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Employment protection reforms and labour market outcomes in the aftermath of the recession: Evidence from Croatia*
Iva Tomić* 
Iva Tomić
Affiliation: Institute of Economics, Zagreb, Department for Labor Markets and Social Policy, Zagreb, Croatia
 0000-0002-4706-7881
Correspondence
itomic@eizg.hr
Article | Year: 2020 | Pages: 3 - 39 | Volume: 44 | Issue: 1 Received: June 1, 2019 | Accepted: November 13, 2019 | Published online: March 3, 2020
|
FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
|
|
2008
|
2013
|
2014
|
|
EP for regular contracts (EPR)
|
2.55
|
2.55
|
2.28
|
|
EP against collective dismissals (EPC)
|
3.75
|
3.00
|
2.25
|
|
EP for temporary contracts (EPT)
|
2.21
|
1.96
|
1.96
|
|
EP for regular open-ended contracts including
collective dismissals (EPRC)
|
2.89
|
2.68
|
2.27
|
|
Ratio of EPT and EPR
|
0.87
|
0.77
|
0.86
|
|
Ratio of EPT and EPRC
|
0.76
|
0.73
|
0.86
|
Notes: Values represent EPL indices based on OECD methodology. Source: Kunovac (2014) and CNB (2014).
Notes: Monthly data are extracted from yearly datasets. No weights are included. Circles represent share of employed/employees in the total working-age (15-64) population and/or share of temporary employees/fixed-term contracts among all employees aged 15-64, while lines represent local linear smoothing plot. Source: Author’s calculation based on Croatian LFS.
Note: Results are from linear probability model with robust standard errors. Employment share includes only employees (15-64) and not self-employed persons and family workers. Quarterly data are extracted from yearly datasets. Regressions control for a basic set of individual characteristics, i.e., age dummies, gender, marriage status and nativity plus time trend and quarterly GDP growth rate. Other model specifications – such as those additionally including education, region and level of urbanisation – are also tested and the results are more or less the same (available upon request). Source: Author’s calculation based on Croatian LFS.
|
Marginal effects
|
Temporary employment (within employees)
|
Total employees (within active)
|
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
|
EPT liberalisation
(2013m7-2014m7)
|
0.015***
|
|
|
-0.002
|
|
|
|
(0.005)
|
|
|
(0.006)
|
|
|
|
EPR liberalisation
(2014m8-2017m12)
|
0.042***
|
|
0.032***
|
0.068***
|
|
0.069***
|
|
(0.005)
|
|
(0.004)
|
(0.006)
|
|
(0.005)
|
|
Both reforms
(2013m7-2017m12)
|
|
0.025***
|
|
|
0.024***
|
|
|
|
(0.005)
|
|
|
(0.005)
|
|
Notes: Besides the reform variables presented, these model specifications include a basic set of individual characteristics, i.e., age dummies, gender, marriage status, nativity and education level, plus urbanisation and region dummies as well as time trend and quarterly GDP growth rate. Employment share includes only employees (15-64) and not self-employed persons and family workers. More detailed information on probit regressions, including other model specifications, is available in the Appendix and upon request. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation based on Croatian LFS.
|
Marginal effects
|
Temporary employment (within employees)
|
Total employees (within active)
|
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
|
EPT liberalisation
(2013m7-2014m7)
|
0.015***
|
|
|
-0.004
|
|
|
|
(0.005)
|
|
|
(0.00598)
|
|
|
|
EPR liberalisation
(2014m8-2017m12)
|
0.037***
|
|
0.027***
|
0.044***
|
|
0.047***
|
|
(0.005)
|
|
(0.004)
|
(0.006)
|
|
(0.005)
|
|
Both reforms
(2013m7-2017m12)
|
|
0.023***
|
|
|
0.014**
|
|
|
|
(0.004)
|
|
|
(0.006)
|
|
Notes: Besides the reform variables presented, these model specifications include a basic set of individual characteristics, i.e., age dummies, gender, marriage status, nativity and education level, plus urbanisation and region dummies as well as time trend and quarterly GDP growth rate. Employment share includes only employees (30-64) and not self-employed persons or family workers. More detailed information on probit regressions is available upon request. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation based on Croatian LFS.
|
Marginal effects
|
Fixed-term contracts
(against permanent)
|
Temporary employment
(within employment)
|
Total employment
(within active)
|
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
|
EPT liberalisation
(2013m7-2014m7)
|
0.010**
|
|
|
0.015***
|
|
|
-0.011***
|
|
|
|
(0.005)
|
|
|
(0.004)
|
|
|
(0.004)
|
|
|
|
EPR liberalisation
(2014m8-2017m12)
|
0.029***
|
|
0.023***
|
0.040***
|
|
0.030***
|
0.044***
|
|
0.051***
|
|
(0.005)
|
|
(0.004)
|
(0.004)
|
|
(0.004)
|
(0.004)
|
|
(0.003)
|
|
Both reforms
(2013m7-2017m12)
|
|
0.017***
|
|
|
0.024***
|
|
|
0.008**
|
|
|
|
(0.004)
|
|
|
(0.004)
|
|
|
(0.004)
|
|
Notes: Besides the reform variables presented, these model specifications include a basic set of individual characteristics, i.e., age dummies, gender, marriage status, nativity and education level, plus urbanisation and region dummies as well as time trend and quarterlyGDP growth rate. More detailed information on probit regressions is available upon request. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation based on Croatian LFS.
