Strong Employers and Weak Employees

Notes: This table examines the effects of employer concentration in a local labor market on the wages of plants. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(emp) are lagged by one year. Columns 1–5 (Columns 6–10) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 6–5 (Columns 3–5 and 8–10) present estimates using three- and four-digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of employer concentration in a local labor market on the wages of plants using a subsample of plants owned by firms that have multiple plants in only one industry segment. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(employment) are lagged by one year. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of employer concentration in a local labor market on the wages of plants including an additional control for labor productivity—valued added (total value of shipments + net increase in inventories of finished goods and works in progress—material and energy costs) scaled by labor hours. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(employment) are lagged by one year. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log (employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of employer concentration in a local labor market on the wages of plants, including an additional control for employer concentration at the national level. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(employment) are lagged by one year. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the relation between local economic conditions and plant opening and closure using a sample of industry–county–year observations constructed using the LBD. In Columns 1–4 (Columns 5–8), the dependent variable is the log (one plus) number of plant openings or closures in a given industry–county–year cell. Local economic conditions are proxied for by the one-year-lagged unemployment-to-population ratio and log median household income, either in level (odd-numbered columns) or first-difference (even-numbered columns). Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute the log number of plant openings or closures. The t-statistics based on standard errors adjusted for sample clustering at the county level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of employer concentration in a local labor market on wages using an instrumental variable (IV) approach. The instrument is the lagged (one to five years, M&A_t–1 to M&A_t–5) value of the log number of plants or employment involved in mergers of two firms in a given local labor market, defined by three-digit SIC codes and counties or CZs. We define a merger as an ownership change of a given plant between two firms that already had plants in the local labor market one year before the merger using the LBD. To ensure that the instruments for employment concentration are relevant, we require that the combined employment share of both the acquiring and target firms in the local labor market was at least 5 percent (Columns 1–4) or 10 percent (Columns 5–8) one year before a merger. Panel A presents estimates for the first-stage IV regression, in which the dependent variable is ΔlogHHI (ind–local–year)_t–5–t, the change in log(HHI) from five years before to the current year. Panel B presents estimates for the second-stage IV regression, in which the dependent variable is Δlog(Avg. wages)_t–5–t, the change in average wages from five years before to the current year. All control variables in Panels A and B, such as Δlog(labor productivity)_t–5→t, are also changes from five years before to the current year. The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousands to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the basic effects of employer concentration in a local labor market on the wages of plants by ten-year period for 1978–2016. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(employment) are lagged by one year. The table presents estimates using three-digit SIC industries to compute HHI, log(employment), and log(plants per segment). Panels A and B present estimates using counties and CZs to compute HHI and log(employment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the interactive effects of employer concentration in a local labor market and industry union coverage rates on the wages of plants. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI), log(employment), and Union are lagged by one year. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines how employer concentration shapes sensitivities of changes in production worker wages to changes in labor productivity. The dependent variable is the log change in average wages per production worker as defined in Table 1. log(HHI) is lagged by one year. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log (employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of employer concentration in a local labor market on wages controlling for the effect of import penetration from China on wages. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(employment) are lagged by one year. China exposure is defined as total value of import from China to the U.S. scaled by total employment at the industry by year level. Columns 1 and 2 (Columns 3 and 4) present estimates using counties (CZs) to define local labor markets. Columns 1 and 3 (Columns 2 and 4) present estimates using three- (four-) digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousands to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines how exposure to China import penetration affects local-level employer concentration. The table uses three-digit SIC industries to compute HHI, China exposure, log(employment), and log(plants per segment). The dependent variable is log(HHI) as defined in Table 1. t-statistics based on standard errors adjusted for sample clustering at the county level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.

Notes: This table examines the effects of contemporaneous employer concentration in a local labor market on the wages of plants. The dependent variable is the log of average wages per worker as defined in Table 1. log(HHI) and log(emp) are contemporaneous with the log of average wages per worker. Columns 1–4 (Columns 5–8) present estimates using counties (CZs) to define local labor markets. Columns 1–2 and 5–6 (Columns 3–4 and 7–8) present estimates using three- and four-digit SIC industries to compute HHI, log(employment), and log(plants per segment). The t-statistics based on standard errors adjusted for sample clustering at the county or CZ level are reported below the coefficient estimates. The numbers of observations are rounded to the nearest thousand to follow the U.S. Census Bureau’s disclosure rules.