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Unequal ChancesEthnic Minorities in Western Labour Markets$

Anthony F Heath and Sin Yi Cheung

Print publication date: 2007

Print ISBN-13: 9780197263860

Published to British Academy Scholarship Online: January 2012

DOI: 10.5871/bacad/9780197263860.001.0001

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Equal Opportunities or Social Closure in the Netherlands?

Equal Opportunities or Social Closure in the Netherlands?

Chapter:
(p.359) 9 Equal Opportunities or Social Closure in the Netherlands?
Source:
Unequal Chances
Author(s):

PAUL TESSER

JAAP DRONKERS

Publisher:
British Academy
DOI:10.5871/bacad/9780197263860.003.0009

Abstract and Keywords

There are four major ethnic-minority groups in the Netherlands: labour migrants from Turkey and Morocco, together with migrants from former Dutch colonies in the Caribbean, namely, Antilles and Surinam. Men from all four groups have lower labour-market participation and higher unemployment than the indigenous Dutch, and this holds for the second generation as well as for the first. First-generation Turkish and Moroccan women participate at considerably lower levels than indigenous women, whereas Surinamese and Antillean women participate at higher levels than their indigenous peers. Among second-generation women, however, these differences in participation have largely disappeared. The distribution of ethnic minorities across occupational classes also reveals a major change between generations. Overall, processes of social closure appear to continue to operate within Dutch society. Equal opportunities have not yet been achieved.

Keywords:   Netherlands, labour migrants, Turkey, Morocco, Antilles, Surinam, labour market, unemployment, social closure, equal opportunities

Summary.

There are four major ethnic minority groups in the Netherlands—labour migrants from Turkey and Morocco together with migrants from former Dutch colonies in the Caribbean, namely Antilles and Surinam. Men from all four groups have lower labour-market participation and higher unemployment than the indigenous Dutch, and this holds for the second generation as well as for the first. For women the patterns of participation and unemployment are more complex. While first generation Turkish and Moroccan women participate at considerably lower levels than indigenous women, Surinamese and Antillean women participate at higher levels than their indigenous peers. Among second-generation women, however, these differences in participation have largely disappeared. The distribution of ethnic minorities across occupational classes also reveals a major change between generations. The first-generation experience substantial disadvantages but the second generation, after controlling for level of education, age and economic fluctuations, have similar chances of being in a particular occupational class as the indigenous Dutch population, with the exception of the salariat which remains more closed to ethnic minorities. This result holds for men as well as for women. Overall, processes of social closure appear to continue to operate within Dutch society. Equal opportunities have not yet been achieved.

(p.360) Introduction

NOTWITHSTANDING A LONG HISTORY OF IMMIGRATION, the Netherlands were considered to be an almost mono-ethnic society far into the twentieth century. Since 1960, however, the picture has changed dramatically. After the post-war economic reconstruction, severe shortages of labour triggered succeeding immigration waves consisting of labour migrants, their families and inhabitants of the former Dutch colonies. Now the Netherlands have a substantial ethnic minority population.

The immigrants themselves, coming from largely agricultural societies, have to deal with a Dutch society that has been changing from an industrial to a post-industrial society. Our chapter analyses the accommodation of the immigrants and their children to this society in change. Our main question is whether the immigrants participate in the same stratification processes that hold for the indigenous Dutch population. More specifically, can (and will) they find the meritocratic path to social attainment by means of education that has become characteristic for the Dutch population in the twentieth century? Or alternatively, has increased immigration resulted in a splitting of the social structure and the elicitation of social closure, increasing the likelihood of the formation of an ethnic underclass?

To explore these questions we study labour-market position, occupational attainment and income for the main groups of immigrant ethnic minorities in the Netherlands. By relating labour-market success to educational attainment we analyse their acquisition of positions within the social strata. Comparing relations between educational qualifications, occupational attainment and income of ethnic minority groups with those of the indigenous population we try to address our main question. First, however, before analysing educational and occupational attainment we give some background information about immigration and ethnic minorities in the Netherlands and about some relevant social and economic developments in the Netherlands during recent decades.

Post-war immigration in the Netherlands

As seen in Figure 9.1, recent Dutch history has seen succeeding waves of immigration. As this figure begins in the 1960s, we skip the return in the early 1950s of around 300,000 Dutch nationals following the independence of the former Dutch colony of the East Indies (now Indonesia). Surprisingly these returning colonials were absorbed into the population (p.361) in a short time. Although most of them had been living in the East Indies for several generations, their reintegration in a Dutch society that was recovering from the damaging effects of the Second World War was rather unproblematic.

The first wave of the more recent immigration started at the end of the 1950s. The post-war reconstruction of Dutch industry was finished and the domestic labour supply was insufficient for further expansion. The industries attracted semi-skilled and skilled workers from Spain, Italy, and Greece. Most of them settled only temporarily. Those who stayed, however, mixed with the Dutch population; about half of the men married Dutch wives. Their children have almost completely integrated in Dutch society. As a group they are by now, in fact, invisible.

The second wave of immigration soon followed in the early and mid 1960s. It consisted of unskilled, low-educated Turkish workers who were employed in semi-or unskilled jobs in the industrial sector. Most of them were recruited from the Turkish countryside. After the Turks, the Moroccans came. Their level of education was even more rudimentary. In addition to deliberate recruitment, many Turks and Moroccans also came on their own. The first of these newcomers returned after some years to their home countries. Those who came later did not return but gave rise to extensive family migration of close and far family members.

Equal Opportunities or Social Closure in the Netherlands?

Figure 9.1. Immigration into the Netherlands, 1960–1997.

Source: Statistics Netherlands 〈http://www.cbs.nl/〉.

(p.362) It should be noted that the economic circumstances that gave rise to this second wave of immigration were different from those of the first wave. In the second-half of the 1960s Dutch industry had already passed its post-war peak levels of expansion. Nevertheless it had to cope with a shortage of labour at the unskilled level. The shortage was mainly a consequence of the rapid expansion of the service sector in the Dutch economy. Jobs in the service sector were more attractive to the young and better-educated Dutch entrants to the labour market than the ‘dirtier’ work of the industrial sector. The expansion of education and subsequent rising levels of education amongst Dutch youth reinforced this process; thus low-level jobs were left to the immigrants.

The next wave of immigration came from the former West Indian colonies: Suriname and the Antillean Islands, both situated in the Caribbean. In 1975, Suriname obtained independence, but the Antillean Islands are still an autonomous part of the Kingdom of the Netherlands. Suriname was, and still is, a very unstable society. So, in the years surrounding independence a large part of the Surinamese population decided to leave the country and to settle in the Netherlands. From 1974 to 1980 more than a 100,000 Surinamese moved from the Caribbean coasts to the coasts of the North Sea.

After the so-called ‘oil crisis’ of 1973 the Dutch economy deteriorated. Signs of social tension between the Dutch native population and the immigrants began to appear, accompanied by a decay of the inner-city neighbourhoods where many immigrants lived in very poor housing conditions. In response, the Dutch government tried to stop immigration and no longer allowed cheap labour migration from Turkey and Morocco. In 1980 the immigration of Surinamese people was also restricted. There are now also restrictions on cheap labour migration from the new East European members of the European Union. However, immigration figures began to rise again in the second-half of the 1980s as the economy recovered from the crisis.

More generally, in the long run the amount of immigration is mostly determined by four factors: (1) an autonomous growth trend reflecting the growth of communication and international trade; (2) the demand for labour in the immigrant country; (3) the high demand for marriage partners from migrant countries; and (4) incidental events (e.g., calamities, changed entrance regulations).

In 1973 the Dutch government introduced a ban on low-level labour migration from outside the EU, but settled immigrants still had a rather extended right of family reunification and this kept immigration levels (p.363) relatively high. But what restrictive measures could not achieve, the economy and family could. The economic crisis of 1980 reduced the labour immigration surplus almost to zero, but the immigration caused by marriages of settled migrants with partners from their homeland continued to grow. Marrying partners from the homeland not only by first-generation migrants, but also by the second generation, became one of the major causes of continuing immigration, regardless of fluctuations in the demand for cheap labour by the Dutch economy. Since the mid-1990s, however, these extended rights of family reunification have become more restricted, and currently, there are proposals from governmental parties to restrict these rights further.

At the end of the 1980s the picture of immigration changed into a new and different wave of migration. Political instability, large differences in economic development and the almost complete closure of the borders for (legal) cheap labour migration from lesser developed countries caused a sharp increase in the influx of refugees and asylum seekers. In the 1990s, the average number of refugees and asylum seekers was about 40,000 people each year. New laws aimed at hindering this inflow of asylum seekers appear to have been rather successful, although it is debatable whether it was these new laws or the changing circumstances in the world that caused inflow to decline. Regardless, the Netherlands still have to solve the problem of those asylum seekers whose request to remain is denied but who do not (want to) leave the Netherlands.

Although reliable numbers are hard to come by, a non-trivial number of illegal migrants live and work in the Netherlands. Cheap and vulnerable illegal workers are important for some industrial and agrarian sectors of the Dutch economy, and also for domestic work in the more affluent Dutch households. The majority of these illegal migrants have entered the Netherlands legally—e.g., as tourists—and some try, with some success, to convert their illegal status into a legal one, for example through marriage, a general pardon or fraud.

As seen in Figure 9.2, these different waves of immigration have increased the number of ethnic minorities in Dutch society considerably. In 1970 the ethnic minority population counted slightly more than 200,000 people; it has since grown to surpass 1.5 million, or about 10% of the total population of 15 million, with further growth still forecast.

Most Surinamese and Antillean immigrants are Dutch citizens, due to the colonial past of the former and continuing colonial status of the latter. It is possible for citizens of non-EU countries to be naturalised as Dutch citizens after three to five years of legal residence, provided they (p.364) are sufficiently integrated into Dutch society, have some command of the Dutch language and sufficient economic resources. The law allows the retention of another citizenship, in addition to the Dutch, which explains the relatively large numbers of naturalized Turks and Moroccans. Recently, however, this has been changed, and now the combination of a Dutch citizenship with another is only allowed for asylum seekers, partners of Dutch citizens and for those foreign citizens who cannot relinquish their other citizenship (for instance, Moroccans).

Equal Opportunities or Social Closure in the Netherlands?

Figure 9.2. Population growth of the main categories of ethnic minorities, 1971–2015.

Source: Statistics Netherlands 〈http://www.cbs.nl/〉.

Anti-discrimination legislation exists in the Netherlands, with both racial and sexual discrimination addressed even in the first article of the constitution, but the balance of this legislation with other rights—such as the freedom of religion and freedom of school choice—has still to be found and is sometimes contested. In general, though, ethnic minorities have more or less the same rights as the various indigenous religious groups receiving state grants for their organisations and schools (for example, Islamic schools).

