working-time policies in switzerland

8/12/2019 Working-Time Policies in Switzerland

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Discussion Paper No. 69

Research Institute for Labour Economics and Labour Law

Working-Time Policies in Switzerland: An Analysis of Desired Working

Time, Overtime, and Hours Constraints of Swiss Salaried Employees

Alfonso Sousa-Poza

Department of Economics and Research Institute for Labour Economics and Labour Law at

the University of St. Gallen, Switzerland

Fred Henneberger

Department of Economics and Research Institute for Labour Economics and Labour Law atthe University of St. Gallen, Switzerland,

Department of Administrative Science, University of Konstanz, Germany

Abstract: In this paper, desired working time, overtime, and hours constraints of Swiss salariedemployees are analysed with data from the 1998 Swiss Labour Force Survey and with data from the1997 International Social Survey Programme. It is shown that (i) most Swiss workers do not facehours constraints, when we compare the desired working time with the contractual working time; (ii)the largest portion of constrained workers would like to work less and earn less (17% of all male and22% of all female salaried employees); (iii) there is a deficit of part-time jobs for both men andwomen, especially for high-qualified individuals; (iv) men and women work on average 3.15 and 1.69hours overtime per week, respectively; the most common form of compensation for this overtime isholidays, followed by no compensation and money; (v) a comparison between actual and desiredworking time reveals that a significant amount of workers are constrained in the sense that they wouldprefer shorter actual working hours; (vi) an international comparison of desired working time showsthat workers in Switzerland are quite satisfied with their current workload/pay combination;Switzerland does, however, have the highest portion of workers wanting to work and earn less. Somepolicy implications of these findings are also discussed.


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1. Introduction

The debate over the length of the workweek has re-entered the public sphere in most

industrialised countries. There are two main reasons for this renewed concern: first, the

persistent unemployment in many of these countries has led to an increased interest in "work-sharing" policies in order to distribute the available work more equitably. It is commonly

argued that a reduction of the working time will increase the number of available jobs in an

economy and that, thereby, unemployment can be reduced or prevented.1A second reason is

the willingness of families to divide paid and unpaid employment more equally among family

members. By reducing the working time, men can devote more of their time to the running of

the household and women can participate in the labour market. In this century, working time

has declined substantially in all industrialised countries, and, currently, the most commonly-reported workweek in OECD countries is 40 hours (see OECD, 1998a, p. 153). Nevertheless,

this decline has slowed significantly in recent decades in almost all OECD countries (the

exceptions being Germany, Japan, and the Netherlands). In a few countries, this decline

appears to have stopped, while, in others, there has even been an increase in hours (most

notably the United States). A further characteristic of the current workweek is that there has

been a growing diversity in the hours worked by employees, with the proportion of employees

working 40 hours having fallen considerably.

The debate over the length of the workweek has also entered the public sphere in

recent years in Switzerland. The largest labour union umbrella organisation, the Swiss

Federation of Trade Unions (Schweizerische Gewerkschaftsbund, SGB) has recently launched

a popular referendum ("Volksinitiative") for a nation-wide introduction of an upper limit of

1872 work hours per year, which corresponds to a 36-hour workweek (see SGB, 1999,

especially p. 27). Furthermore, this de facto reduction of the workweek would take place

without significant changes in earnings.2At this point in time, it is difficult to judge whether

1 The most ubiquitous examples being France and Italy, in which the normal workweek fell from 39 hours to35 hours by legislation. See also OECD (1998a), p. 174. Whether new jobs have been created or not is yetunclear. See Freeman (1998), p. 29, OECD (1998a), p. 182, and, for Germany, Henneberger (2001).Recently, the media has also reported industrial action by French truckers in protest to a reducedworkweek.

2 According to the referendum text, all employees who earn less than 1.5 times the average wage should notface a reduction in earnings (proposed article 24, paragraph 2 of the constitution). Due to the relativeunequal distribution of income in Switzerland, this covers the largest portion of all Swiss employees.


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the voters will accept the proposals in this referendum.3The Swiss employers associations

generally oppose such measures (see, for example, Schweizerischer Arbeitgeberverband

(AGV), 1998; Clemmer, 1997). The Swiss Federal Railways (Schweizerische Bundesbahn,

SBB) have also recently introduced a 39-hour workweek (as in the SGB referendum, based on

a yearly upper limit of the working time), which meant a reduction of two hours per week for

approximately 30,000 employees.4The Swiss Post offers a further example of how working

time reductions are trying to be introduced in Switzerland. In a pilot project in four cantons,

the Swiss Post is employing unemployed individuals as part of a job-sharing scheme. For

groups of three currently employed individuals, an unemployed person is given a job, and the

workload is divided among the four. The working time is thereby reduced by approximately

25%.5Finally, the Swiss telecommunications company (Swisscom) has recently, as part of a

pilot project in three cantons, introduced a four-day workweek, which corresponds to a 36-

hour workweek.6

There are two main reasons for this resurgent interest in working time reductions in

Switzerland (see also Henneberger, Graf and Sousa-Poza, 1999). First, in the 1990s,

Switzerland faced its highest levels of unemployment since the 1930s, and, therefore, "job

sharing" policies and working time reductions have become popular again. A second reason is

that Switzerland has one of the highest weekly and annual working times in the industrialised

world and also one of the highest standards of living. Thus, one could argue that the marginal

value of leisure is relatively high. In Switzerland, the most commonly reported (contractual)

workweek is currently 42 hours followed by 40 hours per week, and these figures cover over

70% of all employed individuals. Compared to its neighbouring countries, Switzerland

therefore has a very long workweek.7

3 The SGB did, however, have problems in collecting the required signatures for a referendum (see NeueZrcher Zeitung, 7th of January 1999). In fact, there even appears to be recent evidence that the SGB itselfis giving this topic less importance (seeNeue Zrcher Zeitung, 14th of January 2000).