Note: Results are from linear probability model with robust standard errors. Employment share includes only employees (30-64) and not self-employed persons and family workers. Quarterly data are extracted from yearly datasets. Regressions control for a basic set of individual characteristics, i.e., age dummies, gender, marriage status and nativity plus time trend and quarterly GDP growth rate. Other model specifications – such as those additionally including education, region and level of urbanisation – are also tested and the results are more or less the same (available upon request). Source: Author’s calculation based on Croatian LFS.
Note: Results are from linear probability model with robust standard errors. Quarterly data are extracted from yearly datasets. Regressions control for basic set of individual characteristics, i.e., age dummies, gender, marriage status and nativity plus time trend and quarterly GDP growth rate. Other model specifications – such as those additionally including education, region and level of urbanisation – are also tested and the results are more-or-less the same (available upon request). Source: Author’s calculation based on Croatian LFS.
|
Variables
|
Total
|
Employed
|
Employees
|
Temporary
employees
|
|
Mean
|
Std. Dv.
|
Mean
|
Std. Dv.
|
Mean
|
Std. Dv.
|
Mean
|
Std. Dv.
|
|
Labour market
status
|
|
|
|
|
|
|
|
|
|
Active
|
0.65
|
0.48
|
|
|
|
|
|
|
|
Employees
|
0.47
|
0.50
|
0.83
|
0.38
|
|
|
|
|
|
Self-employed
|
0.15
|
0.36
|
0.15
|
0.36
|
|
|
|
|
|
Temporary employees
|
0.16
|
0.36
|
0.16
|
0.36
|
0.16
|
0.36
|
|
|
|
Fixed-term contracts only
|
0.13
|
0.34
|
0.13
|
0.34
|
0.13
|
0.34
|
0.85
|
0.35
|
|
Precarious employment
|
0.05
|
0.22
|
0.05
|
0.22
|
0.05
|
0.22
|
0.33
|
0.47
|
|
Age
|
|
|
|
|
|
|
|
|
|
15-19 (ref.)
|
0.09
|
0.28
|
0.01
|
0.10
|
0.01
|
0.10
|
0.04
|
0.20
|
|
20-24
|
0.09
|
0.29
|
0.06
|
0.24
|
0.07
|
0.25
|
0.19
|
0.40
|
|
25-29
|
0.10
|
0.30
|
0.12
|
0.32
|
0.13
|
0.34
|
0.24
|
0.43
|
|
30-34
|
0.10
|
0.30
|
0.14
|
0.35
|
0.15
|
0.35
|
0.16
|
0.37
|
|
35-39
|
0.10
|
0.30
|
0.14
|
0.35
|
0.14
|
0.35
|
0.11
|
0.31
|
|
40-44
|
0.10
|
0.30
|
0.14
|
0.34
|
0.14
|
0.34
|
0.08
|
0.28
|
|
45-49
|
0.11
|
0.31
|
0.13
|
0.34
|
0.13
|
0.34
|
0.07
|
0.26
|
|
50-54
|
0.11
|
0.31
|
0.13
|
0.33
|
0.12
|
0.33
|
0.06
|
0.23
|
|
55-59
|
0.11
|
0.31
|
0.09
|
0.29
|
0.08
|
0.28
|
0.03
|
0.18
|
|
60-64
|
0.09
|
0.29
|
0.04
|
0.20
|
0.03
|
0.18
|
0.01
|
0.10
|
|
Individual/household characteristics
|
|
|
|
|
|
|
|
Female
|
0.50
|
0.50
|
0.45
|
0.50
|
0.47
|
0.50
|
0.48
|
0.50
|
|
Married
|
0.59
|
0.49
|
0.68
|
0.47
|
0.66
|
0.47
|
0.43
|
0.50
|
|
Foreign
|
0.11
|
0.31
|
0.10
|
0.30
|
0.10
|
0.30
|
0.10
|
0.31
|
|
Share of dependent persons in the household
|
0.14
|
0.18
|
0.15
|
0.18
|
0.15
|
0.18
|
0.13
|
0.17
|
|
Education
|
|
|
|
|
|
|
|
|
|
Low skilled (ref.)
|
0.23
|
0.42
|
0.13
|
0.33
|
0.09
|
0.29
|
0.11
|
0.31
|
|
Medium skilled
|
0.60
|
0.49
|
0.64
|
0.48
|
0.65
|
0.48
|
0.68
|
0.46
|
|
High skilled
|
0.17
|
0.37
|
0.24
|
0.42
|
0.25
|
0.43
|
0.21
|
0.41
|
|
Area variables
|
|
|
|
|
|
|
|
|
|
Urban
|
0.61
|
0.49
|
0.62
|
0.49
|
0.65
|
0.48
|
0.60
|
0.49
|
|
Central Croatia (w/o Zagreb) (ref.)
