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.