ReflecT Research Paper
13/004
Governance of Sustainable
Security: The Impact of Institutions
and Values On Labour Market
Transitions Using ESS and SILC
Data?
Ruud Muffels
September 2013
©ReflecT, Website: www.tilburguniversity.edu/research/institutes-and-researchgroups/reflect/, Address: PO Box 90153, 5000 LE Tilburg, The Netherlands, Phone: (+ 31)
(0)13 466 21 81, ISSN
1
Governance of Sustainable Security: The Impact of Institutions
and Values On Labour Market Transitions Using ESS and SILC
Data?
Ruud Muffels1
Abstract
The paper examines the impact of labour market institutions and social norms and
values on the relative performance of countries in balancing flexibility and security. In
a previous paper (Muffels, 2010) we defined a set of institutional and transition
outcome indicators to compare the relative labour market performance of 26
countries in the EU on these two dimensions. The picture provided little support for
the supposition that regimes tend to converge. In this second paper we try to explain
the transition patterns we observe. We are particularly interested in the impact of
labour market institutions and social norms and values on these transition patterns.
The institutions to examine concern not only the usual candidates such as EPL,
Unemployment Insurance and Active Labour Market Policy but also various indicators
for the wage bargain such as union density, collective agreement coverage and level
of centralisation or decentralisation. The novelty is that we also consider the effects
of social norms and values in society associated with work orientations and feelings of
trust and altruism. We estimate multi-level multinomial regression models with
country fixed effects on integrative and exclusionary labour market transitions.
Integrative transitions refer to job-to-job transitions, transitions from a fixed-term into
a permanent job and re-entry into employment; exclusionary transitions to exit out of
employment. The evidence confirms that employment regulation exerts negative
effects and UI generosity and trust positive effects on integrative transitions. Support
is found for the positive impact of UI generosity on the job match. Labour market
policy and wage bargain indicators exert counterintuitive or small and insignificant
effects.
Keywords: flexicurity, welfare regimes, labour market institutions, wage bargain,
social norms and values, SILC-data
JEL Classification Code: J3, J5, J6, D63
1
The paper was presented at the WP3-workshop of the GUSTO project, held on 20-22
September 2010, CES, Sorbonne University, Paris
2
1.
Introduction and background
In an earlier paper (Muffels, 2010) we defined dynamic indicators to measure the
balance between flexibility and what is called “sustainable security” in society and
secondly to apply these indicators to judge the relative performance of countries,
regimes or pathways. The starting point was a ‘Stocks-Flows-Outcome’ conceptual
model based on Sen’s capability approach. The stocks indicate the capabilities or free
choices of people, the flows agency and the outcomes the extent by which people
living in a particular country or belonging to a particular policy regime are able to
safeguard income and employment security or well-being throughout the life course.
Using comparative panel data (SILC), transition outcome indicators on job and
contract mobility and on income, wage and employment security were next
calculated. A distinction was made with respect to these “objectively assessed”
indicators between ‘integrative’ transitions, which are transitions into employment or
out of income insecurity, and ‘exclusionary’ transitions, which are transitions out of
employment or into income insecurity. In the second step the various transition
indicators were combined in a flexibility-mobility index and an income-employment
security index for mapping the countries on the way they balance flexibility and
security.
There appeared little evidence for convergence since huge differences were observed
across the 26 countries. The picture drawn from institutional and dynamic indicators
appears not only dissimilar but also weakly resembling the dominant welfare regime
classification of Esping-Andersen or the ‘coordinated-liberal’ varieties of capitalism
classification of Hall and Soskice. In Figure 1 we show the classification of countries
obtained from our transition indicators on job, contract and wage mobility (mobility
Index) and on employment and income security (security Index)2.
2
The calculation of the transition indicators is explained in Muffels (2008, 2010). The indicators are a
weighted average of the annual transition probabilities between the various income and employment
statuses weighted with the share of each income or employment status in society. The probabilities
are transformed into indices by dividing each indicator by the European average and multiplying by
100. In the last step a composite indicator is defined by taking the mean over the various separate
indices.
3
Figure 1. The relationship between flexibility (job, contract plus wage mobility) and
security (income plus employment security) using transition indicators (indices),
EU26
Source: Muffels, 2010 (based on SILC data for 2005-2006).
The Nordic countries are in the “flexicurity quadrant” with high levels of flexibility and
security but the picture for the other countries is more mixed. The Eastern countries
share a low level of security but very dissimilar levels of flexibility.
Sustainable security
The ‘stocks-flows-outcomes’ model was inspired by Sen’s capability model but also by
the life course approach because what matters to people is that throughout the life
course they are able to balance mobility and security in a satisfactory way. We used
the term ‘sustainable security’ to underline the life course dimension of security.
Sustainable security then translates into the security throughout the life course to be
able or to feel able to do the things in life which one has reason to value most. The
definition has an objective and subjective interpretation. The objective interpretation
requires the setting of a threshold below one is considered insecure like a poverty
threshold for income insecurity that generally implies a normative view about what is
just or fair.
4
In this paper we aim to explain the transition patterns on the labour market. We are
particularly interested in the impact of labour market institutions on these transition
patterns. The institutions to examine concern not only the usual candidates such as
EPL, Unemployment Insurance and Active Labour Market Policy but also various
indicators for the wage bargain such as union density, collective agreement coverage
and level of centralisation or decentralisation. The novelty of the paper is that we also
consider the effects of norms and values in society. We estimate multi-level
multinomial regression models with country fixed effects on integrative and
exclusionary labour market transitions. Integrative transitions refer to job-to-job
transitions, transitions from a fixed-term into a permanent job and re-entry into
employment; exclusionary transitions to exit out of permanent, self or temporary
employment.