|
0.23
|
0.42
|
0.24
|
0.43
|
0.23
|
0.42
|
0.22
|
0.41
|
|
East Croatia
|
0.19
|
0.39
|
0.16
|
0.37
|
0.15
|
0.36
|
0.20
|
0.40
|
|
Zagreb region
|
0.25
|
0.43
|
0.27
|
0.45
|
0.29
|
0.45
|
0.22
|
0.42
|
|
North Adriatic
|
0.13
|
0.33
|
0.14
|
0.35
|
0.14
|
0.35
|
0.13
|
0.34
|
|
South Adriatic
|
0.20
|
0.40
|
0.18
|
0.39
|
0.19
|
0.39
|
0.23
|
0.42
|
|
County unemployment rate
|
0.19
|
0.08
|
0.18
|
0.08
|
0.18
|
0.08
|
0.19
|
0.08
|
|
State of the economy
|
|
|
|
|
|
|
|
|
|
GDP growth rate (qoq)
|
0.05
|
1.21
|
0.05
|
1.23
|
0.06
|
1.22
|
0.17
|
1.12
|
|
GDP growth rate (yoy)
|
0.34
|
3.46
|
0.36
|
3.51
|
0.41
|
3.48
|
0.82
|
3.27
|
|
Firm characteristics
|
|
|
|
|
|
|
|
|
|
Public sector
|
0.36
|
0.48
|
0.36
|
0.48
|
0.36
|
0.48
|
0.21
|
0.41
|
|
Small firm (ref.)
|
0.57
|
0.50
|
0.57
|
0.50
|
0.56
|
0.50
|
0.68
|
0.47
|
|
Medium firm
|
0.20
|
0.40
|
0.20
|
0.40
|
0.21
|
0.40
|
0.16
|
0.37
|
|
Large firm
|
0.23
|
0.42
|
0.23
|
0.42
|
0.23
|
0.42
|
0.16
|
0.37
|
|
Occupation (Managers - ref.)
|
|
|
|
|
|
|
|
|
|
Professionals
|
0.14
|
0.35
|
0.14
|
0.35
|
0.16
|
0.36
|
0.12
|
0.32
|
|
Technicians
|
0.15
|
0.35
|
0.15
|
0.35
|
0.17
|
0.37
|
0.12
|
0.32
|
|
Clerks
|
0.11
|
0.31
|
0.11
|
0.31
|
0.13
|
0.33
|
0.10
|
0.31
|
|
Service & sales
|
0.18
|
0.38
|
0.18
|
0.38
|
0.19
|
0.39
|
0.26
|
0.44
|
|
Agriculture
|
0.08
|
0.27
|
0.08
|
0.27
|
0.01
|
0.08
|
0.01
|
0.09
|
|
Craftsmen
|
0.13
|
0.33
|
0.13
|
0.33
|
0.13
|
0.34
|
0.13
|
0.33
|
|
Plant/machine operators
|
0.10
|
0.31
|
0.10
|
0.31
|
0.12
|
0.32
|
0.11
|
0.32
|
|
Elementary occupations
|
0.07
|
0.26
|
0.07
|
0.26
|
0.08
|
0.27
|
0.15
|
0.35
|
|
Industry (Agriculture, forestry and fishing - ref.)
|
|
|
|
|
|
|
|
Industry (except manufacturing & construction)
|
0.03
|
0.17
|
0.03
|
0.17
|
0.04
|
0.19
|
0.02
|
0.13
|
|
Manufacturing
|
0.18
|
0.38
|
0.18
|
0.38
|
0.20
|
0.40
|
0.18
|
0.39
|
|
Construction
|
0.08
|
0.27
|
0.08
|
0.27
|
0.08
|
0.27
|
0.09
|
0.28
|
|
Wholesale and retail trade, transport, accommodation and food service
activities + communication
|
0.30
|
0.46
|
0.30
|
0.46
|
0.31
|
0.46
|
0.39
|
0.49
|
|
Financial, insurance and real estate activities
|
0.03
|
0.18
|
0.03
|
0.18
|
0.04
|
0.19
|
0.02
|
0.15
|
|
Public administration, defence, education, human health and social work
activities
|
0.19
|
0.39
|
0.19
|
0.39
|
0.23
|
0.42
|
0.15
|
0.36
|
|
Other services
|
0.09
|
0.29
|
0.09
|
0.29
|
0.09
|
0.28
|
0.11
|
0.31
|
|
Observations
|
275,034
|
148,022
|
120,705
|
18,362
|
|
Marginal effects
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(1)
|
(2)
|
(3)
|
(4)
|
(1)
|
(2)
|
(3)
|
(4)
|
|
EPT liberalisation
(2013m7-2014m7)
|
0.0402***
|
0.0149***
|
0.0154***
|
0.0118**
|
|
|
|
|
|
|
|
|
|
(0.00399)
|
(0.00501)
|
(0.00500)
|
(0.00481)
|
|
|
|
|
|
|
|
|
|
EPR liberalisation
(2014m8-2017m12)
|
0.0836***
|
0.0421***
|
0.0420***
|
0.0321***
|
|
|
|
|
0.0776***
|
0.0320***
|
0.0315***
|
0.0241***
|
|
(0.00242)
|
(0.00547)
|
(0.00546)
|
(0.00525)
|
|
|
|
|
(0.00235)
|
(0.00430)
|
(0.00430)
|
(0.00415)
|
|
Both reforms
(2013m7-2017m12)
|
|
|
|
|
0.0742***
|
0.0246***
|
0.0249***
|
0.0192***
|
|
|
|
|
|
|
|
|
|
(0.00228)
|
(0.00461)
|
(0.00460)
|
(0.00443)
|
|
|
|
|
|
Age: 15-19
