	193,400,000	185,900,000	38,240,000
2010	207,200,000	199,300,000	192,300,000	192,300,000	192,300,000	184,800,000	36,790,000
2011	210,900,000	200,900,000	194,100,000	194,100,000	194,100,000	185,600,000	35,480,000
2012	221,500,000	212,000,000	205,200,000	205,200,000	205,200,000	195,200,000	35,790,000
2013	227,000,000	217,500,000	210,500,000	210,400,000	210,500,000	198,900,000	34,880,000
2014	234,900,000	218,400,000	214,800,000	214,700,000	214,800,000	201,500,000	33,670,000
2015	242,500,000	232,600,000	224,300,000	224,300,000	224,300,000	209,100,000	33,370,000

Source: Longitudinal Business Database, Form W-2, and American Community Survey 2005–2015, decennial census 2000 and 2010, Census Numident.
Notes: Estimates have been rounded for disclosure avoidance.

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Table 2

Effects of Industrial Concentration on Earnings, OLS Estimation

Variables	(1)	(2)	(3)	(4)
log(HHI)	-0.108***	-0.0561***	0.00645***	0.00742***
	(0.00660)	(0.00368)	(0.00211)	(0.00117)
Observations	5,446,000	1,527,000	1,519,000	1,519,000
R²	0.658	0.972	0.983	0.872
Years	1976–2015	2005–2015	2005–2015	2005–2015
Earnings measure	LBD	LBD	W-2	W-2
Weighted	Yes	Yes	Yes	No
Market FEs	Yes	Yes	Yes	Yes
CZ by year FEs	Yes	Yes	Yes	Yes

Source: Longitudinal Business Database 1976–2015 and Form W-2 2005–2015
Notes: Table reports OLS regression estimates of the effect of local industrial concentration, as measured by the HHI, on log mean earnings. Earnings measures are constructed using either employment and payroll data from the LBD or earnings data from Form W-2, as indicated. Columns represent separate regressions, which include the indicated years of data and fixed effects. Regressions are employment-weighted as indicated. Coefficients represent elasticities. Sample sizes and statistic values have been rounded for disclosure avoidance.

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Table 3

First-Stage Regressions

Variables	(1)	(2)	(3)	(4)	(5)
1976–2015, LBD sample
log(HHI–m)	1.064***	0.748***	0.829***	0.827***	0.466***
	(0.0120)	(0.0201)	(0.0174)	(0.0173)	(0.0166)
Observations	5,450,000	5,450,000	5,446,000	5,446,000	5,446,000
R²	0.504	0.773	0.930	0.932	0.956
F-stat	7,824	1,389	2,265	2,284	791
2005–2015, LBD sample
log(HHI–m)	1.062***	-0.328***	0.503***	0.505***	0.192***
	(0.0130)	(0.0786)	(0.0303)	(0.0300)	(0.0226)
Observations	1,531,000	1,531,000	1,527,000	1,527,000	1,527,000
R²	0.537	0.792	0.974	0.974	0.985
F-stat	6,667	17	276	284	73
2005–2015, W-2 sample
log(HHI–m)	1.053***	-0.131**	0.505***	0.505***	0.187***
	(0.0128)	(0.0640)	(0.0280)	(0.0274)	(0.0204)
Observations	1,522,000	1,522,000	1,519,000	1,519,000	1,519,000
R²	0.540	0.801	0.975	0.975	0.986
F-stat	6,747	4	326	339	84
Year FEs	No	Yes	Yes	No	No
CZ FEs	No	Yes	No	No	No
Industry FEs	No	Yes	No	No	No
Market FEs	No	No	Yes	Yes	Yes
CZ by year FEs	No	No	No	Yes	Yes
Market trends	No	No	No	No	Yes

Source: Longitudinal Business Database 1976–2015
Notes: Table reports regression estimates of the relationship between local industrial concentration, as measured by the HHI, and its instrument, the leave-one-out mean of the HHI across other markets in the same industry. Columns represent separate regressions, which include the indicated fixed effects (FE) in addition to the instrument. Regressions are employment-weighted. Coefficients represent elasticities. Sample sizes and statistic values have been rounded for disclosure avoidance.

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Table 4

Effects of Industrial Concentration on Mean Earnings

Variables	(1)	(2)	(3)	(4)
log(HHI)	-0.0512**	-0.00857	-0.0324***	-0.109***
	(0.0200)	(0.0122)	(0.0117)	(0.0121)
Observations	5,446,000	1,527,000	1,519,000	1,519,000
R²	0.657	0.972	0.983	0.871
Years	1976–2015	2005–2015	2005–2015	2005–2015
Earnings measure	LBD	LBD	W-2	W-2
Weighted	Yes	Yes	Yes	No
Market FEs	Yes	Yes	Yes	Yes
CZ by year FEs	Yes	Yes	Yes	Yes

Source: Longitudinal Business Database 1976–2015; Form W-2 2005–2015
Notes: Table reports instrumental variables regression estimates of the effect of local industrial concentration, as measured by the HHI, on log mean earnings. Earnings measures are constructed using either employment and payroll data from the LBD or earnings data from Form W-2, as indicated. Columns represent separate regressions, which include the indicated years of data and fixed effects (FE). Regressions are employment-weighted as indicated. Coefficients represent elasticities. Sample sizes and statistic values have been rounded for disclosure avoidance.

