Does occupational welfare matter? Measurement and the importance of
collectively negotiated sickness benefits in cross-national social policy
analyses: Case of the Nordic countries
By Laura Järvi and Susan Kuivalainen
Laura Järvi
University of Turku
laura.jarvi@utu.fi
Susan Kuivalainen
National Institute for Health and Welfare
susan.kuivalainen@thl.fi
Paper to be presented at the annual ESPANET conference, 10 years of European Social
Policy Analysis Network, September 6–8, 2012, Edinburgh.
Please note this is a very first draft – comments and suggestions are welcomed.
Introduction
Comparative studies on welfare states measure social citizenship in order to understand
their development, diversity, and change. Previous studies have primarily focused on
statutory provisions while neglecting occupational welfare and collectively negotiated
benefits even though welfare is channelled through several different routes, as pointed out
by Titmuss (1958). The reason for this narrow focus is the perception that occupational
welfare plays a relatively insignificant role in welfare delivering. Another reason for this
neglect is the methodological challenges to measuring occupational welfare in crossnational comparisons, including the lack of any available systematic data. This paper
aims to include occupational welfare in cross-national analyses on social policy.
The central question in cross-national analyses on social policy – who gets what – is
usually answered with stylised cases, which offer a common yardstick allowing
systematic comparison. The social citizenship approach measures the extent of social
rights via the coverage and level of protection provided. Calculations are based primarily
on the average wage of the standard production worker, a gauge whose ability to reflect
today’s reality is in many ways debatable due to changes in the labour market. Our
analyses move away from the standard production worker and examine five different
occupations representing both low- and high-skilled workers as well as public and private
sector employees. We will generate analyses where the statutory provision can be
compared to collectively negotiated benefits as one form of occupational welfare.
Occupational welfare in this paper is understood as social benefits provided by employers
to employees as a result from the employment. Here we focus on occupational welfare as
agreed upon by labour market organisations, in particular on sickness benefits. Sickness
benefits are one of the key aspects of social security. Many states have given legal
obligation to employers to pay compensation during sickness, and, in addition, labour
market organisations have agreed upon additional support. We have chosen four Nordic
countries as case examples for several reasons. The Nordic countries are characterized
not only by the strong role of the state and high levels of statutory benefits but also by
1
corporatist structures and their long tradition of collective bargaining (e.g. EspingAndersen 1990).
Since the Nordic countries have similar systems of collective bargaining, it is useful to
apply this method in analysing occupational welfare. The paper illustrates the potential of
including collectively negotiated benefits into cross-national analyses covering select
European countries. We discuss the strengths and weaknesses of the new approach,
construct a more nuanced description of social benefits, and illustrate how a narrow focus
on statutory benefits can be misleading. The paper starts by presenting the conventional
method of studying social citizenship and then discusses occupational welfare and
presents previous work. Much of the paper is devoted to presenting methodological
choices. The section prior to the summary and discussion shows the preliminary results of
inclusion of occupational welfare in analyses in year 2010.
Social citizenship approach - conventional measures
Comparative welfare state analyses have for long relied overwhelmingly on public
spending as the indicator of welfare state commitment. In the late 1980s, an alternative
approach emerged. While spending data revealed little about the level of social protection
against risk, the social citizenship approach aimed to understand the impact of the welfare
state on individual life-chances. The essence of this approach is the conditions stipulated
in social insurance programs: under what circumstances are people eligible for social
protection, for how long, and at what level of provision. The social citizenship approach
better encompasses the extent of welfare state generosity. Moving away from the
quantitative aspect toward the quality of social provision has also triggered a question of
why countries with an equal level of public spending can have very different levels of
social rights.
If it was difficult to obtain data on public spending at a time when few international
systems existed, it was even more difficult to access information on institutional rules
2
governing provision. Since institutional settings and rules are complex, researchers
needed to ensure that like things were compared with like. A persistent question was how
to find a common yardstick that could be applied internationally. Previous studies solved
this problem by utilizing stylized cases (or model families). Research has verified that
with stylized cases, cross-national social policy analyses are achievable. Comparisons
with stylized cases created the possibility of studying how the system works at an
individual level as the cases made otherwise disparate rules and circumstances more
comparable and thus amenable to cross-national examination.
One of the best-known research projects in this field is the Social Citizenship Indicator
Program (SCIP) undertaken by Walter Korpi and Joakim Palme (2007) in the early 1980s
to establish a theoretically relevant and empirically reliable set of institutional data for
comparative research on welfare state development. Over the years, a dataset for five
major social insurance programs was collected at five-year increments from the 1930s to
2002 in 18 OECD countries: old-age pensions, work accidents, sickness, unemployment,
and family benefits. In order to have cross-nationally comparable data, SCIP utilized as a
reference point a model of a typical production worker, labelled the ‘standard worker’.
