- draft, not to be quoted -

Diversity Policies in Public and Private Sector Organizations

An Empirical Comparison of Incidence and Effectiveness

Paper to be presented at the EGPA Conference 2010 Study group 3: Public Personnel Policies 8-10 September 2010, Toulouse, France

Sandra Groeneveld Department of Public Administration Erasmus University Rotterdam P.O. Box 1738 NL 3000 DR Rotterdam The Netherlands e-mail: s.m.groeneveld@fsw.eur.nl

Stijn Verbeek Department of Sociology Erasmus University Rotterdam P.O. Box 1738 NL 3000 DR Rotterdam The Netherlands e-mail: s.r.verbeek@fsw.eur.nl

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Diversity Policies in Public and Private Sector Organizations

An Empirical Comparison of Incidence and Effectiveness

Abstract This paper centers on a comparison of diversity policies in Dutch public and private sector organizations and their effectiveness in improving the representation of ethnic minorities in employment. Data are obtained from 8,283 annual reports of Dutch organizations containing information on diversity policies and ethnic minority representation in 2001 and 2002. Three types of diversity policies are analyzed: (1) policies designed to analyze ethnic minority representation, (2) policies designed to improve the influx of ethnic minorities in organizations, and (3) managing diversity instruments designed to improve the management of a diverse workforce in organizations. Results show that public sector organizations report more diversity policies compared to private sector organizations. For policies designed to improve the influx of ethnic minorities the sector differences in the number of policies are the largest. Regarding the effectiveness, managing diversity policies designed to improve the management of a diverse workforce are in general most effective in improving the representation of ethnic minorities in organizations in the short run. No sector differences in the effectiveness of different policy types are found. Key words Diversity policies, Equal opportunities, Affirmative action, Managing diversity, Ethnic minorities, Public sector

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1 Introduction Since the 1980s, national and local governmental integration policies in the Netherlands have been aiming at achieving 'equitable' participation rates of ethnic minorities in the labor market (Jonkers, 2003: 42). In the 1990s, the promotion of 'multicultural’ or 'diversity' policies in organizations became an important part of employment equity legislation. Encouraging employers to 'promote' and 'manage’ diversity is still seen as essential instrument in the fight against discrimination and ethnic minority unemployment, both in the Netherlands and the European Union (European Commission, 2009). This involves government agencies themselves (as employers), but also public sector and private sector organizations in general. In scientific debates on anti-discrimination and labor market integration, the effectiveness of organizational diversity policies is a central issue as well (see Wrench, 2007). However, empirical studies of the effectiveness of diversity policies in improving the representation of ethnic minority employees in organizations are limited (Dobbin, 2009; Groeneveld & Van de Walle, 2010; Kalev, Dobbin & Kelly, 2006; Verbeek & Penninx, 2009) and not much is known about differences between public and private sector organizations (Kellough & Naff, 2004; Naff & Kellough, 2003; Wise & Tschirhart, 2000). This paper centers on a comparison of diversity policies in Dutch public and private sector organizations and their effectiveness in improving the representation of ethnic minorities in employment. In this paper the term diversity policy is used as an umbrella term for related concepts like affirmative action (AA), equal employment opportunity policies (EO) and managing diversity. These are all strategies which aim at getting excluded minorities better represented in employment. Furthermore, whilst diversity policies encompass several dimensions of differences or heterogeneity, such as gender and age, this paper is focused on the dimension of ethnic origin. Approximately two-thirds of migrants to the Netherlands and their descendents are from Turkey, Morocco, Suriname and the Dutch Antilles. Nowadays, these four ethnic groups add up to more than one million people in a total population of 16.4 million. In addition, 600 thousand migrants from other non-western countries and their descendents are living in the Netherlands (Statistics Netherlands, 2008).1 Both first generation (those who actually migrated) and second generation (those who were born in the Netherlands but have at least one foreign-born parent) are counted as ethnic minorities and are the target groups of Dutch governmental integration policies. In comparison with the native population of the Netherlands, the population with a non-western foreign background is young. Their share of the total labor force is relatively high and will continue to grow in the coming decades. The Dutch government has focused on several strategies to integrate ethnic minorities into the labor market since the 1960s. Legislation provided a stimulus to diversity policies in organizations. The Act Stimulation Labor Market Participation of Ethnic Minorities (Wet SAMEN

1 Non-western countries are countries in Africa, South America or Asia (excl. Indonesia and Japan) or

Turkey (Statistics Netherlands, 2008).