4 See also Neue Zrcher Zeitung, 22nd of April 1999. It is also interesting to note that the FederalGovernment has no intention of reducing the working time for its employees (see EidgenssischesPersonalamt (EPA), 1999). The Federal Government does, however, offer individual working-timereductions (see Habltzel and Rebecchi, 1998).

5 See Graf, Henneberger and Schmid (2000), p. 45f.

6 See also St. Galler Tagblatt, 31st of January 2000.

7 In Italy, the most frequently reported workweek is 40 hours (covering 51% of the active labour force), in

Austria, also 40 hours (covering 55% of the active labour force), in Germany, 38 hours (covering 32% ofthe active labour force), and, in France, 39 hours (covering 55% of the active labour force). See OECD(1998a), p. 157.


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What has received surprisingly little attention in this debate on working-time

reductions is the preferences that workers themselves have with regard to the length of the

workweek. This is especially the case in Switzerland.8In our opinion, however, understanding

workers willingness to change their working time and the extent to which workers are

constrained (i.e., for which desired working time deviates from actual working time) is a

prerequisite in any discussion of working-time policies. In fact, since a large portion of Swiss

voters are employed, knowing the extent to which these workers desire shorter working hours

could give us a rough indication of how the SGB referendum will fare.9

The general aim of this paper is to analyse Swiss employees working-time (and thus,

earnings) preferences.10 In section 2, we first take a brief look at the characteristics of the

Swiss labour market. In this paper, we use data from two interesting data sets: the 1998 Swiss

Labour Force Survey (SLFS) and the 1997 International Social Survey Programme (ISSP).

These data sets are discussed in section 3. In section 4, we take a look at contractual and

desired working time. More specifically, we analyse the extent to which desired working time

corresponds to the contractual working time. In section 5, we extend our analysis by

comparing desired with actual working time where actual working time is defined as

contractual working time plus usual overtime. In this section, we also analyse the

determinants of overtime and the determinants of the form of compensation for overtime. In

section 6, a cross-national comparison of hours constraints is undertaken with the ISSP data

set. Section 7 concludes with a few policy implications of our findings.

8 A number of studies exist that analyse desired working time in other countries (see, for example, Kahn and

Lang, 1992 for the United States; Kahn and Lang, 1996 for Canada; Bell and Freeman, 1995 for the UnitedStates and Germany; Bundesmann-Jansen et al. 2000, Bauer et al. 1994 and 1996, Klauder, 1998 andDathe, 1998 for Germany; Sousa-Poza and Henneberger, 2000, 2001 for several countries).

9 Although one must take into consideration that our subsequent analysis is based on reported desiredworking-time data, which assumes that changes in working time are associated with correspondingchanges in earnings. As pointed out above, the SBG referendum, however, does not, in general, foreseesuch a change.

10 In this paper, we do not analyse the reasons for the existence of hours constraints. This is in itself animportant topic since the existence of hours constraints is often not easy to explain, and, in traditionaleconomics, they are often assumed not to exist. The interested reader is referred to Lang and Kahn (2000).


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2. The Swiss Labour Market: An Overview

Switzerland has recently experienced its most severe economic recession since the 1930s.

This was most notably felt by the high level of unemployment, which reached its maximum in

1997 with an unemployment rate of approximately 5.2%. As was mentioned above, onepotential reason for this increased interest in working-time policies could have been caused by

this surge in unemployment (the unemployment rate in 1990 was below 1%). In table 1, a few

summary statistics for the Swiss labour market are presented (see also Birchmeier, 2001).

Table 1: some descriptive statistics of the Swiss labour market

males females total

participation ratea 87.2 71.8 79.7

full-time employmentb(in %) 92.3 53.5

part-time employment (in %) 7.7 46.5

average contractual weekly working time (hours)c 40.3 29.5 35.1

median contractual weekly working time (hours)c 42.0 34.0 41.0

unemployment rated 2.4 3.3 2.7

median income (SFr. per year; gross)e 71,500 54,600 66,000

a1999; as a percentage of individuals between the age of 15 and 64bdefined as at least 30 hours working time per week (1999)cbased on the 1998 SLFS (own calculations); only employees who work at least one hour per week and are at

least 15 years old.d1999e1998Sources: 1998 SLFS, Bundesamt fr Statistik (1999a), OECD (2000), Staatssekretariat fr Wirtschaft (2001)

The Swiss labour market also has, compared to other industrialised countries, a few unique

characteristics:

It has the highest participation rate in Europe. In 1999, for example, about 80% ofindividuals between the age of 15 and 64 were employed. In the European Union (EU),

the corresponding figure was approximately 63% (see OECD, 2000).

The female participation rate (defined as a percentage of all females between the age of 15and 64) is also remarkably high with a rate in 1999 of about 72%. The corresponding EUaverage was only 53% (see OECD, 2000).


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As was mentioned above, Switzerland has one of the longest workweeks in Europe andalso the highest annual working time, i.e., if one includes vacations and public holidays

(see IW, 1999, p. 153).

Another interesting characteristic is that the Swiss labour force has a very high portion ofpart-time jobs. In Europe, only Holland has a higher portion (see Schaufelberger, 1997,

OECD, 2000).

Switzerland also has very few labour disputes and, in an international setting, very fewlost days due to strikes (see IW, 1999, p. 154).

According to the OECD, Switzerland has the third highest disposable GDP per capitaamong 29 industrialised countries (see OECD, 1998b).

3. Data

In order to analyse employeesworking-time preferences in Switzerland, we use data from the

Swiss Labour Force Survey (SLFS). The SLFS is a nation-wide, representative survey

conducted annually by the Swiss Federal Statistical Office (Bundesamt fr Statistik, BFS).

