Working Hours Constraints
Developments
&
Determinants
Dennis Raven s1150278 August 2007Sociology, Faculty of Behavioural and Social Sciences
International Business & Management, Faculty of Management and Organization Supervisors:
dr. R.J.J. Wielers dr. P.H. van der Meer
Thesis title: Working Hours Constraints: Developments & Determinants
Author: Dennis Raven
Student number: s1150278
Supervisors: dr. R. J. J. Wielers dr. P. H. van der Meer dr. M. A. J. van Duijn Institutions: University of Groningen
Department of Sociology, Faculty of Behavioural and Social Sciences
Department of International Business & Management, Faculty of Management and Organization
Date: August 29th 2007
Before you lies the product of a summer that went by in what feels like the blink of an eye. While most people fled to places where the sun would be more likely to shine, in a summer so sad even the autumn seems cheerful, I had no choice but to write this thesis. A thesis that marks the end of eight years of studying. Well, perhaps these eight years weren’t exactly years of hard labour, but at least this summer was. This thesis also marks the end of two very interesting studies. When dividing two studies by eight years, it took me on average four years to complete each study. Therefore, I like to think I did reasonably well. Above average, actually!
Even though I spent a large part of the summer writing this thesis while everyone else was on vacation, I’d like to thank a couple of people for their help and guidance. First, I want to thank Rudi Wielers for having the nerve to let me do this research in the first place. A telltale sign that he clearly didn’t know what he was getting himself into. I’m also grateful for his suggestion of graduating on two separate studies with one thesis. I also want to thank Peter van der Meer for willing to be my supervisor. Due to the deadline for doctoral theses virtually all available supervisors were filled to capacity. Having arranged my supervisors through unofficial channels made graduating suddenly a whole lot easier. I would also like to thank Marijtje van Duijn for being my third supervisor, in particular because there was so little time. It’s too bad we didn’t have the time to discuss the comments on my concept. I’m sure this thesis would have benefited greatly from them. I would like to thank Bartjan Pennink for giving me some leeway with regard to this thesis. Although it does not quite fit all of the official requirements, it does fit Bartjan’s motto “all good ideas deserve a chance”. Finally, I would like to thank Jan Vis for sharing his office with me over the last six months. It has been a pleasure working there, despite the dull walls and file cabinets surrounding my desk.
Index
Chapter 1 - Introduction 5
---1.1 - Working Hours Constraints 5
---1.2 - Relevance 6
---1.3 - Problem Statement 7
---1.4 - Thesis Structure 8
Chapter 2 - Literature Review 9
---2.1 - Working Hours Constraints 9
---2.2 - Cross-National Comparison Literature 10
---2.2.1 - Cross-National Comparison of Working Hours Constraints 11
---2.2.2 - Conclusion Cross-National Comparison of Working Hours Constraints 16
---2.2.3 - Explaining Cross-National Differences in Working Hours Constraints 17
---2.2.4 - Conclusion Explaining Cross-National Differences in Working Hours Constraints 27
---2.3 - Extended Literature Review 28
---2.3.1 - The Four Components Influencing Working Hours Constraints 29
---2.3.2 - The Individual Component 31
---2.3.3 - The Household Component 32
---2.3.4 - The Work Component 33
---2.3.5 - Research Hypotheses 36
Chapter 3 - Research Methodology 39
---3.1 - Sample 39
---3.2 - Variables 43
---3.3 - Analytic Strategy 46
Chapter 4 - Research Results 49
---4.1 - Description of Working Hours Constraints in the Netherlands 49
---4.2 - Correlation Analysis 60
---4.3 - Development of Working Hours Constraints in the Netherlands 61
---4.4 - Determinants of Working Hours Constraints in the Netherlands 63
---4.4.1 - Determinants of Underemployment 65
---4.4.2 - Determinants of Overemployment 69
---4.4.3 - Conclusion Determinants of Working Hours Constraints in the Netherlands 73
---4.5 - Development of the Determinants of Working Hours Constraints 74
---4.6 - Determinants of Working Hours Constraints Developments 76
Chapter 5 - Conclusion 79
---5.1 - Cross-National Differences of Working Hours Constraints 79
---5.2 - Longitudinal Working Hours Constraints in the Netherlands 81
---5.3 - Research Validity 82
---5.4 - Overemployment, Gender and Working Hours Constraints 87
---5.5 - Recommendations 89
Chapter 1
Introduction
In this chapter, a general introduction of this study will be given. Fist, the subject of the study will be briefly explained, after which the relevance will be touched upon. Subsequently, the problem statement will be specified. Finally, the structure of this thesis will be explained.1.1 Working Hours Constraints
Literature indicates that over the last decades people started complaining about a lack of time. Somehow, people feel they do not have enough time to do the things they would want to do. Multiple theories were developed to explain the existence and the development of this lack of time, both on individual and on macro level. A large part of the literature relates this lack of time to working hours.
This research is based on a paper by Wielers & Van der Meer (2006a), presented at the
Dag van de Sociologie 2006. They distinguish two types of mismatches between actual
working hours and preferred working hours. Workers who prefer to work less hours at an equal hourly wage rate, experience time scarcity. A situation where workers prefer to work more hours than they actually work at an equal hourly wage rate, is called income
scarcity. More in general, when there is a mismatch between actual and preferred
working hours, workers are said to be constrained in their working hours (Sousa-Poza & Henneberger, 2000). In this research, the way these working hours constraints have developed through time and their possible causes are the two focal points.
1.2 Relevance
In their paper, Wielers & Van der Meer analyse working hours constraints using cross-national data. However, the results proved to be quite ambiguous, and they concluded many of the important developments were so highly interrelated that it was impossible to draw clear conclusions.
Reynolds & Aletraris (2006) suggest five reasons for studying working hours constraints. First, they argue organizational performance and worker safety are threatened if labour markets provide workers with working hours that differ from their preferred working hours. Such employees are argued to be less loyal, more prone to making mistakes and show increased absenteeism. Second, working hours constraints could result in lower psychological and physical well-being. Underemployment, particularly in the case of involuntary part time work, is associated with alcohol abuse and lowered self-esteem. Overemployment is associated with increased levels of stress and more work-family conflict. Third, in combination with developments of increasing amounts of single-parent households and increasing amounts of dual-earner households, constrained workers may be inhibited from providing adequate (financial) care for their families. Fourth, working hours constraints seem related to gender inequality. The traditional division of household tasks, where men are responsible for income while women are responsible for household tasks, are reflected in the labour market. The final argument for studying working hours constraints Reynolds & Aletraris mention, is of theoretical nature. While neoclassical economists emphasize that the efficiency of labour markets allows for the adjusting of actual working hours in accordance with preferred working hours, sociologists point to social structures that complicate the functioning of labour markets. Sousa-Poza & Henneberger (2002) agree, arguing that the existence of working hours constraints is a sign of inefficient labour markets and a cause of, amongst others, lower quality of life. The majority of working hours constraints literature consists of cross-sectional analyses. Longitudinal research is limited, and even when longitudinal data is used, the research period is often limited to one or a couple of years. Thus, there is need for research in
which working hours constraints are analysed through an extended period of time, using data from a single source. Cross-national working hours constraints literature often also include the Netherlands. In many of these studies, the exceptional position occupied by the Netherlands is noted. Eye-catching characteristics of the Netherlands include in particular the high part time work rate and gender differences. This study aims to make a contribution to existing literature by analysing working hours constraints in the Netherlands over time.