This worker was defined as an employee in manufacturing (the metal industry) and was
assumed to have an average production worker’s wage. To ensure comparability, further
assumptions were made regarding family composition, the age of family members, and
work-career. Many published studies have used SCIP data (e.g. Esping-Andersen 1990;
Palme 1990; Kangas 1991; Wennemo 1994; Korpi and Palme 1998). The second
generation’s studies have produced a number of different welfare state typologies, which
have been classified according to their institutional features. These studies, in line with
many others, placed the Nordic countries in one group characterized by a strong state role
and broad statutory benefits with high coverage.
A very similar approach was initiated by Lyle Scruggs (2004) at the University of
Connecticut more than a decade later, partly to replicate Esping-Andersen’s
decommodification index and partly because the SCIP data was out of the public domain
until the late 2000s. The Comparative Welfare Entitlement Dataset (CWED) covered very
3
similar programme details (with the exception of work accidents) for the same 18 OECD
countries, but did so annually and for a shorter period (1971–2002). Like the SCIP data,
CWED data primarily analysed the level of provision for a six-month (26 weeks) spell of
illness or unemployment. A key concept was the net replacement rate calculated at
previous earnings at the level of the average production worker for two household
situations (single person and couple with one earner). The data for wages was mostly
derived from OECD.
Many individual studies conducted since the 1980s have carried out cross-national
comparisons on social insurance and assistance schemes with many collecting their own
data on institutional characters and benefit levels (e.g. Day 1978; Bradshaw & Piachaud
1980). They have adopted the typical-case approach and followed the same principles.
OECD publishes Benefits and Wages and Taxing Wages annually, providing stylized
information on OECD tax and benefit rules. With a very few exceptions, these studies
(and data sets) have been devoted to comparing benefits granted through legislation. The
basic principle for programme inclusion is that the entitlement conditions are regulated
by the state, that is, the benefits are statutory. This choice was justified since the primary
interest was on the role of the state. Further, the choice was consistent with Marshall’s
(1950) idea of social citizenship, where social rights referred to legislated social
provisions.
This research was subsequently criticized as being too one-dimensional as other forms of
welfare were neglected (e.g. Adema 1999) as well as being based on average production
worker wage calculations (see e.g. van Gerven 2008, 48; Kangas 2010, 404). Labour
markets have changed profoundly during the past decades. While the ‘golden age of the
welfare state’ in Western societies’ industrial era was characterized by stable labour
markets, in post-industrial societies, irregularity and nonstandard work arrangements
characterise increasingly segmented labour markets (Häusermann & Schwander 2012).
Post-industrialization means that the majority of people are nowadays employed in the
service sector, while fewer get their livelihood from industry. For example, in Norway
and Denmark in 1970, around 50 percent of the workforce were in the service sector as
4
compared to almost 80 percent in 2010. Corresponding figures for people employed in
industry were 37 percent and 19 percent (see Appendix table 1). For this reason, prior
assessments of the level of social provision of the average production worker now appear
to be rather a long way from the average case.
At the time, the choice was arguable and presented the industrial blueprint of a wage
earner for whom the welfare state was designed. The massive expansion of tertiary
education has led to a broader and more heterogeneous middle class, which has displaced
the lower-qualified manual worker as being the typical case. The growth of female
employment, particularly in the Nordic countries, has further undermined previous
assumptions: it is no longer sufficient to study the average worker simply by focusing on
the average male worker. In 1970, just above one-third of the employed in the Nordic
countries were females, while in 2010 almost half of employed people were females (see
Appendix table 1).
Due to the past changes in the labour market, fixed-term and part-time employment are
more the rule than the exception, and therefore the ‘average production worker’ no longer
reflects reality. From the viewpoint of occupational welfare, trends in labour markets
towards atypical and precarious employment are meaningful, since these kinds of jobs are
usually those with weak occupational social protection (McGovern et al. 2004; Rueda
2007). In order to be eligible for the perks and benefits offered by an employer,
employees are often required to have some years in service and to be in full-time
employment.
Since 2005, OECD has used the pay for an average earned wage (AW) to calculate
benefit levels. Prior to that, the average pay for an industrial worker was used. The
broadened definition of the average worker includes both manual and non-manual
workers, which are thought to better capture the average wage level in countries (See
OECD 2005). For the Nordic countries, this has meant that the wage level with which the
comparisons are made is lower in Denmark but higher in Finland, Norway, and Sweden
(NOSOSCO 2009).
