# **Table 7. Short-Term Correlates of Mobility, Ordered Logit Model with Individual Random Effects, RLMS**

||_1994-1_|_998_|_1998-2_|_004_|_2004-2_|_009_|_2009-2_|_015_|
|---|---|---|---|---|---|---|---|---|
||Coef|_SE_|Coef|_SE_|Coef|_SE_|Coef|_SE_|
|_Transition variables (base- trans_|_ition to part-_|_time or n_|_o transition_|_within pa_|_rt-time)_||||
|Transition to full-time|0.312***|_0.10_|0.321***|_0.08_|0.367***|_0.09_|0.350***|_0.07_|
|No transition within full-time|0.054|_0.06_|0.133***|_0.05_|0.177***|_0.05_|0.179***|_0.04_|
|||_Individu_|_al Character_|_istics_|||||
|Age|0.005|_0.01_|-0.006|_0.01_|0.013*|_0.01_|-0.007|_0.01_|
|Age squared/100|-0.005|_0.02_|0.012|_0.01_|-0.014|_0.01_|0.015**|_0.01_|
|Male|-0.008|_0.05_|-0.066**|_0.03_|-0.061**|_0.03_|-0.041**|_0.02_|
|Married|-0.020|_0.06_|-0.077**|_0.03_|-0.138***|_0.03_|-0.114***|_0.02_|
|_Education (base- less than second_|_ary educatio_|_n)_|||||||
|Secondary School|0.037|_0.07_|-0.027|_0.05_|0.076|_0.05_|0.007|_0.04_|
|Secondary+vocational|0.033|_0.08_|-0.017|_0.06_|0.010|_0.05_|0.011|_0.04_|
|University and higher|0.119|_0.09_|-0.024|_0.06_|0.062|_0.05_|0.000|_0.04_|
|||_Labor Ma_|_rket Charact_|_eristics_|||||
|Specific experience|-0.011*|_0.01_|-0.002|_0.00_|0.003|_0.00_|-0.003|_0.00_|
|Specific experience squared/100|0.029|_0.02_|0.004|_0.01_|0.001|_0.01_|0.009|_0.01_|
|_Qualification (base- skilled white_|_collar worke_|_rs)_|||||||
|Unskilled white collar workers|0.016|_0.06_|-0.008|_0.04_|-0.028|_0.03_|0.002|_0.03_|
|Skilled blue collar workers|-0.090|_0.09_|0.028|_0.05_|-0.003|_0.05_|-0.012|_0.04_|
|Unskilled blue collar workers|0.097|_0.08_|-0.028|_0.05_|-0.050|_0.04_|-0.012|_0.04_|
|Managerial position|-0.026|_0.05_|0.023|_0.04_|0.048|_0.03_|-0.052*|_0.03_|
|||_Househ_|_old Characte_|_ristics_|||||
|Log of hh size|0.086|_0.06_|0.286***|_0.04_|0.216***|_0.03_|0.155***|_0.02_|
|Share of children aged 0-5|0.224|_0.20_|0.118|_0.15_|0.008|_0.13_|0.182*|_0.10_|
|Share of children aged 6-18|-0.034|_0.12_|-0.130|_0.08_|0.019|_0.08_|-0.063|_0.06_|
|Share of pensioners|-0.158|_0.12_|-0.158**|_0.07_|0.061|_0.06_|-0.105**|_0.05_|
|_Type of locality (base- urban)_|||||||||
|Rural|0.014|_0.05_|-0.013|_0.03_|0.023|_0.03_|-0.026|_0.02_|
|/cut1|-1.221***|_0.30_|-1.115***|_0.20_|-0.999***|_0.18_|-1.437***|_0.14_|
|/cut2|1.309***|_0.30_|1.690***|_0.20_|2.174***|_0.18_|1.870***|_0.14_|
|/sigma2_u|0.000|_0.00_|0.000***|_0.00_|0.000|_0.00_|0.000***|_0.00_|
|Number of observations|6 58|8|13 9|99|18 2|35|30 6|62|
|Number of individuals|3 67|8|5 63|6|7 10|8|11 3|28|
|Log-Likelihood|-6 5|18|-13 2|11|-15 9|84|-26 0|87|

**Note** : *** p<0.01, ** p<0.05, * p<0.1 Robust standard errors in parentheses. The estimation sample is restricted to individuals who are 18 years old and older. Regional and time dummies are included but not showed. The dependent variable is income mobility between year _t-1_ and year _t_ . The terciles are defined using the cross-sectional sample for each year. Incomes are deflated with December to December regional CPIs and weighted with population weights, where the first survey round in each period is used as the base year. All control variables are measured in the reference year _t-1_ except for the occupation transition variables, which are the changes between year _t-1_ and year _t_ .

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