1.3 Problem Statement
The goal of this research is to describe and explain the differences in working hours
constraints between countries, and to describe and explain the development of working hours constraints in the Netherlands in the period between 1988 and 2002.
Based on this goal statement, two research questions can be formulated:
1. How do countries differ in the extent to which their inhabitants experience working hours constraints and how can these differences possibly be explained? 2. How have working hours constraints developed in the Netherlands in the period
between 1988 and 2002 and how can this development be explained?
The research questions can be split up into a number of sub questions:
1. Do countries differ in the extent to which their inhabitants experience working hours constraints?
2. How can these possible differences between countries be explained?
3. How did working hours constraints develop in the Netherlands in the period between 1988 and 2002?
4. What are the determinants of working hours constraints in the Netherlands? 5. How did these determinants of working hours constraints develop in the
6. Which influence do these developments of the determinants of working hours constraints have on the development of working hours constraints in the Netherlands in the period between 1988 and 2002?
1.4 Thesis Structure
In chapter two, a detailed review of existing literature will be given. The first two sub questions will be answered in the first part of the literature review, which will take the shape of a cross-national analysis of the development of working hours constraints and the possible determinants of working hours constraints. After that, an extended literature review will result in several hypotheses regarding the possible determinants of working hours constraints.
Chapter three will discuss methodological issues. The OSA Labour Supply Panel data set
will be introduced, and with it sample and variable related information. Finally, the analytic strategy will be discussed.
The research results will be presented in chapter four. The chapter will begin with an extensive description of the most important (working hours related) variables. After that, the developments of working hours constraints in the Netherlands will be analysed (sub question three). Subsequently, the determinants of working hours constraints in the Netherlands will be analysed (sub question four). Finally, the developments of the determinants will be analysed (sub question five) after which will be analysed whether the longitudinal developments of these determinants could explain the developments of working hours constraints (sub question six).
The final chapter, chapter five, discusses the answers to the two research questions. Also, the research validity is discussed. The chapter will conclude by discussing some noteworthy findings and with some suggestions for future research.
Chapter 2
Literature Review
By means of a detailed literature review, the first research question will be answered: “How do countries differ in the extent to which their inhabitants experience workinghours constraints and how can these differences possibly be explained?“ First, a
cross-national comparison of working hours constraints is used to answer the first sub question. After that, cross-national differences in working hours constraints will be explained. Finally, as a preparation for the case study used to answer the second research question, an elaborate framework of working hours constraints with accompanying determinants will be drawn up based on both cross-national analyses and additional relevant literature. However, this chapter begins with a short introduction of working hours constraints and the literature used to answer the first research question.
2.1 Working Hours Constraints
Traditional microeconomic theory suggests workers can set their actual working hours in accordance with their working hours preferences. In such a case, workers will want to work more (or less) hours until their hourly wage rate equals the marginal value of hours not spent doing paid work. However, due to existing market imperfections this is not always possible. Whenever actual working hours do not equal preferred working hours, one speaks of working hours constraints (Sousa-Poza & Henneberger, 2000, 2002). Working hours constraints exist in two types. If the hourly wage rate exceeds the marginal value of time spent away from work, the worker will want to increase the actual working hours. In this case, one speaks of underemployment. When the opposite is the case, one speaks of overemployment. Workers whose actual and preferred working hours match, are unconstrained.
2.2 Cross-National Comparison Literature
The cross-national analysis of working hours constraints will be based on a literature review, consisting of studies that have incorporated a cross-national analysis. Research based on only one or a few countries is much more difficult to compare. The selected research includes Bielenski, Bosch & Wagner (2002), Corral & Isusi (2003), OECD (1998), Sousa-Poza & Henneberger (2000), Sousa-Poza & Henneberger (2002) and Wielers & Van der Meer (2006a). First, a brief description will be given of the databases used in the selected studies. A number of countries will be selected that will be used in this analysis. Second, the possible existence of working hours constraints in these countries will be described and compared (sub question 1). Finally, an attempt will be made to explain the possible differences found (sub question 2).
Bielenski, Bosch & Wagner (2002) based their research report on the Employment Options of the Future Survey. This survey was carried out on behalf of the European Foundation for the Improvement of Living and Working Conditions in 1998 in the 15 EU member states and Norway. In their report they analyse labour market participation and preferences of respondents between 16 and 64 years of age. Corral & Isusi (2003) describe and explain part-time work in Europe in their research. They use multiple sources for their information, but the most important database used is the Eurostat Labour Force Survey (LFS) 2002. The longitudinal development of part-time work they analyse, concerns 1992 and 2002 and includes the same 15 EU member countries as Bielenski, Bosch & Wagner used. A study by the OECD (1998) uses databases from multiple sources, including a varying amount of countries during several points in time to discuss trends in working hours. Sousa-Poza & Henneberger (2000) analyse working-hours constraints in 9 OECD countries using the 1989 International Social Survey Program (ISSP). They included only employed respondents between 18 and 60 years of age in their analysis. Sousa-Poza & Henneberger (2002) used the 1997 ISSP database to analyse and compare the working-hours constraints in 21 countries. Their analysis includes over 15.000 full-time and part-time workers. Wielers & van der Meer (2006a) wrote a paper in which they analyse international differences in time scarcity (overemployment). They
based their analysis on the second round of the European Social Survey (ESS) in 2004, including 23 European countries.
In total thirty countries were used at least once, of which eight were included in at least four studies. These are Denmark, Germany, Italy, the Netherlands, Norway, Portugal, Spain and the United Kingdom. Five additional countries (all included in three of the five selected studies) were selected because of inclusion in other relevant literature: Belgium, Finland, France, Sweden and the United States. Data are available roughly for the period between 1985 and 2004.
2.2.1 Cross-National Comparison of Working Hours Constraints
In this section, the first sub question will be answered: “Do countries differ in the extent
to which their inhabitants experience working hours constraints?” This sub question can
be answered by using one of two sorts of information. Working hours constraints can be analysed by comparing actual working hours with preferred working hours, but also by comparing the proportions of under- and overemployed workers. Combining both types of information in one analysis will yield the best results. Unfortunately, the studies included provide only one of these types of information.