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1998-2003) is an example of this specific strategy. The law applied to organizations employing 35 or more employees and required to strive for proportional representation of ethnic minorities. Employers had to supply government on a yearly basis with information on the number of ethnic minorities employed on different job levels and with information on diversity policies and practices in the organization. This would make employers aware of their performance with respect to the representation of ethnic minorities in their organizations. In addition, government could keep track of the performance of individual organizations more easily using this information. In this paper the data that were collected in the context of the act are analyzed. This paper is focusing on differences between public sector and private sector organizations. It is hypothesized that public sector and private sector organizations differ in their motivations to formulate and implement diversity policies. These different motivations may imply that different types of diversity policies are conducted (Groeneveld & Van de Walle, 2010). In addition, these different motivations may influence the effectiveness of different types of diversity policies (Kirton & Greene, 2005; Wrench, 2007). The research questions are:

(1) Do public and private sector organizations differ in number and type of diversity policies, and if so in what way?

(2) Do public and private sector organizations differ in the effectiveness of diversity policies in improving the representation of ethnic minorities, and if so in what way?

The next section gives a brief review of the literature on diversity policies and their effectiveness in public and private sector organizations. In section 3 the dataset and research methods are described. In section 4 the results are presented. Section 5 discusses the findings and concludes. 2 Theoretical considerations and previous research 2.1 Diversity policies Over the past decades Dutch government has set up several initiatives to improve the representation of ethnic minorities in employment by influencing organizational policies and practices. Government has, for instance, set numerical targets and has mandated positive action programs in government agencies. Furthermore, it has concluded covenants with both public and private sector employers who commit themselves to taking diversity policy measures and setting numerical targets on the number of ethnic minorities to be employed. These initiatives are often referred to as equal opportunity (EO) policies and affirmative action (AA) policies. In the literature on employment equity policies and diversity management much reference is made to these EO and AA policies in organizations in the US, Canada and in European countries (see e.g. Wrench, 2007). Since the 1960s these policies have represented responses to the diversity and inequality in the labor market. Both equal opportunity policies and affirmative action are aiming at increasing the representation of ethnic minorities in all levels of employment. To this end, equal opportunity policies are focused on removing barriers to the equal treatment of groups

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in the labor market, whereas affirmative action policies are focused on the effects of equal treatment: equal results for diverse groups in the labor market (Verbeek, forthcoming). In the public administration literature the concept of representative bureaucracy emphasizes that for democratic reasons government bureaucracies should represent the composite demographic characteristics of the population (Mosher, 1968). It reflects a concern about equal opportunities in the administration, a concern that grew in the 1960s. Access to public sector jobs was seen as a basic democratic right, and as a tool for social promotion. To promote equal opportunities, efforts had to be made to increase the proportion of underrepresented groups in the administration. Equal opportunities policies and affirmative action became tools to address this democratic deficit. The attention for representative bureaucracy also stemmed from a concern to see the interests of (disadvantaged) groups better represented, and to make the public sector more responsive. Bureaucracies would need to be representative of the population for them to have legitimacy and public credibility (Krislov, 1974). The increasing diversity of the population due to immigration and increasing female labor market participation has substantially changed the composition of the workforce in Western countries. In a context where a diverse workforce is simply a reality, effective management of diversity becomes more and more a managerial issue. It can be questioned whether managers would be able to realize the full potential of their diverse workforce when their management techniques are derived from general Human Resource Management (HRM) models that are based on an abstract worker - without gender, age or ethnic background (Groeneveld & Van de Walle, 2010). In response to the growing diversity of the US workforce Roosevelt Thomas coined the term ‘Managing diversity’ in 1990. In his often cited article in Harvard Business Review he (1990: 109) argues to move beyond affirmative action policies, because these are unable to develop the full potential of a diverse workforce:

“Affirmative action gets the new fuel into the tank, the new people through the front door. Something else has to get them to the driver’s seat. That something else consists of enabling people, in this case minorities and women, to perform to their potential. This is what we now call managing diversity. […] Just managing diversity in such a way as to get from a heterogeneous work force the same productivity, commitment, quality, and profit that we got from the old homogeneous work force.”