(ref.)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
20-24
|
-0.243***
|
-0.245***
|
-0.247***
|
-0.242***
|
-0.243***
|
-0.246***
|
-0.248***
|
-0.243***
|
-0.244***
|
-0.245***
|
-0.248***
|
-0.243***
|
|
(0.0166)
|
(0.0165)
|
(0.0167)
|
(0.0178)
|
(0.0166)
|
(0.0166)
|
(0.0168)
|
(0.0178)
|
(0.0165)
|
(0.0165)
|
(0.0167)
|
(0.0178)
|
|
25-29
|
-0.380***
|
-0.383***
|
-0.381***
|
-0.359***
|
-0.380***
|
-0.384***
|
-0.382***
|
-0.361***
|
-0.379***
|
-0.383***
|
-0.381***
|
-0.360***
|
|
(0.0161)
|
(0.0161)
|
(0.0163)
|
(0.0174)
|
(0.0162)
|
(0.0161)
|
(0.0164)
|
(0.0174)
|
(0.0160)
|
(0.0161)
|
(0.0163)
|
(0.0174)
|
|
30-34
|
-0.487***
|
-0.491***
|
-0.488***
|
-0.453***
|
-0.487***
|
-0.492***
|
-0.489***
|
-0.454***
|
-0.486***
|
-0.492***
|
-0.489***
|
-0.454***
|
|
(0.0161)
|
(0.0161)
|
(0.0164)
|
(0.0175)
|
(0.0162)
|
(0.0161)
|
(0.0164)
|
(0.0175)
|
(0.0160)
|
(0.0161)
|
(0.0163)
|
(0.0175)
|
|
35-39
|
-0.537***
|
-0.542***
|
-0.537***
|
-0.495***
|
-0.537***
|
-0.543***
|
-0.538***
|
-0.496***
|
-0.536***
|
-0.542***
|
-0.538***
|
-0.496***
|
|
(0.0161)
|
(0.0161)
|
(0.0163)
|
(0.0175)
|
(0.0162)
|
(0.0161)
|
(0.0164)
|
(0.0175)
|
(0.0160)
|
(0.0161)
|
(0.0163)
|
(0.0175)
|
|
40-44
|
-0.558***
|
-0.563***
|
-0.558***
|
-0.514***
|
-0.558***
|
-0.564***
|
-0.560***
|
-0.515***
|
-0.557***
|
-0.563***
|
-0.559***
|
-0.514***
|
|
(0.0161)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
(0.0162)
|
(0.0161)
|
(0.0163)
|
(0.0175)
|
(0.0160)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
|
45-49
|
-0.570***
|
-0.575***
|
-0.571***
|
-0.527***
|
-0.571***
|
-0.576***
|
-0.573***
|
-0.528***
|
-0.569***
|
-0.576***
|
-0.572***
|
-0.528***
|
|
(0.0160)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
(0.0161)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
(0.0159)
|
(0.0160)
|
(0.0162)
|
(0.0174)
|
|
50-54
|
-0.585***
|
-0.590***
|
-0.586***
|
-0.540***
|
-0.586***
|
-0.591***
|
-0.587***
|
-0.541***
|
-0.584***
|
-0.590***
|
-0.587***
|
-0.541***
|
|
(0.0160)
|
(0.0160)
|
(0.0162)
|
(0.0174)
|
(0.0161)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
(0.0159)
|
(0.0160)
|
(0.0162)
|
(0.0174)
|
|
55-59
|
-0.595***
|
-0.600***
|
-0.597***
|
-0.550***
|
-0.596***
|
-0.602***
|
-0.598***
|
-0.551***
|
-0.594***
|
-0.601***
|
-0.598***
|
-0.551***
|
|
(0.0160)
|
(0.0160)
|
(0.0162)
|
(0.0175)
|
(0.0161)
|
(0.0160)
|
(0.0163)
|
(0.0175)
|
(0.0159)
|
(0.0160)
|
(0.0162)
|
(0.0174)
|
|
60-64
|
-0.605***
|
-0.610***
|
-0.607***
|
-0.566***
|
-0.605***
|
-0.612***
|
-0.609***
|
-0.567***
|
-0.604***
|
-0.611***
|
-0.608***
|
-0.567***
|
|
(0.0162)
|
(0.0162)
|
(0.0164)
|
(0.0176)
|
(0.0163)
|
(0.0162)
|
(0.0164)
|
(0.0176)
|
(0.0161)
|
(0.0162)
|
(0.0164)
|
(0.0176)
|
|
Females
|
0.0176***
|
0.0175***
|
0.0190***
|
0.0135***
|
0.0176***
|
0.0175***
|
0.0190***
|
0.0136***
|
0.0176***
|
0.0174***
|
0.0190***
|
0.0136***
|
|
(0.00229)
|
(0.00229)
|
(0.00228)
|
(0.00246)
|
(0.00229)
|
(0.00229)
|
(0.00228)
|
(0.00246)
|
(0.00229)
|
(0.00229)
|
(0.00229)
|
(0.00246)
|
|
Married or
cohabiting
|
-0.0444***
|
-0.0436***
|
-0.0452***
|
-0.0389***
|
-0.0448***
|
-0.0436***
|
-0.0452***
|
-0.0389***
|
-0.0443***
|
-0.0434***
|
-0.0450***
|
-0.0388***
