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Table 2 Probit regression for part-time spell reported, women

From: The 2011 break in the part-time indicator and the evolution of wage inequality in Germany

 (1)(2)(3)(4)(5)
20002005201020112012
Rank diff from Upper bd. (\(\theta\))2.814 (146.8)2.558 (135.2)2.355 (133.6)2.804 (156.4)3.061 (163.4)
Age0.224 (45.8)0.220 (46.6)0.197 (44.4)0.218 (49.6)0.229 (52.0)
Age2− 0.002 (39.8)− 0.002 (40.1)− 0.002 (37.3)− 0.002 (42.3)− 0.002 (44.1)
Low education− 0.009 (0.2)0.017 (0.3)0.090 (2.0)0.109 (2.6)0.075 (1.9)
Medium education− 0.027 (0.6)0.005 (0.1)0.067 (1.6)0.209 (5.1)0.153 (4.0)
High education0.382 (7.8)0.341 (6.5)0.327 (7.3)0.511 (11.9)0.497 (12.3)
N155,868142,906158,310164,041166,134
  1. Probit regressions for different years (columns). t statistics in parentheses. rank diff from upper bd. (\(\theta\)) rank difference between the rank of the individual’s own wage and the rank of the upper bound for correction, \(\theta _{tsi}=0.29-F_{t \_ m}(wage_{tsi})\) (see Sect. 3). low education intermediate high school degree after ten years, medium education high school degree after at least twelve years or a vocational degree, high education college degree. The regression also includes ten dummies for different occupation categories, 13 dummies for different industries, and ten dummies for the West German states. The reference category involves observations with missing values for education, occupation, industries, and states. The employment spells are weighted by their length