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Table 6 Robustness check: fixed effects estimation results based on the stock-flow matching model and data set disaggregated by occupations and NUTS3 regions

From: Revisiting German labour market reform effects—a panel data analysis for occupational labour markets

  Dependent variable: logM
  FE 1 FE 2 FE 3 FE 4
β Us 0.543*** 0.554*** 0.565*** 0.583***
  (0.016) (0.016) (0.013) (0.013)
β Uf 0.044*** 0.047*** 0.071*** 0.049***
  (0.014) (0.014) (0.009) (0.011)
β Vs 0.036*** 0.029*** 0.020*** 0.022***
  (0.005) (0.004) (0.003) (0.003)
β Vf 0.044*** 0.044*** 0.031*** 0.035***
  (0.007) (0.007) (0.004) (0.004)
Year dummies, effect coded (reference year: 2000):
d 2001     −0.116***
     (0.030)
d 2002     −0.141***
     (0.026)
d 2003     −0.115***
     (0.017)
d 2004     −0.109***
     (0.019)
d 2005     −0.074***
     (0.022)
d 2006     −0.023
     (0.015)
d 2007     0.068***
     (0.020)
d 2008     0.136***
     (0.015)
d 2009     0.140***
     (0.017)
d 2010     0.168***
     (0.020)
d 2011     0.142***
     (0.020)
γ   1.712*** 1.400*** 1.433***
   (0.543) (0.271) (0.270)
a −4.449*** −4.694*** −0.829** −0.812*
  (0.609) (0.590) (0.399) (0.412)
Control variables Yes Yes Yes Yes
Monthly time dummies No No Yes No
Quarter dummies No No No Yes
Observations 2,393,683 2,393,683 2,393,683 2,393,683
Number of groups 55,316 55,316 55,316 55,316
Within R-squared 0.241 0.245 0.309 0.279
  1. Driscoll-Kraay standard errors in parentheses. Column FE 3 includes monthly time fixed effects with effect coding (reference period is January 2000), compared with Fig. 6, left panel. Control variables are the share of female workers, the shares of workers at different skill levels (‘vocational training’ and ‘academic degree,’ reference group is ‘without vocational training’) in each NUTS3 region and occupation and the average age by the population by NUTS3 regions. The estimated coefficients are provided on request
  2. *** p <0.01, ** p <0.05, * p <0.1