Table 2.

Discrete-Time Competing Risks Model Predicting Labor Force Transitions for Women Working in Standard Employment

	Labor force exit					Change to nonstandard employment
Variable	Model 1	Model 2	Model 3	Model 4	Model 5	Model 1	Model 2	Model 3	Model 4	Model 5
Duration in current status (years)	−0.20***	−0.14**	−0.21***	−0.18***	−0.14*	−0.38***	−0.34***	−0.39***	−0.33***	−0.31***
Duration in current status (squared term)	0.01**	0.01*	0.01**	0.01*	0.01*	0.01**	0.01*	0.01**	0.01*	0.01*
Education
High school or lessa
Vocational school	−0.47	−0.46	−0.34	−0.33	−0.35	0.07	0.07	0.10	−0.04	−0.07
Junior College	−0.61*	−0.51	−0.49	−0.20	−0.16	−0.13	−0.07	−0.11	0.46	0.47
University or more	−0.57	−0.5	−0.45	−0.10	−0.07	−1.46*	−1.40*	−1.42*	−0.91	−0.87
Income (logged)		−0.45***			−0.40***		−0.21**			−0.20*
Work orientation
Reason for choosing final schoolb			−0.25		−0.02			−0.05		0.00
Reason for choosing the current companyb			−0.16		−0.24			−0.37		−0.43
Job characteristics
Occupation
Clericala
Professional/managerial				−0.09	−0.05				0.27	0.31
Manual labor				0.53	0.42				0.79*	0.75*
Sales/service				0.40	0.33				1.25***	1.27***
Firm size
Small (1–99)a
Medium (100–499)				0.03	0.08				−0.5	−0.47
Large (≥ 500)				0.23	0.24				−1.44***	−1.47***
Public sector				−2.17***	−2.09***				−2.17***	−2.11***
Missing				0.88	0.35				−0.29	−0.64
Constant	−2.13	−0.52	−1.99	−3.00*	−1.32	−0.85	0.1	−0.71	−1.58	−0.39
Number of person–years	1,995	1,995	1,995	1,995	1,995	1,995	1,995	1,995	1,995	1,995
Log likelihood	−795.76	−778.43	−794.35	−748.62	−734.42	−795.76	−778.43	−794.35	−748.62	−734.42

^aOmitted category.

^bDichotomous variables coded 1 = yes, 0 = no (reference category).

^*p < 0.05

^**p < 0.01

^***p < 0.001.

Note: All models control for women’s demographic characteristics (age, parity, having interwave birth, presence of a preschooler), husbands’ characteristics (income, education, share in housework), and family characteristics (coresidence with parents [-in-law]). Supplementary tables provide results from full model.