Integration of immigrants into the labour market

This chapter could certainly discuss immigration and the demography of ethnic minorities in much more detail, but our interest is largely concerned (p.365) with the integration of the immigrants into the Dutch social structure. Just as in most other western countries, in the second-half of the twentieth century the Dutch economy transformed from an industrial to a post-industrial economy. In 1965 the labour volume of the industrial sector reached its top level of nearly 1.9 million labour-years (De Beer 2001). Since then it has declined, to less than 1.4 million in 1990. While in 1965 the service sector was nearly as large as the industrial sector, from that year on the service sector has progressively outgrown the industrial sector. In 1990 the labour-volume of the service sector was about three times greater than the labour-volume of the industrial sector.

As previously mentioned, the growth of the service sector drained the supply of labour for low-level industrial jobs, triggering the second postwar immigration wave of Turkish and Moroccan workers. The low educational level of these groups was not much of problem up until about 1980. The economic crisis of 1980 was a turning point. The crisis meant the end of labour-intensive forms of industrial production, which had been prevalent in the foregoing decades. From then on only technology-driven forms of industrial production appeared to have a future in the service-dominated economy.

After the economic crisis of 1980 and the reconstruction of the economy in the years that followed, the labour-market position of immigrants drastically changed. The demanded level of qualification in the modernised industry was much higher than before the crisis, and also much higher than the qualifications that the Turkish and Moroccan workers could offer. They also lacked the qualifications demanded in the rapidly expanding service sector. Only a small part of the jobs in this sector—for example, in the cleaning services—remained open to them. As a consequence of this mismatch of supply and demand a considerable part of the minority workers lost their jobs and newcomers had little opportunity on the labour market.

In 1983, unemployment levels among Turkish and Moroccan men rose to one in three. Even this number, however, may have overestimated their true position on the labour market, as about half of those migrants over 40 were dependent on the National Insurance for disabled workers. However, these people are not counted in the unemployment figures.

Thanks to the reconstruction of the economy after 1983, unemployment in the native population declined quickly. As Figure 9.3 shows, in 1991 this rate was half the rate in 1983. During this same period, however, minority groups showed no improvement at all; this same pattern holds for the rest of the early 1990s.

(p.366)

Equal Opportunities or Social Closure in the Netherlands?

Figure 9.3. Unemployment, by ethnic group and year.

Source: Various labour surveys 〈http://www.cbs.nl/〉.

Only in recent years have ethnic minorities benefited from the ongoing expansion of the labour market. Since 1994, unemployment among minorities has decreased considerably by up to 15%. Notwithstanding this recent improvement, even in 1998 the risk of unemployment for members of ethnic minorities was between two and seven times larger than for the Dutch native labour force. In addition, recently there has been an increase in the public upheaval around ‘family reunion’ migration, asylum seekers, the religious values of some ethnic minorities, and Islamic schools within Dutch society. This upheaval has resulted in the rise of right-wing populist parties (with leaders like Pim Fortuyn) as coalition members in local and national government, as well as changes in the position of the established parties.

Theoretical framework

The description in the previous section of the position of immigrants in the Dutch labour market over the last several decades raises questions about the integration of the immigrants into the Dutch labour market and, more generally, their integration into the Dutch social structure. Why is it that unemployment among the native Dutch labour-market participants declined after 1983 while the labour-market position of the ethnic minorities apparently remained unchanged, at least until 1994? Is the position of ethnic minorities in the labour market governed by regularities (p.367) other than the position of the indigenous-market participants? Has there been a process of ethnic closure in the 1980s, eventually leading to the formation of an ethnic underclass? If so, what accounts for the drop in the unemployment figures for minority groups in 1998?

In the absence of valid and reliable data, these questions can only be answered in a speculative or ad hoc way. Now, however, data on the labour-market position of immigrant minority groups are available. In this chapter, we analyse these data against a theoretical framework combining theories of stratification, immigration and the labour market. In this section we concentrate on the theoretical framework and on the subject of our analyses.

From a more general point of view, the questions about the fate of ethnic minorities on the labour market refer to the factors that determine success on the labour market, occupational attainment and ultimately social stratification. Two competing theoretical perspectives are offered to explain social stratification: functionalist modernisation theory (Blau and Duncan 1967) and class conflict theory (Wright 1985).

Modernisation theory states that in modern societies the position of individuals in the social structure depends on the weight of their contribution to societal production and reproduction. From the perspective of modernisation theory, stratification in a modern society is fluid and open. Positions are acquired, not ascribed. What counts is achievement realised by the employment of human capital. As human capital is built up by individual investment in education, modernisation theory stresses the importance of levels of education for processes of stratification. Modernisation presupposes an open educational system without any entrance barriers. Modernisation theory does not allow for any independent influence of an ascribed distinctive category—like ethnicity—on social attainment.

According to class conflict theory, however, it is precisely these distinctive ascribed features that could be the crystallisation points for social inclusion or exclusion. Ideas about these processes of inclusion and exclusion carry back to Max Weber (Parkin 1974; Murphy 1988) who stated that the correspondence of arbitrary features can bring individuals together in communities, through which mutual interests can develop. Power and property give status to these interest groups and provide them with ‘class’ characteristics.

Classes include some individuals, but exclude others. When competition for resources is sharpened, social closures may result in the marginalisation of individuals with specific characteristics, for example blacks or other ethnic groups or the low educated. Wilson (1987) offers a straightforward (p.368) application of the idea of social closure in his analysis of the change in the position of the black population within the inner cities of the US in the early 1980s. According to Wilson, the transformation of the old industries in the northern cities of the US in the beginning of the 1980s moved employment out of the city centres. This diminished the demand for low-skilled workers, thereby driving the black workers into long-term unemployment and in that way fostered the development of a black ‘ghetto’ underclass.

Since its introduction in the US, the concept of the ‘underclass’ has been distorted to the point of becoming synonymous with criminal, marginalised and asocial individuals who reject mainstream American values (Gans 1990, Jencks 1992). Jencks argues that the concept of an underclass suggests more homogeneity among individuals than can be found in social reality. Not all blacks, of course, are unemployed inner-city school dropouts.

Criticism of the concept of the underclass, however, does not imply that the concept of social closure is of no use in the analysis of the social position of ethnic minorities. Indeed, Figure 9.3 suggests that, at least within the labour market, a form of social closure against ethnic minorities could be at work. Social closure against immigrant ethnic groups on the labour market implies ‘independent’ effects of ethnicity on labour-market success and social position, ‘independent’ in this sense meaning independent of achieved productive characteristics, especially level of education.

Here then we have two theoretical perspectives for analysing the position of immigrant ethnic groups on the labour market, leading to different expectations about the effects of minority membership on labour-market activity. According to modernisation theory, we should expect no ethnic minority effects on labour-market position, occupational attainment or income after controlling for levels of human capital. Class theory, on the other hand, would predict such an effect as ethnic minorities run the risk of being driven into an underclass position, especially in times of growing competition on the labour market.

Assuming levels of human capital are solely indicated by levels of education, we might even expect a positive effect of membership of an ethnic minority group, due to unmeasured effects of factors associated with migration, for example higher initiative, achievement orientation or open mindedness.

The two perspectives, although providing for specific expectations about the effects of minority membership, are too general to analyse the (p.369) development of labour-market position over time. Their main shortcoming is that the dynamics of immigration, the labour market and social security schemas are not sufficiently taken into account.

The ethnic minority groups that are the subject of this study are also immigrant groups. The incorporation of immigrants into a society has its own regularities, some of which are relevant to understanding the social position of ethnic minorities. This holds especially for the development of ethnic and immigrant characteristics over generations. In most cases first-generation immigrants tend to conserve and stress their ethnic characteristics. They will do this even more so when there are movements toward closure in the surrounding society. Members of the second generation, on the contrary, are brought up in the immigration country, receive their education in the new country and come in close contact with their indigenous peers. Thus, if segregation is not too severe, they will likely lose at least a part of the ethnic characteristics which were distinctive for their parents.

This dynamic property of migration will have consequences especially when viewed from the perspective of social closure. It could be expected that the second generation, since exhibiting fewer of the ethnic characteristics of their parents, would be less affected by social closure; thus we might predict ethnic minority membership to have a smaller effect on the position of the second generation than on the first generation.

From the viewpoint of modernisation theory, differences in labour-market position between the first and second generation are expected as well, but these differences will be ascribed to an ameliorating effect of the human capital attained by the second generation, due to their education in the immigrant country.

The second missing link is the dynamics of the labour market. Positions of individuals on the labour market can be viewed as a result of decision processes on the part of the suppliers of labour. To begin with, there is the decision to participate or not to participate. Next there is the decision to invest in skill development, thereby postponing entrance onto the market. Other decisions pertain to the actions of the unemployed or the amount of effort exerted to obtain promotion. In these decisions economic fluctuations can play a decisive role. Although choice is relevant for labour–market participation as well as for unemployment, it is perhaps more relevant in the former case than in the latter (since unemployment will depend on the choices made by other actors such as potential employers).

Economic fluctuations will also influence the demand-side of the labour market. When there is a great supply of labour, there is room (p.370) for exclusion of job seekers by means of (statistical) discrimination. Conversely, when supply is scarce, discrimination involves a risk for the demanders.

The third missing link is the dynamics of social security arrangements. A generous social security schema can help migrants to overcome economic hardship arising from the migration processes by offering economic benefits, and thus may promote integration into Dutch society. But the same social security arrangements might also create ethnic niches for the migrants, discouraging contact with the indigenous surroundings (either in-or outside the labour market) and thus may hinder integration into Dutch society.

The theoretical ideas presented in this section point to different patterns of influence on the position of ethnic minorities in relation to the labour market. To study these patterns we analyse relations between aspects of labour-market position and income as dependent variables and membership of minority groups, immigrant status, age, human capital and supply-and-demand fluctuations on the labour market as independent explanatory factors. One would also like to include the human capital of the parents of individuals in the analyses but unfortunately no data about this aspect are available. Gender differences also call for attention within our analysis, as from every relevant point of view gender plays a special role.

Data sources, variables and procedures

For the analyses of the labour-market position of ethnic minorities in the Netherlands, the Sociale Positie en Voorzieningengebruik van Allochtonen (Social Position and Facilities Use of Ethnic Minorities) (SPVA) data sets provide four surveys of samples of households from the four largest immigrant ethnic minority groups (Turks, Moroccans, Surinamese and Antilleans). SPVA surveys on these four immigrant groups have been conducted in 1988, 1991, 1994 and 1998.

Within these surveys, an individual is classified into a minority group if he or she was born in the respective country or if one of their parents was born there. Turkish and Moroccans whose parents had different countries of birth hardly exist. That is less true for Surinamese and Antillean parents, one of whom might not have been born in Suriname or Antilles; nonetheless a more restricted definition (e.g., both parents born in Suriname or Antilles) would misrepresent the mixed nature of these (p.371) ethnic groups due to the long standing colonial relations between Suriname, the Antilles and the Netherlands (longer than the British relationship with India). As a consequence, the racial composition of Antillean and Surinamese ethnic minorities is relatively heterogeneous, reflecting the mixed racial composition of these societies (African, Indonesian, Hindu, Jewish, White), although a majority do belong to ‘visible minorities’ of various skin colours.