2.
Flexibility and security
2.1. Trade-off versus flexicurity
The definition of flexibility and security used here is derived from Wilthagen’s matrix
(2004) and Standing’s (1999) definition of five forms of flexibility (internal and external
numerical flexibility, functional internal and external and wage flexibility) and seven
forms of security (job, work-life balance, employment, employability, representation
or voice, workplace and income security). The use of the SILC data does not allow us
to focus on internal or functional flexibility and employability or representation
security since that would require company or demand side data. For this paper we
focus therefore on external numerical flexibility, wage flexibility, and on job, income
and employment security but not on internal flexibility and combination security.
2.2
Flexibility and security indicators
A second element is that we want to examine the effects of various policy/institutional
indicators on transition patterns. From the literature on indicators three sets of
institutions can be distinguished:
5

Institutional indicators on labour law and labour market policy: they pertain to
EPL regulations, minimum wage, taxes, working time regulations and LMP
spending as percentage of GDP (or per unemployed).

Another set of institutional indicators concern indicators on unemployment
insurance such as benefit replacement rates, benefit access conditions and
benefit coverage.

A third set refer to company practices (pay schemes, working time
arrangements) and those dealing with the wage bargain (union density, union
coverage, centralisation versus decentralisation etc.).
For this paper we restrict ourselves to macro-level indicators for which data were
readily available for most of the countries participating in SILC. Indicators can be
measured in a static (stocks) and a dynamic way (flows). Institutional and outcome
indicators, whether they are static or dynamic, are then used to map countries in twodimensional space showing the bivariate relationships between the indicator variable
and the country dummy. That has been the approach in the previous paper (Muffels,
2010). Another approach is to examine the multivariate relationships between the
outcome indicators and the institutional and/or country variables. In such a modelbased approach the static (though they might vary over time) institutional indicators
act as explanatory factors and the dynamic (or transition based) outcome indicators
as dependent variables (see Muffels & Luijkx, 2008). This paper focuses on the
multivariate approach.
3.
Data
The institutional indicators to be explained in section 4 are derived from the macrolevel information mostly contained in the OECD and Eurostat databases. Most of the
information in these databases stem from the European labour Force Survey. We used
the time-varying information for the years 2003-2006 since these years overlap with
the years for which we had panel data. For the calculation of the transition outcome
indicators we used the micro-level data of SILC for the years 2003-2006. The data
contain information on 26 countries for 2005-2006 but only 15 countries for 20042005 and even less countries for 2003-2004 for which reason we used the 2005-2006
6
data. The macro-level information for the corresponding years were next linked to
the individual-level longitudinal SILC data for the years 2003-2006.
The data on norms and values come from the European Social Survey that is a
comparative repeated cross-sectional social survey on opinions, political and social
attitudes, social norms and values in Europe. We used the information for the years
2002-2006 which corresponds rather nicely to the SILC data. We linked the ESS data
to the SILC data by first calculating the mean scores of values by sex, age class, country
and year and then matching these values to the SILC data. The ESS is though a twoyearly survey and hence not containing information for the years in between, that is
for 2003 and 2005. For these years we imputed the data by taking the means for 2002
and 2004, and for 2004 and 2006 and assigned these to 2003 and 2005.
4. Institutional and outcome indicators
4.1. Institutional flexicurity indicators in the European Employment Strategy
The three indicators used in the European Employment Strategy (EES) to measure and
monitor flexibility, pertain to the strictness of Employment Protection Legislation (EPL)
and the share of temporary and part-time workers in a country (see Chung et al.,
2009). For analysis purposes also employment tenure figures are often used. The first
is an institutional indicator, the other two can be viewed as outcome indicators for the
employment protection legislation and part-time work legislation.
For employment security the agreed institutional indicators in the EES are: the
percentage of the adult population participating in education and training
programmes, the expenditures on active labour market policies (ALMP) as a
percentage of GDP or per capita and the frequency of unemployed people moving into
paid work through the public employment services. Another indicator used is the skill
level or level of educational attainment of the labour force reflecting firms’
investments in skill development programs (investment in life-long learning and
continuous vocational training). Institutional indicators for income security in the EES
are the replacement rates of the unemployment benefits (UIB) and the expenditures
to passive labour market policies (PLMP) as a percentage of GDP. Another institutional
7
measure for income security that is often used in EU policy circles, is the headcount of
people in poverty before and after social transfers. It shows how well governments
with their social transfer system are able to reduce the number of people in poverty.
These indicators reflect the existing social security and passive labour market policies.
Most of the institutional indicators on employment security comes from the EU-LFS
(Labour Force Survey) data, whereas the information for the income security
indicators comes from the EU SILC data (Statistics on Income and Living Conditions).
Due to increasing interest in the EES for work-life balance issues, indicators on
combination security or work-life balance (WLB) security are proposed, referring to
the ability to combine work and private life acting as one of the seven security aspects
distinguished before. WLB indicators mentioned in the literature also pertain to
indicators like the availability of child care relief facilities, the options for working in
flexible working times, and the options for care leaves and other types of leave. In
addition we must mention the existing EES indicators on the issue of gender equality,
such as the gender pay gap and the gender-based occupational segregation rates
(Philips et al, 2007b, EC 2007).