Table 2.1 Proportions of under- and overemployment (1)
Country Overemployed Unconstrained 1 Underemployed Ratio (underemployed /
overemployed) 1985 1994 1985 1994 1985 1994 1985 2 1994 Denmark 51% 66% - - 38% 32% 0,75 0,48 Netherlands 47% 52% - - 46% 43% 0,98 0,83 Italy 39% 39% - - 55% 54% 1,41 1,38 Belgium 36% 40% - - 58% 48% 1,61 1,20 France 34% 40% - - 62% 53% 1,82 1,33 Germany 30% 34% - - 56% 54% 1,87 1,59 Spain 31% 24% - - 64% 70% 2,06 2,92 United Kingdom 19% 32% - - 77% 62% 4,05 1,94 Portugal 11% 35% - - 82% 58% 7,45 1,66 Unweighted average 33,1% 40,2% - - 59,8% 52,7% 1,81 3 1,31 3 1 People unable to choose between more earnings or less hours were excluded from the analysis
2 Countries ranked according to the 1985 underemployment / overemployment ratio 3 Based on unweighted averages
Table 2.1 shows the proportions of over- and underemployment in 1985 and 1994, as presented in OECD (1998). The nations are ranked according to the 1985 working hours constraints ratio. Only the workers that perceived working hours constraints were included in the analysis, hence the relatively high proportions. On average, workers in Europe are most often underemployed (60% in 1985 and 53% in 1994). However, between 1985 and 1994 the proportion of overemployed increased. While in 1985 there were 1,8 underemployed workers for every overemployed worker, by 1994 this had dropped to 1,3 underemployed workers for every overemployed worker. This is the case in all countries except Spain. In Spain, the proportion of underemployed workers has increased. In two out of thirteen countries, Denmark and the Netherlands, the ratios are below 1, indicating that the proportion of overemployment exceeds the proportion of underemployment. In Portugal and the United Kingdom, the proportion of overemployed workers rises fastest. Overall, two main conclusions can be drawn from this data (OECD, 1998). First, underemployment is more common in the European countries than overemployment. Second, there appears to be a trend towards increasing overemployment in the European countries.
Results from Sousa-Poza & Henneberger (2000, 2002) are displayed in table 2.2. Although they analysed working hours constraints of two different years in two different studies, they used the same source for their data (ISSP). Although caution is at place, it is believed that the two studies are quite suitable for a comparison of the results (in fact, they do so themselves as well although they keep their comparison limited).
On average, in 1989 as well as in 1997 a vast majority of the workers is satisfied with the amount of hours worked and the matching income (respectively 67,8% and 66,7%). Also, both in 1989 and in 1997 underemployment was more abundant than overemployment. The proportion of underemployed workers decreased slightly to 23,6%, the proportion of overemployed workers increased to 9,8%. Overall, the ratio of underemployed divided by overemployed workers dropped from about 3 to about 2,4.
Table 2.2 Proportions of under- and overemployment (2)
Country Overemployed Unconstrained Underemployed Ratio (underemployed /
overemployed) 1989 1997 1989 1997 1989 1997 1989 2 1997 2 Germany 1 9,6% 9,0% 77,0% 69,1% 13,4% 21,9% 1,40 2,43 Netherlands 12,2% 11,5% 69,7% 69,3% 18,0% 19,2% 1,48 1,67 United Kingdom 8,1% 6,3% 67,8% 70,9% 24,2% 22,8% 2,99 3,62 Norway 7,6% 14,9% 66,3% 73,5% 26,1% 11,6% 3,43 0,78 Italy 6,0% 6,9% 63,3% 59,7% 30,7% 33,3% 5,12 4,83 United States 4,2% 10,1% 62,5% 57,4% 33,2% 32,5% 7,90 3,22 Denmark - 13,7% - 75,6% - 10,8% - 0,79 Sweden - 16,5% - 66,3% - 17,2% - 1,04 France - 14,9% - 65,1% - 20,0% - 1,34 Spain - 6,7% - 63,4% - 29,9% - 4,46 Portugal - 4,2% - 50,7% - 45,1% - 10,74 Unweighted average 3 8,0% 9,8% 67,8% 66,7% 24,3% 23,6% 3,05 4 2,41 4 Unweighted average 10,4% 65,5% 24,0% 2,30 4 1 West German data only for 1989
2 Countries ranked according to the 1989 (first) and 1997 (second) underemployment / overemployment ratios 3 Countries included in 1989 analysis only
4 Based on unweighted averages
Source: Sousa-Poza & Henneberger (2000), p. 360 and Sousa-Poza & Henneberger (2002), p. 220-221, adapted
In Germany, the Netherlands and the United Kingdom the proportion of underemployed workers increased while the proportion of overemployed workers decreased. For Germany a distorting factor might be the inclusion of East Germany in the 1997 data. The proportion of overemployed workers increased in the United States, mostly at the expense of the proportion of satisfied workers. In Norway, the proportion of underemployed workers dropped from 26,1% to 11,6%, increasing the proportions of satisfied and overemployed workers. In fact, Norway went from relatively underemployed in 1989 to relatively overemployed in 1997.
A large proportion of Portuguese workers was underemployed in 1997 (45%), and the same goes for Italian, American and Spanish workers. These countries combine high proportions of underemployed workers with low proportions of overemployed workers. The Scandinavian countries show a different picture in 1997, with Denmark and Norway being relatively overemployed while in Sweden the proportion of underemployed workers is almost equal to the proportions of overemployed workers.
Sousa-Poza & Henneberger (2000, 2002) come up with three general conclusions in both studies. First, there are substantial differences between countries, especially in the
proportion of underemployed workers. Second, the majority of the workers do not experience working hours constraints. And third, the proportion of underemployment is larger than the proportion of overemployment. A fourth conclusion might be added based on a longitudinal comparison of the unweighted averages. Despite the cross-national differences a subtle overall trend of increasing overemployment and decreasing underemployment appears.
Wielers & Van der Meer (2006a) have analysed the proportions of under- and overemployment based on data from 2004. Their findings are reported in table 2.3. On average, the proportions of over- and underemployment are quite well balanced. Some 45% of all workers don’t feel constrained at all. Individual countries, however, do differ a lot on proportions of over- and underemployment. In Spain, Germany, Sweden, the Netherlands, Finland and Denmark more than a quarter of all workers feel overemployed, whereas in Portugal, Norway, Belgium, Germany, the United Kingdom and the Netherlands more than a quarter (also) feel underemployed. In Spain and Sweden, overemployment clearly dominates while in Portugal, Norway and Belgium underemployment clearly dominates. The remaining 5 countries show signs of underemployment as well, but the ratios are still reasonably close to 1.