During telephone interviews lasting approximately 20 minutes, individuals (including

foreigners) are questioned on a number of labour-market related topics. The first SLFS surveywas conducted in 1991, and the sample size is approximately 16,000 individuals (see BFS,

1996). One of the advantages of the SLFS, in the context of this study, is that it has very

precise information on desired working time. The wording of the relevant question, posed to

all currently employedindividuals11, is as follows: "How many hours per week would you like

to work assuming that your wage is adjusted proportionally?" One drawback of this data,

however, is that not all workers were posed this question. More specifically, the following

workers were not set this precise question: (i) employees who work full-time and would not

prefer to work part-time; (ii) certain part-time workers who would like to work full-time. In

the former case, it was assumed that these full-time workers are not constrained, i.e., their

actual working time corresponds to their desired working time, and, in the latter case, these

part-time employees were assumed to want to work 42 hours per week. Naturally, assuming

that these full-time workers are not constrained need not always apply, since they may, for

11 An analysis of hours constraints faced by non-employed individuals would also merit investigation. Thiswould especially be interesting for women since it is often claimed that (frequently well-qualified) women

remain non-employed due to the fact that there is a deficiency of part-time jobs in the economy.


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Data on desired working time do have some problematic characteristics. The main

problem with such data is that they are based on hypothetical questions. As with most such

subjective data, one could question its reliability and validity. It should, however, be noted

that there is ample evidence that such data is not purely "noise", i.e., it correlates with

observable actions such as job mobility and labour supply (see, for example, Ham, 1982;

Altonji and Paxson, 1986; Euwals, 1999). In section 5, we do discuss some problematic

aspects of the SLFS data on desired working time.

4. Desired vs. Contractual Working Time in 1998

Table 2 depicts the portion of salaried employees in 1998 that would like to change theircontractual working time, and also the extent of the desired change. As can be seen, however,

the large majority of workers do not face hours constraints (81.4% and 64.3% of males and

females, respectively). Of those workers that are constrained, the majority would like to work

less and earn less. This is especially the case in the male sample.

Table 2: portion of workers wanting to change their contractual working time in 1998 and to what extent

> 10 hrs less

per week

6-10 hrs less

per week

1-5 hrs less

per week

not

constrained

1-5 hrs more

per week

6-10 hrs more

per week

> 10 hrs more

per week

no. obs.

males 3.9% 9.0% 3.6% 81.4% 0.7% 0.6% 0.7% 4095

females 5.0% 9.3% 7.8% 64.3% 6.0% 3.6% 3.9% 3727

total 4.4% 9.2% 5.6% 73.3% 3.2% 2.1% 2.2% 7822

The relationship between desired and contractual working time is shown in figures 1 to 3. In

figures 1 and 2, distributions of desired and contractual working time are plotted for females

and males, respectively. These figures clearly show that women are more constrained than

men, and the most predominant difference is the "excess demand" of jobs ranging from 15 to

38 hours per week.15This is most notably the case for women working between 20 and 38

hours per week. In figure 2, one notes that mens desired working time mirrors their

contractual working time remarkably well. There is, however, a notable difference between

15 It is interesting to note that, despite the fact that women are less satisfied with thier working-time/wagecombination, they often have higher job-satisfaction levels than men. This is also the case for Switzerland

(see Sousa-Poza and Sousa-Poza, 2000).


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desired and contractual working time in the male sample at around 30 to 38 hours per week.

More specifically, the desire to work 30 to 38 hours per week is more common than the

number of contracts offered in this range.

Figure 1: distribution of contractual and desired working time for women

contractual/desired working time (hrs./week)

5651464136312621161161

percent

20

10

0

contractual working

desired working time

The fact that, in both the male and female samples, there is an apparent deficiency of part-

time jobs does speak in favour of the often-proposed introduction of flexible part-time work

with a work rate varying between 70% and 90% of a full-time job (and with an appropriate

adjustment of the hourly wage rate). In a survey conducted by the State Secretariat for

Economic Affairs (Staatssekretariat fr Wirtschaft, seco), about 57% of all Swiss firms have a

good opinion of such flexible part-time contracts (see Blum and Zaugg, 1998, p. 180).

Although there still appears to be a deficiency of part-time jobs, there has, in the past years,

been a gradual increase in the number of offered part-time jobs. In 1999, approximately

41,000 new part-time jobs were created, approximately 60% of which are occupied by women

(see BFS, 1999b, p. 40 and BFS, 1998, p. 38).16As was mentioned above, Switzerland has, in

an international comparison, one of the largest portions of part-time jobs (see Schaufelberger,

1997).

16 The fact that about 40% of the new part-time jobs were filled by men is an interesting observation.Between 1997 and 1998 the corresponding figure was only 20%.


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Figure 2: distribution of contractual and desired working time for men

contractual/desired working time (hrs./week)

5651464136312621161161

percent

40

30

20

10

0

contractual working


In figure 3, the difference between desired and contractual working time is plotted. In the

female sample, we observe that the desire to work more than is foreseen in the contract is

most pronounced at weekly working hours below 26 hours, whereas the desire to work less is

most favoured by women who work between 36 and 46 hours per week. It also appears to be

the case that women who work less than about 10 hours per week are the most likely to want

to work more. The same applies to women who have an actual working time between 17 and

25 hours per week. In the male sample, the difference between the contractual and desired

working time more or less fluctuates around zero. Only males working more than 38 hours

per week seem to prefer being employed a few hours less.