As the SPVA surveys cover four different ethnic groups and a sample of the indigenous population, a total of five ethnic groups are compared within the analyses: Turks, Moroccans, Surinamese, Antilleans, and the native Dutch population. Each of the minority groups are also classed as first- and second-generation. As a consequence of the Dutch migration history, however, there are many more first-generation minorities than second-generation amongst 18–59 year-olds. Moreover, as the members of the second generation are much younger, they have less labour-market experience. Additionally, they are concentrated in the 1994 and (especially) the 1998 surveys.

The analyses in this chapter utilise independent and dependent variables as laid out in the Introduction of this volume. Education is the sole exception, with only four categories utilised: (1) primary; (2) lower secondary; (3) higher secondary; and (4) tertiary. Labour-market position is considered in terms of (1) participation; (2) unemployment; and (3) occupational class.

With regard to labour-market participation, as in other chapters, individuals are divided into two groups: those who are working or actively looking for a job vs. those that are not working and not looking for work. In the Netherlands, among people aged 18–59 the main reasons for non-participation in the labour market are housekeeping and occupational disability. For many social security, covering the loss of income by occupational disability, is a better option than unemployment benefits. Occupational disability is therefore preferred and widely used both by employees and employers as an attractive alternative to unemployment.

In terms of unemployment, participants are counted as unemployed if they are on the labour market and actively looking for work. In 1992, Dutch authorities changed all of the definitions of the labour-market statistics. For the sake of comparability in most cases categories of the older definitions have been used. This implies, for example, that the cutting point for ‘small jobs’ is set on nineteen hours a week; thus people who work less than nineteen hours are not counted as working. This definition of ‘working’ has consequences for the classification of unemployment (p.372) and labour-market participation, particularly as individuals looking for work for less than nineteen hours a week are not counted in the labour-market participation data.

Workers who work more than nineteen hours a week are classified according to their position in the occupational class structure—in these analyses, the five-class schema outlined in the Introduction. Income data in the SPVA are obtained by asking for net weekly or monthly income. Respondents could tell their exact income or could indicate it in categories. The categories have been recoded to their midpoints. Reported income includes not only income from work but also social security benefits (occupational disability; unemployment, etc.). As a consequence, persons without paid work could still report an income. Income is still measured in Dutch guilders (1 Euro=2.20 guilders), and is not corrected for inflation (since we already control for year of the survey). The natural log of income is used in our analyses.

These independent variables have been considered in this chapter through a two-step analysis. First, in the following section, a bivariate description of relations between the dependent variables and the explanatory factors are introduced. In the second section, various types of regression equations are employed to further elucidate the effects of minority membership on labour-market outcomes. Multivariate models are used to analyse effects of minority membership on labour-market position and income; a binary logistic regression is fitted in analyses of labour-market participation and unemployment; for the analysis of occupational class, a multinomial logistic model is estimated; and income is analysed via ordinary least squares (OLS) estimation.

Descriptive analyses

From previous sections it can be expected that there are large differences in labour-market characteristics related to ethnic minority group membership. The theoretical framework discussed above points to possible differences related to level of education, immigration status (first vs. second generation), year and gender.

Tables 9.19.3 present the basic bivariate information showing the education, economic activity and occupation of the different ethnic groups. We discuss each one in turn. When considering these descriptive tables, it should be kept in mind that the total sample is not representative of the total population of the Netherlands. Because of the sampling (p.373) design discussed above, the four minority groups are over represented by a factor of approximately thirteen.

Table 9.1A. Highest educational qualification, by ancestry and generation: Men (row percentages).

 

Primary or none

Lower secondary

Higher secondary

Tertiary

N

Indigenous Dutch

23.4

24.9

25.9

25.8

2,915

First-generation

 

 

 

 

 

     Turkish

67.1

18.0

11.6

3.3

4,093

     Moroccan

79.7

10.5

6.5

3.3

3,818

     Surinamese

38.3

34.1

17.2

10.4

2,393

     Antillean

35.5

31.4

20.5

12.6

1,432

Second-generation

 

 

 

 

 

     Turkish

40.7

31.0

22.9

5.4

297

     Moroccan

57.2

24.2

15.2

3.4

178

     Surinamese

35.6

27.4

25.6

11.4

457

     Antillean

28.8

17.0

31.3

22.9

288

Table 9.1B. Highest educational qualification, by ancestry and generation: Women (row percentages).

 

Primary or none

Lower secondary

Higher secondary

Tertiary

N

Indigenous Dutch

24.7

29.8

24.5

21.0

2,913

First-generation

 

 

 

 

 

     Turkish

81.3

9.9

7.6

1.2

3,428

     Moroccan

89.1

5.6

4.2

1.1

2,649

     Surinamese

41.4

30.9

18.4

9.3

2,925

     Antillean

42.0

32.0

18.0

8.0

1,782

Second-generation

 

 

 

 

 

     Turkish

49.9

28.2

17.2

4.7

383

     Moroccan

57.4

20.5

17.4

4.7

322

     Surinamese

34.3

28.6

27.3

9.8

605

     Antillean

34.1

22.9

26.8

16.2

414

We begin in Tables 9.1A and 9.1B with the highest education of the four ethnic groups compared with that of the indigenous Dutch population. In both generations we see that all four groups tend to have lower levels of education than the indigenous population, with the Turks and Moroccans heavily concentrated in the lowest educational level. This pattern is even more accentuated in the case of women. However, there is considerable progress between generations with the second generation of all four ethnic groups showing higher levels of education than the first, although still falling short of the indigenous population.

(p.374) Tables 9.2A and 9.2B then present distributions of economic activity for both men and women. The most important source of variation in labour-market participation is of course gender. With respect to labour-market participation gender interacts with ethnic minority status. Among men differences in participation reach a maximum of 23 percentage points between second-generation Moroccan and indigenous men. Among women differences are much larger, up to a 44 percentage point difference between first-generation Moroccan and Surinamese women. Labour-market participation juxtaposes Moroccan and Turkish women to the other groups. It should also be noted that among the women participation of Surinamese women is higher than the participation rate of indigenous women.

There is also an interaction between gender and immigration status. Among men there is a small difference in participation between the first and the second generation (with the latter participation 6 percentage points or more lower), in contrast to women where the second-generation participation rate for Turks and Moroccans tends to be considerably higher than in the first generation. The lower participation rate of the second-generation men can perhaps been explained by their relatively young age, with many of them still in full-time education.

Table 9.2A. Economic activity, by ancestry and generation: Men (row percentages).

 

Economically active

Inactive and other

N

Indigenous Dutch

83.7

16.3

2,915

First-generation

 

 

 

     Turkish

77.5

22.5

4,093

     Moroccan

70.6

29.4

3,818

     Surinamese

82.3

17.7

2,393

     Antillean

79.5

20.5

1,432

Second-generation

 

 

 

     Turkish

71.3

28.7

297

     Moroccan

60.9

39.1

178

     Surinamese

73.8

26.2

457

     Antillean

71.3

28.7

288

Table 9.2B. Economic activity, by ancestry and generation: Women (row percentages).

 

Economically active

Inactive and other

N

Indigenous Dutch

55.0

45.0

2,913

First-generation

 

 

 

     Turkish

31.0

69.0

3,428

     Moroccan

18.5

18.5

2,649

     Surinamese

62.4

37.6

2,925

     Antillean

56.7

43.3

1,782

Second-generation

 

 

 

     Turkish

52.1

47.9

383

     Moroccan

45.6

54.4

322

     Surinamese

59.6

40.4

605

     Antillean

61.3

38.7

414

(p.375) Tables 9.3A and 9.3B present the distributions of current occupation and unemployment by ancestry. Compared to employment participation, the figures on unemployment reveal much more pronounced differences associated with ethnic minority membership. Unemployment among minorities is much higher than among the indigenous labour-market participants, but there are also clear differences between the minority groups. The Moroccans and Turks are decisively in the most unfavourable position with both the first and second generations experiencing high levels of unemployment.

Table 9.3A. Current occupation, by ancestry and generation: Men (row percentages).

 

Salariat

Routine non-manual

Petty bourgeoisie

Manual supervisor/ skilled manual

Semi- and unskilled

Unemployed

N

Indigenous Dutch

38.3

16.0

5.7

14.3

17.4

8.3

2,413

First-generation

 

 

 

 

 

 

 

     Turkish

4.5

4.1

3.7

14.3

41.4

32.1

3,134

     Moroccan

5.6

5.2

2.7

11.0

40.4

35.2

2,654

     Surinamese

17.2

17.6

3.7

17.1

23.8

20.6

1,950

     Antillean

18.8

14.2

2.5

16.5

22.9

25.1

1,126

Second-generation

 

 

 

 

 

 

 

 Turkish

10.0

23.3

4.5

10.9

29.8

21.6

199

 Moroccan

8.4

15.9

4.2

11.7

30.6

29.1

103

 Surinamese

20.4

19.1

3.2

10.5

21.0

25.8

318

 Antillean

21.6

16.3

2.8

19.0

26.4

13.8

189

Table 9.3B. Current occupation, by ancestry and generation: Women (row percentages)

 

Salariat

Routine non-manual

Petty bourgeoisie

Manual supervisor/ skilled manual

Semi- and unskilled

Unemployed

N

Indigenous Dutch

30.6

38.6

3.6

3.1

8.9

15.2

1,602

First-generation

 

 

 

 

 

 

 

     Turkish

4.7

11.0

3.0

11.0

46.7

23.7

1,038

     Moroccan

4.4

16.2

1.4

2.3

21.1

54.6

476

     Surinamese

15.5

36.7

1.1

3.2

14.8

28.7

1,806

     Antillean

14.5

33.4

0.9

2.2

12.8

36.2

1,000

Second-generation

 

 

 

 

 

 

 

     Turkish

10.5

36.6

2.8

1.9

15.7

32.4

185

     Moroccan

5.0

32.7

3.8

1.2

16.4

40.8

130

     Surinamese

17.6

46.8

3.2

2.6

11.0

18.8

336

     Antillean

18.5

35.0

2.4

4.1

18.0

22.0

209

(p.376) The bivariate distributions of class and minority group membership also take the expected form. Turks and Moroccans are concentrated in the categories of the manual workers. Surinamese and Antilleans have an intermediate position in these categories, while they concentrate also in the routine non-manual class. The indigenous workers have their highest representation in the salariat class. Again the pattern of first vs. second generation deserves attention. In the second generation there appears to be a considerable movement of ethnic minorities out of the manual working classes into the non-manual classes (but not into the petty bourgeoisie).

Gender plays its own special role in the distribution of workers between occupational classes. In the indigenous population there is the well known over-representation of women in the nonmanual occupations. We can see the same pattern among all the second-generation groups, but first-generation Turkish and Moroccan women are under-represented in nonmanual work and instead are concentrated in semi-and unskilled work.

The bivariate distributions discussed so far do not fail to have their consequences for the distribution of income over ethnic minority groups, migrant generation and of course gender. Income differences are as expected. All four ethnic groups have income substantially lower than the indigenous Dutch, but with the Turks and Moroccans again falling some way behind the Surinamese and Antilleans. The lower mean incomes of the second generation could be a consequence of their younger ages and continued educational participation.