Managing diversity is the most recent of the approaches and fundamentally different from the previous affirmative action and equal employment opportunity approaches. The desire to produce employment equity is at the core of equal opportunity and affirmative action policies, whereas managing diversity is primarily concerned with improving human relations in teams that are already diverse in order to enhance team and organizational performance. In other words, EO/AA approaches are based on moral and legal arguments formulated more or less independent of the organization’s economic goals. Managing diversity policies, however, are internally and economically driven instead of imposed externally by legislation or moral claims about non-

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discrimination and equality. In fact, the term inequality is not even a part of the managing diversity vocabulary. In other words, managing diversity rests on a business case argument, the hypothesis that –if properly managed- a diverse work force contributes to the organization’s economic success (Roosevelt Thomas, 1990; Thomas & Ely, 1996; Verbeek, 2010a).2

The business case argument is fundamental to managing diversity theory and practice and refers to its strategic function. Through the employment of a diverse workforce new business opportunities would be created. A diverse workforce would appeal to a wider customer base and in that way would contribute to the performance of the organization (Thomas & Ely, 1996; Ely & Thomas, 2001). In the public administration context this (external) effect of diversity can be conceived as closing the gap between the organization and the clients (citizens) it serves. Apart from the strategic function of diversity management, another aspect in the business case for diversity is the increased need to effectively manage a diverse workforce. Managing diversity would be helpful in recruitment, selection and retention of the diverse resources available in the labor market (Ng & Burke, 2005). Moreover, managing diversity aims at maximizing the human resources within the organization. Like Human Resource Management approaches, but contrary to the equal opportunity and affirmative action approaches, managing diversity is based on individual recognition (Verbeek, forthcoming) and focuses on the development of the individual employee. Related to this, managing diversity is seen as an inclusive policy directed at all employees, where EO/AA approaches can be considered as exclusive policies directed at the interests of minorities (Wrench, 2007; Wise & Tschirhart, 2000).3 As a consequence of different objectives and motives different instruments are developed and implemented. Policy instruments typically associated with equal opportunities and affirmative action approaches include the formal announcement of equal opportunities policies and equal opportunity pledges, quotas for the employment of certain groups, recruitment targets, and monitoring ethnic minority representation in organizations. Equal opportunity and affirmative action policies are generally focused on enhancing the influx of ethnic minorities into organizational employment in general or at specific job levels. Managing diversity approaches are more focused on the inner workings of organizations and on behavioral change. Policy instruments used are diversity training for managers aimed at countering stereotyping and increasing awareness of cultural biases and education and training for ethnic minority employees.

2 The business case argument for diversity fitted very well into the rise of neoliberalism in the 1980s and

1990s which is another explanation for its growing popularity (compare Groeneveld & Van de Walle, 2010). 3 Unless they have a purely individualistic focus, diversity policies can be meaningfully interpreted as anti-

discrimination policies (Verbeek, forthcoming). The distinction between diversity policies primarily aiming at

increasing diversity and policies primarily aiming at the existing workforce is not only consistent with the idea

that discrimination takes place in different domains of the labour market, but also with the idea that "pre-

entry" and "post-entry" discrimination (Andriessen et al., 2007) may take different forms (Verbeek, 2010b).

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Focusing on numerical representation the policy instruments associated with equal opportunities and affirmative action do not address issues of integrating and retaining ethnic minorities in organizations once they are hired. Managing diversity addresses exactly this: changing organizational practices and climate in order to effectively manage a diverse workforce. Therefore, it is not uncommon to see that in organizational practice equal opportunity policies and affirmative action are complemented by managing diversity instruments (Wrench, 2007). Differences between public and private sector organizations For several reasons organizations may differ in the number and type of diversity policies they develop and implement. In this paper hypotheses are derived about the differences between public and private sector organizations, all other circumstances being equal. These hypotheses are primarily based on the arguments for sector differences in HRM policies in general that are found in the literature on HRM (Boyne, Poole & Jenkins, 1999; Steijn & Groeneveld, 2010). First, HRM in public sector organizations is –ceteris paribus- more standardized and more formalized compared to HRM policies in private sector organizations. As a consequence, it can be expected that public sector organizations more often adopt diversity policies that are legalistic in nature and can be operationalized in quantitative terms. Moreover, their diversity policies will be more often formalized and as a result will be more often reported in the context of the law. In addition, public sector employers are supposed to serve as an example to private sector employers. Public sector organizations are subject to political pressure to improve ethnic minority representation and to expose that policy measures are taken in this direction. It therefore can be expected that public sector organizations more often report policies that are visible, contributing to the symbolic effect of having diversity policies. Related to this, public sector organizations are more often driven by moral claims and are more concerned with issues of legitimacy. In private sector organizations on the other hand, economic motives and objectives will be relatively more emphasized than in public sector organizations. Despite the fact that in the recent years the business case for diversity is adopted in public sector discourse (Groeneveld & Van de Walle, 2010), in the public sector motives for designing diversity policies will still be more often linked to issues of legitimacy and democracy. Showing that public organizations offer equal opportunities for all, increases their legitimacy. It can therefore be expected that public sector organizations more often report visible and ‘hard’ policies, e.g. target figures, because of their symbolic value. Based on the above, the following hypotheses can be formulated: Hypothesis 1: Public sector organizations report more diversity policies compared to private sector organizations. Hypothesis 2: Public and private sector organizations differ in the type of policies that are reported. Public sector organizations more often report legalistic and visible policy types with measurable goals.