4.2
Institutional indicators on flexicurity in the literature
In the economic literature the most often used indicators are the employment
protection legislation indicators as developed by the OECD, the Active Labour Market
Policy Expenditures indicators expressed in % of GDP and job tenure figures. In the
industrial relations literature though also indicators are proposed concerning e.g. the
features of the industrial relations system. The particular features and configuration
of industrial relation systems impact on the wage levels as well as on the wage
distribution across skill levels and industrial sectors and therewith affect wage mobility
in the economy. The literature generally refers to three main indicators:
-
Trade union density (the % of workers being a union member)
-
Collective Wage Bargain coverage (% of workers covered by a Collective
Agreement (CA)
8
-
Degree of centralisation of the wage bargain that can differ from country to
country ranging from a very decentralised way of bargaining, that is at the
company or plant level, to a very centralised wage bargain at the national level.
We collected information on these wage bargain indicators from the OECD and from
Heejung (2009). Table 1 shows the evidence on macro-level institutional indicators for
the years closest to the SILC data of 2005-2006. The information on EPL, trade union
density and collective agreement coverage is available for 2003 or 2004. The EPL for
2003 as constructed by the OECD is used while this comes closest to the time period
considered in SILC (2005-2006).
9
Table 1: Institutional Indicators by country (2003-2006)
Internal Labour Market
Employment protection (2003)
EU26
Austria
Belgium
Cyprus
Czech Rep.
Germany
Denmark
Estonia
Spain
Finland
France
Greece
Hungary
Ireland
Iceland
Italy
Lithuania
Luxembourg
Latvia
Netherlands
Norway
Poland
Portugal
Sweden
Slovenia
Slovakia
U Kingdom
EU26
EPL
2.15
2.51
.
2.10
2.40
1.78
2.31
3.01
2.13
2.90
2.82
1.75
1.33
1.57
2.33
2.76
3.36
2.50
2.27
2.72
2.19
3.36
2.50
2.58
1.75
1.11
2.51
EPLR
2.37
1.73
.
3.31
3.00
1.63
2.58
2.46
2.17
2.47
2.33
1.92
1.60
1.73
1.77
2.93
2.75
2.30
3.05
2.25
2.06
4.17
2.86
3.15
2.31
1.12
2.41
EPLT
1.50
2.63
.
0.88
1.25
1.38
1.53
3.50
1.88
3.63
3.13
1.13
0.63
0.63
1.88
2.07
3.75
2.10
1.19
3.13
1.75
2.75
1.63
1.88
0.38
0.38
2.33
EPLCD
3.25
4.13
.
2.13
3.75
3.13
3.63
3.13
2.63
2.13
3.25
2.88
2.38
3.50
4.88
4.03
3.88
4.00
3.00
2.88
3.63
2.88
3.75
2.88
3.75
2.88
3.22
Wage Bargain
(2003-2004)
CACO
TUD V
32
98
54
96
70
68
21
35
21
65
69
83
.
.
15
81
72
90
8
90
23
65
18
42
35
.
.
.
33
70
.
.
40
58
16
20
21
81
55
.
14
35
18
87
75
92
44
100
24
.
29
35
22
73
External
Labour
Market (20052006)
CACEN
0.71
0.61
0.26
0.27
0.47
0.54
.
0.38
0.57
0.17
0.39
0.26
0.64
.
0.34
.
0.33
0.30
0.58
.
0.20
0.30
0.56
43.00
.
0.13
0.51
ALMP
0.72
1.22
0.09
0.26
0.86
1.37
0.07
0.72
0.87
0.92
0.16
0.28
0.66
.
0.45
0.27
0.43
0.26
1.19
0.58
0.45
0.58
1.32
0.27
0.32
0.33
0.73
NRR
62
63
66
57
65
78
37
50
71
61
22
52
70
69
8
40
70
45
73
79
54
60
72
68
39
61
53
Notes: EPL Employment Protection Regulation; EPLR=EPL for Regular Contracts; EPLT=EPL for FixedTerm Contracts; EPLCDM=EPL for Collective Dismissal;
TUD=Trade Union Density; CACOV Collective Agreement Employees Coverage; CACEN=Measure of
Centralization of Wage Bargain; ALMP=Active LMP expenditures as % of GDP; NRR=5 year
Replacement Rates Benefits OECD
Source: OECD Database for EPL, ALMP, NRR and TUD; H. Chung (2009) for CACOV, CACEN
10
4.3
Indicators on attitudes, social norms and values
The observed dissimilar performance of countries in balancing flexibility and security
outcomes might indeed be related to institutional differences between countries as
we contended in the previous section. Institutions though are designed and
implemented according to the dominant social norms and values in society. If the
norm for women is to work full-time the institutions for employment and income
support might function properly to get women into full-time work but will likely to
render poor support to women who prefer caring for children while not working or
working part-time. Values then have an indirect effect mediated through the
institutions. Values though might also exert a direct effect on integrating or
exclusionary transitions through affecting agency decisions of people. In countries
with a stronger work ethos people might quicker re-enter employment after being
dismissed than in countries with weaker work values (integrating transition). In
countries with higher levels of trust in other people or in national institutions people
might be more willing to take risks and to more easily change jobs than in countries
where people are more left alone. But higher levels of trust might also reflect higher
levels of social capital and stronger social networks because of which people are more
likely to experience integrating transitions (re-entry) and less likely exclusionary
transitions (exit). Societies with a higher level of tolerance to homosexuals or
undemocratic parties or where the opinions towards immigrants are more positive
(open pluralist societies) or less negative (less competition for scarce jobs) are likely
to experience more integrative and less exclusionary transitions. It is not the purpose
of this paper to unravel the causal links between values, institutions and outcomes but
to examine the possible direct impact of values on transitions and to see to what
extent they contribute to explain the cross-country differences in flexibility-security
outcomes. The information on norms and values used are from the two-yearly
European Social Survey covering the years 2002-2006 which correspond nicely with
the 2003-2006 period for the SILC data. In Figure 3 we depict the figures for trust in
other people, altruism and positive opinions about the contribution of immigrants to
the economy, culture and lifestyle for 2004 for 24 European countries including
11
Switzerland (CH). The largest variation exists in trust with the Scandinavian countries
on top; the variation in altruism and opinions about immigrants are less uneven.
