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Table 7 Estimated hazard ratios for the piecewise exponential model of the apprenticeship non-completion hazard for different starting ages and years

From: Apprenticeship non-completion in Germany: a money matter?

 

Model of Table 3, column 3

Start before age 24

Start before year 2006

Start after year 2006

Economic upturns\(^1\)

Economic downturns\(^1\)

HR

SE

HR

SE

HR

SE

HR

SE

HR

SE

HR

SE

\(W/W^{(l)}\)

0.023\(***\)

(0.002)

0.021\(***\)

(0.002)

0.029\(***\)

(0.004)

0.024\(***\)

(0.002)

0.034\(***\)

(0.003)

0.027\(***\)

(0.003)

\(ln \text { }W^{(m)}\)

0.456\(***\)

(0.028)

0.448\(***\)

(0.028)

0.469\(***\)

(0.044)

0.484\(***\)

(0.040)

0.381\(***\)

(0.029)

0.692\(***\)

(0.067)

Time

            

(ref: (547–1000] days)

            

   (0–60]

0.985

(0.027)

0.983

(0.027)

0.699\(***\)

(0.034)

1.121\(**\)

(0.038)

1.596\(***\)

(0.058)

0.517\(***\)

(0.026)

   (60–121]

1.536\(***\)

(0.038)

1.541\(***\)

(0.039)

1.014

(0.044)

1.810\(***\)

(0.058)

2.550\(***\)

(0.086)

0.811\(***\)

(0.035)

   (121–212]

1.296\(***\)

(0.031)

1.298\(***\)

(0.032)

0.874\(**\)

(0.036)

1.536\(***\)

(0.048)

2.041\(***\)

(0.069)

1.786\(***\)

(0.031)

   (212–425]

0.933\(**\)

(0.020)

0.944\(**\)

(0.021)

0.772\(***\)

(0.026)

0.996

(0.029)

1.297\(***\)

(0.042)

0.737\(***\)

(0.023)

   (425–547]

0.983

(0.026)

0.985

(0.026)

0.794\(***\)

(0.033)

1.096\(**\)

(0.038)

1.409\(***\)

(0.055)

0.764\(***\)

(0.029)

Female

0.864\(***\)

(0.023)

0.859\(***\)

(0.023)

0.767\(***\)

(0.038)

0.963

(0.032)

0.852\(***\)

(0.029)

0.947

(0.039)

High school diploma

            

(ref: lowest track)

            

   None

0.907\(***\)

(0.027)

0.909\(***\)

(0.023)

0.841\(***\)

(0.032)

0.930\(*\)

(0.031)

0.933\(*\)

(0.032)

0.870\(***\)

(0.032)

   Intermediate track

0.733\(***\)

(0.013)

0.738\(***\)

(0.013)

0.749\(***\)

(0.022)

0.733\(***\)

(0.016)

0.744\(***\)

(0.017)

0.739\(***\)

(0.020)

   Academic track

0.590\(***\)

(0.016)

0.595\(***\)

(0.016)

0.724\(***\)

(0.033)

0.555\(***\)

(0.019)

0.556\(***\)

(0.019)

0.694\(***\)

(0.030)

Start. age

2.023\(***\)

(0.116)

2.627\(***\)

(0.207)

2.000\(***\)

(0.191)

1.854\(***\)

(0.133)

1.907\(***\)

(0.139)

1.972\(***\)

(0.182)

Start. age sqr.

0.984\(***\)

(0.001)

0.977\(***\)

(0.002)

0.984\(***\)

(0.002)

0.986\(***\)

(0.002)

0.985\(***\)

(0.002)

0.985\(***\)

(0.002)

Start. year

1.187\(***\)

(0.005)

1.189\(***\)

(0.005)

1.512\(***\)

(0.015)

1.121\(***\)

(0.008)

1.100\(***\)

(0.006)

1.303\(***\)

(0.010)

Foreign

1.106\(***\)

(0.031)

1.119\(***\)

(0.032)

1.071

(0.055)

1.121\(**\)

(0.038)

1.090\(*\)

(0.039)

1.080

(0.050)

Est. size

            

(ref: 1–49 employees)

            

   50–249

0.859\(***\)

(0.005)

0.862\(***\)

(0.018)

0.859\(***\)

(0.029)

0.855\(***\)

(0.023)

0.934\(***\)

(0.025)

0.776\(***\)

(0.026)

   250+

0.798\(***\)

(0.023)

0.800\(***\)

(0.023)

0.807\(***\)

(0.037)

0.793\(***\)

(0.030)

0.853\(***\)

(0.032)

0.735\(***\)

(0.033)

Est. age

0.991\(***\)

(0.001)

0.991\(***\)

(0.001)

0.991\(***\)

(0.001)

0.990\(***\)

(0.001)

0.990\(***\)

(0.001)

0.991\(***\)

(0.001)

East Germany

0.975

(0.030)

0.972

(0.030)

0.696\(***\)

(0.043)

1.071

(0.042)