|
|
(0.00262)
|
(0.00261)
|
(0.00261)
|
(0.00252)
|
(0.00262)
|
(0.00261)
|
(0.00261)
|
(0.00252)
|
(0.00262)
|
(0.00261)
|
(0.00261)
|
(0.00252)
|
|
Foreign-born
|
0.0326***
|
0.0330***
|
0.0357***
|
0.0242***
|
0.0330***
|
0.0333***
|
0.0360***
|
0.0243***
|
0.0324***
|
0.0331***
|
0.0357***
|
0.0242***
|
|
(0.00373)
|
(0.00373)
|
(0.00376)
|
(0.00362)
|
(0.00373)
|
(0.00373)
|
(0.00376)
|
(0.00362)
|
(0.00373)
|
(0.00373)
|
(0.00376)
|
(0.00362)
|
|
Low skilled
(ref.)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Medium skilled
|
-0.0884***
|
-0.0897***
|
-0.0874***
|
-0.0341***
|
-0.0880***
|
-0.0899***
|
-0.0875***
|
-0.0342***
|
-0.0871***
|
-0.0897***
|
-0.0875***
|
-0.0342***
|
|
(0.00485)
|
(0.00487)
|
(0.00491)
|
(0.00427)
|
(0.00485)
|
(0.00487)
|
(0.00491)
|
(0.00427)
|
(0.00484)
|
(0.00487)
|
(0.00492)
|
(0.00427)
|
|
High skilled
|
-0.110***
|
-0.112***
|
-0.105***
|
0.00294
|
-0.110***
|
-0.112***
|
-0.105***
|
0.00276
|
-0.108***
|
-0.112***
|
-0.105***
|
0.00300
|
|
(0.00508)
|
(0.00509)
|
(0.00523)
|
(0.00628)
|
(0.00507)
|
(0.00509)
|
(0.00523)
|
(0.00628)
|
(0.00507)
|
(0.00509)
|
(0.00523)
|
(0.00629)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Urbanisation
dummy
|
no
|
no
|
-0.00796***
|
-0.00525**
|
no
|
no
|
-0.00852***
|
-0.00567**
|
no
|
no
|
-0.00777***
|
-0.00511**
|
|
|
|
(0.00243)
|
(0.00236)
|
|
|
(0.00242)
|
(0.00236)
|
|
|
(0.00242)
|
(0.00236)
|
|
Time trend
|
no
|
yes
|
yes
|
yes
|
no
|
yes
|
yes
|
yes
|
no
|
yes
|
yes
|
yes
|
|
GDP growth rate
(qoq)
|
no
|
yes
|
yes
|
yes
|
no
|
yes
|
yes
|
yes
|
no
|
yes
|
yes
|
yes
|
|
Regional dummies
|
no
|
no
|
yes
|
yes
|
no
|
no
|
yes
|
yes
|
no
|
no
|
yes
|
yes
|
|
Firm-level
variables
|
no
|
no
|
no
|
yes
|
no
|
no
|
no
|
yes
|
no
|
no
|
no
|
yes
|
|
Observations
|
120,666
|
120,662
|
120,662
|
118,433
|
120,666
|
120,662
|
120,662
|
118,433
|
120,666
|
120,662
|
120,662
|
118,433
|
|
Log likelihood
|
-5.533e06
|
-5.527e06
|
-5.479e06
|
-5.130 e06
|
-5.542e06
|
-5.530e06
|
-5.482e06
|
-5.132e06
|
-5.541e06
|
-5.528e06
|
-5.480e06
|
-5.13 e06
|
|
chi2
|
10142
|
10211
|
10578
|
11657
|
10025
|
10161
|
10536
|
11629
|
10114
|
10218
|
10584
|
11658
|
|
p
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
r2_p
|
0.129
|
0.130
|
0.138
|
0.157
|
0.127
|
0.129
|
0.137
|
0.157
|
0.128
|
0.130
|
0.137
|
0.157
|
Notes: More detailed information on probit regressions, including other model specifications, is available upon request. Robust standard errors in parentheses. ***p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation based on Croatian LFS.
|
Marginal effects
|
Both reform variables
|
Cumulative effect
|
Only EPR reform
|
|
(1)
|
(2)
|
(3)
|
(1)
|
(2)
|
(3)
|
(1)
|
(2)
|
(3)
|
|
EPT liberalisation
(2013m6-2014m6)
|
-0.0278***
|
0.000621
|
-0.00152
|
|
|
|
|
|
|
|
(0.00430)
|
(0.00533)
|
(0.00536)
|
|
|
|
|
|
|
|
EPR liberalisation
(2014m7-2017m12)
|
0.0189***
|
0.0660***
|
0.0676***
|
|
|
|
0.0230***
|
0.0656***
|
0.0686***
|
|
(0.00279)
|
(0.00582)
|
(0.00586)
|
|
|
|
(0.00273)
|
(0.00468)
|
(0.00472)
|
|
Both reforms
(2013m6-2017m12)
|
|
|
|
0.00702***
|
0.0248***
|
0.0240***
|
|
|
|
|
|
|
|
(0.00255)
|
(0.00504)
|
(0.00508)
|
|
|
|
|
Age: 15-19
(ref.)