Figure 2: Trust in people, altruism and positive opinions
about immigrants (contribution to economy, culture,
lifestyle) in the EU, ESS 2004
8
6
4
2
DK
NO
FI
SE
NL
IE
CH
EE
AT
UK
LU
ES
DE
BE
altruism
Pos opinions immigrants
EU24
trustpeople
FR
IT
CZ
SI
HU
SK
PT
GR
PL
0
4.4 Transition outcome indicators
In previous work using the European Community Household panel for 1994-2001 we
constructed flexibility indicators for job and contract mobility and security indicators
for income and employment security (Muffels & Luijkx, 2008; Muffels, 2008). The
same indicators are used again now for this paper but applied on the SILC data
covering EU26 for 2005-2006 including the Baltic and Eastern welfare states3.
Flexibility measures: job, contract, working time and wage mobility
The ECHP did not allow estimating job mobility due to lack of information on whether
a job change involves an employer’s change or not. SILC however contains information
on self-reported job change in the last 12 months and whether the change is a
voluntary or an involuntary change. This variable is now used to construct a simple
measure for voluntary and involuntary job mobility, the percentage of employed
3
Indicators on combination or work-life balance security are part of the framework elaborated in
Muffels (2010) but not discussed here.
12
people changing jobs across two years voluntarily or involuntarily. Involuntary
mobility deals with (collective) dismissal, business close downs and end of contract
whereas voluntary mobility deals with people seeking better jobs or jobs that match
their working time preferences better. A second simple flexibility indicator that we
used in previous work is the so-called contract mobility (CM) or the annual transition
rate for the various employment contract statuses. The mobility from a temporary into
a permanent job is only one of the CM indicators used here, another is the mobility
from a permanent job into self-employment which seems to become increasingly
important in a number of countries (own account self-employed workers).
Wage or pay flexibility and mobility
Wage flexibility indicated by wage mobility is an important dimension of flexibility
since it touches the question whether the labour market and its institutions create
sufficient incentives to workers and unemployed people to search for a job or to move
to another job. It is also associated with one of the key issues in the flexicurity debate
on transition security, the security attained when people either voluntarily or
involuntarily change positions and because of that become more or less income
secure. We therefore see yearly changes in wage or pay primarily as indicators for the
level of wage flexibility. We can associate wage mobility to the occurrence of a
voluntary and involuntary job change in the last year. For wage mobility we use a
simple metric on wage deciles changes (income groups ranging from low to high
incomes with 10% of all income earners in each group). We calculated the percentage
of people moving at least one wage decile up or down the wage ladder. Those who
stay in the same decile are considered to experience a lateral move.
4.2 Security indicators: dynamic income and employment security
The advocates of the Transitional Labour Market approach break a lance for ‘make
transitions pay’ policies which are considered more effective than ‘make work pay’
policies. TLM policies therefore facilitate ‘integrative’ transitions and prevent
‘exclusionary’ transitions. To assess whether a job change is an ‘integrative’ or
13
‘exclusionary’ transition we might calculate upward or downward job moves
determined by the employment security or the level of hourly pay .
The Employment Transition Security (ETS) indicator is such a measure that allows to
make this distinction. The security indicator departs from the matrix of employment
status changes across two years. It is a weighted average of the “entry’ and “exit’ rates,
but with stays in employment considered as entries and stays out of employment as
exits. In Table 3 we show the transition matrix used to construct the ETS employment
security indicator. Entries into statuses with more security are defined as upward
transitions (indicated by a + sign), and exits into statuses with lower security as
downward transitions (indicated by -). Stays are defined as lateral or neutral
transitions (indicated by =).
The matrix shows the contract statuses at t cross-tabulated with the contract statuses
at t+1. The signs (+, -, =) assigned to each cell depend on the relative ranking of each
of the various contract statuses with a view to the level of employment security.