The bivariate distributions tell us a great deal about the position of members of ethnic minority groups in the Dutch labour market and occupational (p.377) structure. It is clear that their position is not nearly as strong as the position of the indigenous population. At the same time one can see that minority status is not a matter of all or nothing; Tables 9.1 through 9.3 show large differences between Turkish and Moroccan immigrants on one side, and Surinamese and Antillean immigrants on the other. Moreover there are differences associated with the immigrant generations suggesting that acculturation is a factor. The special role of gender is highlighted by the interactions with minority membership.

Table 9.4. Mean income, by ancestry and gender (Dutch Guilders).

 

Men

N

Women

N

Indigenous Dutch

2,507

2,372

1,713

1,817

First-generation

 

 

 

 

     Turkish

1,829

3,473

1,329

1,097

     Moroccan

1,724

3,145

1,344

556

     Surinamese

2,038

1,885

1,633

2,044

     Antillean

1,859

1,209

1,584

1,460

Second-generation

 

 

 

 

     Turkish

1,734

218

1,365

227

     Moroccan

1,419

127

1,284

160

     Surinamese

1,724

299

1,584

393

     Antillean

2,039

232

1,533

259

Being bivariate, the above tables do not give much of a clue about the meaning of the relations. Are minorities the targets of social closure or is it their lack of human capital that makes their position as unfavourable as the tables show? How can the differences between the ethnic groups be explained? What about the much better positions of the second generation? Is it their better education, are they more assimilated into Dutch culture, or do they exhibit fewer of the characteristics that trigger exclusion? What is the role of economic circumstances, in this case represented by the time factor? Are the answers to these questions the same for men and women? Only if we can answer these questions can we judge the validity of the theoretical perspectives we introduced earlier.

Models of labour-market position, occupational structure and income

The inconclusiveness of the descriptions above follows from the bivariate nature of analyses as presented. This bivariate analysis strategy does not allow us to determine the relative weight of the variables in explaining variance in the dependent variables. Another source of indeterminacy is caused by the covariation between the explanatory variables. Members of minority groups have lower levels of education than the indigenous population, so a bivariate analysis is inconclusive as to the effects of membership of minority groups. The same holds for immigrant status.

It is quite clear that the problem asks for a multivariate approach. Therefore a model of the variables under study is needed. The model should explain the position of individuals in the labour market, in the occupational class structure and in the income distribution. The model should be as parsimonious as possible, meaning that it should describe a maximum of variance in the dependent variables using a minimum of degrees of freedom. A model that includes all of the relevant variables best serves this objective.

(p.378) Unfortunately there are some obstacles for the analysis of all the relevant variables in one model. A first obstacle is in the different levels of measurement that hold for the dependent variables. Some of them, i.e. participation on the labour market and unemployment are dichotomous. Occupational class is a polytomous nominal variable, and income is continuous.

Another obstacle is the selective nature of some of the explanatory variables. Unemployment, for example, is only defined for individuals who participate on the labour market. Occupational class is only defined for workers. Migrant generation is only relevant for members of minority groups.

A third obstacle is the special role of gender in processes of stratification. The bivariate analysis already shows that gender interacts in many ways with the other explanatory variables, so inclusion of gender in a model consumes many degrees of freedom. Therefore it seems wiser to analyse separate models for men and women.

Considering the obstacles for the analysis of a joint model for all of the variables, we have chosen the less ambitious strategy of analysing separate models for the four dependent variables. Thus, we have estimated logistic models for labour-market participation and unemployment, a multinomial model for class position and a linear model for income.

Constructing dummy variables for ethnic group membership and generation solves the problem of the selective nature of the migrant generation variable. We also use dummy variables for ethnic group membership and age to take into account the possible different consequences of labour-market experience for migrant generations and the indigenous population. Dummy variables for ethnic group membership and year measure the changing relation between the migrants and the Dutch society. Throughout the indigenous population is taken as the reference category.

Labour-market participation

Table 9.5 summarises the results for labour-market participation of men and women separately. The models for these aspects are logistic regression models. In Model 1, participation is regressed on the combinations of ethnic group membership, level of education, age, age-square and year. Model 2 adds significant interaction terms for the combinations of migrant generation and education, migrant generation and age, and migrant generation and measurement year. The addition of these terms improves the fit of the model.

(p.379)

Table 9.5. Logistic regression of labour-market participation (parameter estimates; contrasts with non-participation).

 

Men

Women

 

Model 1

Model 2

Model 1

Model 2

Intercept

0.68

(0.10)

0.41

(0.12)

−0.07

(0.09)

−0.17

(0.10)

Ancestry

 

 

 

 

 

 

 

 

     Native Dutch

0.0

 

0.0

 

0.0

 

0.0

 

     Turkish 1

0.23

(0.07)

1.40

(0.12)

0.49

(0.06)

0.09

(0.12)

     Moroccan 1

0.42

(0.07)

0.58

(0.12)

1.18

(0.08)

0.43

(0.13)

     Surinamese 1

0.16

(0.08)

0.61

(0.15)

0.54

(0.06)

0.52

(0.06)

     Antillean 1

−0.13

(0.10)

0.04

(0.10)

0.28

(0.07)

0.25

(0.12)

     Turkish 2

0.28

(0.18)

0.68

(0.56)

−0.08

(0.13)

−0.04

(0.14)

     Moroccan 2

−0.28

(0.23)

−0.89

(0.65)

0.31

(0.15)

0.91

(0.36)

     Surinamese 2

−0.18

(0.16)

−0.62

(0.32)

0.13

(0.11)

0.09

(0.12)

     Antillean 2

0.61

(0.18)

0.18

(0.24)

0.18

(0.14)

0.22

(0.14)

Age/10

1.99

(0.08)

2.38

(0.09)

0.33

(0.07)

0.52

(0.08)

(Age/10)2

0.56

(0.02)

0.54

(0.02)

0.18

(0.02)

0.20

(0.02)

Education

 

 

 

 

 

 

 

 

     Primary

0.0

 

0.0

 

0.0

 

0.0

 

     Secondary lower

0.63

(0.06)

0.78

(0.08)

0.71

(0.05)

0.68

(0.06)

     Sec higher

0.17

(0.07)

0.63

(0.11)

1.12

(0.05)

1.09

(0.07)

     Tertiary

1.01

(0.11)

1.53

(0.16)

1.93

(0.09)

1.86

(0.09)

Year

 

 

 

 

 

 

 

 

     1988

0.58

(0.06)

0.56

(0.07)

0.84

(0.06)

0.95

(0.06)

     1991

0.29

(0.06)

0.29

(0.07)

0.51

(0.05)

0.58

(0.06)

     1994

0.70

(0.06)

0.69

(0.06)

0.54

(0.05)

0.59

(0.06)

     1998

0.0

 

0.0

 

0.0

 

0.0

 

Significant interactions

 

 

 

 

 

 

 

 

     Turkish 1 * education

 

 

0.46

(0.08)

 

 

 

     Moroccan 1 * education

 

 

0.35

(0.08)

 

0.27

(0.05)

     Surinamese 1 * education

 

 

0.20

(0.08)

 

 

 

     Antillean 1 * education

 

 

0.34

(0.10)

 

 

 

     Turkish 1 * age

 

 

0.90

(0.05)

 

0.24

(0.05)

     Turkish 1 * age

 

 

0.81

(0.36)

 

 

 

     Moroccan 1 * age

 

 

0.55

(0.05)

 

0.42

(0.08)

     Surinamese 1 * age

 

 

0.39

(0.06)

 

 

 

     Antillean 1 * age

 

 

 

 

 

0.31

(0.06)

     Turkish 1 * year

 

 

 

 

 

0.05

(0.01)

     Surinamese 2 * education

 

 

0.48

(0.18)

 

0.30

(0.13)

     Antillean 2 * education

 

 

0.67

(0.20)

 

 

 

     Turkish 2 * year

 

 

0.20

(0.07)

 

 

 

     Moroccan 2 * year

 

 

0.18

(0.09)

 

 

 

     Surinamese 2 * year

 

 

0.17

(0.05)

 

 

 

Chi-Square (D.F.)

 

1,866 (16)

2,232 (29)

3,424 (16)

3,581 (24)

N

 

14,623

14,623

13,973

13,973

Note: Standard errors are given in brackets; emboldened coefficients indicate significance at 0.05 level or higher.

(p.380) The first thing that meets the eye when looking at the estimations for labour-market participation certainly is the outspoken differences between the models for men and women. The model for men fits the data only partly. It describes no more than approximately 12–14% of the ‘variance’ in the chances for participation. However, despite the small R2, the estimates of the effects for men exhibit some definite patterns. First, in all cases but one (Antilleans) there are significant negative effects of first-generation ethnic group membership, while the effects of second-generation membership are not significant for all but one group (again, the Antilleans). Being a male member of a first-generation ethnic minority group reduces the labour-market participation to about 50% compared to that of the indigenous male population. However, this is only true if we do not take into account the smaller benefits of more than primary education for migrant men of the first generation. While more education boosts the odds for participation among all men, this is less true for the first (and partly the second) generation of males, given the negative interactions with education in Model 2. This does not mean that the better-educated migrant does not have more attractive prospects on the labour market than his lower-educated brother, but that his prospects are less bright than those of his equally educated indigenous neighbour. If we take this smaller yield of education for migrant males into account, the lower-educated migrants (especially the first generation Turks, Moroccans and Surinamese) have higher labour-market participation than equally low-educated indigenous men. The smaller yield of education for the higher-educated migrant generations indicates a certain degree of social exclusion from the Dutch labour market.

Age has a common effect on labour-market participation: the older one is, the higher the chances of being in the labour market. The age-square term also has its expected effect—beyond a certain age labour-market participation starts to decline due to occupational disability, long-term unemployment, early pension, etc. Interestingly, age has a weaker effect for Turks of both generations and for Moroccans and Surinamese as a mechanism for entering the labour market. This smaller yield of age for these migrant generations indicates also a certain degree of social exclusion from the Dutch labour market.

In the bivariate description we found hardly any difference in participation between the first and the second generation. Table 9.5 however reveals systematically smaller effects for men belonging to the second generation. Partly this can be explained by the inclusion of age into the equation, which takes account of the fact that a younger generation has yet to (p.381) find its way into the labour market after finishing education. Moreover, after taking into account the lower yield of education and age for the second generation, the second-generation Turks, Moroccans and Surinamese have significantly lower labour-market participation than the first generations. This lower yield of education and age is however partly compensated by the interactions with migrant generation and year: the significant interaction shows that during the 1990s the second-generation migrants (Turks, Moroccans and Surinamese) improved their labour-market participation. The lower labour-market participation of the young second generation reflects their situation at the end of the 1980s, but during the 1990s their situation in the labour market improved.

The pattern of the parameter estimates over the years clearly reflects the economic circumstances of the time. The mini recession of 1994 and the economic boom of 1998 have their impact on the rates of participation. As it is easier to enter the labour market in times of economic growth, during such a period social closure will be less strong. Thus in 1998 there was a sharp rise in the likelihood of participation.