5
Adding occupational welfare to the examination
Occupational welfare – definition and previous research
The concept of ‘occupational welfare’ has been defined in many different ways. To put it
simply, occupational welfare is the welfare that is distributed by employers to employees
as a result from employment (see also Titmuss 1958). Broadly speaking, occupational
welfare can be understood as not only covering the benefits and services related to social
provision but also other non-wage benefits (‘fringe benefits’) that do not ordinarily link
to social policy (Farnsworth 2004). In this work, occupational welfare is understood as a
social protection, including benefits and services, with a functional role towards public
welfare (see e.g. Shalev 1996; Cutler & Waine 2001; Greve 2008). This occupational
social protection is approached via collective agreements that are negotiated by employer
and employee organisations.
There is relatively little theoretical and even less empirical research dealing with
occupational social protection (but see, respectively, e.g. Farnsworth 2004; Greve 2007;
Yerkes & Tijdens 2010), with most studies focusing on occupational pensions (e.g.
Shalev 1996; Rein & Wadensjö 1997; Forssell et al 1999; Ebbinghaus 2011). It is no
coincidence that only a few studies exist on the subject. Occupational welfare is less
distinct than statutory provision, covering a range of statutory and non-statutory benefits.
Hence, the line between the private and public sector can be fuzzy (Rein 1982; Shalev
1996; Greve 2008) and examination of occupational benefits difficult. This is especially
the case when measuring occupational welfare in cross-national comparisons. Each
country has its own systems, and information from different occupational schemes is not
easily available and even when it is, it is scarcely comparable. As a result, comparative
studies dealing with occupational welfare have primarily focused on a small number of
countries (e.g. Forssell et al 1999). In a more detailed manner, occupational social
provision has been examined only from a national perspective (see e.g. Farnsworth 2004,
Sjögren Lindqvist & Wadensjö 2006; Yerkes & Tijdens 2010).
6
Empirical analyses on occupational social protection have mostly focused on spending. In
doing this, studies bear a resemblance to the first generation’s welfare state studies, which
also focused on spending. The availability of cross-nationally comparable data on
occupational social provision spending is far from adequate. Studies have mostly used
data on non-wage costs, for example from the Labour Cost Survey (e.g. Rein 1996);
researchers have also drawn their data from national statistics and studies in order to
collect evidence on the extent of occupational welfare. Empirical analyses verify that
there is more to welfare than what the state provides and the inclusion of occupational
welfare in total spending leads to smaller variations between countries (Rein 1996; see
also Adema 1999). The data on labour unit costs, however, appears to be inadequate for
studying the importance of occupational welfare cross-nationally for different
occupations and socioeconomic groups, since the studies are only from a national
perspective. With stylised cases, one can study occupational welfare also from the
viewpoint of different occupations and groups.
Several studies provide analyses of coverage (e.g. Farnsworth 2004), which give
important information on the extent of occupational welfare at the individual level.
However, it is very rare for empirical research on occupational welfare to have adopted a
social rights approach, involving an analysis of the importance of occupational welfare
with the help of stylised cases. This type of analysis adds valuable information on the
importance of occupational welfare not only for understanding its meaning for
individuals but also to understand the logic of a public-private mix in providing welfare
as well as to grasp potential stratifying effects.
Occupational welfare through collective agreements
One way to gain access to occupational benefits with at least somewhat comparable
means is to approach them through collective agreements. Collective agreements are a
justified approach in the Nordic countries in particular as they form the most common
channel in which employment-related social benefits (sick pay benefits in particular) are
agreed upon. However, there are several methodological challenges. The number of
7
complex collective agreements is large, and there is no systematic data available. There is
also great variation between occupations and branches in their respective benefit
conditions and levels.
In addition, countries vary in their collective bargaining systems. In Nordic countries,
collective bargaining is mainly industry-level, though much is also left to company
negotiations and decentralization is becoming more common, especially in the private
sector (see e.g. Elvander 2002). In some countries, such as the UK and most of the
countries of Central and Eastern Europe, collective bargaining is mainly company-level
(European trade union institute 2012). When it comes to data collection, sector-level
agreements are easier to manage as their coverage extends beyond one workplace, and
therefore the total amount of these kinds of agreements is more comprehensible. This is
contrary to those countries where company-level agreements predominate: data collection
is difficult not only because of the extent of the agreements but also because firm-based
agreements are not usually publicly available. Thus, if we want to compare like things
with like, different bargaining systems set serious difficulties to comparing countries.
Nordic countries share the same kind of systems and therefore they are good countries to
be compared.
Another thing that affects comparability is the great differences between countries in their
levels of collective bargaining coverage. In addition, the coverage may also vary within
one country according to occupational status and sector (Scheuer 1997). The significance
of collectively negotiated benefits is, of course, much lower in countries where few
employees are covered by collective agreements. Nordic countries represent relative high
coverage rates (from 91 percent in Finland to 70 percent in Norway). In the public sector,
the coverage is 100 percent, which is significant as employment in this sector is high. At
the other end, there is, for example, the UK, with only 30 percent of employees covered
by collective agreements. (European trade union institute 2012.) Of course, this is not to
say that there is not any occupational welfare available in the countries with low
collective agreement coverage, merely that it is agreed on in a more individual manner
without collective negotiations. In the Nordic countries, individually agreed perks and
8
benefits may also exist, but these are usually fringe benefits and do not concern benefits
related to social protection.