Table 2.3 Proportions of under- and overemployment (3)
Country Overemployed Unconstrained 1 Underemployed Ratio (underemployed /
overemployed) 2 Spain 33,8% 47,5% 18,7% 0,55 Sweden 30,0% 53,2% 16,8% 0,56 Finland 28,2% 47,9% 23,9% 0,85 Netherlands 29,4% 45,2% 25,4% 0,86 Germany 33,7% 36,8% 29,5% 0,88 Denmark 27,5% 48,1% 24,4% 0,89 United Kingdom 30,7% 39,8% 29,5% 0,96 Belgium 22,8% 42,5% 34,7% 1,52 Norway 16,4% 43,7% 39,9% 2,43 Portugal 10,7% 47,6% 41,7% 3,90 Unweighted average 26,3% 45,2% 28,5% 1,08 3
1 calculated; based on columns 2 and 4
2 Countries ranked according to the underemployment / overemployment ratio 3 Based on unweighted averages
Wielers & Van der Meer conclude that substantial differences exist between countries. They also conclude that cross-national differences in underemployment are larger than differences in overemployment. Their second conclusions does not apply to this analysis, however. The four countries that have the highest proportions of underemployment, Poland (79,6%), Czech Republic (59,2%), Slovakia (60,4%) and Hungary (50,9%), were excluded from this analysis because they were not included in enough other studies. Unfortunately, Bielenski, Bosch & Wagner (2002) do not present their data (from 1998) in the same way the other authors did. They listed the actual and preferred weekly working hours, as shown in table 2.4. This makes their data more difficult to compare with the other data presented, but does bring an additional dimension to the analysis.
Table 2.4 Actual and preferred weekly working hours
Country Actual working hours Preferred working hours Working hours
constraints (preferred / actual) Ratio 1
Finland 39,1 34,2 -4,9 0,87 United Kingdom 37,3 32,9 -4,4 0,88 Norway 36,7 32,6 -4,1 0,89 Denmark 36,4 32,4 -4,0 0,89 Germany 37,5 33,7 -3,8 0,90 France 38,0 34,3 -3,7 0,90 Sweden 38,1 34,4 -3,7 0,90 Belgium 37,5 34,3 -3,2 0,91 Portugal 39,7 36,4 -3,3 0,92 Spain 39,3 36,1 -3,2 0,92 Italy 37,4 34,4 -3,0 0,92 Netherlands 33,7 31,5 -2,2 0,93 Unweighted average 37,6 33,9 -3,6 0,90
1 Countries ranked according to the preferred hours / actual hours ratio
Source: Bielenski, Bosch & Wagner (2002), p. 44, adapted
Strikingly, according to Bielenski, Bosch & Wagner the actual working times exceed the preferred working times in all countries. On average, the workers in the European countries mentioned prefer to work 3,6 hours per week less, which would come down to a decrease in weekly working hours of 10%. The relative decrease is largest in Finland, the United Kingdom, Norway and Denmark, while it is smallest in the Netherlands, Portugal, Spain and Italy. In the Netherlands the actual working week and the preferred working week are both the shortest of all countries, whereas they are both the longest in Portugal.
Apart from the apparent dominance of overemployment in European countries and the preferred decrease of working hours by about 10%, an important observation is that the actual weekly working hours differ more between countries than do the preferred weekly working hours.
The exact wording of the question regarding preferred working hours deserves some attention, however. As was said in OECD (1998), such questions are very sensitive to the precise wording. While most questions stress the assumption of equal hourly wage, the question used in the Employment Options of the Future Survey is a lot less clear. It is defined as follows:
“Provided that you (and your partner) could make a free choice so far as working hours are
concerned and taking into account the need to earn your living: How many hours per week would you prefer to work at present?”
(Bielenski, Bosch & Wagner, 2002, p. 138)
This somewhat vague question might have resulted in an underestimate of preferred working hours and an overestimate of working hours constraints.
2.2.2 Conclusion Cross-National Comparison of Working Hours Constraints The data presented above do not provide a consistent picture of working hours constraints in Europe. Thus, answering the first sub question, countries do seem to differ regarding working hours constraints. Underemployment is most common according to three sources, two of which were tightly related (OECD and twice Sousa-Poza & Henneberger). Data from Wielers & Van der Meer show that in some countries underemployment predominates while in other countries overemployment predominates. Bielenski, Bosch & Wagner provide data showing overemployment all across Europe. Their data should be interpreted with caution, however, due to the wording of the question regarding preferred working hours they use.
Longitudinal data (OECD and Sousa-Poza & Henneberger) suggest underemployment has decreased and overemployment has increased between the second half of the 1980’s and the middle of the 1990’s. However, some countries have remained mainly underemployed.
In most studies, Portugal be can considered quite heavily underemployed, and the same goes for Italy. Spain seems underemployed as well, but according to Wielers & Van der Meer Spain should be considered as largely overemployed. Belgium and France seem moderately underemployed. The United Kingdom appears to be somewhat heavier underemployed, but the data by Wielers & Van der Meer indicate the proportions of under- and overemployment are about equal. All data suggest that in the United Kingdom underemployment is rapidly decreasing in favour of overemployment.
Denmark and Sweden seem on average overemployed, as well as the Netherlands. However, data by Sousa-Poza and Henneberger suggest underemployment is most common in the Netherlands. Finland seems also overemployed, but is included in only two studies, one of them being the study by Bielenski, Bosch & Wagner.
For Norway, the data are inconclusive. Data from 1989 and 2004 indicate underemployment whereas data from 1997 and 1998 indicate overemployment. Finally, the United States seem overemployed. However, the United States were only included in the studies by Sousa-Poza & Henneberger.
2.2.3 Explaining Cross-National Differences in Working Hours Constraints
The previous results clearly show cross-national differences in the extent to which workers experience working hours constraints. The next step is to try to explain these differences by means of the selected literature. The sub question that will be answered is: “How can the differences in working hours constraints between countries be explained?”
