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Training during recessions: recent European evidence Cover

Training during recessions: recent European evidence

Open Access
|Sep 2022

Figures & Tables

The effects of the business cycle (U_cycle) on training hours and employment status

(1)(2)(3)(4)

Dependent variableTraining hoursEmployment probabilityTraining hoursTraining hours

SampleAllAllEmployedNot Employed
Cyclical component of unemployment rate × 10−0.038 (0.133)−0.004*** (0.001)0.006 (0.011)−0.783*** (0.022)z
Demand shock: Zct 0.007*** (0.001)
Inverse Mills ratio 0.099 (0.147)7.073*** (0.386)
Male−0.116*** (0.011)0.140*** (0.002)−0.130*** (0.039)1.916*** (0.095)
Age−0.034*** (0.001)−0.008*** (0.001)−0.025*** (0.002)−0.159*** (0.007)
Has tertiary education1.044*** (0.032)0.154*** (0.002)0.970*** (0.037)3.341*** (0.142)
R-squared0.0180.0980.0190.028
Observations43,173,98443,173,98430,372,26712,801,617
Estimation methodOLSProbitOLSOLS

The relationship among employment protection, public training expenditure on GDP, and the sensitivity of training participation to the business cycle: second step estimate

Dependent variable: the sensitivity of training participation to the business cycle
Employment protection index0.022** (0.010)
Public expenditure for training as % of GDP0.045* (0.023)
Observations22
R-squared0.25

The effects of the business cycle (U_cycle) on training participation and employment status (excluding the inactive)

(1)(2)(3)(4)

Dependent variableTraining participationEmployment probabilityTraining participationTraining participation

SampleLabor forceLabor forceEmployedUnemployed
Cyclical component of unemployment rate × 100.018** (0.008)−0.026*** (0.006)0.026*** (0.008)0.036*** (0.008)
Demand shock: Zct 0.005*** (0.001)
Inverse Mills ratio −0.127*** (0.026)−0.121*** (0.031)
Observations32,998,70332,998,70330,372,3672,626,336
Estimation methodOLSProbitOLSOLS

The effects of the business cycle (U_cycle) on training participation (by gender, age, education and industry)

(1)(2)(3)

Cyclical component of unemployment rate × 10AllEmployedNot Employed
Males0.011* (0.006)0.011* (0.006)−0.002 0.006
Females0.018** (0.007)0.030*** (0.009)0.011** (0.006)
Age 25–44 years0.015** (0.007)0.026*** (0.008)0.015*** (0.005)
Age 45–64 years0.015** (0.006)0.038*** (0.007)0.015** (0.005)
Less-than-upper-secondary education0.002 (0.006)0.022*** (0.008)−0.007 (0.006)
Upper secondary education0.011** (0.005)0.009 (0.005)0.005 (0.005)
Tertiary education0.039*** (0.001)0.042*** (0.015)0.034*** (0.012)
Manufacturing 0.011 (0.008)
Private services 0.023** (0.009)
Public services 0.039** (0.015)

The effects of the business cycle (U_cycle) on training participation by employment status – 5% random sample by country and time period

(1)(2)

Dependent variableTraining participationTraining participation

SampleEmployedNot employed
Cyclical component of unemployment rate × 100.021*** (0.008)0.007 (0.007)
Inverse Mills ratio−0.110*** (0.012)0.045*** (0.012)
Observations1,518,752639,964

Descriptive analysis

Training participationTraining hours
Gender: male−0.020*** (0.001)−0.030*** (0.007)
Age × 10−0.005*** (0.000)−0.038*** (0.002)
Upper secondary education0.008*** (0.002)0.212*** (0.031)
Tertiary education0.058*** (0.003)1.301 *** (0.054)
Not employed−0.029*** (0.001)0.645*** (0.047)
Second quarter−0.001 (0.004)0.038 (0.084)
Third quarter−0.028*** (0.003)−0.367*** (0.073)
Fourth quarter0.003 (0.004)0.068 (0.083)
Western and Central Europe0.051*** (0.003)1.342*** (0.049)
Southern Europe0.018*** (0.002)0.660*** (0.065)
Northern Europe0.123*** (0.006)1.783*** (0.120)
Observations43,173,98443,173,984
R-squared0.0480.011

Descriptive statistics

ObservationsMeanSD
Participated in training43,173,9840.0660.248
Participated in training – employed30,372,3670.0790.271
Participated in training – not employed12,801,6170.0340.181
Training hours43,173,9841.1139.205
Training hours – employed30,372,3671.0907.664
Training hours – not employed12,801,6171.17012.100
Age (years)43,173,98445.3811.07
Male43,173,9840.4860.500
Has a tertiary education degree or higher43,173,9840.2490.432
Employed43,173,9840.7030.457
Unemployment rate – cyclical component1,62001.128
Unemployment rate – trend1,6200.0920.041
Employment rate – cyclical component1,62000.994
Employment rate – trend1,6200.6430.059

The effects of the business cycle (U_cycle) on training participation and employment status

(1)(2)(3)(4)

Dependent variableTraining participationEmployment probabilityTraining participationTraining participation

SampleAllAllEmployedNot employed
Cyclical component of unemployment rate × 100.015** (0.006)−0.038*** (0.006)0.024*** (0.007)0.006 (0.005)
Demand shock: Zct 0.007*** (0.001)
Inverse Mills ratio −0.108*** (0.010)0.051*** (0.005)
Male gender−0.015*** (0.001)0.140*** (0.002)−0.045*** (0.003)0.006*** (0.001)
Age−0.001*** (0.009)−0.008*** (0.001)0.001*** (0.001)−0.003*** (0.001)
Has tertiary education0.058*** (0.002)0.154*** (0.002)0.036*** (0.003)0.052*** (0.002)
R-squared0.0760.0980.0770.062
Observations43,173,98443,173,98430,372,26712,801,617
Estimation methodOLSProbitOLSOLS

The effect of selection into employment on the estimates of the effects of the business cycle on training participation

(1)(2)(3)(4)

Dependent variableTraining participationTraining participationTraining participationTraining participation

SampleEmployedNot employedEmployedNot employed
Cyclical component of unemployment rate × 100.024*** (0.008)0.006 (0.005)0.017** (0.007)0.010* (0.005)
Inverse Mills ratio−0.108*** (0.009)0.055*** (0.005)
Observations30,372,26712,801,61730,372,26712,801,617
Estimation methodOLSOLSOLSOLS

The effects of the business cycle (U_cycle) on training participation and labor force participation status

(1)(2)(3)(4)

Dependent variableTraining participationLabor force participationTraining participationTraining participation

SampleAllAllActiveInactive
Cyclical component of unemployment rate × 100.015** (0.006)−0.006** (0.003)0.019** (0.007)0.005 (0.005)
Demand shock: Zct 0.004*** (0.001)
Inverse Mills ratio −0.062*** (0.005)0.086*** (0.035)
Male−0.015*** (0.001)0.145*** (0.002)−0.035*** (0.002)0.015*** (0.001)
Age−0.001*** (0.000)−0.010*** (0.001)0.001*** (0.000)−0.002*** (0.001)
Has tertiary education0.058*** (0.002)0.126*** (0.001)0.048*** (0.002)0.052*** (0.002)
R-squared0.0760.0980.0770.062
Observations43,173,98443,173,98430,372,26712,801,617
Estimation methodOLSProbitOLSOLS
Language: English
Accepted on: Jul 17, 2022
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Published on: Sep 14, 2022
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Marco Bertoni, Giorgio Brunello, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 License.