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Table 2 Linear probability model of labor force participation

From: Money also is sunny in a retiree’s world: financial incentives and work after retirement

Dependent variable: labor force participation Women Men
Individual characteristics
 Estimated earnings (log) 0.056* (0.019) 0.246** (0.055)
 Pension entitlements (log) − 0.055** (0.006) − 0.165** (0.008)
 Bridge option: partial retirement − 0.078** (0.007) − 0.060** (0.005)
 Bridge option: unemployment − 0.323** (0.006) − 0.266** (0.005)
 No degree Ref. Ref.
 Vocational training 0.032** (0.006) 0.025 (0.013)
 University degree 0.005 (0.012) − 0.075* (0.031)
 Manufacturing occupations Ref. Ref.
 Service occupations 0.011 (0.008) − 0.021 (0.014)
 Administrative occupations − 0.010 (0.008) − 0.042** (0.012)
 Accumulated labor market gaps prior to age 65 in months − 0.006** (0.0007) − 0.001 (0.001)
Employer characteristics
 Firm size: < 10 employees Ref. Ref.
 10 to 100 employees − 0.027** (0.006) − 0.019** (0.007)
 > 100 employees − 0.044** (0.007) − 0.059** (0.008)
 Mean imputed earnings of all full-time employees − 0.0004** (0.00009) − 0.000006 (0.00006)
 Share of highly qualified employees − 0.027 (0.016) − 0.112** (0.016)
 Share of employees in partial retirement − 0.204** (0.061) − 0.128** (0.049)
 Share of employees aged 55–59 − 0.030 (0.017) − 0.013 (0.017)
 Share of employees aged 60–64 − 0.033 (0.023) − 0.065** (0.021)
 Share of employees aged 65 and older 0.514** (0.048) 0.527** (0.051)
 N 30,784 44,887
 R2 0.307 0.210
  1. Additional controls: year of employment exit, and economic sector of the employer. Standard errors in parentheses are computed by bootstrapping with 200 repetitions and are clustered on the individual level. Data: SIAB 7514
  2. *p < 0.05
  3. **p < 0.01