Choices regarding stylized cases
In order to work, the applied method requires many specifications and assumptions to
make cases comparable and situations identical across countries. Next, we present and
discuss in more detail the specifications and assumptions of stylized cases. All
information regarding statutory benefits, collective agreements and wages is collected
from the year 2010.
Occupations
In order to analyze occupational welfare, we need to define occupations so we can choose
the applicable collective agreements. We have selected occupations that are known and
cross-nationally comparable. To keep things simple, five occupations are a good starting
point. We have chosen the following occupations: cleaner, nurse, electrician, information
technology (IT) engineer, and university teacher. The chosen occupations represent
different industries, low- and high-skilled workers, and public and private sector
employees.
Incorporation of public sector employment is important because the public sector is a
significant employer in the Nordic countries. Most public sector employees are nonmanual workers and are female. The inclusion of public sector employees is also
important from a theoretical standpoint. Civil servants in many countries, particularly in
corporatist countries, have enjoyed a relatively privileged position and had lavish welfare
provisions. It is more likely that they are also offered better occupational benefits. In
Esping-Andersen’s (1990, 70) etatism score, Finland was clearly above the mean value,
whereas the other three Nordic countries were below.
9
Among the cited occupations, nurse and university teacher represent public sector1. In the
Nordic countries, a nurse is a white-collar worker working in the service sector.
According to our assumptions, a public sector nurse is a general nurse (all kinds of nurses
being covered) who works in a hospital for the biggest public sector employer in the
field. These definitions help us to collect reliable comparative wage data. A university
teacher, on the other hand, is a high-skilled professional with a doctoral degree. The
assumption regarding education has been made even though there are also university
teachers who do not necessarily have a doctoral degree. The university teacher represents
all fields of science, that is, there is not any specific discipline defined. This has been
done in order to keep the number of teachers at a more comprehensive level, as there
usually are only a few university teachers in each country per discipline. In Nordic
countries, public sector nurses work at the local level, that is, in municipalities or
counties, and most university teachers work at government-level universities. The local
level plays an important role in the Nordic countries and, therefore, it is essential to make
a distinction between local and government levels.
Employees in the private sector usually work in the manual industry or in the service
sector. The cleaner and electrician represent blue-collar workers, with the cleaner being a
low-skilled service sector employee and the electrician a manual worker. One criterion
for the selection of these two occupations has been that one is dominated by women and
the other by men. Equality is one of the profound values of the Nordic welfare state and
women have a long history of participation in the labour market. Many women work in
the public sector where collectively negotiated benefits are relatively good and coverage
is 100 percent. On the other hand, the welfare state was originally developed on a male
breadwinner idea. Even today, women still earn less than men although women on
average have a higher education. In Finland, for example, women’s wages are
approximately 81 percent of men’s wages (Statistics Finland 2012). This supports the
idea that male-dominated working sectors have better occupational benefits than female-
1
In all countries except in Finland, where university employees have not worked for government since
2010.
10
dominated ones. All in all, the gender aspect is interesting when examining occupational
benefits.
Our third private sector employee is an IT engineer who represents a high-skilled
employee who has a university education. The IT engineer was chosen because this
occupation is a comparatively new and modern occupation, which makes it interesting to
compare with more traditional occupations. IT engineering is also relatively clear when
the applicable collective agreement and wage data are concerned. A selection of highskilled white-collar occupations (university teacher and IT engineer) has not been simple,
as employees at this level engage in various kinds of tasks and titles, which makes
comparable data collection complicated.
Collective agreements
The collective agreements selected in this research are sector-level agreements (see
Appendix table 2). Selected collective agreements are either the only ones applicable or
one of the applicable ones to each occupation. In the private sector, the field of collective
agreements is large, and there is usually no sole agreement that is applicable to each
occupation. The applicable collective agreement is determined by the employer; however,
as we have not defined a specific working place to our stylized cases in the private sector,
we have chosen the most extensive agreement applied to each occupation, that is, the
agreement that is applicable to the largest group of employees. We have made more
presumptions regarding public sector employees; as a result, there is only one collective
agreement that is applicable to each occupation. One assumption is that the nurse is
working in a hospital for the biggest public sector employer and that the teacher is
working in university. Without these assumptions, the applicable collective agreement
might have been something else, for example, in the case of nurse, a government
collective agreement.