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Figure 3: differences between contractual and desired working time for men and women

contractual working time (hrs./week)

4946434037343128252219161310741

desired-contractualworkingtime(hrs./week)

8

6

4

2

0

-2

-4

-6

-8

males

females

In order to analyse the determinants of hours constraints in a multivariate way, we estimate

regressions for males and females. In table 3, the results of an ordered probit model are

presented, for which the dependent variable can take on seven possible values corresponding

to the categorisation in table 2, i.e., 0for workers wanting to work more than 10 hours less

per week, up to 6for workers wanting to work more than 10 hours more per week. Thus, this

variable captures the magnitude and direction of hours constraints among employees. Several

independent variables are included in the regressions: six demographic variables, five

working-time characteristics, three other work-related characteristics, and twelve dummy

variables characterising different sectors.17

17 Since, in Switzerland (as in many other industrialised countries), working conditions are negotiated on a

sectoral level, the inclusion of the twelve dummy variables captures sector-specific differences. For thesake of clarity, however, the estimated coefficients for these variables have been omitted in the subsequent

tables.


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Table 3: determinants of hours constraints - estimated coefficients and marginal effects of the ordered probitmodel

males females

coef. MEb

coef. MEb

constant 3.135** 1.541**

demographic variables

marrieda

0.042 0.008 0.023 0.002

childrena 0.067 0.013 0.268** 0.023high educationa -0.232** -0.047 -0.153** -0.013

low educationa

0.262** 0.052 0.107* 0.009

age10-1 -0.680** -0.136 -0.027 -0.002

age210-3 0.769** 0.200 0.156 0.122

working-time characteristics

works on weekenda

0.081 0.016 0.013 0.001

works at nighta 0.014 0.028 0.081 0.007

works block timesa

-0.076 -0.015 -0.090 -0.008

flexible working timesa

0.034 0.007 0.286** 0.024

works shifts

a

-0.038 -0.008 -0.097 -0.008other work-related characteristics

tenure 0.009 0.002 -0.021** -0.002

tenure210-3 -0.068 -0.123 0.255** 0.212

is in managementa -0.049 -0.010 -0.189** -0.016

small firm (< 100 employees)a -0.013 -0.003 -0.064 -0.005

number of observations 4037 3670

log likelihood -2784 -4428

pseudo-R2

0.026c

0.034c

Note: The dependent variable can have seven possible values ranging from "work more than 10 hours lessper

week" to "work more than 10 hours moreper week" (see also table 2). Furthermore, the regressions included

twelve dummy variables for different sectors, which, for the sake of clarity, are not presented here. The reference

industry is the banking and insurance sector.adummy variables

bME = marginal effect calculated at a score equal to 3cthe pseudo-R2measure is that of McFadden (1973)

*/** significant at the 5%/1% level, respectively

Besides presenting the estimated coefficients, we also show the marginal effects calculated at

a score equal to 3.18 These marginal effects therefore show the effect that an explanatory

variable has on the probability of being unconstrained. In the male sample, one notes that, in

general, middle-aged men with a high education19would most likely want to work less than

they are contractually required to. The relationship between the dependent variable and age is

18 The marginal effects (calculated at the sample means) are defined as follows:[ ]

( ) =

x

x

xyE, and

where is the standard normal probability density function.

19 Degrees from the following institutions were considered to be "high education": university, technical

college ("hhere Fachschule", "Technikon"), and high school ("Matura", "Diplommittelschule"). Thefollowing categories were considered to be "low education": no degree (i.e., still in compulsory schooling),

only compulsory schooling, and lower apprenticeship schemes ("Anlehre", "Haushaltslehrjahr"). The


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a parabolic one, with its minimum at around 44 years. Thus, as age increases to 44 years, the

probability that individuals report wanting to work less than they are contractually required to

increases; thereafter the probability declines again.20Stated somewhat differently, men in this

age group are, ceteris paribus, the most willing to reduce their working time. Men with a low

education are generally more likely to report wanting to work more, and the marginal effect

shows that these individuals are less constrained than workers with a medium education

(reference group). Women with a high education, women with higher tenure21, and women in

management positions22have a tendency to prefer to work less. Women with children, women

with a low education, and women with flexible working times prefer to work more than

stipulated in their contract.23A look at the marginal effects also reveals that these women

have a lower probability of being constrained. It is, therefore, interesting to note that women

with flexible working times are less constrained than women who do not have the freedom to

regulate their working times. This is a result that one could expect. The level of education has

the same effects as in the male sample; the magnitude of these effects is, however, much

smaller in the female sample. The coefficients of the education variables thus imply that there

is a deficiency of part-time jobs for high-qualified individuals, especially among males.24 It

should finally be noted that the explanatory power of these models is quite small, implying

that a large degree of variation remains unexplained. This is a standard result in these kinds of

models.

reference category was primarily made up of apprenticeships ("Berufslehre") and similar qualifications

("Vollzeitberufsschule", "hhere Berufsausbildung").

20 The marginal effects show, on the other hand, that the probability of not being constrained is at itsminimum at around 34 years of age, i.e., men in this age group are most likely to be contrained.

21 The underlying question for the tenure variable is as follows: "How many years have you been working foryour current employer?"

22 The management-position variable is defined rather broadly. The exact wording is: "Do you have amanagement position?". About 20% of the female sample has such a position.

23 The survey question associated with the variable "flexible working times" is worded as follows: "How areyour working times regulated in your main job?" The respondents then had three options: (i) fixed working

times; (ii) block working times ("gleitende Arbeitszeit"); (iii) fully flexible working times. Totally flexible

working times imply that the employee can plan his or her own working day. Running working times

imply that the worker has to be in his or her office at certain times of the day (e.g., between 8 and 10 in the

morning). Fixed working times are the most common and imply that the worker cannot, in any way, choose

his or her daily working time.

24 In a study on women's working-time preferences in Germany it is shown that there also exists a deficiency

of part-time jobs for high-qualified individuals. See Beckmann and Kempf (1996).