The interaction of ethnic group membership with year is significant for the second generation only. This implies that economic fluctuation affected the second-generation minority members less than comparable indigenous men, and that the integration of the second generation into the labour market is increasing as they become a longer-established component of Dutch society.

For women the model performs better than for men, and in particular the explained variance is higher. Education is a stronger predictor of participation among women and there is less oscillation over time along the linear growth trend. However, the pattern of significant parameters for the combinations of minority group membership and generation is more complex and contradictory among women than among men.

First, the likelihood of participation in the labour market is considerably smaller for Moroccan women of the first generation and also (to a lesser extent) for Turkish women. Contrarily, the odds for Surinamese and Antillean first-generation women are higher than the odds for indigenous women. The result for the second-generation minority women is strikingly different. The labour-market participation of the second-generation Turkish, Surinamese and Antillean females does not differ significantly from that of the comparable indigenous women. Only the second-generation Moroccan women still participate less than comparable indigenous women, although their shortfall is far smaller than the first-generation Moroccan woman with the same age and educational level.

(p.382) Second, the impact of education is stronger for women than for men. Moreover, the yield of education for labour-market participation is larger for first-generation Moroccans and second-generation Surinamese than for comparable indigenous women, while for the analogous male migrants this age yield was smaller than for comparable indigenous men. Only the yield of education for Turkish first-generation women is significant smaller than that for indigenous women.

Thirdly, the age effects (both the linear and the squared) are also smaller for women than for men. This is not unexpected given the still dominant difference in roles for men and women as breadwinner and housewife. More interestingly, the age effect on labour-market participation is smaller for first-generation Turkish and Moroccans females, but is higher for first-generation Antillean women compared to analogous indigenous women. Lastly, over the years the only trend for women appears to be a growth of participation, a growth that was even larger for first-generation Turkish females.

The high participation of Surinamese and Antillean women deserves special attention. These levels may be due to instability of relations between men and women that characterises the Surinamese and Antillean communities in the Netherlands, no less than in their homelands. This instability may force the women of these groups not to rely on a husband or a male partner but to secure economic independence.

Unemployment

Labour-market participation can be conceived as the result of the active decisions of individuals. In unemployment, although one can expend more or less effort in looking for a job, an individual is much more the object of the decisions of others. Thus, when social closure of ethnic minorities is occurring, it should come to light in models of unemployment.

And indeed it does, as one can see in the Table 9.6. As in other chapters in this volume, we model the avoidance of unemployment and hence a negative parameter estimate indicates that the group in question has a greater risk of unemployment than the reference category of the native Dutch. With only two exceptions (second-generation Antillean males and Surinamese females) all combinations of minority membership and migrant generation result in considerably higher odds of unemployment than the indigenous population with the same age and educational level. This holds for men as well as for women, although the odds for men are worse. Lower levels of education or younger age structures (p.383) of minority groups clearly are not sufficient to explain their higher risks of unemployment.

Table 9.6. Logistic regression of employment (parameter estimates; contrasts with unemployment).

 

Men

Women

 

Model 1

Model 2

Model 1

Model 2

Intercept

1.37

(0.12)

1.07

(0.13)

0.69

(0.14)

0.63

(0.15)

Ancestry

 

 

 

 

 

 

 

 

     Native Dutch

0.0

 

0.0

 

0.0

 

0.0

 

     Turkish 1

1.33

(0.09)

0.85

(0.12)

1.09

(0.10)

0.64

(0.18)

     Moroccan 1

1.38

(0.09)

1.42

(0.10)

1.38

(0.13)

1.02

(0.20)

     Surinamese 1

1.02

(0.10)

1.37

(0.16)

0.72

(0.09)

0.75

(0.09)

     Antillean 1

1.26

(0.11)

1.24

(0.11)

1.04

(0.10)

0.55

(0.16)

     Turkish 2

0.82

(0.20)

0.72

(0.21)

0.56

(0.20)

0.56

(0.20)

     Moroccan 2

1.11

(0.26)

−0.65

(0.34)

0.90

(0.23)

0.91

(0.23)

     Surinamese 2

1.14

(0.16)

1.09

(0.16)

−0.23

(0.17)

−0.04

(0.20)

     Antillean 2

−0.41

(0.25)

−0.40

(0.25)

0.42

(0.20)

0.42

(0.20)

Age/10

0.88

(0.09)

0.99

(0.10)

0.60

(0.12)

0.72

(0.12)

(Age/10)2

0.19

(0.02)

0.21

(0.02)

0.12

(0.03)

0.14

(0.03)

Education

 

 

 

 

 

 

 

 

     Primary

0.0

 

0.0

 

0.0

 

0.0

 

     Secondary lower

0.62

(0.06)

0.78

(0.07)

0.56

(0.08)

0.63

(0.08)

     Secondary higher

0.69

(0.07)

0.96

(0.10)

1.11

(0.09)

1.24

(0.09)

     Tertiary

0.89

(0.10)

1.19

(0.12)

1.33

(0.11)

1.46

(0.12)

Year

 

 

 

 

 

 

 

 

     1988

0.25

(0.07)

0.27

(0.07)

0.44

(0.09)

0.73

(0.11)

     1991

0.32

(0.06)

0.33

(0.06)

0.39

(0.08)

0.60

(0.09)

     1994

0.60

(0.06)

0.61

(0.06)

0.52

(0.08)

0.64

(0.08)

     1998

0.0

 

0.0

 

0.0

 

0.0

 

Significant interactions

 

 

 

 

 

 

 

     Turkish 1 * education

 

0.32

(0.05)

 

 

0.26

(0.09)

     Moroccan 1 * education

 

0.23

(0.07)

 

 

 

 

     Turkish 1 * age

 

0.33

(0.05)

 

 

 

 

     Turkish 1 * age

 

 

 

 

 

0.18

(0.09)

     Moroccan 1 * age

 

 

 

 

 

0.27

(0.13)

     Surinamese 1 * age

 

0.23

(0.07)

 

 

 

 

     Turkish 1 * year

 

 

 

 

 

0.06

(0.02)

     Antillean 1 * year

 

 

 

 

 

0.09

(0.02)

     Moroccan 2 * education

 

1.03

(0.41)

 

 

 

 

     Surinamese 2 * education

 

 

 

 

 

0.41

(0.16)

Chi-Square (D.F.)

 

1,079 (16)

1,176 (21)

853 (16)

894(22)

N

 

11,543

11,543

6,344

6,344

The pattern of effects of migrant generation status is irregular. The lower unemployment rate for the second generation seen in Table 9.3 does not hold for all ethnic groups. The odds of unemployment for Moroccan and Surinamese men belonging to the second generation are only slightly less than for the first generation, once one controls for age and education. (p.384) Among the women however the odds of unemployment for the second generation are consistently lower than for the first generation.

Education has its normal effect on the chances of unemployment: the higher the education, the greater the chance of avoiding unemployment. This is true for both men and women. But this yield of education is smaller for first-generation Turkish and Moroccan men, indicating a certain degree of exclusion of even higher-educated Turkish and Moroccan men, who migrated themselves, from the labour market. A possible mechanism explaining the closure might be the non-recognition of their educational qualifications. The same holds for first-generation Turkish and second-generation Surinamese females: they also have lower yields from their education for avoiding unemployment than comparable indigenous women. However, second-generation Moroccan men have a larger education yield than comparable indigenous men.

Getting older increases the chances of being unemployed more strongly for various migrant generations (first-generation Turkish males and females; first-generation Moroccan females) than for the comparable indigenous Dutch population. Again, there is an exception: getting older increases the chances of becoming unemployed less for first-generation Surinamese men than for comparable Dutch men.

The parameter for unemployment in 1994 indicates a sharp drop in unemployment between 1994 and 1998, another indicator of the improvement of Dutch economy during that period. But the unemployment of first-generation Turkish and Antillean women decreased during 1988–98 more strongly than for indigenous women, and this cannot be explained by their age. This can be interpreted as a modernisation effect for migrant women as the economically active first-generation women increasingly found jobs in an expanding labour-market. The absence of other interaction effects for males suggests that during 1988–98 the less favourable economic circumstances did not lead to further exclusion amongst minorities.

The results for unemployment clearly provide evidence for the closure perspective. Despite controls for level of education and age, unemployment for most minority generations is considerably higher than for the comparable indigenous population. Also age and education have a lower yield for avoiding unemployment for a number of migrant generations, indicating evidence of exclusion and closure processes.

(p.385) Occupational position

The analysis of the position of minorities in the occupational class structure calls for a different type of analysis than that used to model labour-market participation and unemployment. Since occupational classes are represented as a nominal variable and most of the explanatory variables are categorical in nature, we use a multinomial logistic model for the analyses of the position of minorities in the occupational class structure. In this analysis a series of logistic regressions of the categories of occupational class on the explanatory variables is evaluated simultaneously (see Table 9.7A and 9.7B).

In the analysis the lowest class, unskilled manual worker, is treated as the reference category for the dependent variable. Thus the dependent variable represents the chances of being a member of each of the four higher classes relative to the chances of belonging to the unskilled manual class. The effects of the explanatory variables represent the chances of the categories of the explanatory variables relative to their reference categories.

The models’ test parameters indicate that the two models provide a fairly good prediction of the position of men and women within the occupational class structure. We also searched for significant interaction terms in the models for men and women. We selected from these analyses those interaction terms that improved the fit of the model. These few significant interaction terms were introduced together into the equation. Only those interaction terms which significantly improved the fit of the model are included in Model 2. The explanatory variables cover approximately 30% of the ‘variance’ in the log-odds for the classes of males, and 20% for females.

The pattern of the parameters for the combinations of minority group membership and migrant generation is interesting. After controlling for level of education, migrant generation appears to be decisive for the position of minorities in the occupational class structure. For men and women of the first generation, many minority membership effects are significantly negative, indicating a lower chance of belonging to a given class relative to belonging in the unskilled manual class. These effects tend to be much closer to zero for the second generation.

Nonetheless, all second-generation males, with the exception of the Antilleans, have lower chances of belonging to the salariat class than comparable indigenous men. However, older second-generation Surinamese men have a higher chance of entering the salariat than comparable indigenous men, and as a consequence their final chances to enter the salariat become equal to those of indigenous men of the same age and educational qualifications. Apart from access to the salariat, second-generation men do not appear to be disadvantaged in gaining access to the other three classes compared to indigenous men. None of the other parameter estimates for the second generation men are statistically significant. The only exception is the higher chances of the second-generation male Antilleans of belonging to the petty bourgeoisie than indigenous men with the same age and education.

(p.386)

Table 9.7A. Logistic regression of occupational class: Men (parameter estimates; contrasts with semi- and unskilled manual).