There exists no databank for collective agreements in any of the Nordic countries and,
therefore, the agreements have been collected by using the websites of each occupation’s
trade union. Most of the agreements are available on the Internet. In some of the cases,
11
the applicable collective agreement has been relatively easy to find, but in some cases, we
have consulted the trade union in question to confirm the data. Denmark is an exception
in that many white-collar workers (presuming that certain conditions are met) are covered
by a ‘law on salaried employees’ that offers them full sick pay for an unlimited time.
Regarding this, there are not any better conditions that collective agreements can offer.
However, there is a ‘120-day rule’ in Denmark which means that different dismissal
notices apply after 120 days of sickness absence; this is where collective agreements may
stand out and state that the rule is not valid. All white-collar workers in our research are
covered by the law on salaried employees, and, in addition, all occupations except IT
engineer are covered by sector-level collective agreements.
Wages
All wage data are collected from national statistic offices and cover the average wage of
each occupation in 2010. It can be assumed that there is a variation according to
occupation on how well the average wage reflects the common wage: it is common that
manual workers have more standardized salaries, whereas white-collar workers have
more personalized and employer-attached wages. Furthermore, the private sector usually
has a wider wage dispersion than the public sector does (see e.g. Statistics Finland 2012).
Though we have an assumption that the employee has been working for the employer for
a relatively long time, the wage data is not collected by seniority. We could assume that
the average wage reflects relatively well the wage of an employee who is somewhere in
the middle of his/her working career. When collecting wage data, we made the
assumption that the employee is working full time and is in permanent employment.2
This choice has been made even though in some of our occupations, this does not
necessary reflect the reality. For example, in Finland, only approximately half of the
cleaners in the private sector work full time (Statistics Finland 2012). Fixed-term
employment is usually more common in the public sector than the private.
2
However, the wage data from Finland also includes employees with permanent and fixed-term
employment.
12
Collected wage data has been defined as pay of regular working time, which means that it
includes other pay, such as supplements, but excludes overtime. As with previous
assumptions, this choice also relates differently for the selected occupations. Nursing is
an occupation in which shift work is typical and therefore it is important that supplements
related to this are also calculated. Overtime is excluded because sick pay according to
collective agreements is usually calculated in a way that does not take overtime into
account. Statutory sickness benefits, on the other hand, are calculated by the total annual
wage, so the disadvantage that comes with this decision is that they are not calculated in
an entirely truthful way.
National average wage compared to wage of selected occupations
When we compare the average wage of each country to the average wage of each
occupation (see Table 1), we can see why it is important to move away from the
traditional production worker to more specific calculations. The wage of the electrician
and nurse is close to the national average in each country, but the cleaner, at one end, and
university teacher, at the other, seem to be far from it. OECD defines low pay as less than
two-thirds of median earnings for all full-time workers (AW). This threshold has gained
wide acceptance in research and statistics. For example, NOSOSCO uses this 67 percent
of AW. Thus, the cleaner clearly represents a low-wage earner.
Different occupations help us to gain information in a more comprehensive and reliable
way. In Table 1, we have compared the national average wage to the average wage of
each occupation. It can be seen that one general average wage can be far from the reality
as wage dispersion between occupations is wide. According to OECD (2011), income
inequalities have increased in almost all OECD countries and Nordic countries stand out
as places where the growth has been particularly significant. Finland is one of the top
countries in this respect, as can also be seen from Table 1.
13
Table 1. National average wage compared to average wage of occupations
Cleaner
Electrician
Nurse
IT engineer
University
teacher
Finland
60%
92%
94%
145%
161%
Denmark
69%
90%
97%
157%
129%
Norway
79%
95%
92%
129%
135%
Sweden
70%
94%
95%
145%
145%
General assumptions of stylized cases
We have made an assumption that the employee has been working for the employer for
more than five years. Assumption regarding the previous working time has to be made
because in Finland, the length of the sick pay period depends on the duration of the
uninterrupted employment. In the private sector in particular, the rule is that the longer
the employment duration has been before the sickness, the longer the benefit period.
Another thing that is important in all countries is the length of sickness. The longer the
duration of sickness and absence from work, the greater the importance of sickness
benefits becomes for the employee. Noteworthy is that all occupational groups do not
become unable to work due to sickness the same way; for example, in Sweden, manual
workers are on sick leave 2.4 times more often than salaried employees (Svenskt
Näringsliv 2012).
We will examine three different sickness periods in order to illustrate the significance of
collectively negotiated benefits. Firstly, we have a relatively short sickness period of one
week. This is because most of the sickness periods are short ones, caused by flu or other
illnesses that do not require a long recovery time (see e.g. Svenskt Näringsliv 2010).
Secondly, we will examine a somewhat mid-length sickness period, that is, one month.
This mid-length period is important because this is when collective agreements most
clearly offer better benefits, and therefore the significance of collectively negotiated
sickness benefits usually lie within this period. Thirdly, we have a longer sickness period
14
of 26 weeks. This is the same sickness spell that was used by Scruggs (2004) in his
CWED-data analyses.