Wielers & Van der Meer (2006a) used a logistic multi-level analysis in order to combine data of individual respondents with country specific data. As people get older, they have a higher chance of being underemployed while they simultaneously have a lower chance of being overemployed. As people are higher educated, they have a higher chance of being overemployed. Women have a higher chance of being overemployed, and people with children have both a higher chance of being overemployed and a lower chance of being underemployed. People with a managerial job have a higher chance of being underemployed. People employed in the commercial service sector have a higher chance of being underemployed and a higher change of being overemployed. The effect on underemployment is twice as large, however. Working part time was one of several variables that had no significant effect on either underemployment or overemployment. Subsequently, country effects were separately added to the model. The annual amount of working hours has a negative effect on the chance of being overemployed, and has a positive effect on the chance of being underemployed. An increase in the labour force participation results in a higher chance of being overemployed. In countries where the labour force participation of women has increased, the chance of being overemployed increases and the chance of being underemployed decreases. The change in women’s labour force participation is the single most influential factor. In countries with a high gross domestic product (GDP) per capita the chance of being underemployed is smaller. As the share of the commercial service sector increases, the chance of being overemployed increases and the chance of being underemployed decreases. As the share of the public service industry increases, the chance of being underemployed decreases. Finally, as the share of part time work increases, the chance of being overemployed increases and the chance of being underemployed decreases. The share of part time work is the most influential country effect mentioned. Income inequality and the use of child care do not appear to influence under- and overemployment. When all country effects are combined, however, the effects on overemployment disappear. The effects of the change in women’s labour force participation, the commercial and the public service sector on underemployment remain. The use of child care now has a negative relationship with the chance of being underemployed, the effect of which is about half that of the change in
women’s labour force participation on underemployment. The scores on the country effects are listed in table 2.5. The country effects will be illustrated by discussing the countries with the highest and lowest under- and overemployment (as reported in table 2.4). Highest and lowest scores on country effects are marked in boldface.
Table 2.5 Cross-national differences of country effects
Spa Swe Fin Net Ger Den UK Bel Nor Por Fra Av. 1
Constraints ratio 2 0,55 0,56 0,85 0,86 0,88 0,89 0,96 1,52 2,43 3,90 - 1,34
Part time work 11% 12% 9% 27% 21% 11% 29% 23% 19% 10% - 17% GDP per capita 3 98 117 112 124 109 122 116 118 154 72 109 114
Annual working hours 1.746 1.563 1.718 1.309 1.361 1.423 1.650 1.449 1.338 1.677 1.346 1.507
Labour force participation 68% 77% 75% 77% 72% 80% 75% 65% 79% 73% 69% 74% Income inequality 4 5 3 4 4 4 4 5 4 4 7 4 4
Commercial service industry 39% 37% 36% 41% 36% 37% 42% 38% 36% 32% 36% 37% Public service industry 19% 33% 28% 26% 24% 31% 27% 25% 33% 18% 26% 26% Women's LFP increase 5 17% -9% -6% 17% 4% 0% 4% 4% 5% 7% -1% 4%
Child care use 5% 50% 28% 12% 18% 44% 9% 10% 28% 22% 14% 22% Men's household participation 22% 38% 35% 29% 28% 34% 30% 28% 33% 16% 26% 29%
1 Unweighted average 2 Countries ranked according to table 2.4 (France was not included in table 2.4)
3 Index, 100 is European average
4 Income received by the top 20% of the population / income received by the lowest 20% of the population 5 LFP stands for Labour Force Participation
Source: Wielers & Van der Meer (2006a), p. 18, adapted
Table 2.5 shows a clear division of the countries into three groups. The first group consists of the four countries with the smallest constraints ratios, Spain, Sweden, Finland and the Netherlands. These countries score very high or very low on four (Finland) through eight (Spain) of the eleven country effects. The second group consists of the two countries with the highest constraints ratios (Norway and Portugal). Norway scores very high or very low on five out of eleven country effects and Portugal scores very high or very low on seven out of eleven country effects. The intermediate group consists of countries that score twice or less very high or very low on the country effects (Germany, Denmark, the United Kingdom and Belgium). This suggests there might be a relation between extreme scores on country effects and working hours constraints. The most remarkable observations will be discussed below.
In the Netherlands, overemployment is more common than underemployment. However, when looking at the country effect scores and the relations found by Wielers & Van der
Meer, a much lower constraints ratio might have been expected. The part time work rate (27%) and the increase in women’s labour force participation (17%) are both very high, and both indicate high overemployment and low underemployment. The annual amount of working hours (1.309) is the lowest of all countries and the proportion of the commercial service industry (41%) is very high. These scores are indications of high overemployment and low underemployment as well. Finally, the high gross domestic product (GDP) per capita (124) is a sign of low underemployment. Based on this information, the proportion of underemployment in the Netherlands (25%) is perhaps not as low as could be expected. Portugal has the highest constraints ratio of all countries. This is in accordance with the low part time work ratio (10%), the low GDP per capita (72) and the small relative size of both the commercial service industry (32%) and the public service industry (18%). These are all indications of high underemployment and/or low overemployment.
However, some countries defy the results found by Wielers & Van der Meer. Finland has a low constraints ratio (0,85), almost equal to that of the Netherlands. However, the low part time work ratio (9%) and the decrease of women’s labour force participation (-6%) are two very strong indicators of high underemployment and low overemployment, as is the high amount of annual working hours (1.718). Norway, on the other hand, has a high constraints ratio. The most important indicators of under- and overemployment, the part time work rate (19%) and women’s labour force participation increase (7%), are close to the unweighted average. The high GDP per capita (154), the low amount of annual working hours (1.338), the high labour force participation (79%) and the relatively large public service industry (33%) all point towards high overemployment and/or low underemployment.
Spain has the highest overemployment rate (33,8%) of all countries, but this is consistent only with the large increase of women’s labour force participation rate (17%). The remaining country effects on which Spain scores very high or very low suggest the opposite. Germany, despite having the second highest overemployment rate (33,7%), does not score very high or very low on any of the country effects.
Based on these observations, it can be concluded that the prevailing type of constraint more often than not differs from what could be expected based on the majority of country effect scores. Often, a country scores very high or very low on at least one of the most important determinants of working hours constraints that is in accordance with the prevailing type of constraint. The most important determinants are the part time work rate and women’s labour force participation increase.
In their article, Sousa-Poza & Henneberger (2000) analyse the influence of work conditions and work attitudes on working hours constraints. They find that men are more likely to be underemployed, that marriage increases the likelihood of being overemployed and that the likelihood of overemployment increases with age. The country scores on the work attitudes and work conditions that have a significant effect ( = 0,05) on working hours constraints are listed in table 2.6. Workers who find job security, high income or advancement opportunities important, are more likely to be underemployed. Workers who find a job that leaves enough leisure time and a job that is interesting important, are more likely to be overemployed. Regarding working conditions, Sousa-Poza & Henneberger found workers who have a secure job, a high income, exhausting work or freedom to plan daily work are more likely to be overemployed. Workers with a job that leaves much time for leisure, that has flexible hours or that is unhealthy, are more likely to be underemployed.
The work condition regarding leisure time is the most important determinant of working hours constraints, followed by the work attitudes regarding leisure time and having an interesting job (equally important). The work condition and the work attitude regarding a high income are ranked fourth and fifth respectively among the most important determinants. Remarkably, the effect of working attitudes is in most cases the opposite of the effect of the matching working conditions.
Below, an attempt will be made to explain cross-national differences in under- and overemployment (see table 2.3) by cross-national differences in work attitudes and conditions. Like in table 2.5, the highest and lowest scores are marked in boldface.
