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Table 3 Robustness of estimates to dropping individual states with an E-Verify law

From: Do state work eligibility verification laws reduce unauthorized immigration?

  All Not recent Recent New
A. All states −0.061** (0.023) −0.026 (0.026) −0.258*** (0.071) −0.464* (0.259)
N 510 510 510 510
B. Without Alabama −0.043*** (0.013) −0.017 (0.026) −0.212*** (0.059) −0.463* (0.266)
C. Without Arizona −0.060* (0.033) −0.050* (0.028) −0.306*** (0.093) −0.055 (0.180)
D. Without Georgia −0.070** (0.034) −0.024 (0.040) −0.233** (0.102) −0.629*** (0.219)
E. Without Mississippi −0.062** (0.023) −0.029 (0.027) −0.256*** (0.074) −0.469* (0.265)
F. Without North Carolina −0.060* (0.030) −0.015 (0.029) −0.247*** (0.086) −0.514* (0.290)
G. Without South Carolina −0.057** (0.024) −0.014 (0.025) −0.279*** (0.079) −0.514* (0.277)
H. Without Utah −0.069*** (0.022) −0.032 (0.025) −0.280*** (0.069) −0.456* (0.270)
N 500 500 500 500
  1. *p < 0.1; **p < 0.05; ***p < 0.01
  2. Note: Shown are estimated coefficients on a variable measuring the fraction of the year that a universal E-Verify law was in effect in a state. The dependent variable is logged. Each entry is from a separate OLS regression. The regressions include the log of state real GDP per capita, the unemployment rate, housing permits, housing starts, and the log of real state government expenditures per capita (all lagged 1 year); state and year fixed effects; and state-specific linear time trends. Observations are weighted using the sum of the person weights in the population group. Standard errors are robust and clustered on state