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We can therefore conclude this section by stating that: (i) the overwhelming majority

of both male and female workers appears to be satisfied with their contractual working time;

(ii) there seems to be a deficit of part-time jobs for women, especially for jobs with around 20

hours per week; (iii) there is a deficiency of part-time jobs for high-qualified individuals and

part-time jobs in the range between 30 and 38 hours per week; (iv) women with very low

contractual working times (especially less than 10 hours per week) would like to work more;

(v) a few socio-economic and demographic variables have an influence on hours constraints,

most notably the level of education: especially middle-aged men with a high education as well

as highly qualified women prefer working less than they are contractually obliged to. The

contrary seems to apply to individuals, most notably women, at lower working-time levels,

which, in turn, are associated with lower income levels.

5. Desired vs. Actual Working Time in 1998: The Role of Overtime

In the above discussion, we analysed the relationship between contractual and desired

working time. Our daily experience tells us, however, that actual working time may deviate

from contractual working time since most employees work non-trivial amounts of overtime.

In table 4, overtime statistics for Swiss salaried employees in 1998 are presented.25

Table 4: overtime in 1998 - summary statistics (hours per week)

no. obs.a

mean standard deviation Total hours per

week

males 3782 3.15 4.60 4365994

females 3416 1.69 3.27 1802365

total 7198 2.47 4.10 6168359

abased on the whole sample, i.e., including employees that do no overtime

As can be seen, men work, on average, more overtime hours than women (3.15 compared to

1.69 hours per week).26Taken over the whole population, men (women) work approximately

25 The wording of the relevant question is as follows: "Taken over the past 12 months, how many hours perweek did you work in excess of the number of hours stipulated in your contract?" Thus, this variable

measures the overtime usually worked in a week (and not necessarily the actual overtime worked in, say,

the previous week).

26 A total of 56% of all salaried employees do overtime work on a regular basis (males 65% and females47%). These results show that, on average, the demand of the SGB referendum to limit the number of

overtime hours to 100 per year is, currently, clearly not being met. According to a recent representative


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4.4 (1.8) million hours overtime per week. Thus, in total, over 300 million hours overtime are

performed each year (based on 1998 data). It therefore comes as no surprise that overtime

plays an important role in any discussion on working time policies.

Overtime, however, can take on many different forms. In general, one can distinguish

between "transitional" overtime, which is compensated with additional free time, and

"permanent" overtime which is paid out or not compensated in any way. In table 5, we show

the form of compensation for overtime. A total of 59.8% (57.9%) of all males (females) that

usually do overtime get compensation in the form of additional holidays. Only 10.6% (16.8%)

of males (females) receive payment for their overtime. Finally, 29.6% (25.3%) of males

(females) received no compensation. It is interesting to note that forms of compensation differ

between genders: males are more likely than females to receive no compensation or

compensation in the form of free time, whereas females are more likely than males to receive

payment for their overtime.27 These differences between genders are, needless to say,

primarily a result of segregated labour markets.

Table 5: forms of compensation for overtime in 1998 - summary statistics

no.

obs.a

percentage hours per week

none money holidays none money holidays

males 2454 29.6% 10.6% 59.8% 6.50 5.70 3.82

females 1610 25.3% 16.8% 57.9% 4.44 3.96 3.06

total 4064 27.9% 13.1% 59.0% 5.76 4.81 3.52

abased on a sample of salaried employees that reported their form of compensation and usually do overtime

In table 5, we also depict the average number of hours overtime according to the different

forms of compensation. We note that, in both the male and the female samples, employees

that do not get compensation for their overtime also work more overtime than workers who

get some form of compensation. Another interesting result is that, although women are morelikely to receive paid compensation, they, on average, work less overtime than the

corresponding group of men (3.96 as opposed to 5.70 hours per week). Figure 4 depicts the

distribution of overtime according to gender. Compared to men, a larger portion of women do

study for Germany, a strikingly similar result was obtained, i.e., 56% of all employees are confronted with

regular overtime (see Gro/Munz, 1999).

27 Below we show that primarily white collar workers do unpaid overtime. Thus, it comes as no surprise thatfemales are more likely to receive payment for their overtime. Note, however, that, on average, women

work less paid overtime than men. This can easily be deduced from the results in tables 4 and 5.


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shorter overtime hours per week. Men, on the other hand, are more likely to spend longer

hours per week on overtime.

Figure 4: distribution of overtime for men and women

overtime (hrs./week)

423020151050

percent

60

50

40

30

20

10

0

males

females

In table 6, we present the results of probit and tobit regressions. In the case of the probit

model, a dichotomous dependent variable is used with a value equal to 0if the respondent

does not usually work overtime and equal to 1otherwise. Thus, these regressions reflect the

determinantsof doing overtime. In the case of the tobitmodel, the dependent variable has a

value equal to 0 if the respondent does no overtime and equal to the number of overtime

hours usually done per week otherwise. These regressions show how the numberof overtime

hours is affected by the explanatory variables. We have used the same explanatory variables

as in the regressions of the previous section.28Furthermore, and for the sake of clarity, we

only present the marginal effects (calculated at sample means) here.

28 As in the above analysis, these regressions also included twelve dummy variables for different sectors.

Although we do not present the results here, one interesting observation is that workers in the banking and

insurance sector have a relatively high probability of working long overtime hours and also have a high

probability of wanting to work less than contractually required to (relative to other industries). One

possible explanation is that firms in these sectors often try to recruit very productive workers, and they doso by offering relatively high wages together with long required working times (especially overtime). This

topic is analysed in Sousa-Poza and Ziegler (2001).