Table 3: Change in employment security from year t to t+1 by type of contract (ETS)
Perm
Rank ES
SE
Temp
Une
Stud
Ret
Inact
[4]
[4]
[4]
[4]
[1]
[2]
[3]
Perm
1 [+]
2 [-]
3 [-]
4 [-]
5 [-]
6 [-]
7 [-]
SE
8 [+]
9 [+]
10 [-]
11 [-]
12 [-]
13 [-]
14 [-]
Temp
15 [+]
16 [+]
17 [+]
18 [-]
19 [-]
20 [-]
21 [-]
Une
22 [+]
23 [+]
24 [+]
25 [-]
26 [-]
27 [-]
28 [-]
Stud
29 [+]
30 [+]
31 [+]
32 [-]
33 [-]
34 [-]
35 [-]
Ret
36 [+]
37 [+]
38 [+]
39 [-]
40 [-]
41 [-]
42 [-]
Inact
43 [+]
44 [+]
45 [+]
46 [-]
47 [-]
48 [-]
49 [-]
Note: Perm=Permanent contract; SE=Self-Employment including family workers,
Temp=Temporary Contract; Une=Unemployment, Stud=Studies, i.e. Education,
Training; Ret=Retirement; Inact=Inactivity.
Source: Derived from EMCO-IG (2009) and own additions
The ranks implicitly assigned by the ETS indicator are presented in the second panel
(Rank ES) ranging from 1 (high) to 4 (low) showing that the ETS assigns a higher score
14
of employment security to any employment status compared to any non-working
status. The ranks within the non-working groups are identical whereas the ranks
within the employed are highest for permanent, second highest for self-employed and
lowest for temporary workers4.
Income security transitions
For income security we employed various measures for poverty and wage income
transitions using the SILC data. We developed measures for upward or downward
income transitions such as the share of people moving upwards or downwards in
terms of wage plus social security income or for the movements out or into low wage
jobs and for movements out of or into working poverty. Here we only discuss the YTS
or Income Transition Security (YTS) indicator. This is similarly to the employment
security indicator calculated as the weighted average of the “entry into’ and “exit out
of’ poverty rates, in which a stay in poverty is counted as an entry and a stay out of
poverty as an exit, weighted with the shares of people in or out of poverty at t for the
years of observation. Poverty is defined according to the 60% threshold of median
equivalent household income.
Table 4 shows the means of all outcome indicators for the year 2006 for EU26. We
also include in table 4 a few static indicators such as the poverty head count ratio
based on the 60% OECD threshold and the headcount for the working poor according
to the same threshold.
Voluntary mobility is shown to be much higher than involuntary mobility in all
countries. Job mobility turns out to be high especially in the UK but very low in Poland,
France and Luxembourg, Also Denmark did at that time not show very high mobility
rates though high mobility rates are observed in the other Nordic countries Norway
and Sweden. In the next step we calculated the contract mobility indicator (CM) as
the mean of the transition rates between the three different contract statuses
4
To avoid normative statements about these rankings, we used in an earlier study (Muffels and Luijkx,
2008) the subjective assessment of people on how secure or insecure they judge their employment status
based on the European Household Panel Data. SILC though contains no such information unfortunately.
Another way would be to empirically assess the probability to be in stable employment over a particular
period.
15
distinguished: a permanent job, a temporary job and self-employment. Table 4 shows
the contract mobility rate but also the mobility from a temporary job into a permanent
job because the latter indicator shows whether temporary jobs act as stepping stones
into permanent jobs or as dead-end jobs from which it is hard to escape.
Table 4. Flexibility and Transition Security Outcome Indicators Based on SILC
2005-2006
Employment
security
Job mobility
EU26
AT Austria
BE Belgium
CY Cyprus
CZ Czech Rep.
DE Germany
DK Denmark
EE Estonia
ES Spain
FI Finland
FR France
GR Greece
HU Hungary
IE Ireland
IS Iceland
IT Italy
LT Lithuania
LU Luxembourg
LV Latvia
NL Netherlands
N
O Norway
PL Poland
PT Portugal
SE Sweden
SI Slovenia
SK Slovakia
UK Un. Kingdom
EU EU26
TJM
0.07
0.09
0.10
0.09
0.08
0.10
0.14
0.18
0.15
0.06
0.07
0.19
0.09
0.18
0.11
0.11
0.06
0.11
0.09
VJM
0.04
0.06
0.08
0.06
0.04
0.09
0.12
0.13
0.11
0.04
0.05
0.16
0.07
0.15
0.07
0.10
0.04
0.10
0.07
INVJ
M
0.02
0.03
0.02
0.03
0.04
0.01
0.02
0.05
0.04
0.03
0.02
0.03
0.02
0.03
0.04
0.02
0.02
0.01
0.02
0.22
0.06
0.08
0.20
0.07
0.16
0.26
0.10
0.21
0.04
0.06
0.15
0.05
0.14
0.26
0.07
0.01
0.02
0.03
0.05
0.02
0.03
0.00
0.03
and
Income
TP
0.40
0.35
0.31
0.35
0.31
.
0.61
0.30
0.28
0.15
0.18
0.53
0.52
0.23
0.24
0.33
0.47
0.59
0.20
ETS
0.30
0.15
0.24
0.20
0.20
0.45
0.31
0.17
0.32
0.25
0.19
0.11
0.16
0.63
0.15
0.22
0.24
0.23
0.21
YTS
0.76
0.80
.
.
.
0.81
0.73
0.70
0.74
0.73
0.68
.
0.75
0.83
0.63
.
0.76
.
.
POOR
0.12
0.12
0.11
0.08
0.13
0.06
0.16
0.18
0.12
0.13
0.18
0.14
0.15
0.08
0.16
0.20
0.16
0.18
0.09
WPOOR
0.09
0.06
0.08
0.04
0.08
0.04
0.11
0.13
0.08
0.08
0.15
0.09
0.06
0.07
0.10
0.15
0.12
0.13
0.07
0.46
0.29
0.09
0.52
0.46
0.46
0.51
0.26
0.44
-0.05
0.29
0.43
0.13
0.13
0.38
0.20
0.79
.