Table 2.6 Cross-national differences of work attitudes and work conditions
Germany West Netherlands Kingdom United Norway Italy United States Av.
1 Constraints ratio 2 1,40 1,48 2,99 3,43 5,12 7,90 3,72 Work attitudes 3 Job security 96% 84% 96% 96% 96% 93% 94% High income 87% 64% 81% 73% 84% 82% 79% Advancement opportunities 74% 80% 81% 57% 79% 92% 77% Leisure time 76% 49% 49% 35% 70% 34% 52% Interesting 94% 92% 95% 97% 95% 93% 94% Work conditions 4 Job security 78% 68% 59% 55% 76% 71% 68% High income 27% 16% 16% 17% 26% 23% 21% Leisure time 33% 35% 25% 26% 46% 24% 32% Flexible hours 21% 38% 32% 33% 36% 41% 34% Exhausting work 28% 17% 42% 33% 36% 35% 32% Unhealthy work 10% 9% 9% 8% 9% 8% 9%
Plan daily work 63% 76% 75% 68% 77% 74% 72%
Working hours 38 37 38 33 38 42 37,7
1 Unweighted average
2 Countries ranked according to table 2.2
3 Percentage of workers indicating the respective working condition is important to them 4 Percentage of workers indicating the respective working condition applies to their work
Source: Sousa-Poza & Henneberger (2000), p. 359, adapted
West Germany has the lowest constraints ratio. Having a job that leaves much leisure time is important to 76% of the German workers. German workers also score highest on having a secure job (78%) and having a high income (27%). They score lowest on having flexible working hours (21%). These are indications of high overemployment (or low underemployment). A high proportion of German workers thinks having a high income (87%) and having job security (96%) is important. A relatively high proportion of workers indicates having unhealthy work (10%) and a low proportion says they are able to plan their daily work (63%). These are four indications of high underemployment. This data therefore does not appear to provide clear evidence for the low constraints ratio of West Germany.
The United States has by far the largest constraints ratio. A small proportion of workers indicate that having a job that leaves much leisure time is important (34%), while large proportions of workers say that advancement opportunities are important (92%) and that they have flexible working hours (41%). These indications are in line with the high proportion of underemployment in the United States. However, small proportions of workers indicate that they have a job that leaves much time for leisure (24%) or that they
have an unhealthy job (8%). Interestingly, US workers don’t think a job that leaves much time for leisure is important and (probably because of that) not many US workers have such a job. Astonishingly, according to Sousa-Poza & Henneberger these characteristics are oppositely related to working hours constraints. Thus, also in the case of the United States, the data do not show unambiguous support for the (in this case very high) constraints ratio.
When looking at the remaining countries (they are not discussed in detail), while focusing on the scores in boldface, the pattern found for West Germany and for the United States remains the same. Scores on work attitudes and work conditions do not show unanimous support for either over- or underemployment. Support seems to be almost equally divided between the two types of working hours constraints for all countries. A further remarkable observation is that on only two occasions a score for West Germany indicates overemployment while simultaneously the score for the United States indicates underemployment (work attitude regarding leisure time and work condition regarding flexible hours). Sousa-Poza & Henneberger also found strong country effects in their analysis. Only Italy did not differ significantly from the United States (reference category). Italy also happened to have the second highest constraints ratio. The analysis by Sousa-Poza & Henneberger thus could not explain all cross-country differences. The ambiguous results provided by table 2.6 support this conclusion. Cross-country differences were identified, but could not be explained.
In their subsequent article on working hours constraints, Sousa-Poza & Henneberger (2002) do not report the actual country scores on each of the variables they included. They come up with 3 general observations: men are more likely to be underemployed than women, income is an important determinant of working hours constraints (workers with a high income are more likely to be overemployed) and part time workers are often underemployed. After closer inspection of they data, 2 additional observations can be made. Age and education seem important determinants of working hours constraints in countries with high underemployment, in particular Norway and France. Further, as
Sousa-Poza & Henneberger also concluded, the significance of determinants varies between countries.
In OECD (1998), for only 1 possible determinant of working hours constraints, annual working hours, detailed information is given (see table 2.8). When comparing the absolute annual working hours with the data from table 2.2, a relation becomes visible.
Table 2.8 Cross-national differences of annual working hours
Den Net Ita Bel Fra Ger Spa UK Por Av. 1
Constraints ratio 1985 2 0,75 0,98 1,41 1,61 1,82 1,87 2,06 4,05 7,45 1,81
Constraints ratio 1994 0,48 0,83 1,38 1,20 1,33 1,59 2,92 1,94 1,66 1,31 Annual working hours 1985 1.586 1.654 1.710 1.643 1.696 1.674 1.684 1.871 1.664
Annual working hours 1994 1.568 1.447 1.682 1.603 1.670 1.590 1.741 1.683 1.847 1.648
Working hours ratio 3 0,99 0,87 0,98 0,98 0,98 0,95 1,00 0,99 0,97 1 Unweighted average, based on table 2.2
2 Countries ranked according to table 2.2
3 Annual working hours 1994 / Annual working hours 1985
Source: OECD (1998), p. 167, adapted
In Spain, the United Kingdom and Portugal, the constraints ratios were highest both in 1985 and 1994. Thus, in these countries underemployment dominates. In these countries workers also work the most working hours per year. For instance, in 1994 the constraints ratios of Spain, the United Kingdom and Portugal are 2,92, 1,94 and 1,66. In the same year, workers in these countries work respectively 1.741, 1.683 and 1.648 hours per year. Conversely, the constraints ratios are smallest in Denmark and the Netherlands. Danish and Dutch workers annually work relatively few hours. Annual working hours thus seem to be negatively related to overemployment and positively to underemployment. France and Germany have constraints ratios close to the averages. The annual amount of working hours worked by French and German workers is neither high nor low. An exception is Italy, where high annual working hours are combined with relatively low constraints ratios.
However, when looking from a longitudinal perspective, it appears this relation cannot explain changes in working hours constraints. For instance, in Portugal the constraints ratio has dropped between 1985 and 1994 from 7,45 to 1,66, due to an enormous increase
in overemployment and a accompanying decrease in underemployment. However, annual working hours have decreased by 30 hours. The same can be said for the United Kingdom. Even though the constraints ratio was divided in half (from 4,05 to 1,94), annual working hours remained virtually the same. In the Netherlands, where annual working hours dropped by a staggering 207 hours, the constraints ratio decreased from 0,98 to 0,83 between 1985 and 1994. In Denmark, the constraints ratio went down from 0,75 in 1985 to 0,48 in 1994. Annual working hours decreased by only 18 hours. Thus, in the countries that saw the largest relative decline in annual working hours, the decrease of the constraints ratios were limited, while in countries where annual working hours remained relatively unchanged, the constraints ratios dropped the most.
