Back to work: the effect of a long-term career interruption on subsequent wages in Switzerland

Swiss Journal of Economics and Statistics

Table 4 Future wage effects of a long-term non-employment spell for labor market attached workers. Dependent variable: log real hourly wage, j waves after the interruption

Waves after interruption (= j):	1	2	3	4	5	6
Lag j long-term non-employed	− 0.057^b (0.024)	-0.049^b (0.020)	− 0.113^a (0.017)	− 0.054^a (0.015)	− 0.011 (0.013)	− 0.003 (0.012)
Observations with long-term career interruption indicated j waves ago^c	84	113	139	180	250	246
Total observations	11,079	12,176	13,135	14,242	15,088	14,997

Source: Swiss Household Panel (SHP), own calculations
The sample in column j is restricted to individuals who reported to be employed in j interview waves since the interruption ended, where j equals 1, 2, …, 6, respectively. Full set of control variables is: age, age², children, sector, firm size, type of job, dummies for married, part-time, fixed-term contract, lag j final period of education, lag j further education and wave. Standard errors are in parentheses. ^a significant at the 1% level, ^b significant at the 5% level.
^c The number of observations with previous long-term interruptions is almost steadily increasing with the number of interview waves after the interruption. This is correlated with the fact that the share of people, having changed their labor market status, job or workload since the last interview, decreases during the years after a long-term interruption. The issue is that for interviewees who indicated yearly wage information and have changed their job or labor market status since the previous interview, monthly wages could not be constructed (Kuhn, 2010). Hence, we are missing wage information for these people.