Calculations3
We are interested in the net replacement rate of statutory and collectively negotiated
sickness benefits. From the claimant’s point of view, perhaps the most central aspect of
the provision is the adequacy of income loss replacement. Income tax and social security
contributions have been deducted from the average gross income of each occupation. The
only exception is Sweden, where the social contributions are tax deductible; therefore,
these deductions have been left out of calculations. Church tax has not been taken into
account, as this is usually the procedure that is used, for example, by OECD. We have
collected the taxation and social contribution rules regarding statutory and collectively
negotiated sickness benefits from each of the investigated countries. Municipal tax is
calculated in Sweden and Denmark according to the taxation in the capital cities; in
Finland and Norway, we have used the national municipal tax average. Information on
2010 Finnish and Norwegian income taxes has been received by using the information in
the OECD tax-benefit calculator. Information on Sweden and Denmark has been
collected by using national tax calculators. We have used a case of a single adult with no
children.
Does occupational welfare matter?
In this final section, we will shortly present differences between statutory and collectively
negotiated sickness benefits. In this paper, we will not go further into the differences
between occupations, working-sectors, or sexes. We will leave analysis regarding these to
future investigations and concentrate in this paper on how the picture alters after bringing
the occupational welfare into analyses. First, we carry out an analysis with conventional
3
We owe great thanks to our research assistant, Lauri Mäkinen M.Soc.Sc, for gathering the relevant
information for calculations.
15
measures where only the statutory sickness benefit is included. Contrary to most previous
studies, we use in addition to the average wage earner’s wage varying income levels to
illustrate how the net replacement rates differ with income level and how the single case
indicator (100 AW) actually provides a partial picture of cross-national differences.
Income levels are those of our selected occupations.
Table 2. Net replacement rates according to statutory sickness benefits, case of one week
Denmark
Finland
Norway
Sweden
100 AW
100%
100%
100%
80%
Cleaner
100%
100%
100%
80%
Electrician
100%
100%
100%
80%
Nurse
100%
100%
100%
80%
IT engineer
100%
100%
100%
80%
University teacher
100%
100%
100%
80%
Table 2 displays the statutory net replacement rates for the one-week sickness period. In
the case of a short sickness period, only statutory benefits are relevant since in all Nordic
countries, the employer has a statutory obligation to pay compensation during this time.
Employers are obligated to pay full salary in Denmark, Finland, and Norway, whereas in
Sweden the compensation is a bit lower, with 80 percent compensation rate. It is clear
that statutory net replacement rates (Table 2) are good in all four countries, and
occupational welfare does not play any importance.
In all four Nordic countries, the first 10-21 days (depending on the country) are paid by
the employer; after this, the responsibility is passed to national insurance companies.
Next, we focus on mid-length sickness of one month. In Table 3, we present the net
replacement rates according to statutory sickness benefits (Table 3a) and according to
collectively negotiated benefits (Table 3b).
16
Table 3a. Net replacement rates according to statutory sickness benefits, case of one
month
Denmark
Finland
Norway
Sweden
100 AW
47.9%
66.3%
100%
72.4%
Cleaner
69.7%
67.6%
100%
77.6%
Electrician
53.5%
71%
100%
77.0%
Nurse
49.2%
71%
100%
75.9%
IT engineer
30.5%
58.4%
80%
50%
University teacher
37.1%
56.4%
76.5%
50%
Table 3 b. Net replacement rates according to collectively negotiated sickness benefits,
case of one month
Denmark4
Finland
Norway
Sweden5
Cleaner
100%
100%
-
87.3%
Electrician
100%
100%
-
86.6%
Nurse
100%
100%
100%
78.5%
IT engineer
100%
100%
100%
88%
University teacher
100%
100%
100%
88%
It can be seen that the net replacement rates of statutory benefits are reduced from that of
the short sickness period. The replacement rates decreases mainly with the wage. The
only exception is Finland where the taxation on sickness allowance causes the net
replacement rate of cleaner to be lower than the replacement rates of the electrician and
nurse. The significance of collectively negotiated benefits is obvious as most collective
agreements offer full sick pay. The importance of occupational benefits can especially be
seen in Denmark. Only in Norway is the relevance of occupational benefits minor since
4
In Denmark, IT engineers are not paid compensation according to collective agreements but according to a
special law on salaried employees. Here, we refer to them as collectively negotiated benefits.
5
In Sweden, collectively negotiated benefits are not distinguished in a simple way from statutory benefits as
occupational top-up sickness benefits from the Swedish Social Insurance Agency. Here, the replacement
rate of collectively negotiated benefits is calculated together with statutory benefits, as this is the true
compensation that the employee receives.