|
|
|
|
|
|
|
|
|
|
|
20-24
|
0.247***
|
0.248***
|
0.241***
|
0.247***
|
0.247***
|
0.241***
|
0.247***
|
0.248***
|
0.241***
|
|
(0.0110)
|
(0.0109)
|
(0.0110)
|
(0.0110)
|
(0.0110)
|
(0.0110)
|
(0.0110)
|
(0.0109)
|
(0.0110)
|
|
25-29
|
0.322***
|
0.323***
|
0.306***
|
0.321***
|
0.322***
|
0.305***
|
0.322***
|
0.323***
|
0.306***
|
|
(0.0107)
|
(0.0107)
|
(0.0107)
|
(0.0107)
|
(0.0107)
|
(0.0108)
|
(0.0107)
|
(0.0107)
|
(0.0107)
|
|
30-34
|
0.338***
|
0.339***
|
0.317***
|
0.337***
|
0.338***
|
0.315***
|
0.338***
|
0.339***
|
0.317***
|
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
|
35-39
|
0.334***
|
0.336***
|
0.310***
|
0.334***
|
0.335***
|
0.309***
|
0.334***
|
0.336***
|
0.310***
|
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0110)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
|
40-44
|
0.338***
|
0.340***
|
0.315***
|
0.338***
|
0.339***
|
0.314***
|
0.338***
|
0.339***
|
0.315***
|
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
|
45-49
|
0.328***
|
0.329***
|
0.305***
|
0.327***
|
0.328***
|
0.304***
|
0.328***
|
0.329***
|
0.305***
|
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
(0.0108)
|
(0.0108)
|
(0.0109)
|
|
50-54
|
0.316***
|
0.318***
|
0.291***
|
0.316***
|
0.317***
|
0.290***
|
0.316***
|
0.318***
|
0.291***
|
|
(0.0108)
|
(0.0108)
|
(0.0110)
|
(0.0108)
|
(0.0108)
|
(0.0110)
|
(0.0108)
|
(0.0108)
|
(0.0110)
|
|
55-59
|
0.274***
|
0.277***
|
0.250***
|
0.274***
|
0.275***
|
0.249***
|
0.274***
|
0.277***
|
0.250***
|
|
(0.0111)
|
(0.0111)
|
(0.0112)
|
(0.0111)
|
(0.0111)
|
(0.0112)
|
(0.0111)
|
(0.0111)
|
(0.0112)
|
|
60-64
|
0.185***
|
0.188***
|
0.161***
|
0.186***
|
0.187***
|
0.160***
|
0.185***
|
0.188***
|
0.161***
|
|
(0.0120)
|
(0.0120)
|
(0.0121)
|
(0.0120)
|
(0.0120)
|
(0.0121)
|
(0.0120)
|
(0.0120)
|
(0.0121)
|
|
Females
|
0.0157***
|
0.0158***
|
0.0131***
|
0.0157***
|
0.0158***
|
0.0131***
|
0.0157***
|
0.0158***
|
0.0131***
|
|
(0.00251)
|
(0.00251)
|
(0.00252)
|
(0.00251)
|
(0.00251)
|
(0.00252)
|
(0.00251)
|
(0.00251)
|
(0.00252)
|
|
Married or
cohabiting
|
0.0229***
|
0.0220***
|
0.0280***
|
0.0226***
|
0.0222***
|
0.0282***
|
0.0229***
|
0.0220***
|
0.0280***
|
|
(0.00305)
|
(0.00305)
|
(0.00306)
|
(0.00305)
|
(0.00305)
|
(0.00307)
|
(0.00305)
|
(0.00305)
|
(0.00306)
|
|
Foreign-born
|
-0.0195***
|
-0.0198***
|
-0.0269***
|
-0.0192***
|
-0.0192***
|
-0.0262***
|
-0.0195***
|
-0.0198***
|
-0.0269***
|
|
(0.00414)
|
(0.00414)
|
(0.00419)
|
(0.00414)
|
(0.00414)
|
(0.00419)
|
(0.00414)
|
(0.00414)
|
(0.00419)
|
|
Low skilled
(ref.)
