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Table 10 Additional robustness checks

From: A new look at technical progress and early retirement

  (1) (2) (3)
Dep. var.: Retired Benchmark Year-by-year cohort Lagged controls
TFP growth 0.075 0.075 0.059
  (0.010) (0.010) (0.015)
TFP growth squared –0.015 –0.015 –0.015
  (0.002) (0.002) (0.004)
Married (d) 0.009 0.009 –0.008
  (0.004) (0.004) (0.006)
Spouse working (d) –0.042 –0.042 –0.027
  (0.004) (0.004) (0.005)
Emp. health ins. (d) –0.001 –0.001 0.002
  (0.005) (0.005) (0.007)
Gov. health ins. (d) 0.127 0.128 0.072
  (0.013) (0.013) (0.016)
Wealth 0.062 0.062 0.043
  (0.023) (0.024) (0.036)
Pension (d) –0.079 –0.079 0.002
  (0.009) (0.009) (0.006)
Very good health (d) 0.014 0.014 0.024
  (0.005) (0.005) (0.007)
Good health (d) 0.026 0.025 0.041
  (0.005) (0.005) (0.008)
Fair health (d) 0.076 0.075 0.095
  (0.010) (0.010) (0.014)
Poor health (d) 0.279 0.277 0.264
  (0.026) (0.026) (0.036)
Pseudo R-squared 0.239 0.241 0.153
Observations 21,856 21,826 15,693
  1. Notes: All models include race, foreign-born, geographical, education, occupation, age, cohort, and sector dummies, as well as controls for the unemployment rate in the survey year and the sector experience. Statistical significance is represented by * for p<0.10, ** for p<0.05, and *** for p<0.01. Standard errors are clustered at the sector-wave level. All models report the marginal effects of logit regressions. Column (2) includes year-by-year cohort dummies instead of 5 years-by-5 years cohort dummies that we use in the benchmark regression. Column (3)’s time-varying covariates are all lagged by one period except for TFP growth and the unemployment rate