 

Salariat

Routine non-manual

Petty bourgeoisie

Skilled manual

 

1

2

1

2

1

2

1

2

Intercept

2.55

(0.80)

1.29

(0.85)

1.03

(0.78)

0.34

(0.82)

0.82

(1.06)

0.47

(1.13)

0.12

(0.80)

−0.66

(0.84)

Ancestry

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Native Dutch

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

     Turkish 1

−2.19

(0.12)

−2.17

(0.12)

−1.80

(0.12)

−1.78

(0.12)

−0.95

(0.14)

−0.94

(0.14)

−0.60

(0.10)

−0.58

(0.10)

     Moroccan 1

−1.90

(0.12)

−1.46

(0.18)

−1.43

(0.12)

−1.15

(0.16)

−1.10

(0.16)

−0.77

(0.22)

−0.75

(0.11)

−0.41

(0.14)

     Surinamese 1

−0.64

(0.11)

−0.64

(0.11)

0.02

(0.11)

0.02

(0.11)

−0.45

(0.16)

−0.45

(0.16)

0.05

(0.11)

0.05

(0.11)

     Antillean 1

−0.78

(0.13)

−0.77

(0.13)

−0.31

(0.13)

−0.30

(0.13)

−0.58

(0.20)

−0.58

(0.20)

−0.02

(0.12)

−0.02

(0.12)

     Turkish 2

−0.75

(0.27)

−0.64

(0.28)

−0.32

(0.21)

0.05

(0.21)

−0.10

(0.32)

0.16

(0.32)

−0.16

(0.25)

−0.08

(0.26)

     Moroccan 2

−0.69

(0.33)

−0.59

(0.34)

−0.25

(0.28)

−0.18

(0.28)

0.29

(0.36)

0.34

(0.36)

−0.04

(0.30)

0.04

(0.30)

     Surinamese 2

−0.40

(0.20)

0.05

(0.25)

0.04

(0.19)

0.18

(0.22)

0.23

(0.26)

0.06

(0.34)

0.00

(0.21)

0.14

(0.25)

     Antillean 2

−0.08

(0.23)

−0.03

(0.23)

0.06

(0.24)

0.10

(0.24)

0.61

(0.29)

0.65

(0.29)

0.27

(0.25)

0.32

(0.25)

Age-group

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     18−30

0.60

(0.09)

0.82

(0.10)

−0.13

(0.09)

0.03

(0.10)

0.10

(0.12)

0.24

(0.14)

0.26

(0.08)

0.43

(0.09)

     31−10

0.18

(0.09)

0.28

(0.09)

−0.02

(0.09)

0.06

(0.09)

0.01

(0.12)

0.09

(0.13)

0.10

(0.08)

0.19

(0.08)

     41−60

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

Education

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Primary

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

     Lower

0.34

(0.10)

0.33

(0.10)

0.54

(0.09)

0.54

(0.09)

0.48

(0.12)

0.46

(0.12)

0.62

(0.08)

0.62

(0.08)

     secondary

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Higher

1.77

(0.10)

1.77

(0.10)

1.47

(0.10)

1.47

(0.10)

1.12

(0.14)

1.11

(0.14)

0.97

(0.09)

0.97

(0.09)

     secondary

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Tertiary

3.56

(0.13)

3.56

(0.13)

1.69

(0.14)

1.68

(0.14)

1.53

(0.19)

1.56

(0.19)

0.75

(0.16)

0.74

(0.16)

Year

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     1988

−0.92

(0.10)

−0.96

(0.10)

−0.09

(0.11)

−0.11

(0.11)

−1.29

(0.12)

−1.31

(0.12)

−1.20

(0.09)

−1.23

(0.09)

     1991

−0.25

(0.10)

−0.28

(0.10)

−0.02

(0.09)

−0.03

(0.09)

0.05

(0.15)

0.04

(0.15)

−0.83

(0.08)

−0.85

(0.08)

     1994

−0.34

(0.10)

−0.37

(0.10)

−0.33

(0.09)

−0.34

(0.09)

−0.52

(0.19)

−0.52

(0.19)

−0.48

(0.09)

−0.50

(0.09)

     1998

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

Significant Interactions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Moroccan 1 * age group

0.43

(0.13)

 

 

0.29

(0.12)

 

 

0.34

(0.16)

 

 

0.33

(0.09)

     Surinamese 2 * age group

0.71

(0.27)

 

 

0.23

(0.26)

 

 

−0.27

(0.32)

 

 

0.20

(0.28)

Chi-square (D.F.)

Model 1: 1,229 (64)

 

 

 

 

 

Model 2: 1,197 (72)

 

 

 

N

 

 

 

 

 

 

 

8851

 

 

 

 

 

 

 

 

Note: Standard errors are given in brackets; emboldened coefficients indicate significance at the 0.05 level or higher.

(p.387)

(p.388)

Table 9.7B. Logistic regression of occupational class: Women (parameter estimates; contrasts with semi- and unskilled manual).

 

Salariat

Routine non-manual

Petty bourgeoisie

Skilled manual

 

1

2

1

2

1

2

1

2

Intercept

2.13

(1.03)

2.97

(1.11)

2.54

(0.88)

3.86

(0.93)

−1.13

(1.40)

−0.78

(1.46)

−2.60

(1.41)

−2.69

(1.47)

Ancestry

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Native Dutch

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

     Turkish 1

−2.42

(0.19)

−2.25

(0.38)

−2.54

(0.15)

−2.45

(0.31)

−1.03

(0.23)

−0.37

(0.37)

−0.08

(0.21)

0.72

(0.29)

     Moroccan 1

−1.54

(0.24)

−1.56

(0.24)

−1.39

(0.18)

−1.48

(0.17)

−0.30

(0.29)

−0.38

(0.29)

0.03

(0.28)

−0.06

(0.28)

     Surinamese 1

−0.77

(0.14)

−0.84

(0.16)

−0.39

(0.12)

−0.50

(0.12)

−0.93

(0.23)

−0.93

(0.25)

−0.18

(0.21)

−0.14

(0.21)

     Antillean 1

−0.78

(0.16)

−0.80

(0.16)

−0.44

(0.14)

−0.47

(0.14)

−0.50

(0.25)

−0.54

(0.25)

−0.11

(0.24)

−0.15

(0.24)

     Turkish 2

−0.78

(0.29)

−0.82

(0.29)

−0.64

(0.22)

−0.72

(0.22)

0.48

(0.34)

0.42

(0.34)

0.56

(0.36)

0.47

(0.36)

     Moroccan 2

−1.11

(0.35)

−1.12

(0.35)

−0.82

(0.25)

0.87

(0.25)

0.49

(0.38)

0.44

(0.37)

0.68

(0.41)

0.58

(0.40)

     Surinamese 2

0.40

(0.22)

−0.41

(0.22)

−0.21

(0.19)

−0.25

(0.19)

0.56

(0.28)

0.52

(0.28)

0.74

(0.30)

0.67

(0.29)

     Antillean 2

0.23

(0.25)

−0.23

(0.24)

−0.49

(0.22)

−0.50

(0.22)

0.55

(0.31)

0.54

(0.31)

0.78

(0.31)

0.77

(0.31)

Age-group

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     18−30

0.44

(0.13)

0.50

(0.13)

−0.34

(0.11)

−0.32

(0.11)

0.51

(0.18)

0.56

(0.18)

0.52

(0.16)

0.58

(0.17)

     31−40

0.15

(0.12)

0.16

(0.13)

−0.10

(0.11)

−0.10

(0.11)

0.21

(0.18)

0.20

(0.18)

0.33

(0.17)

0.33

(0.17)

     41−60

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

Education

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Primary

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

     Lower

0.54

(0.14)

0.49

(0.15)

0.98

(0.10)

0.82

(0.11)

0.38

(0.19)

0.24

(0.20)

0.18

(0.16)

0.08

(0.18)

     secondary

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Higher

1.93

(0.14)

1.72

(0.16)

1.53

(0.16)

1.15

(0.13)

1.20

(0.19)

0.91

(0.21)

0.70

(0.18)

0.47

(0.21)

     secondary

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Tertiary

3.55

(0.17)

3.23

(0.20)

1.30

(0.16)

0.77

(0.19)

1.90

(0.23)

1.49

(0.26)

1.42

(0.23)

1.09

(0.27)

Year

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     1988

−1.27

(0.15)

−1.15

(0.16)

−0.36

(0.14)

−0.22

(0.15)

−1.60

(0.20)

−1.38

(0.22)

−2.85

(0.18)

−2.40

(0.20)

     1991

−0.20

(0.13)

−0.21

(0.14)

0.30

(0.11)

0.31

(0.12)

−0.26

(0.21)

−0.17

(0.22)

−0.92

(0.19)

−0.67

(0.20)

     1994

0.16

(0.12)

0.13

(0.13)

0.18

(0.10)

0.15

(0.10)

−0.48

(0.17)

−0.45

(0.18)

−0.42

(0.19)

−0.31

(0.20)

     1998

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

0.0

 

Significant Interactions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     Turkish 1 * education

 

−0.38

(0.18)

 

 

−0.58

(0.15)

 

 

−0.37

(0.21)

 

 

−0.33

(0.19)

     Surinamese 1 * education

−0.48

(0.13)

 

 

−0.63

(0.11)

 

 

−0.48

(0.20)

 

 

−0.36

(0.17)

     Turkish 1 * year

 

0.03

(0.05)

 

 

0.02

(0.04)

 

 

0.10

(0.05)

 

 

0.20

(0.05)

Chi-square (D.F.)

 

 

Model 1:916(64)

 

 

 

 

 

Model 2: 732 (76)

 

 

N

 

 

 

Model 1: 5,110

 

 

 

 

 

Model 2: 4,995

 

 

Note: Standard errors are given in brackets; emboldened coefficients indicate significance at the 0.05 level or higher.

(p.389)

(p.390) Turkish and Moroccan women of the second generation also have lower chances of belonging to the salariat or to the routine non-manual class than comparable indigenous women. But second-generation Antillean and Surinamese women have higher chances of belonging to the petty bourgeoisie or the skilled manual class than indigenous women with the same age and education. On the whole the inclusion of the active second generation of migrants into the Dutch class structure does not indicate strong exclusion. But the salariat class remains relatively more closed to this second generation and this closure cannot be explained by age or education.

The male first-generation migrants, whatever their origin, age and education, have higher chances of being members of the unskilled manual class than comparable indigenous men (although Surinamese are the exception for the routine non-manual and skilled classes and Antilleans for the skilled class). Given the labour-migration history of the Turks and Moroccans this is not surprising, but our results indicate that this low class position cannot be explained by their educational qualifications. The colonial-migration history of the first-generation Surinamese and Antilleans gave them more opportunities to enter classes above the unskilled manual classes, but prevented them from gaining entrance into the salariat.

The results for the first-generation females resemble that of the male migrants; the only exception is that for women there is in general no significant difference between entrance chances into the unskilled and skilled manual classes.

From the point of social closure against migrants by Dutch society, second-generation men have better chances of entering the higher classes of Dutch society than first-generation men, but there still appears to be closure of the salariat class. This is also true, albeit to a lesser degree, for second-generation female migrants.

Level of education has its expected effect on the chances of entering the various social classes—the greater the distance from the lowest class, the stronger the effects of education on the chances of belonging to a (p.391) higher class. For migrant men, both first and second generation, there is no lower yield of education on entrance to the various classes. For Turkish and Surinamese women of the first generation, however, there are significantly lower yields of education on the chances to enter the petty bourgeoisie or higher classes than for equally educated indigenous women.