0.72
0.81
.
.
.
0.72
0.08
0.22
0.18
0.09
0.09
0.13
0.15
0.14
0.06
0.19
0.14
0.06
0.05
0.10
0.09
0.10
Note: TJM=Total Job Mobility; VJM=Voluntary Job Mobility; INVJM=Involuntary Job
Mobility; TP=Mobility from temp to permanent job; ETS=Employment Transition Security;
YTS=Income Transition Security; POOR=Poor according to OECD’s 60% median equivalent
household income standard; WPOOR=% of people Working Poor (poor and employed)
16
Source: Eurostat, SILC data, 2003-2006
The mobility into permanent jobs is especially high in the UK, the Baltic States and
some Eastern and Nordic countries, moderate in most Continental countries and
rather low in the Southern countries. Contract mobility rates on the other hand are
very low in Iceland, Portugal, France and the Netherlands (The Danish figures are
biased, see note 3) but high in Hungary, Slovakia and again in Spain. A low level of
contract mobility signals a low turnover on the labour market.
The last indicator on flexibility is the wage mobility indicator as we explained before.
We defined our wage mobility measure as the percentage of people moving up or
down at least one decile. In Figure 3 we depict the results graphically. The picture on
wage mobility is very dissimilar to the job or contract mobility figures we presented
earlier.
Remarkably so, the highest mobility is achieved in Latvia, Slovakia, Poland and Estonia
since these countries show high upward but also high downward wage mobility rates.
In Slovakia more than 40% of the working people saw their wage rise by one decile or
more from 2005 to 2006 but also one in four saw their wages decline. Wages are
flexible in these countries but not very secure. The UK, Netherlands, Denmark and
17
Finland perform rather poor but as Figure 3 clearly shows, wages are much more
stable across years in these countries than in Slovakia, Latvia or Poland. There seems
to be a trade-off between wage stability and total mobility. The higher total mobility
is the lower wage stability. Remarkable is that Germany has a relatively low stability
and the UK a rather high wage stability.
The two employment -and income transition indicators show the levels of security
attained in the various countries. Employment transition security is high in Denmark,
Sweden, the UK and Austria but rather low in Poland and the other Eastern states. The
country scores according to the mobility figures in Table 2 appears to correspond
generally fairly well with those according to the institutional indicators though not for
all countries like Belgium, Spain and Norway. It illustrates that the institutional rules
exert a strong effect on outcomes but that they still tell only part of the story since it
depends also on other factors how regulations work out in practice. The underlying
reason is that actors might not behave in accordance to the norms or regulations, and
therefore cause unexpected outcomes. Institutional indicators need for that reason to
be supplemented with outcome indicators to obtain information on the achieved level
of mobility or flexibility in a country.
4.
Estimation of transition state multinomial regression models
In the final step we estimated various transition state models in which the dependent
variable represents the various mobility and security indicators. For this paper we
restricted ourselves to:

job-to-job transitions (the mobility, voluntarily or involuntary, from one job
into another with those not moving acting as the reference group)

the mobility from a fixed-term contract into a permanent contract (staying in
a fixed-term contract acting as the reference group);

re-entry mobility into either an open-ended contract, self-employment or a
fixed-term contract after unemployment or inactivity (those staying
unemployed/inactive as reference group).
18

exit mobility out of employment from an open-ended contract, from selfemployment or from a temporary contract into unemployment/inactivity
(those staying in employment acting as the reference group).
The first job mobility measure is a measure for flexibility whereas the last three
measures indicate the level of employment security and changes therein over time.
Five models are estimated and reported in Table 5 and Table 6. In Table 5 the focus is
on explaining job mobility and employment security transitions. In Table 6 we report
on the so-called values model because the focus shifted to the impact of social norms
and values on the various transitions. The baseline model containing all the controls
at the micro-level is not presented here. The models in Table 5 and Table 6 include the
micro-level controls plus some macro-level institutional measures for flexibility
(Model 1), income and employment security (Model 2,3) and for norms and values
(Model 4). Four models are hence formulated:

Model 1: the Employment Protection model with all the micro-level controls
plus the institutional measures protecting the employee such as the
employment protection regulations but also the level of replacement income.

Model II: the Labour Market Policy model with all the controls plus the
variables indicating the investments in Active Labour Market Policies and the
net replacement rates.

Model III: the Wage Bargain model again with all controls plus the three wage
bargain measures discussed before.

Model IV: The Values model again with all controls plus the four values and
norms variables: trust, altruism, positive and negative attitudes to immigrants.
The controls are chosen so as to correct for obvious compositional differences
between countries. These are gender, age and age squared to account for the nonlinearity in the relationship of age with job mobility and exit and (re)-entry mobility
(e.g. due to differences in early retirement patterns across countries), household type
and number of children indicating life course stage accounting for differences in
household formation and fertility behavior, type of job accounting for differences in
19
the shares of non-standard jobs (part-time and temporary job), health status and
regional unemployment rate.
The models are estimated as multi-level multinomial regression models with robust
estimation of the standard errors correcting for country fixed-effects. The models are
multinomial transition state models because they estimate the transitions from one
origin state (employment, unemployment/inactivity, fixed-term contract) into various
destination states (temporary contract, open-ended contract, self-employment,
unemployment/ inactivity).