|
|
|
|
|
|
|
|
|
|
|
Medium skilled
|
0.223***
|
0.224***
|
0.197***
|
0.223***
|
0.224***
|
0.197***
|
0.222***
|
0.224***
|
0.197***
|
|
(0.00398)
|
(0.00399)
|
(0.00407)
|
(0.00398)
|
(0.00398)
|
(0.00407)
|
(0.00398)
|
(0.00399)
|
(0.00407)
|
|
High skilled
|
0.301***
|
0.303***
|
0.260***
|
0.302***
|
0.302***
|
0.260***
|
0.299***
|
0.303***
|
0.260***
|
|
(0.00435)
|
(0.00436)
|
(0.00461)
|
(0.00435)
|
(0.00435)
|
(0.00461)
|
(0.00435)
|
(0.00436)
|
(0.00461)
|
|
|
|
|
|
|
|
|
|
|
|
|
Urbanisation
dummy
|
no
|
no
|
0.0529***
|
no
|
no
|
0.0511***
|
no
|
no
|
0.0529***
|
|
|
(0.00266)
|
|
|
(0.00265)
|
|
|
(0.00266)
|
|
Time trend
|
no
|
yes
|
yes
|
no
|
yes
|
yes
|
no
|
yes
|
yes
|
|
GDP growth rate
(qoq)
|
no
|
yes
|
yes
|
no
|
yes
|
yes
|
no
|
yes
|
yes
|
|
Regional dummies
|
no
|
no
|
yes
|
no
|
no
|
yes
|
no
|
no
|
yes
|
|
Firm-level
variables
|
no
|
no
|
no
|
no
|
no
|
no
|
no
|
no
|
no
|
|
Observations
|
171,113
|
171,108
|
171,108
|
171,113
|
171,108
|
171,108
|
171,113
|
171,108
|
171,108
|
|
Log likelihood
|
-1.150e07
|
-1.150e07
|
-1.140e07
|
-1.150e07
|
-1.150e07
|
-1.140e07
|
-1.150e07
|
-1.150e07
|
-1.140e07
|
|
chi2
|
7661
|
7777
|
9164
|
7568
|
7602
|
8938
|
7618
|
7776
|
9163
|
|
p
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
0
|
|
r2_p
|
0.0469
|
0.0475
|
0.0578
|
0.0462
|
0.0464
|
0.0566
|
0.0466
|
0.0475
|
0.0578
|
Notes: Employment share includes only employees (15-64) and not self-employed persons and family workers. More detailed information on probit regressions, including other model specifications, is available upon request. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Source: Author’s calculation based on Croatian LFS.
Notes: Results are from linear probability model with robust standard errors. Employment share includes only employees (15-64) and not self-employed persons and family workers. Monthly data are extracted from yearly datasets. Regressions control for basic set of individual characteristics, i.e., age dummies, gender, marriage status and nativity plus time trend and quarterly GDP growth rate. Other model specifications – such as those additionally including education, region and level of urbanisation – are also tested and the results are more-or-less the same (available upon request). Source: Author’s calculation based on Croatian LFS.
Figure 1Employment and temporary employment for the population aged 15-64 – Croatia and the EU DISPLAY Figure
Table 1EPL reforms in Croatia DISPLAY Table
Figure 2Composition of employment on the Croatian labour market (population aged 15-64) DISPLAY Figure
Figure 3Monthly shares of employment and temporary employment for the population aged 15-64 DISPLAY Figure
Figure 4Event study results – temporary employment (upper part) and employment (lower part) DISPLAY Figure
Table 2Marginal effects after probits – temporary employment among employees and employment (employees) for population aged 15-64 DISPLAY Table
Table 3Marginal effects after probits – temporary employment among employees and employment (employees) for population aged 30-64 DISPLAY Table
Table 4Marginal effects after probits – fixed-term contracts, temporary employment among total employment and total employment for population aged 15-64 DISPLAY Table
Figure 5Event study results - temporary employment (upper part) and employment (lower part) for population aged 30-64 DISPLAY Figure
Figure 6Event study results for fixed contracts only DISPLAY Figure
Table A1Descriptive statistics DISPLAY Table
Table A2Marginal effects after probits for temporary employment DISPLAY Table
Table A3Marginal effects after probits for employment DISPLAY Table
Figure A1Event study results on a monthly level DISPLAY Figure
* The author would like to thank Valerija Botrić, Marina Kunovac, Ivica Rubil and Ivan Žilić, as well as participants at the LSEE Workshop on Economics of the Western Balkans and two anonymous referees for helpful discussions and valuable comments on the paper.
1 See Saint-Paul (  1996), Boeri ( 2011) or Bentolila, Dolado and Jimeno ( 2019) for synthesis reports on dualism in (European) labour markets.
2 Matković ( 2013) finds that in the pre-crisis period temporary contracts were more frequently used in the peripheral part of the private sector for hiring young workers and low-skilled workers in routine manual and service occupations.
3 As often argued, due to downward wage rigidity labour market adjustments in the crisis happened through employment cuts. The literature suggests that the effects of EPL on temporary employment are actually stronger in countries that exhibit more downward wage rigidity (Kahn, 2007).
4 A part of the underlying reason is the decline of the working-age population and a change in generational composition of the workforce due to population ageing. Nevertheless, the employment rate surpassed (by a small margin) the 2008 levels only in 2018 (not covered in the empirical analysis).
5 Act on Amendments to the Labour Act (OG 73/2013) was passed on 18 June 2013 (in force after 8 days).
6 The main changes of the law in 2013 were that it introduced the possibility that the first fixed-term contract lasts longer than three years (concluding more successive employment contracts remains limited to a maximum of three years), while the provisions on collective surpluses of workers have been simplified and the whole process was shortened.