The results suggest that for active workers the mechanism for acquisition or ascription of occupational-class position might be different for the second generation as compared to the first. For the second generation the acquisition of an occupational-class position appears to follow the same path as it does for the indigenous workers. Occupational-class position for them depends mainly on human capital. This supports modernisation theory, although the highest classes are still a domain more closed to second-generation migrants than the modernisation theory would assume.

The modernisation viewpoint, however, applies little to the position of the male first generation. Controlling for education (and thus partly for the degree of fluency either in the Dutch or the English language) their chances of reaching higher-class levels in the occupational structure are much lower than the chances of the indigenous workers. Moreover the Antillean and Surinamese first-generation males (especially the higher educated) will have some fluency in the Dutch language, as the same language is also used in the Antilles and Suriname, but our results do not show chances equal to those of the comparable indigenous population. Thus this result supports the social closure viewpoint.

Does this conclusion mean that different theoretical frameworks are needed for the explanation of the position of the first and second generation minorities? This option is not very attractive. It could be argued that social exclusion holds for both the first and the second generation but that the second generation no longer has some of the minority characteristics (like low educational level or lack of fluency in the Dutch language) that trigger exclusion from the middle classes.

Income

Considering the results discussed so far it could be expected that the closure tendencies on the labour market and in the occupational structure will have their consequences for the incomes of members of minority groups, having the same age, educational level and class position. While overall income differences are associated with labour-market participation, unemployment, age, education and position in the class structure, if (p.392) closure tendencies exist ethnic minorities should have lower incomes than comparable members of the indigenous population.

For the interpretation of the results of Table 9.8 it is important to remember three points: (1) the income measure is inclusive of social benefits, unemployment benefits, occupational disability benefits, etc. In short, income measures the available money of the individual; (2) the reference category in these analyses is an indigenous person with only primary education and without a job (but on benefits); (3) there are missing values for the income of a substantial number of male and female respondents. They are not included in our analyses.

The estimates for income in Table 9.8 show that minority membership has something of the expected effect on income. Controlling for class, education, age, age-square and year of measurement, incomes of men from the Moroccan, Surinamese and Antillean minority groups of the first generation are significantly lower than the incomes of the comparable indigenous male population. For the second generation this is only true for the Surinamese, as other second-generation male migrants have incomes equal to their indigenous counterparts within the same occupational class.

Yet there is a remarkable feature in the estimates for women: the coefficients for female migrants of both generations are positive and significant, indicating that they have a larger income than their indigenous equals. Considering income differences between men and women it should be kept in mind that women who do not participate in the labour market are not earning an independent income nor have substantial social benefit rights. Several explanations for the gender differences could be suggested. It could be possible that the overall lower rate of labour-market participation of all women as compared to men has a levelling influence on the differences between minority women and indigenous women. A second explanation is that income-generating minority women are a stronger positive selection from the total population of all minority women than income-generating women from indigenous population are compared to indigenous women as a whole.

Table 9.9 then includes the significant interactions between migrant generation group and class, education and age. (The main effects of the control variables are not shown as they do not alter appreciably.) A large number of significant negative interactions exist, of which all but three indicate that first-generation male and female migrants earn lower incomes from jobs in all classes, from the salariat down to the unskilled manual class. One might suggest that this is just a consequence of the gross classes used in the analyses and the apparently lower positions of (p.393) migrants within each of these classes; but we believe that this is a misleading explanation of these negative interaction terms, as main effects of age and education are controlled for within the model, and these control variables should take care of these assumed lower positions of migrants within the classes.

Table 9.8. Regression of logged income (parameter estimates).

 

Men

Women

Intercept

6.77

(0.02)

6.72

(0.03)

Ancestry

 

 

 

 

     Native Dutch

0.0

 

0.0

 

     Turkish 1

0.00

(0.01)

0.06

(0.02)

     Moroccan 1

−0.05

(0.01)

0.09

(0.03)

     Surinamese 1

−0.09

(0.01)

0.15

(0.02)

     Antillean 1

−0.12

(0.01)

0.15

(0.02)

     Turkish 2

0.04

(0.03)

0.15

(0.04)

     Moroccan 2

0.01

(0.04)

0.05

(0.05)

     Surinamese 2

−0.12

(0.02)

0.10

(0.03)

     Antillean 2

−0.02

(0.03)

0.05

(0.03)

Age/10

0.53

(0.01)

0.35

(0.02)

(Age/10)2

−0.09

(0.00)

−;0.08

(0.01)

Education

 

 

 

 

     Primary

0.0

 

0.0

 

     Secondary lower

0.07

(0.01)

0.03

(0.02)

     Secondary higher

0.04

(0.01)

0.09

(0.02)

     Tertiary

0.18

(0.01)

0.25

(0.02)

Year

 

 

 

 

     1988

−0.25

(0.01)

−0.26

(0.02)

     1991

−;0.10

(0.01)

−0.11

(0.02)

     1994

−0.09

(0.01)

−0.11

(0.02)

     1998

0.0

 

0.0

 

Class

 

 

 

 

     Salariat

0.60

(0.01)

0.48

(0.02)

     Routine non-manual

0.45

(0.01)

0.30

(0.02)

     Petty bourgeoisie

0.46

(0.02)

0.20

(0.03)

     Skilled manual

0.44

(0.01)

0.04

(0.03)

     Unskilled manual

0.37

(0.01)

0.11

(0.02)

     Unemployed

0.0

 

0.0

 

Adjusted R squared

0.50

 

0.28

 

N

12,196

 

7,368

 

Note: Standard errors are given in brackets; emboldened coefficients indicate significance at the 0.05 level or higher.

Another plausible explanation for these negative interactions between migrant generation and class may be high social benefits obtained outside the labour market by first-generation migrant groups compared to their indigenous equals. The still-generous Dutch social welfare system, combined with special social policies directed at migrants, might have led to higher incomes for lower-educated older migrants outside the labour market compared to their equally low-educated older indigenous neighbour. If this second explanation is (also) correct, it can explain the erosion among the working classes and social-democrat voters of their former support for generous policies towards labour-migration. Interestingly, some second-generation migrants in the unskilled classes have higher incomes than their indigenous equals. We do not have a good explanation for this result, next to the suggestion that they might have more sources for income than the indigenous equals (illegal work in family business perhaps).

(p.394)

Table 9.9. Regression of logged income: interaction effects (parameter estimates).

 

Men

Women

Main effects of Ancestry

 

 

 

 

     Native Dutch

0.0

 

0.0

 

     Turkish 1

0.40

(0.02)

0.17

(0.04)

     Moroccan 1

0.24

(0.02)

0.10

(0.05)

     Surinamese 1

0.11

(0.02)

0.19

(0.02)

     Antillean 1

0.06

(0.03)

0.20

(0.02)

     Turkish 2

−0.13

(0.09)

0.19

(0.04)

     Moroccan 2

0.13

(0.04)

−0.14

(0.08)

     Surinamese 2

−0.15

(0.04)

0.13

(0.03)

     Antillean 2

0.05

(0.03)

0.15

(0.06)

Significant interactions between ancestry and class

 

 

     Turkish 1 * salariat

−0.25

(0.04)

−0.14

(0.10)

     Moroccan 1 * salariat

−0.32

(0.04)

−0.28

(0.12)

     Surinamese 1 * salariat

−0.05

(0.03)

−0.13

(0.04)

     Antillean 1 * salariat

 

 

−0.08

(0.05)

     Turkish 1 * non-manual

−0.26

(0.04)

−0.19

(0.06)

     Moroccan 1 * non-manual

−0.27

(0.04)

−0.20

(0.07)

     Turkish 1 * PB

−0.22

(0.05)

 

 

     Moroccan 1 * PB

−0.24

(0.06)

 

 

     Surinamese 1* PB

−0.07

(0.03)

 

 

     Antillean 1* PB

−0.29

(0.09)

 

 

     Turkish 1 * skilled

−0.26

(0.03)

 

 

     Moroccan 1* skilled

−0.23

(0.03)

 

 

     Turkish 1 * unskilled

−0.13

(0.02)

 

 

     Turkish 2 * unskilled

0.11

(0.06)

 

 

     Moroccan 1 * unskilled

−0.15

(0.02)

 

 

     Moroccan 2 * unskilled

 

 

0.40

(0.12)

     Surinamese 2 * unskilled

0.08

(0.06)

−0.19

(0.09)

Significant interactions between ancestry and education

 

 

     Turkish 1 * education

−0.05

(0.01)

−0.07

(0.02)

     Moroccan 1 * education

−0.04

(0.01)

 

 

     Moroccan 2 * education

 

 

−0.10

(0.05)

     Surinamese 1 * education

 

 

−0.05

(0.02)

     Antillean 1 * education

 

 

−0.07

(0.02)

Significant interactions between ancestry and age

 

 

     Turkish 1 * age

−0.16

(0.01)

−0.07

(0.02)

     Moroccan 1 * age

−0.10

(0.01)

 

 

     Moroccan 2 * age

 

 

0.23

(0.07)

     Surinamese 1 * age

−0.09

(0.01)

 

 

     Surinamese 2 * age

0.09

(0.03)

 

 

     Antillean 1 * age

−0.08

(0.01)

 

 

     Antillean 2 * age

 

 

−0.32

(0.04)

     Turkish 1 * year

 

 

0.01

(0.00)

     Turkish 2 * year

0.03

(0.01)

 

 

     Moroccan 1 * year

0.004

(0.002)

0.01

(0.01)

Adjusted R squared

 

0.52

 

0.29

N

 

12,196

 

7,368

Note: Standard errors are given in brackets; emboldened coefficients indicate significance at the 0.05 level or higher. PB stands for petty bourgeoisie.

(p.395) The lower yields of education, particularly for women of the first generation, suggest that they had a weaker position than their indigenous peers in obtaining the same amount of money. But first-generation male Turks and Moroccans also have lower yields from their education for their income. This result underpins a closure tendency within the Dutch labour market.

The lower yield of ageing on income among the first-generation male migrants might reflect this closure tendency of Dutch society. However, another explanation might be that social benefits are generally independent of the age of the receiver and that thus the income of the first-generations migrants, who received mostly social security at a relatively young age, did not change with their age.

Conclusion

From the analyses of the position of ethnic minorities in the Dutch labour market, the following conclusions can be derived.

Among men, minority group membership has definite negative effects on labour-market participation and unemployment. Controlling for level of education, age and economic fluctuations, the chances of labour-market participation for ethnic minority men are consistently lower than for indigenous men and their risk of unemployment is consistently higher. This pattern is evident among both generations, but holds for the second generation less than for the first.