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16

Taking a look at the probit results first we note that men with a high education, men

that have block or flexible working times, and men in management positions are likely to do

overtime. Men with a low education have a higher probability of not doing overtime. The age-

overtime function for men is a parabolic one with its maximum at around 31 years. Thus,

younger employees are primarily affected by overtime. The determinants of overtime in the

female sample are very similar to those in the male sample with the exception that marriage

and the presence of children reduce the probability of doing overtime. This result reflects the

much-cited observation that women are primarily responsible for household tasks and child-

care (see, for Switzerland, Sousa-Poza et al., 2001).

Table 6: the determinants of overtime - marginal effects of the probit and tobit models

probit tobit

males females males females

demographic variables

marrieda 0.009 -0.059** 0.088 -0.247**

childrena -0.011 -0.116** -0.014 -0.605**

high educationa

0.056** 0.025** 0.874** 0.208*

low educationa

-0.225** -0.149** -1.547** -0.676**

age10-1 0.144** 0.193** 0.120** 0.112**

age210-3 -0.227** -0.283** -1.160** -1.152**


works on weekenda

-0.009 0.027 0.429* 0.183

works at nighta -0.014 -0.023 0.309 0.005

works block timesa 0.179** 0.168** 0.964** 0.520**

flexible working times

a

0.086** 0.009 1.325** 0.222works shiftsa

0.060 0.026 0.225 -0.138

other work-related characteristics

tenure 0.001 0.003 0.002 -0.001

tenure210-3 0.044 -0.008 0.249 0.363is in managementa 0.220** 0.225** 1.852** 1.061**

small firm (< 100 employees)a

0.021 0.003 0.044 -0.059

sigma 4.883** 4.515**

number of observations 3775 3412 3775 3412

log likelihood -2150 -2102 -8312 -5738

pseudo-R2

0.122b

0.109b

0.211c

0.171c

Note: The dependent variable in the probit model has a value equal to 0if the respondent does not usually workovertime and equal to 1otherwise. In the case of the tobit model, the dependent variable has a value equal to 0if the respondent does no overtime and equal to the number of overtime hours usually done per week

otherwise.The regressions include a constant and twelve dummy variables for different sectors. Only the

marginal effects are depicted here.adummy variablesbthe pseudo-R

2measure is that of McFadden (1973)

c the pseudo-R2measure is that of McKelvey and Zavoina (1975)


The results of the tobit model show how the independent variables affect the length of

overtime work. We note that men with a high education work about 52 minutes more

overtime per week than workers in the reference group, whereas men with a low education


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17

work about one and a half hours less overtime per week. A further interesting result is that

men with flexible working times work approximately one hour and 20 minutes more overtime

per week than individuals that have fixed working times. As one would expect, the effect of

having a management position is very strong: managers work nearly two hours more overtime

per week than workers without a management position. The results are similar in the female

sample with the exception of the marriage and child coefficients.

As was shown above, there are different forms of compensation for overtime work. In

order to establish the determinants of the form of compensation for overtime, we estimate

multinomial logit functions for both males and females. The dependent variable can have

three possible values, depending on the form of compensation. The summarised results are

presented in table 7. The marginal effects of these multinomial logits are presented in table A

in the appendix. In order to keep things simple, we only select some of the most interesting

variables for the exposition in table 7.

Table 7: determinants of the form of compensation for overtime (results of the multinomial logit model)

none holidays money

males - high education

- works on weekend- does not have block

times

- flexible working times

- does not work shifts

- in management

- does not have a high

education- does not work on

weekend

- does not work at night

- works block times

- does not have flexible

working times

- works shifts

- not in management

- low education

- not middle aged

a

- works on weekend

- works at night


- not in management

females - high education

- elder workers

- works at night

- does not have block

times- does not work shifts

- in management

- does not have a high

education

- younger workersb

- single

- no children- does not work at night

- works block times

- works shifts

- have high tenure

- in management

- low education

- older workers

- married

- children

- works at night- does not have block

times


- does not have high

tenurec

- not in management

Note: Some stylised results which are based on the estimates of the multinomial logits presented in table A in the

appendix.ais a parabolic function with its minimum at around 42 years of agebis a parabolic function with its maximum at around 26 years of age

cis a parabolic function with its minimum at around 43 years of age

As can be seen in table 7, several factors influence the form of compensation. In fact, the

picture presented here is that the determinants of the form of compensation are complex, and


19/30


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19

primarily affect blue-collar workers. A similar argument may apply for men who work on

weekends. On the one hand, such men could be white-collar workers (and thus tend to receive

no compensation for overtime) who have a fair amount of autonomy with regard to the

planing of their workweek or, on the other hand, these are primarily blue-collar workers that

have to work on weekend (and thus tend to receive compensation for their overtime). The

same reasoning applies to women who work at night. Thus, once again, the picture presented

here is a complex one with a certain degree of heterogeniety in groups of individuals

receiving a specific form of compensation. Perhaps the only stylised fact which can be made

is that white collar workers are the most likely to receive no compensation for overtime and

blue collar workers are more likely to get compensation in the form of money or holidays.

As we pointed out in the comparison above between desired and contractual working

time, most workers are satisfied with their contractual working time (see section 4). It

therefore comes as no surprise that the number of constrained workers increases substantially

when we analyse actual working time, actual working time being defined as contractual

working time plus overtime. Figures 5 and 6compare actual with desired working time. As

can be seen in both the male and the female samples, the distribution of the actual working

time curve has become flatter with a larger tail in the upper end, i.e., a large portion of the

distribution has shifted toward the higher hours. Thus, these figures reveal that actual working

time is, in general, too long. More specifically, the predominant desire to work approximately

40 to 42 hours per week is not being fulfilled, i.e., a substantial portion of employees work

more than 42 hours per week. Taken at face value, these results would imply that hours

constraints can be reduced by decreasing the number of overtime hours worked. This, in fact,

is often demanded by unions (see SGB, 1999, p. 27).