Summarizing, annual working hours seem to relate to working hours constraints in a specific way. Low annual working hours are related to overemployment and high annual working hours are related to underemployment. However, if a relation between changes in annual working hours over time and changes in working hours constraints over time were to be deduced from this data, it would be that minimal reductions in annual working hours are related to reduced underemployment and increased overemployment (and thus to lower constraints ratios).
Bielenski, Bosch and Wagner (2000) do not provide detailed information regarding the determinants in their working hours constraints analysis. However, Corral & Isusi (2003) have written a report concerning part time work in Europe, often referring to Bielenski, Bosch & Wagner. Because part time work is often included in working hours constraints literature, the possibility to combine cross-national working hours constraints data with cross-national part time work data was taken advantage of (shown in table 2.9). Note that Bielenski, Bosch & Wagner use data from 1998 while Corral & Isusi use data from 1992 and 2002.
Table 2.9 does not present a clear picture of a relationship between working hours constraints and part time work. Finland and the United Kingdom have the lowest constraints ratio, indicating that actual and preferred working hours differ the most (and
overemployment is thus largest) in these two countries. However, in neither country the part time work rate was particularly large or small in 1992 and 2002. The same goes for the part time work ratio, although the ratio is below average. Differences in involuntary part time work are very large. Of the Finnish part time workers, 32% would prefer to have a full time job. In the United Kingdom, only 8% of the part time workers would prefer a full time job.
Table 2.9 Cross-national differences of part time work
Fin UK Den Ger Fra Swe Bel Por Spa Ita Net Av. 1
Constraints ratio 2 0,87 0,88 0,89 0,90 0,90 0,90 0,91 0,92 0,92 0,92 0,93 0,90
Part time work 1992 10% 23% 23% 15% 13% 21% 13% 7% 6% 6% 35% 16% Part time work 2002 12% 25% 21% 21% 16% 21% 19% 11% 8% 9% 44% 19% Part time work ratio 1,19 1,09 0,90 1,43 1,24 1,04 1,53 1,57 1,33 1,56 1,26 1,29 Involuntary part time work 3 32% 8% 16% 12% 24% 22% 16% 18% 19% 31% 2% 18% 1 Unweighted average
2 Countries ranked according to table 2.4
3 Proportion of respondents with a part time job that prefer to work full time (data from 2002).
Sources: Corral & Isusi (2003), p. 3, 9, adapted & Bielenski, Bosch & Wagner (2000), p. 44, adapted
Of the countries with the largest constraints ratio (the least overemployed countries), three show low part time rates in 1992 and 2002: Portugal, Spain and Italy. In the Netherlands, part time work is most common. In Portugal and Italy, the part time work rate has increased by over 50%. In the Netherlands and Spain, the increase was close to the average. In Portugal and Spain, the proportion of involuntary part time work is about average (18% and 19% respectively), while it is very large in Italy (31%) and very small in the Netherlands (2%).
The Netherlands takes a particularly unique position. The part time work rate is in both 1992 and 2002 twice as large as the European average, and the proportion of involuntary part time work is minimal. When disregarding the Netherlands, some minor regularities turn up. Countries with high constraints ratios typically have below average part time rates and above averages increase in part time rates. The opposite goes to a certain extent for countries with low constraints ratios. Finland is clearly an exception, though. There
does not seem to be a relation between the proportion of involuntary part time work and the other variables.
2.2.4 Conclusion Explaining Cross-National Differences in Working Hours Constraints
Above, an attempt was made to answer the sub question “How can the differences in
working hours constraints between countries be explained?” However, it proved rather
difficult to do this based on existing cross-national literature. Each study apparently focused on a particular subset of determinants, making it hard to create a comprehensive picture of the relative influence of certain (groups of) determinants and the corresponding cross-national differences. An analysis of the results by Wielers & Van der Meer (2006a) led to the general conclusion that cross-national differences of working hours constraints appear to be related to extraordinary scores on the most important determinants of working hours constraints (part time work rate and women’s labour force participation increase). However, the analysis of the results by Sousa-Poza & Henneberger (2000) showed differences in work attitudes and work conditions could not explain all cross-national differences. In fact, based on work attitudes and work conditions, support for underemployment and overemployment seemed to be almost equally divided for all countries. One reason why the study by Wielers & Van der Meer performed better than the study by Sousa-Poza & Henneberger is probably that in the latter study national scores were based on individual respondents’ scores while in the first study existing macro indicators were used. The study by OECD (1998) led to the conclusion that in a cross-sectional analysis low annual working hours are related to overemployment and high annual working hours are related to underemployment. A longitudinal analysis, however, suggests that minimal reductions in annual working hours are related to reduced underemployment and increased overemployment. Finally, an analysis of the results found by Corral & Isusi (2003) suggests that countries in which underemployment predominates, part time rates are relatively low and increases in part time rates are relatively high.
It should thus be concluded that cross-national differences in working hours constraints cannot unequivocally be explained by analyzing existing cross-national literature. Evidence supporting certain conclusions almost always is accompanied by evidence against. The most important reason for this appears to be the lack of comprehensive analyses. All too often authors focus on a particular subset of determinants, neglecting the influence of others. Although this has led to important new insights, it does not appear to be suitable for the purpose of fully explaining cross-national differences of working hours constraints.
2.3 Extended Literature Review
The conclusion that existing literature often focuses on a particular subset of determinants of working hours constraints, leads to the question how many of such subsets can be identified. Bielenski, Bosch & Wagner (2002) provide a framework of six intertwined factors influencing employment rates and working hours: regulation of labour markets, the household situation, the household’s economic situation, work organisation, employment situation and individual characteristics. These six distinguished factors seem to be based on 4 key components: an individual component, a household component, a
work component and a macro component. These components can be used to analyse not
only actual and preferred working hours, but also working hours constraints (as Bielenski, Bosch & Wagner do as well). Figure 2.1 gives a graphical representation of the four components. Two aspects of these components seem important. First, some determinants of working hours constraints cannot be assigned to one component in particular. The components are overlapping. Second, in addition to the effect of a certain determinant on working hours constraints also the perception of that determinant might play an important role (e.g. Sousa-Poza & Henneberger, 2000; Moens, 2004).
Figure 2.1 The four components influencing working hours constraints
2.3.1 The four Components Influencing Working Hours Constraints
Some characteristics of the individual component are rather straightforward, and are included in most studies. These characteristics include gender, age and education. However, some characteristics are more difficult to measure, and thus hardly ever included in working hours constraints research. These are often more sophisticated, latent characteristics like value systems.