For women the patterns of participation and unemployment are more complex. There are differences between ethnic groups and differences associated with migrant generation. For the first generation, as far as participation is concerned, there is a sharp divide between, on one side, Turkish and Moroccan women and, on the other, Surinamese and Antillean women. (p.396) While Turkish and Moroccan women participate at considerably lower levels than indigenous women, Surinamese and Antillean women participate at higher levels than their indigenous peers. Among second-generation women, however, these differences in participation have disappeared (with the exception of Moroccan women). Second-generation women also have a smaller risk of unemployment than the first generation; however this risk remains higher than the risk for indigenous women, and differs somewhat by ethnic group.

The distribution of ethnic minorities across occupational classes reveals a consistent pattern. For the second generation, again controlling for level of education, age and economic fluctuation, the chances of being in a particular occupational class are the same as for the indigenous population, with the exception of the salariat which remains more closed to migrants. This result holds for men as well as for women. But the distribution of the first generation within occupational classes is strikingly different from the distribution of the second generation. In most cases the odds of first-generation migrants being in a class higher than manual worker are considerably lower than the odds for comparable indigenous workers.

After controlling for education, age, occupational class and year, first-generation migrants also have lower incomes than the indigenous population. A possible explanation for this finding could be the relatively high level of social benefits which lower-educated older migrants receive compared to their similarly low-educated older indigenous neighbours. The higher social benefits might be an unintended consequence of the Dutch social welfare system, which developed various special policies directed to migrant groups. Some second-generation ethnic groups who have an unskilled job have higher incomes than the comparable indigenous people. The lower yield of age and education for the male and female first generation suggests a closure tendency in the Dutch labour market, especially for the better educated.

To what extent are these results new? Compared with recent publications (Tesser, Merens and van Praag 1999; Dagevos 2001) using the same type of data, our results on labour-market participation and unemployment are not contradictory, although we make the distinction between first- and second-generation migrants (due to our combining the SPVA data), and thus can see the progress of the second generation in their labour-market participation. However, because these publications focus largely on the lower strata of the migrants, there is no comparable analysis of the SPVA data on the chances of entrance to the different occupational (p.397) classes. In particular, the lower odds of entrance into the salariat of the second generation have not been studied before. The same holds for income—one will not find a section on income in these publications. This omission might be explained by the dominant definition of the migrant problem (low education and bad entrance to the labour market) and by the political incorrectness of comparing the amount of social security benefits obtained by various migrant groups to those obtained by the indigenous population.

What do the results tell us about the two theoretical perspectives on stratification: modernisation and social closure? At first sight the results are rather confusing. Results for men generally support the thesis of social closure for minorities, but there is one important exception: the equal participation chances of second-generation minority men in most of the higher occupational classes. However, one could maintain that the unequal access of the second generation to the salariat provides further evidence of a closure tendency, as the other classes are less accretive.

Aside from their lower odds of entrance to the salariat, our results could be interpreted as showing that men of the second generation are less likely to be affected by social closure, perhaps because they exhibit fewer ethnic characteristics (such as a lack of fluency in the Dutch language) that trigger exclusion than did first-generation men. However if this argument is valid, what explains the continued lower levels of labour-market participation among the second generation, or their increased risk of unemployment?

One possible explanation for these results might be that the second generation has survived a more severe selection at the entrance to the labour market than the indigenous workforce. One might assume that entrance selection follows the logic of social closure, hence the results on labour-market participation and unemployment support closure for the second generation as well as for the first. However, those second-generation migrants who survive the entrance selection are hired more or less according to the same rules as the indigenous workforce: occupational class is largely determined by human capital. By successfully entering the labour market, minority members have shown that they possess the necessary qualifications to compete with the indigenous workforce on an equal footing.

However, there is another possible interpretation of the same results. The more severe entrance selection of the second generation would normally have produced higher positions within the occupational class structure, compared to the less selective indigenous workforce. The absence of (p.398) this positive effect of the more severe entrance selection for the second generation suggests the existence of social closure not only at the entrance but also within the labour market. In this interpretation the positive effect of a more severe selection balances the negative effect of social closure at the labour market.

Then the mirror question comes up regarding the first generation: why does the selection process not apply to their position in the occupational class structure? The main result from our analyses is that the two driving forces in advances within the labour market (age and education) pay off less for the first generation. This result might be caused by problems of recognition of educational and occupational qualifications, but might also be caused by closure, especially in the higher strata of society and thus within the labour market. Another argument is that in the first generation there is much less variance in various characteristics within ethnic groups; most variance, rather, is between groups. This between-group variance indeed has its effects on chances in the occupational structure as can be derived from the better odds for Surinamese and Antillean minorities vs. Turks and Moroccans in obtaining higher positions within the occupational structure.

The more severe selection argument could also serve to explain some of the deviating results among women. However, an unknown part of the entrance selection among women is that there is likely to be more self-selection. Thus women who decide to participate on the labour market, regardless of their ethnic background, have characteristics that distinguish them from the women who decide not to participate. Social closure may operate less among women because of the greater importance of self-selection. Not participating on the labour market for women is likely a more attractive alternative than for men. However, an alternative interpretation of the women’s results could argue that the social closure for second-generation women is balanced by the positive effect of the more severe entrance selection, because they are an even more selective group at the entrance to the labour market than second-generation men.

Certainly the special position of Surinamese and Antillean women may have to do with cultural factors. In particular, marriage and partnership relations among Surinamese and Antillean men and women tend to be very unstable. Thus, many Surinamese women cannot trust that a man will take responsibility for the common household, and she subsequently orients herself to being economically independent.

Our findings do not therefore allow us an unambiguous answer to our question about equal opportunities or closure. While many of our results are consistent with modernisation theory, the continued high levels of (p.399) unemployment among second-generation men, and their difficulties in gaining access to the salariat, suggest that social closure plays continues to play some role in Dutch society, although problems of selection prevent us from saying categorically how large that role is.

Appendix

SPVA data sets provide four surveys of samples of households from the four largest immigrant ethnic minority groups (Turks, Moroccans, Surinamese and Antilleans). SPVA surveys on these four immigrant groups have been conducted in 1988, 1991, 1994 and 1998, on behalf of the Social and Cultural Planning Office (an independent governmental agency monitoring social-cultural developments in Dutch society). Other ethnic minorities (like Chinese or West African) are not included in the SPVA samples as their position is not considered as problematic by Dutch authorities which have financed these samples. More information on the Social and Cultural Planning Office can be found at 〈http://www.scp.nl/miss/spva.htm〉.

An individual is classified into a minority group if he or she was born in the respective country or if one of their parents was born there. Turks and Moroccans whose parents had different countries of birth hardly exist. This is less true for Surinamese and Antillean parents, one of whom might not have been born in Suriname or Antilles; nonetheless a more restricted definition (e.g., both parents born in Suriname or Antilles) would misrepresent the mixed nature of these ethnic groups due to the long-standing colonial relations between Suriname, the Antilles and the Netherlands (longer than the British relation with India). As a consequence, the racial composition of Antillean and Surinamese ethnic minorities is relatively heterogeneous, reflecting the mixed racial composition of these societies (African, Indonesian, Hindu, Jewish, White), although a majority do belong to ‘visible minorities’ of various skin colours.

The SPVA samples of the minority groups are two-stage samples: for reasons of efficiency the samples are drawn in a limited number of municipalities in which ethnic minorities are concentrated. First only those municipalities with high concentrations of these four ethnic groups were selected. The four largest municipalities (Amsterdam, Rotterdam, The Hague and Utrecht) are among the selected municipalities; 80% of these four ethnic groups live in these selected municipalities. Then a sample of the relevant households was drawn from the civic register of that municipality. The SPVA samples are representative of the four ethnic populations from which they are drawn; however, while the group samples are roughly of the same size, the total sample is not proportional to the total size of the four groups within the Dutch population. In each year the sample size of the subgroups is approximately the same, except for the last. In 1998 the sample size was augmented by a factor 1.5.

Each of the surveys contains a comparison group of households from the indigenous population. The comparison sample is drawn in the same municipalities as the minority samples. Therefore it is not representative of the whole indigenous population, because municipalities without minorities had no chance of entering the first (p.400) stage of the SPVA samples. As a consequence of white flight to the latter municipalities, the richer and more highly educated sections of the indigenous population are under-represented. However, analyses have shown that this under-representation of municipalities with few migrants hardly affects the strength of the correlations.

Data have been obtained by interviewing the head of the sampled household. In the interview a standardised questionnaire is used. A shortened form of the questionnaire is presented to all other members of the household 12 years of age and older. To diminish extraneous influences on the relations under study, analyses are constrained to persons 18–59 years of age.

Response rates have averaged around 60% in 1988, 1991 and 1994 but were slightly lower in 1998, varying from 48% to 61% in the different municipalities.

Membership of minority groups

As mentioned, membership of minority groups is determined by country of birth of a person and/or his or her parents. Five groups are compared: Turks, Moroccans, Surinamese, Antilleans and the indigenous population.

Immigrant status

Immigrant status classifies members of minority groups into a first generation and a second generation. Minority group members who are born in their home country or who immigrated after six years of age are considered first generation, whilst minority group members either born in the Netherlands or who immigrated before six years of age are classified as second generation.

As a consequence of the Dutch migration history, there are many more first-generation members than second-generation among 18–59 year-olds. Moreover, as the members of the second generation are much younger, they have less labour-market experience. Additionally, they are concentrated in the 1994 and (especially) the 1998 surveys.

Human capital

Variation in human capital is represented by levels of educational attainment. The variable has four classes: (1) primary or less; (2) secondary lower; (3) secondary higher; (4) tertiary.

Demand and supply fluctuations on the labour market

The different years in which the data are collected are characterised by different levels of economic activity, accompanied by fluctuations in demand and supply on the labour market. The year variable is treated as a proxy for fluctuations of the economy.

Gender

A straightforward measure with two categories: men and women.

(p.401) Age

Measured in years and taken into account because the two migrant generations differ in their age and deviate from the indigenous Dutch population as a consequence of the migration processes. The age-square term is added to the equations to account for the non-linear relation between age and labour market outcomes.

References

Bibliography references:

Blau, P. M. and Duncan, O. D. (1967), The American Occupational Structure (New York: Wiley).

Dagevos, J. M. (2001), Rapportage Minderheden 2001. Deel II Meer werk (The Hague: Sociaal en Cultureel Planbureau).

de Beer, P. T. (2001), Over Werken in de Postindustriele Samenleving (The Hague: SCP).

Gans, H. J. (1990), ‘Deconstructing the underclass’, Journal of the American Planning Association, 56, 271–7.

Jencks, C. (1992), Rethinking Social Policy: Race, Poverty, and the Underclass (New York: Harper-Perennial).

Murphy, R. (1988), Social Closure, the Theory of Monopolization and Exclusion (Oxford: Clarendon Press).

Parkin, F. (1974), ‘Strategies of social closure in class formation’. In F. Parkin (ed.), The Social Analysis of Class Structure (London: Tavistock), pp. 1–18.

Tesser, P. T. M., Merens, J. G. F., and van Praag, C. S. (1999), Rapportage Minderheden 1999. Positie in het Onderwijs en op de Arbeidsmarkt (The Hague: SCP).

Wilson, W. J. (1987), The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy (Chicago: University of Chicago Press).

Wright, E. O. (1985), Classes (London: Verso).