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20

Figure 5: distribution of actual and desired working time for women

actual/desired working time (hrs./week)

5651464136312621161161

percent

20

10

0


actual working time

Figure 6: distribution of actual and desired working time for men

actual/desired working time

5651464136312621161161

percent

40

30

20

10

0


actual working time


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21

At this stage, however, a word of caution needs to be included. Based on the available data, it

is not clear to what extent the reported desired working time refers to the contractual or the

actual working time. Although the wording of the question would make us assume that the

respondents mean desired actual and not desired contractual working time, this need not

always be the case. It is conceivable that respondents did not explicitly take overtime into

consideration when reporting their desired (actual) working time. Stated somewhat

differently: if some respondents reported desired contractualworking time instead of desired

actual working time and if these two responses are different in the sense that the former

explicitly excludes overtime, then one does face a problem.32In such a case,figures 5 and 6

are potentially flawed since they would be comparing desired contractual with actual working

time. Unfortunately, the only way to solve this problem would be by stating a more precise

question in the survey. In any case, the analysis in this section does show that the nature of

overtime plays a very important role in the design of working time policies. Furthermore, it

does not change our conclusion from section 3, namely that there does not appear to be much

leeway for a collective reduction of the workweek below 40 hours.33

Thus, we can conclude this section by stating that: (i) a fair amount of overtime is

performed each week and that the most common form of compensation for overtime is

holidays; (ii) a substantial amount of overtime work is not compensated in any form and only

a small portion is actually paid out; (iii) women are more likely to receive payment for

overtime than men; (iv) no compensation for overtime is most probable among white collar

workers, whereas blue-collar workers have a higher probability of obtaining paid

compensation; (v) if one compares actual working time with desired working time, then one

notes that a large discrepancy between the most common desired weekly working time of

between 40 and 42 hours and actual working time exists. Thus, overtime would appear to

increase the number of constrained workers, in the sense that these workers would like to

work less.

32 Desired actual and desired contractual working times are only equivalent if a respondent does not want towork overtime.

33 A further possible problem with a comparison of desired with actual working time is that, as pointed outabove, a substantial portion of overtime is compensated by free time. It is difficult to judge the extent to

which this additional free time is taken into consideration when reporting desired working time. Thus, therelationship between contractual working time, desired working time, overtime, and the form of

compensation for overtime is quite complex and cannot be clearly interpreted with the available data.


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22

6. An International Comparison of Desired Working Time

As was pointed out in section 2, with regard to the weekly working time, Switzerland is

somewhat of an exception since it has one of the longest workweeks in Western Europe and

one of the highest in the industrialised world (see, OECD, 1998a). It is therefore interesting to

see how hours constraints in Switzerland differ from those in other countries. In order to do

this we analyse the latest Work Orientations data from the 1997 ISSP (see section 3 above).

We analyse a sample of workers in 14 industrialised countries. In figure 7, the portion of

workers wanting to work less and earn less, work the same and earn the same, and work more

and earn more are depicted. A first interesting result is that the extent of hours constraints is

relatively small. Furthermore, in most countries, the portion of workers wanting to work more

and earn more is larger than the portion of workers wanting to work less and earn less. Onlyin three countries is this not the case: Denmark, Norway, and Switzerland. Of all the

countries considered here, Switzerland has the largest portion of workers wanting to work less

and earn less. This could be a result of the relatively high income in Switzerland and long

working hours which could give rise to a higher marginal value of leisure. 34 In figure 8, a

ranking of the degree of hours constraints is shown. As can be seen, Switzerland is ranked

fourth out of the 14 countries analysed here. Approximately 70% of all Swiss employees

reported no hours constraints. Thus, in an international comparison, Swiss workers appear to

be quite satisfied with their current workload/pay combination. This is an interesting result if

one considers that Swiss employees work relatively long working hours. Furthermore, this

outcome confirms the results obtained with data from the SLFS (see section 4).35

34 This in itself, however, does not explain why these employees should be constrained. Sousa-Poza and

Ziegler (2001) provide a possible explanation as to why employees may work inefficient long hours in the

sense that they work more than they would like to.

35 The results are, in fact, strikingly similar. Since both surveys use somewhat different questions, thissimilarity does provide some support for the reliability of the results presented above. Another similar

result was obtained by a survey conducted in October 1998 by the GfS-Research Institute. In this survey, a

total of 641 Swiss workers were asked whether they would like to work more, work less, or work the sameamount (no reference was made to earnings). 65% said that they were satisfied and 23% reported

overemployment. See GfS (1998).


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23

Figure 7: hours constraints by country

0%

20%

40%

60%

80%

100%

Denmark

France

Germany

GreatBritain

Italy

Japan

Netherlands

NewZealand

Norway

Portugal

Spain

Sweden

Switzerland

UnitedStates

work less and earn less work the same and earn the same work more and earn more

Source: Based on Sousa-Poza and Henneberger (2001)

Figure 8: ranking by country according to the percent of unconstrained workers

0%

10%

20%

30%

40%

50%

60%

70%

80%

Denmark

Norway

GreatBritain

Switzerland

Netherlands

Germany

Sweden

France

NewZealand

Spain

Japan

Italy

UnitedStates

Portugal

Source: Based on Sousa-Poza and Henneberger (2001)


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7. Conclusions

Workers desired working time, workers hours constraints, overtime, and the form of

compensation of this overtime are fundamental aspects in the development of working-time

policies. Yet, these issues have received surprisingly little attention in the current working-

time debate in Switzerland. The aim of this paper is to present a number of empirical results

on these topics. With data from the 1998 Swiss Labour Force Survey and with data from the

1997 International Social Survey Programme we show that:

Most Swiss workers (81% and 64% of all salaried males and females, respectively) do notface hours constraints when we compare the desired working time with the contractual

working time. The largest portion of constrained workers would like to work less and earn

less (17% of males and 22% of females). There does appear to be a deficit of part-time jobs for both men and women. This deficit is

most pronounced for women who would like to work around 20 hours per week, and also

for men and women with a high education (i.e., there is a deficit of high-qualification part-

time jobs).