17
the level of statutory benefits is high. Norway differs from other Nordic countries in that
it offers one year of full salary paid by the national insurance company (NAV). Full
salary is paid up to a certain wage level (approximately 61,449 euro in year 2010), after
which the compensation rate is gradually reduced. Low-income occupations do not
receive any collectively negotiated sickness benefits in Norway; nonetheless, these
occupations receive full compensation from NAV. In all countries, the importance of
collectively negotiated benefits can most clearly be seen in high-income occupations; the
net compensation rate of the IT engineer and university teacher is most often many times
higher when we move on from statutory to occupational benefits. In Sweden, the IT
engineer and university teacher have the same compensation rate since they happen to
have the same average wage.
Table 4a. Net replacement rates according to statutory sickness benefits, case of 26
weeks
Denmark
Finland
Norway
Sweden
100 AW
47.9%
66.3%
100%
72.4%
Cleaner
69.7%
67.6%
100%
77.6%
Electrician
53.5%
71%
100%
77.0%
Nurse
49.2%
71%
100%
75.9%
IT engineer
30.5%
58.4%
80%
50%
University teacher
37.1%
56.4%
76.5%
50%
Table 4b. Net replacement rates according to collectively negotiated sickness benefits,
case of 26 weeks
Denmark
Finland
Norway
Sweden
Cleaner
-
-
-
87.3%
Electrician
-
-
-
86.6%
Nurse
100%
66.6%
100%
77.6%
IT engineer
100%
-
-
79.1%
University teacher
100%
75%
100%
78%
18
In Table 4a and b, we present the results of 26 weeks of sickness in line with previous
studies. Compared with the one-month sickness period, there are no changes in statutory
benefits. This is because statutory benefits are usually paid the same way up to the point
where the employee is no longer eligible for the sickness allowance. The maximum
length of sickness benefit is usually approximately one year depending on the country.
When looking at the Table 4b, we can see that the importance of collectively negotiated
benefits is now less than it was in the case of one month. Occupations representing bluecollar workers are no longer eligible for occupational benefits, except in Sweden. Sweden
differs from other countries as it usually has comparatively the lowest compensation rates
(see Table 3) but on the other hand, the benefit period is longer. High-wage occupations
and the public sector employee nurse continue receiving occupational benefits after 26
weeks of illness. The only exceptions are the IT engineer in Finland and Norway. It
seems that public sector agreements offer benefits for a longer time than private sector
ones. All in all, it is evident that the level of protection is significantly different with
occupational welfare.
Summary and discussion
In this paper, we aimed to bring occupational welfare into cross-national social policy
analyses. Although comparative welfare state research has flourished for the past
decades, studies have predominantly focused on statutory provisions, while ignoring
occupational welfare. Those studies that have analyzed occupational welfare are mainly
theoretical; the few empirical studies are for the most part single-country studies. Titmuss
(1958) brought occupational welfare into the scientific discussion when he pointed out
there are different routes to welfare and these alternative routes should not be
underestimated when evaluating the total provision of welfare. Our paper sheds light
upon the theoretical understanding of the complex public-private mix. Our first-hand
interest was, however, methodological—whether and how the commonly used stylized
case approach could be applied to study occupational welfare in cross-national analyses.
The stylized case method is widely utilized in prominent academic work on welfare states
19
(e.g. Esping-Andersen 1990; Korpi & Palme 1998). We aimed to overcome one of the
great weaknesses of previous studies, which have been criticized for being too onedimensional as they build their analyses solely on average production worker wage. The
average production worker concept is no longer seen as representing the typical worker in
a postmodern society where segmentation and irregularity characterize the labour
markets. When studying collectively negotiated benefits, we were able to a certain extent
to tackle this question by choosing different occupations to reflect low-skill as well as
high-skilled workers. Existing wage dispersion allowed us not only to analyze the impact
of different earning levels on the level of social protection but also to analyze the
importance of collectively negotiated occupational benefits in the case of sickness.
Five different occupations were chosen for which the level of total provision was
stipulated and calculated. Occupations were chosen to present not only the typical lowand high-skills occupations but also female- and male-dominated occupations and
occupations in both the public and private sector. However, in this paper, the interest was
not to analyze the differences between occupations, working-sectors or sexes but instead
leave this to future theoretically driven investigations. Visibly selected occupations are
vulnerable to critique. Our goal was to present thorough arguments for the choices. The
number of occupations could have been higher, but the more the cases you have, the more
complex and blurry are the analyses. Five occupations were regarded as a good starting
point, with a number large enough to have information from several cases and to avoid
conclusions drawn solely on one or two occupations.