The household component consists of some characteristics that are more often than not included in working hours constraints research. These are for instance marital status, the presence of children and (to a lesser extent) the children’s age. Like the straightforward individual characteristics, these are relatively easy to measure in using a questionnaire. However, other important characteristics like the household’s financial situation and the division of household chores are often absent.
Among the characteristics related to the work component that are often included in working hours research, are income, working hours, level and sector of employment. Related to working hours is an indication whether someone is working full time or part time. Analysis of the work component often also includes questions regarding opinion, as opposed to analyses of the individual and the household component. Sousa-Poza and
Work Individual
Household
Henneberger (2000) explicitly differentiate between work conditions and work attitudes. Their dataset includes variables that describe job characteristics and variables that measure the importance of these job characteristics to the respondents. They show work conditions and work attitudes both have a significant effect on working hours constraints. Characteristics of interest include job satisfaction, job security, income, advancement opportunities, having an interesting job and having flexible working times.
The macro component consists of policy and regulation on the one hand and certain macro level developments on the other. Policy and regulation can be enforced by multiple institutions like governments or trade unions. Characteristics that are often included in working hours constraints research are for example the provision of child care and trade union coverage. A characteristic that might also be of importance (but rarely used in working hours constraints research) is regulation regarding flexible working times. In OECD (1998) an elaborate cross-national comparison of government policies on working time is included. Macro level developments are of economic and demographic nature. Well known characteristics are, for example, the (female) employment rate, the unemployment rate, the relative size of sectors of industry, income inequality, annual working hours, economic prosperity and the share of (involuntary) part time work.
An extensive analysis of working hours constraints should include important determinants from all four components. Sousa-Poza & Henneberger focus on the work component while including some individual and household characteristics as control variables. Bielenski, Bosch & Wagner pay more attention to household related characteristics (analyses not discussed because country averages were not reported) while also including a reasonable amount of work related variables. Wielers & Van der Meer used multilevel analysis to combine micro level data with macro level data. Unfortunately, they have included only some very basic and objective measures regarding the individual, household and work components. It should be noted, however, that including more variables into a particular statistical model will likely result in less significant relations, as Wielers & Van der Meer reported as well. Below, for the individual component, the household component and the work component some
determinants will be discussed. As a result, several hypotheses will be formulated. The macro component will not be discussed because it is not included in the final analyses. 2.3.2 The Individual Component
In most studies, gender is included as a control variable. Bielenski, Bosch & Wagner (2002) show men work longer hours than women. Also, they show men prefer to work longer hours than women. Jacobs & Gerson (2004) claim Dutch women have the shortest average working hours out of all countries they analysed. According to Sousa-Poza & Henneberger (2000; 2002), men are more likely to be underemployed than women. Wielers & Van der Meer (2006a) find similar results in their study. Women are more likely to be overemployed than men, although there seem to be no gender differences when considering underemployment. This might be a reflection of the traditional division of household tasks, but it is seemingly in contradiction with the increasing labour force participation of women.
Hypothesis 1: Women are more likely to be overemployed.
Age is also a frequently used control variable. Research results suggest the likelihood of
being overemployed increases with age (Wielers & Van der Meer, 2006a). However, Bielenski, Bosch & Wagner (2002) argue that the relation between working hours and age takes the shape of an inverted parabola. Young workers seem to gradually enter the labour market while older workers gradually retreat from the labour market. Workers work the longest hours when they are of middle age. Moens (2004) believes most ambitions, obligations and responsibilities concentrate between the age of 20 and 50, which makes this phase in life the busiest. As a result, subjective time pressure is likely to be at its peak. According to Böheim & Taylor (2003), who found similar results, overemployment peeks at the age of 50.
Education is a third variable that is often included in working hours analyses, although a
significant effect is not always confirmed. Jacobs & Gerson (2004) show education is positively related to working hours in a number of countries, including the United States and the Netherlands. The opposite seems to count for countries like Italy and Finland. Böheim & Taylor (2003) conclude academic success increases the chance of being overemployed and decreases the chance of being underemployed. Wielers & Van der Meer (2006a) find higher educated workers are more often overemployed. A commonly used argument is that higher educated workers are more likely to be overemployed because of increased autonomy and responsibility (e.g. Bielenski, Bosch & Wagner, 2002). Moens (2004) believes higher educated workers have broader interests and more diverse social networks. He found subjective time pressure among higher educated workers is not due to higher workload, but is caused by time allocation and coordination problems instead. Higher educated workers are involved with more (social) activities, and thus have less time available for each activity and switch more often between activities.
Hypothesis 3: Higher educated workers are more likely to be overemployed.
2.3.3 The Household Component
Marital status is one of the household related characteristics that is included most often in
working hours related research. Sousa-Poza & Henneberger (2000, 2002) and Böheim & Taylor (2003) show married workers are more likely to be overemployed. Bielenski, Bosch & Wagner (2002) find this relation only for women, while Wielers & Van der Meer (2006a) don’t find this relation at all.
Hypothesis 4: Married or cohabiting workers are more likely to be overemployed.
The presence of children in the household is also included often. Most authors impose age restrictions, assuming young children require more attention. Bielenski, Bosch & Wagner (2002) show workers with children work less than workers without children, although this relation was not found for Dutch workers. They also show women with children are more likely to be overemployed, which is also found by Böheim & Taylor
(2003). Wielers & Van der Meer (2006a) conclude that workers with children are more likely to be overemployed and less likely to be underemployed.
Hypothesis 5: Workers with young children are more likely to be overemployed.
The use of daycare facilities is hardly ever included in working hours constraints literature. Nevertheless, it is reasonable to assume that daycare facilities provide better opportunities for combining the raising of children with paid labour. This is also the line of thought put forward by Wielers & Van der Meer (2006a). However, workers (probably mainly women) with children who do not make use of childcare facilities while raising young children are likely to (temporarily) withdraw from the labour market altogether, thus self-selecting them out of the sample (Bielenski, Bosch & Wagner, 2002). In such cases the partners (usually male workers) are likely to compensate for the loss of income by increasing their working hours.
Hypothesis 6: Workers with young children who make use of daycare facilities are less likely to be overemployed.
2.3.4 The Work Component
Income is tightly related to working hours constraints. Sousa-Poza & Henneberger (2000;
2002) find that workers who indicate earning a ‘high’ income are more often overemployed than workers who do not believe they earn a high income. According to Wielers & Van der Meer (2006a), however, this is partially due to differences in working hours. Böheim & Taylor (2003) conclude from their research that overemployment is inversely related to the hourly wage rate, but they have not included a variable for (total) income.
Hypothesis 7: Workers with a high income are more likely to be overemployed.
Preferred working hours are strongly influenced by actual working hours. Sousa-Poza & Henneberger (2000; 2002) argue that the relation between actual working hours and working hours constraints is parabolic. Full time workers are overemployed more often