Women with very short contractual working hours (less than about 10 hours per week)generally would prefer working more and earning more.

Men and women with a high education are more likely to want to work less and earn less,whereas the opposite applies to workers with a low education. Women who have flexible

working times are less likely to be constrained.

Men and women work on average 3.15 and 1.69 hours overtime per week, respectively.The most common form of compensation for this overtime is holidays, followed by no

compensation and money. Women are much more likely to receive paid compensation

than men.

Men and women with a high education and who have a management position arepredominantly affected by overtime. Furthermore, it is primarily such workers who

receive no compensation for their overtime.

Young, single women with no children are likely to get compensation in the form ofholidays, whereas elder, married women, with children have a higher probability of

getting paid compensation for overtime.

A comparison between actual and desired working time, where actual working time isdefined as contractual working time plus overtime, reveals that a significant amount of

workers are constrained in the sense that they would prefer shorter actual working hours.


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25

An international comparison of desired working time reveals that workers in Switzerlandare quite satisfied with their current workload/pay combination (Switzerland ranks fourth

out of the 14 industrialised countries analysed here). Switzerland does, however, have the

highest portion of workers wanting to work (and earn) less out of all the 14 countries.

In the light of the current working-time debate in Switzerland, most notably the

referendum launched by the SGB, which foresees the introduction of a de factoworkweek of

36 hours and a mandatory upper limit of 100 hours overtime per year, our analysis could

suggest the following:

Our results show quite clearly that the 42 and 40-hour workweek is preferred by anoverwhelming majority of employees. Thus, one could at least question the optimality of a

nation-wide reduction of the workweek by, on average, four to six hours per week.

Naturally, the extent to which earnings change plays an important role in such a

conclusion. If a reduction of the workweek leaves earnings unaffected (something which

is questionable), then this conclusion obviously needs to be put into perspective.

If working-time policies at least partially aim at reducing the number of constrainedindividuals, then an increase in part-time jobs and a reduction of overtime is

recommendable. Our results show that there is a deficiency of part-time jobs for high-

qualified individuals and also part-time jobs in the range between 30 and 38 hours per

week. The fact that Switzerland has the largest portion of workers wanting to work less

and earn less out of the 14 industrialised countries analysed in this paper reinforces this

conclusion.

The determinants of hours constraints, overtime, and the form of compensation ofovertime are quite complex. This is primarily due to the high and, to a large extent,

unobservable heterogeneity of working time preferences between and within different

groups of employees. As a result, individual (as opposed to collective) working-time

regulations would seem to be more appropriate. The fact that the goodness-of-fit of the

above regressions is relatively low implies that a high degree of variability exists, i.e.,

hours constraints appear to be quite randomly distributed among the underlying

population, and, thus, the variability of hours constraints cannot be well explained by the

numerous regressors implemented here. Hours constraints therefore are largely affected

by unobservable factors such as personality, motivation, etc. Collective working-time

regulations, by nature, cannot adequately capture this heterogeneity. Therefore, individual

agreements - perhaps on the basis of a shorter averageworkweek - seem better suited to

reduce workershours constraints and generally improve their well-being at work.


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26

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Appendix

Table A: determinants of the form of overtime compensation - estimated marginal effects of the multinomial

logit model

males females

none holidays money none holidays moneydemographic variables

marrieda 0.030 -0.031 0.001 0.018 -0.121** 0.103**

childrena

0.016 -0.026 0.010 0.031 -0.150** 0.119**

high educationa 0.123** -0.128** 0.005 0.169** -0.074* -0.095**

low educationa

-0.100* 0.059 0.042* -0.294 -0.013 0.043*

age10-1 0.006 0.005 -0.111** -0.009 0.141* -0.005

age210-3 0.011 -0.140 0.130** 0.152* -0.272** 0.120*


works on weekenda

0.085** -0.151** 0.066** 0.018 -0.021 0.003

works at nighta 0.042 -0.101** 0.059** 0.080* -0.176** 0.096**

works block timesa -0.052* 0.064** -0.012 -0.105** 0.225** -0.120**

flexible working timesa

0.100** -0.147** 0.046** -0.011 -0.043 0.054**

works shiftsa -0.156** 0.141** 0.015 -0.288** 0.285** 0.003other work-related characteristics

tenure -0.243 0.004 -0.002 -0.001 0.008** -0.007**

tenure210-3 0.028 -0.047 0.020 0.026 -0.107 0.081*

is in managementa

0.086** -0.040* -0.046** 0.044** 0.068** -0.112**

small firm (< 100 employees)a -0.003 0.011 -0.007 0.031 -0.045 0.015

number of observations 3132 2394

log likelihood -2505 -1936

pseudo-R2 0.125b 0.199b

Note: The dependent variable can have three possible values depending on the form of overtime compensation.

The regressions include a constant and twelve dummy variables for different sectors. Only the marginal effects

are presented here. The sample includes all employees that answered to the question dealing with the form ofcompensation for overtime. It should also be noted that over 20% of employees that do not usually work

overtime also reported their overtime form of compensation. These individuals have alsobeen included in theseregressions (and therefore the sample size here does not correspond to the sample size in table 5).adummy variablesbthe pseudo-R

2measure is that of McFadden (1973)


working-time policies in switzerland

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