0.998

(0.039)

0.958

(0.046)

Industry

            

(ref: Retail/wholesale/gastronomy)

            

   Farming/fishing/forestry

1.039

(0.079)

1.047

(0.080)

0.907

(0.112)

1.117

(0.106)

0.938

(0.089)

1.185

(0.146)

   Earths/food/textiles

0.719\(***\)

(0.028)

0.714\(***\)

(0.028)

0.767\(***\)

(0.047)

0.687\(***\)

(0.035)

0.757\(***\)

(0.038)

0.707\(***\)

(0.045)

   Chemical/oil/metal

0.581\(***\)

(0.023)

0.576\(***\)

(0.023)

0.551\(***\)

(0.036)

0.582\(***\)

(0.029)

0.576\(***\)

(0.030)

0.581\(***\)

(0.035)

   Electronics/vehicles/misc. prod.

0.617\(***\)

(0.030)

0.612\(***\)

(0.030)

0.595\(***\)

(0.048)

0.609\(***\)

(0.037)

0.625\(***\)

(0.041)

0.628\(***\)

(0.047)

   Construction/water, energy supply

0.815\(***\)

(0.032)

0.822\(***\)

(0.033)

0.828\(**\)

(0.053)

0.775\(***\)

(0.039)

0.836\(**\)

(0.044)

0.765\(***\)

(0.047)

   Logistics/Postal/Banking

0.961

(0.043)

0.972

(0.044)

0.972

(0.072)

0.941

(0.052)

0.909

(0.054)

1.045

(0.070)

   Public/private services

0.843\(***\)

(0.028)

0.844\(***\)

(0.029)

0.792\(***\)

(0.044)

0.868\(**\)

(0.037)

0.830\(***\)

(0.036)

0.859\(**\)

(0.045)

   Health/education

1.309\(***\)

(0.038)

1.297\(***\)

(0.038)

1.097

(0.053)

1.487\(***\)

(0.053)

1.220\(***\)

(0.046)

1.398\(***\)

(0.063)

   NGOs/culture/sports

1.229\(***\)

(0.044)

1.217\(***\)

(0.044)

1.164\(*\)

(0.070)

1.331\(***\)

(0.059)

1.088

(0.051)

1.455\(***\)

(0.081)

SDR

0.728

(0.123)

0.720

(0.125)

0.013\(***\)

(0.007)

1.173

(0.218)

0.941

(0.176)

1.772\(*\)

(0.476)

MES

1.286\(***\)

(0.058)

1.285\(***\)

(0.059)

1.283\(**\)

(0.098)

1.324\(***\)

(0.074)

1.332\(***\)

(0.075)

1.228\(***\)

(0.091)

\(u^{(l)}/u^{(m)}\)

0.770\(***\)

(0.013)

0.767\(***\)

(0.013)

0.502\(***\)

(0.021)

0.824\(***\)

(0.017)

0.841\(***\)

(0.018)

0.835\(***\)

(0.023)

\(u^{(h)}/u^{(m)}\)

1.438\(***\)

(0.087)

1.447\(***\)

(0.089)

1.331\(**\)

(0.134)

1.111

(0.098)

1.558\(***\)

(0.121)

1.098

(0.105)

Constant

0.000\(***\)

(0.000)

0.000\(***\)

(0.000)

0.000\(***\)

(0.000)

0.000\(***\)

(0.000)

0.000\(***\)

(0.000)

0.000\(***\)

(0.000)

\(\theta\)

0.115

0.120

0.205

0.098

0.083

0.171

LR-test of \(\theta\)

1,509

1,500

873

743

506

775

Log pseudolikelihood

− 171,485

− 167,376

− 66,548

− 104,393

− 94,778

− 74,157

Wald test

10,821

10,821

4,300

6,186

5,840

4,915

AIC

343,038

334,821

133,164

208,854

189,625

148,381

Observations

641,921

631,465

296,318

345,603

253,124

388,797

Apprenticeships

94,223

92,544

40,881

53,342

66,623

27,600

Non-completion

19,697

19,211

7,412

12,285

11,584

8,113

  1. \(^1\) Column 5 is based on apprenticeships, which took place in periods of economic upturn entirely. Column 6 is based on apprenticeships, which had overlapping with years of economic downturn. Downturn years are defined by a decrease in the growth of GDP with respect to the previous year (2000–2003 and 2008–2009).
  2. \(***\)p < 0.001, \(**\)p < 0.01, \(*\)p < 0.05. The table reports conditional hazard ratios (HR) of the fixed component adjusted for shared frailties in 35 occupation clusters and occupation cluster robust standard errors (SE). \(W/W^{(l)}\) refers to the apprenticeship wage in relation to low skilled workers wage, \(ln \text { }W^{(m)}\) to the natural logarithm of daily skilled worker wage, SDR to the supply-demand ratio of apprenticeships, MES to the marginal employment share of the establishment, u to the number of unemployment days, and \(\theta\) to the variance of the shared frailty