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Table 7 Estimation of working time patterns—working time autonomy

From: COVID-19 and the labour market: What are the working conditions in critical jobs?

  Binary logistic regression Binary logistic regression Multinomial logistic regression (Base outcome: Not expected to be accessible in private life) Binary logistic regression
  Regular on-call or standby service (AME) Make own decisions about breaks (AME) Partially expected to be accessible in private life (AME) Expected to be accessible in private life (AME) Separation of work and private life possible (AME)
Critical job (1 = yes) 0.086*** (0.008) − 0.032** (0.011) 0.010 (0.008) 0.040*** (0.010) − 0.036*** (0.011)
Sociodemographic characteristics x x x x x
Job characteristics x x x x x
Structural characteristics x x x x x
Number of observations 7,240 7,247 7,263 7,263 7,266
Pseudo R2 0.112 0.048 0.035 0.035 0.035
  1. The table shows the estimates obtained from the regression model indicated in Eq. (2). The estimations also include the sociodemographic, job-related and structural characteristics (without occupational segments) presented in model 3 of Table 3 as control variables. AMEs are the average marginal effects. Cluster-robust standard errors for 144 occupational groups in parentheses; *p < 0.05, **p < 0.01, ***p < 0.001
  2. Source: Working Time Survey 2019; own calculations