A decisive choice in cross-national comparisons is the sample of countries. Here we
followed a common road in the field of welfare state studies and chose the ‘most similar’
research strategy. Four Nordic countries were included in analyses. Cross-national
comparisons on occupational welfare are rare, partly because countries vary in their
schemes and the field of collective agreements is complex. The Nordic countries bear
resemblances in their collective bargaining systems, and therefore it served well that our
methodological exercise focused on cases of illness negotiated in collectively bargained
agreements. Our analyses brought evidence to show the not-so-equal aspects of the
20
model, that is, different occupational groups have varying levels of support with
occupational welfare having stratifying rather than redistributive effects (cf. EspingAndersen 1990, Bradley et al. 2003). Future work should be elaborated to cover more
countries; only in this way can better understanding of the role of occupational welfare be
gained and the total welfare consisting of private and public parts revealed. One way
forward in comparing countries with entirely different systems is that instead of focusing
on sector-wide collective agreements, one could concentrate on company-level
agreements representing different occupations. We have tried to proceed this way in our
investigation, but so far it has proved challenging to collect these kinds of agreements
that are often treated as company secrets.
In the paper, we focused only on income maintenance. We followed earlier work where
analyses excluded benefits ‘in-kind’. Hence, free or subsidized health care provided by
employers was not included. For example, in Finland, occupational health services have a
very important role, since it is statutory for the employers to organize free-of-charge
health services for employees.
The choice to have only a single adult as the family type is also vulnerable to critique. It
is customary to have at least two family types, single, and a couple with children. In the
case of collectively negotiated benefits in case of illness, the rules do not make any
difference whether a person is single or has a family. In none of our studied countries do
spouse earnings or situations alter the level of provision, nor do they consider any extra
benefit for children. In the case of including a couple with children as our second family
type, the analyses would have become more complicated and would not have revealed the
role of occupational welfare any more than the single adult case does. However, the
family type is not wholly irrelevant. For example, in Finland many collective agreements
state that in case a parent is absent from work due to his/her minor age child’s illness,
he/she is entitled to pay during that time. This kind of question, however, requires another
study.
21
Since the focus of this paper was on occupational welfare, analyses covered only
employees. Hence, self-employed workers, students, and the unemployed were not
included. Preliminary results show occupational welfare to have great importance on the
level of overall welfare. Further, they demonstrated occupational welfare to have a
stratifying nature. These differences between groups would be even larger if unemployed
people were included in analyses. This is indeed a question that reserves attention in
future work.
This was one of the first attempts to study occupational welfare cross-nationally via the
stylized case method. As the method proved to be suitable for its purpose, it is essential to
extend the work to cover more cross-sectional points. This way, research can bring better
understanding to the complex public-private mix. Occupational welfare can be seen as
related to the general debate over the welfare state’s condition and possible retrenchment
policies. In some countries, collective agreements may have a role in compensating the
declining welfare state (Yerkes & Tijdens 2010). It has even been argued that social
policy that is based on collective agreements influences and supports welfare state
retrenchment policies (Trampusch 2006). To gain a more complete picture of welfare
delivering, further investigations are required and methodology work elaborated.
22
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24
Appendix table 1. Employment by sector and gender in 1970 and 2010
Denmark
Finland
Norway
Sweden
Civilian employment in industry as % of civilian employment
1970
37.8
34.6
37.2
38.4
2010
18.2
23.2
19.7
20
Civilian employment in service as % of civilian employment
1970
50.7
42.8
48.9
53.5
2010
79.4
72.3
77.7
77.9
Civilian employment females as % of civilian employment
1970
39.4
44.9
30.8
39.4
2010
48.1
48.7
47.5
47.2
Source: OECD, Labour Force Statistics (online)
Appendix table 2. Selected collective agreements
University
teacher
Cleaner
Electrician
Nurse
IT engineer
Finland
Kiinteistöpalvelualan TES
2010–2012
Sähköistysalan
TES 2010–
2013
Serviceoverenskomst
2010–2012
Elektriker
overenskomst
2007–2010
Teknologiateollisuuden
TES 2009–
2012
Law on
salaried
employees
Yliopistojen
yleinen TES
2010–2012
Denmark
Norway
Overenskomst
for renholdsbedrifter 2010–
2012
Landsoverens
komst for
elektrofagene
2010–2012
Kunnallinen
yleinen virka- ja
työehtosopimus
2010-2011
Overenskomst
for ikke-ledende
personale på
Sundhedskartell
ets område 2008
Overenskomst
mellon Spekter
og NSF
2008–2010
Hovedtariffavta
len i staten
2010–2012
Sweden
Kollektivavtal
Serviceentreprenad
2010–2012
Installitionsavtalet
2012–2012
Overenskomst
Norges
Ingenior- og
teknologorgan
insasjon HSH
og NITO
Anställningsvillkor
IT-företag
2010–2012
Allmännä
bestämmelser
Overenskomst
for akademikere
i staten
2008–2011
Allmänt löneoch
förmånsavtal
25
26