7 Labour Act (OG 93/2014) was passed on 30 July 2014 (in force after 8 days).
8 The main changes in this regard have been the simplification of procedures when firing workers on permanent contracts (the abolition of the provisions regarding the obligatory retraining or displacement to another job before the dismissal), changes in the organisation of work with respect to working hours, plus potential lowering of the firing costs as the compensation for termination of employment contract in court has been reduced from a maximum of 18 to a maximum of 8 average wages.
9 The possibility of working via a temporary agency has been increased from one to three years. However, fewer than 1% of workers are employed through temporary agency, without significant changes in recent years.
10 More details on EPL reforms in Croatia in 2013 and 2014 can be found in Kunovac ( 2014), CNB ( 2014), Potočnjak ( 2014) and Brkić ( 2015), and additional information on previous reforms can be found in Matković and Biondić ( 2003), Vukorepa ( 2010), Tomić and Domadenik ( 2012) and Tomić ( 2013).
11 See Tomić and Žilić ( 2018) for more details about this. For example, they report that the number of participants in the programme increased from below 500 in 2010 to 33,366 in 2016.
12 Both vocational training without commencing employment (up to a year) and seasonal work in agriculture via vouchers (up to 90 days over the year) have been introduced by the Law on the Promotion of Employment (OG 57/2012, 120/2012, 16/2017).
13 According to the Law on Social Security Contributions (OG 84/2008, 152/2008, 94/2009, 18/2011, 22/2012, 144/2012, 148/2013, 41/2014, 143/2014, 115/2016, 106/2018). The Croatian Pension Insurance Institute reports that the number of people using this possibility for employment increased from slightly more than 10,000 in March 2015 to more than 83,000 at the end of 2017 (more than 108,000 at the end of 2018).
14 See the next subsection and Table A1 in the Appendix for more details.
15 I also test for non-random selection of individuals into (temporary) employment by applying the so-called Heckman correction for selection, i.e., I estimate the model in two stages where in the first stage the probability of a person being employed (or economically active) is estimated, which is then used as an adjustment parameter in the second-stage equation.
16 Linear trends should also help account for differences in pre-trends in the incidence of temporary employment, i.e., they would help absorb a spuriously significant coefficient (Simon, 2016).
17 One could argue that the date of the contract is endogenous as a person is employed based on his/her observable and unobservable characteristics; however, I control for other characteristics in the model as well.
18 Apart from fixed-term contracts, the OECD definition of temporary employment covers temporary agency workers, daily workers, trainees, people in job creation schemes, workers on contracts for a specific task, those on replacement contracts, and on-call workers (OECD, 2002).
19 It has been mentioned earlier that the Government introduced the law in 2012 with the possibility of seasonal work in agriculture via vouchers up to 90 days throughout the year. However, the share of seasonal workers among temporary employees actually decreased in 2012 and 2013 before it rose again in 2014-2017 (excluding 2015, Figure 2), but mainly due to seasonal work in the tourism sector. Other factors, such as different forms of youth employment via Government incentives, might have influenced the incidence of temporary employment; however, the two incentives (vocational training without commencing employment (temporary employment by definition) and employment of youths on permanent contract without the payment of employers’ contributions) actually work in the opposite directions regarding temporary employment.
20 I show the results on a quarterly instead on a monthly level given that “using more aggregated event dummies reduces noise and makes the pattern of the coefficients smoother” (Simon, 2016: 139). The same results estimated on a monthly level are available in the Appendix (Figure A1) where it is obvious that since the estimation contains “thrice as many coefficients with the same number of observations, each individual coefficient is less precisely estimated” (Perez-Truglia, 2019: i).
21 Available upon request.
22 Table 2 presents the preferred model specification, while other model specifications are available in Appendix and/or upon request.
23 For example, the second reform dummy variable (August 2014-December 2017) also includes the ‘cumulative effect’ as the reform came in on top of the first (from June 2013) reform. In addition, the results of the reform variables modelled as dummies are presented here; however, using EPL indices (Table 1) instead of dummy variables gives qualitatively the same results (available upon request). Additionally, I have estimated all the models using linear probability regressions and the obtained results are much the same as those presented here (available upon request).
24 Available in tables in the Appendix and/or upon request.
25 The same model predicts that in the case when restrictions for permanent and temporary contracts are similar (the same), the easing of the former will lead to more permanent contracts as well as to more fixed-term contracts. All the same, this theory predicts that liberalisation of the permanent contracts would lead to a reduction of the share of temporary employment on the labour market in the end (Bentolila, Dolado and Jimeno, 2019), which is not what the obtained results here show.
26 For example, Cahuc, Charlot and Malherbet ( 2016) in their theoretical model show that the protection of permanent jobs does not have an important effect on total employment; however, it does induce the substitution of temporary jobs for permanent jobs.
27 Detailed results available upon request.
28 Detailed results available upon request.
29 It is important to remember that in the event study models I have used specific dummies referring to j periods away from the reform but related to the individuals’ employment contract date, whereas in the probit regressions reform variables are just dummies indicating 1 after the reform occurred and 0 before that (not specifically related to the time of the contract).
30 Detailed results available upon request.
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March, 2020
I/2020
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