The estimation of the baseline model shows that the controls have the
suspected effects, negative effects of bad health, low education and the regional
unemployment rate. The relationship with age is non-linear, inversely U-shaped for
upward transitions and U-shaped for downward transitions. Households with children
show lower transition rates indicating that transition patterns vary over the life
course.
Table 5 shows that the best performing model is the employment protection
model with the EPL and the replacement rate included, then the labour market policy
model and last the Wage Bargain model that does not add much to the explanation.
The employment protection regulations for regular contracts exerts significant
negative effects on voluntary job mobility and on the mobility from a temporary job
into open-ended contracts. On the other hand it leads to more unemployed workers
to move into a temporary job instead of moving into an open-ended contract. This
seems obvious and reflecting the situation in Southern countries where strict
regulations act as barriers to school leavers and unemployed workers to find regular
jobs. The stricter EPL for temporary workers is the less likely to move from
unemployment into a permanent contract and the more likely to move from a
temporary job into unemployment instead of a permanent job. The results show a
number of interesting institutional effects that needs however further scrutiny by
including interaction terms between the indicators while many of these institutions
are highly correlated. The wage bargain variables exert hardly any effect on the
transitions on the labour market except for the coverage rate and the union
centralization measure on the mobility from a fixed-term contract into selfemployment. The more people are covered in collective agreements the less likely to
20
make a move from a temporary job into a permanent job. This seems to reflect the
insider-outsider characteristics of labour markets with those workers falling under a
CA representing the insiders. Centralization of the wage bargain on the other hand has
a positive effect on the move into a regular job.
The replacement rate impacts strongly on the transitions observed here but the
impact is not necessarily negative. It exerts a positive effect on movements into a
permanent job or into self-employment after enrollment in a temporary job. This
might point to the job matching argument as referred to by Gangl (2006) suggesting
that benefits allow job seekers to wait and to search for the best match. It however
also has a positive effect on involuntary job mobility suggesting that in countries with
strong income protection employers tend to shift the costs of economic adjustment
to the government knowing that employees are well covered. The effects of ALMP are
puzzling, most of the effects are negative except for the effect on involuntary job
mobility. Due to ‘creaming off’ practices it might be that ALMP measures are applied
unevenly to involuntarily dismissed workers. There is also a negative effect of ALMP
spending on entry into a temporary job after unemployment. Job seekers might be
‘hold up’ in labour market programs because of which the transition into a temporary
job is delayed.
In Table 6 the negative attitudes towards immigration concerns the opinion
that many or no immigrants from the own, another region or from poorer countries
should be allowed to move into the own country. The higher the score the less tolerant
people are towards immigrants. The largest effects are observed for the trust variable
measuring the extent by which people trust other people. The higher the level of trust
in a country the higher voluntary job mobility, the higher the mobility from a
temporary
into
a
permanent
job
and
the
higher
the
re-entry
from
unemployment/inactivity into a permanent job. This seems to reflect the situation in
the Nordic countries with high levels of trust and high levels of integrative transitions.
High levels of trust seem to have negative effects on re-entry into self-employment
but positive effects on exit into unemployment/inactivity after stopping one’ s
business. Societies with higher levels of altruism are performing worse in terms of
reintegrating people back into a job and are more likely to have high exit rates from
self-employment or a temporary job into non-activity.
21
Table 5: Results of multinomial logit regression models on 2005-2006 transitions: Institutions
(robust estimation corrected for country fixed effects)
Exit out of employment
Job Mobility
Fixed-term contracts
Volunt Involunt Perm
SE
Une
Model 1: Employment Protection
EPLreg
-0.513*
0.176
-0.473*** -0.073
-0.136
EPLtemp
-0.205
-0.026
-0.151
-0.116 0.166***
EPLCDM
-0.258
0.170
0.048
0.390***
0.054
NRR5yr
-0.002
-0.005
0.011*
-0.005
0.006
Model 2: Labour Market Policies
ALMP
-0.741 0.652*** -1.126*** -0.417
NRR5yr
0.005 -0.012*** 0.011*** -0.116***
-0.27
0.005
Ina
Entry in work after Une/Ina
Perm
SE
Tmp
Perm
SE
Tmp
-0.387*
0.017
0.210*
-0.106 -0.314*** -0.018
-0.032
-0.095
0.153
0.005
0.014*
0.009
0.293***
0.104
-0.016
0.016***
-0.116
-0.045
-0.117
-0.002
-0.219
0.108
0.145
0.262**
0.047
-0.129
-0.018*** -0.004
-0.289
0.002
0.155
0.017***
-0.253
-0.002
-0.440*
-0.020***
0.159
-0.001
0.001
-0.005
-0.005
-0.01
0.010*
-0.002
-0.431
0.020***
-0.211
0.009*
Model 3: Wage Bargain
TUDensity
0.011
0.002
0.08
0.006
0,000
0.011
0.004
0.001
-0.005
0.001
CACov
-0.113
0.007
-0.014** -0.010**
0.003
-0.006
-0.012
-0.008*
0.004
-0.03
CACentr
-0.008
-0.007
0.020***
0.011
0.005
-0.017
-0.005
-0.001
-0.005
0.003
N Model 1 115814
11742
69759
108907
R2 Model 1
0.09
0.05
0.12
0.09
2
R Model 2
0.08
0.04
0.11
0.09
2
R Model 3
0.09
0.04
0.10
0.08
Controls: country, part-time; temporary job; household type; gender; age, age squared, regional unemployment rate
Source: SILC, 2005-2006
22
Table 6: Estimation Results of multinomial logit models on 2005-2006 transitions: Values
(robust estimation corrected for country fixed effects)
Exit out of employment
Job Mobility
Fixed-term contracts
Volunt
Invol. Perm