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Table 5

Effects of Industrial Concentration on Earnings Inequality

Variables	90/10 (1)	50/10 (2)	90/50 (3)	Gini (4)
log(HHI)	0.173***	0.107***	0.0659***	0.0124***
	(0.0265)	(0.0210)	(0.0123)	(0.00273)
Observations	1,519,000	1,519,000	1,519,000	1,519,000
R²	0.895	0.841	0.880	0.940
Market FEs	Yes	Yes	Yes	Yes
CZ by year FEs	Yes	Yes	Yes	Yes

Source: Longitudinal Business Database and Form W-2 2005–2015
Notes: Table reports instrumental variables regression estimates of the effect of local industrial concentration, as measured by the HHI, on measures of earnings inequality, constructed using earnings data from Form W-2. The dependent variables are the logs of the ratios of the 90th and 10th (Column 1), 50th and 10th (Column 2), or 90th and 50th (Column 3) percentiles of the earnings distribution, and the Gini coefficient (Column 4). Columns represent separate regressions, which include the indicated years of data and fixed effects (FE). Regressions are employment-weighted as indicated. Coefficients in Columns 1 -3 represent elasticities, while the coefficient in Column 4 is a semi-elasticity. Sample sizes and statistic values have been rounded for disclosure avoidance.

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Table 6

Effects of Industrial Concentration on Earnings Outcomes, Combined Nontradable and Construction Sector

Variables	HHI (1)	Mean Earnings (2)	90/10 (3)	90/50 (4)	50/10 (5)	Gini (6)
log(HHI–m)	0.344***
	(0.0285)
log(HHI)		-0.184***	0.396***	0.0976***	0.298***	0.0148***
		(0.0278)	(0.0691)	(0.0223)	(0.0538)	(0.00506)
Observations	333,000	333,000	333,000	333,000	333,000	333,000
R²	0.976	0.970	0.867	0.936	0.767	0.933
Market FEs	Yes	Yes	Yes	Yes	Yes	Yes
CZ by year FEs	Yes	Yes	Yes	Yes	Yes	Yes
F-stat	145.0

Source: Longitudinal Business Database and Form W-2 2005–2015
Notes: Table reports instrumental variables regression estimates of the effect of local industrial concentration, as measured by the HHI, on measures of earnings and inequality, constructed using earnings data from Form W-2, within the combined nontradable and construction sector, as defined by Mian and Sufi (2014). The first column reports the first-stage regression. In the subsequent columns, the dependent variables are the log of mean earnings (Column 2), the logs of the ratios of the 90th and 10th (Column 3), 50th and 10th (Column 4), or 90th and 50th (Column 5) percentiles of the earnings distribution, and the Gini coefficient (Column 6). Columns represent separate regressions, which include the indicated years of data and fixed effects (FE). Regressions are employment-weighted. Coefficients in Columns 2–5 represent elasticities, while the coefficient in Column 6 is a semi-elasticity. Sample sizes and statistic values have been rounded for disclosure avoidance.

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Table 7

HHI Exposure by Demographics

	2005		2015
	People	HHI	People	HHI	ΔHHI
Male	71,550,000	0.1511	76,910,000	0.1512	0.0001
Female	68,980,000	0.1408	74,150,000	0.1375	-0.0033
Age <25	25,920,000	0.1218	26,110,000	0.1217	-0.0001
Age 25–54	91,140,000	0.1491	92,320,000	0.1452	-0.0039
Age 55+	23,490,000	0.1609	32,640,000	0.1605	-0.0004
White	96,610,000	0.1538	95,980,000	0.1552	0.0014
Black	15,680,000	0.1501	17,530,000	0.1483	-0.0018
Hispanic	15,880,000	0.1142	19,850,000	0.1141	-0.0001
Low education	11,720,000	0.1702	8,469,000	0.1736	0.0034
High education	20,300,000	0.1588	16,660,000	0.1617	0.0029

Source: Longitudinal Business Database, Form W-2, and American Community Survey 2005–2015, decennial census 2000 and 2010, Census Numident.
Notes: The white and Black categories refer to non-Hispanic white and non-Hispanic Black. The Hispanic category includes Hispanics of any race. The “low education” category includes individuals with a high school diploma or less, while the “high education” category includes individuals who have at least attended some college. Estimates have been rounded for disclosure avoidance.