SE
Une
Model 4: Values
Trust people
0.726***
Altruism
0.699
Neg attitudes
to Immigrant -0.270
Pos attitudes
to Immigrant -1.119***
N Model 4
R2 Model 4
83838
0.09
0.132
0.328
0.355*** 0.028
-0338
1.117
0.110
-0.299
-0.298 -0.134
0.084
0.329
Ina
-0.029 0.725*** -0.309*** -0.041
0.046 -1.498*** 0.267
0.023
-1.077*** 0.316*** -0.097
-0.833*** 0.303***
Entry in work after Une/Ina
Perm
SE
Temp
1.402
10753
0.05
Perm
SE
0.102
-0.318
0.408*** -0.141
1.599*** 1.443**
0.348
0.141
0.362
0.189
-0.212
0.555***
-0.154
0.530*
0.823**
-0.047
-0.144
0.688***
64054
0.126
98727
0.088
Note: Controls are country, part-time; temporary job; household type; gender; age, age squared, regional unemployment rate
23
Temp
Finally with respect to positive and negative attitudes towards immigrants we find that
countries with negative attitudes towards immigrants are less likely to re-integrate
temporary workers into permanent employment and more likely to experience higher
levels of exclusionary transitions out of temporary jobs into unemployment or
inactivity. Remarkably so, countries with more positive attitudes towards immigrants
show lower voluntary job mobility, are more likely to re-integrate unemployed people
in temporary jobs instead of in permanent jobs but also experience higher levels of
exclusionary transitions from temporary jobs into unemployment .
6. Conclusions
By way of conclusion, the paper clearly shows that the institutional and static
indicators generally used for evaluating a country’s achievement on flexicurity are
inadequate to show the performance of labour markets from a dynamic perspective
since flexicurity policies demand information about transitions and durations. We
started the paper by explaining our conceptual model for arriving at dynamic
indicators for monitoring and analyzing a country’s labour market performance. We
called this model the stock-flow outcome model (SFO) on flexibility and security in
which the stocks of capabilities (forms of human, social and cultural capital), together
with the flows (choices and events) determine the outcomes in terms of flexibility and
sustainable security. The model served already as the starting point for estimating
multivariate models to explain the transitions as captured in the various dynamic
indicators and then to add institutional measures and country characteristics to the
models to control for compositional differences and to examine the effect of
institutions on these transitions. We have done that before on the European
Community household panel. We conducted some preliminary analyses on the SILC
data, which we discussed briefly.
A number of single indicators on labour market mobility and on income and
employment security were calculated and we looked into how well the various labour
markets perform according to these. We in the end constructed two composite
24
indicators on flexibility and security combining the information embedded in the
single indicators.
The picture for the countries that we derived from the various outcome indicators is
mixed. It shows that the picture derived from the institutional indicators (e.g. on the
regulations for temporary and permanent jobs) is rather different from the picture
obtained by using the dynamic indicators. The findings on the Eastern and Southern
countries translate strongly into the relative poor outcomes of these segmented
labour markets with respect to exhibiting low levels of mobility in terms of job,
contract and wage mobility and simultaneously achieving low standards of income and
employment security. The Scandinavian countries seem to attain fairly high levels of
dynamic employment and income security. But also the UK and Ireland perform well
with respect to employment security though less well with regard to income security.
The information presented here covers the years 2005-2006, but a period in which the
labour market was flourishing. This suggests that there is ground to suspect the
outcomes to become worse in the years to come as a result of the economic crisis
most of the EU countries faced since the end of 2007. We found some evidence that
some of the institutions we have looked at in this paper exert rather strong effect on
flexicurity transitions and outcomes. Especially the employment protection legislation
create strong barriers on the labour market either to enter or to leave a job and to
move into a permanent job. For the replacement rates we found mixed evidence
showing positive effects on movements from a temporary job into a permanent job or
into self-employment but also facilitating involuntary job mobility. This might point to
the job matching argument suggesting that benefits allow job seekers to wait and to search for the best match. It however also has a positive effect on involuntary job
mobility (dismissals) suggesting that in countries with strong income protection
employers tend to shift the costs of economic adjustment to the government knowing
that employees are well covered. We looked into the impact of values on integrative
and exclusionary transitions and found significant effects for trust and positive and
negative opinions about immigrants. Societies with high levels of trust seem to allow
people to take more risks either to change jobs more easily or to move into selfemployment and to be more mobile. Societies with high levels of altruism on the
25
contrary seem to have higher levels of exclusionary transitions from the labour
market. Countries with stronger positive or negative feelings about immigrants seem
to perform worse in reintegrating temporary workers or unemployed people back into
standard jobs. Much of these findings especially on the impact of values need further
scrutiny to come to more evaluative conclusions. One conclusion though is that the
differences in institutions and values undeniable contribute to explain the large
diversity in the transition patterns in Europe and in the way countries are trying to
attain a better balance between flexibility and security.
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