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2.2 Effectiveness of diversity policies This section provides a brief review of the literature on the effectiveness of diversity policies. It is important to emphasize that even though EO and AA policies and managing diversity aim at different things, they may well have similar effects. Hence, this study analyzes the impact of these diversity policy types on a single dependent variable: the aggregate representation of ethnic minorities. Most importantly, even though policies designed to manage diversity are pre-occupied with the existing workforce, they may lead to increases in diversity. Firstly, these organizations may be more successful than other organizations in retaining ethnic minority employees (see e.g. Roosevelt Thomas, 1990). Secondly, these organizations may be more successful in attracting ethnic minority job applicants, as these candidates may be attracted to organizations that value diversity (Ng & Burke, 2005). Reviewing the literature it must be concluded that not much is yet known about the effects of diversity policies on the representation of ethnic minorities in employment. When scrutinizing the existing research, the findings are mixed and they are often based on case studies that only apply to a specific context (see for example Wise & Tschirhart, 2000; Wrench, 2007; Pitts & Wise, 2010). In particular best practice studies have become very popular in the field of diversity management. These studies are however unsuitable to assess the effectiveness of policies, as they are based on a select sample of successful cases. There are a few large N studies that are helpful, but these are often restricted to particular policies. In the Netherlands, Callender (1989, in Gras & Bovenkerk, 1995) for example investigated 258 vacancies mentioning the policy of tiebreak preferential treatment and found that in only 12 of these cases an ethnic minority applicant had actually been appointed. Other studies are mostly based in the US. In their study of 3,200 organizations in four US metropolitan areas, Holzer and Neumark (2000) found that the effects of preferential treatment on the different target groups (black males, black females, white women, and Hispanics) were mixed and that white women benefited most. In the United States, research on affirmative action has shown that work organizations falling under affirmative action regulations witnessed greater improvements in minority participation rates than organizations not falling under these regulations. In particular, affirmative action in United States involved a shift of minority workers towards the public sector (see Glazer, 2000) and towards larger organizations (Carrington et al., 2000). It remains unclear, however, whether policies at the organizational level made the difference (Dobbin, 2009; Holzer & Neumark, 2000; Kalev, Dobbin & Kelly, 2006). In addition, based on a sample of 4,479 U.S. establishments, Leonard (1985) reported that organizations that promised to employ more blacks and females did actually witness an improvement in minority employment shares in subsequent years: total employment in these establishments fell by 3%, but, contrary to expectations, white males were overrepresented in the decline. More ambitious affirmative action goals were strongly correlated with greater subsequent achievements, even though projections outran actual realizations by roughly 10 to 1 on average.

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Apparently, these companies somehow succeeded in living up to their promises by protecting minority staff during periods of downsizing. Unfortunately, Leonard’s data could not show how these companies succeeded in living up to their promises. Kalev et al. (2006) found that establishing structures of responsibility, among which responsibility for affirmative action plans, led to the greatest increases in managerial diversity in organizations compared to efforts through other diversity policies. Managing diversity policies, such as mentoring programs and networking only showed modest effects. Diversity training for managers appeared to be ineffective. The study of Kalev et al. (2006) is one of the very few large N studies that assess the effects of managing diversity policies on the representation of ethnic minorities in employment. Another study that relates managing diversity to equity in the workplace is the study of Naff & Kellough (2003) on managing diversity programs in US federal agencies. The program components included in the study were diversity training, internal communications, accountability, and resource commitments. The authors found that there is little evidence that either broad-based diversity programs or the separate programmatic components have created a more equitable work environment for ethnic minorities. It must be noted that neither the study of Kalev et al. (2006) nor the study of Naff & Kellough (2003) evaluate managing diversity policies by their impact on the representation of ethnic minorities in the organizational workforce in general. Instead, Kalev et al. (2006) assess the effects on the share of ethnic minorities in management. Naff & Kellough (2003) point out that they prefer to assess the impact of managing diversity on more dynamic measures, such as promotions and turnover. As managing diversity is not primarily aiming at improving the representation of ethnic minorities in employment, but at effective management once they are hired, it is understandable that most managing diversity studies focus on HRM outcomes such as job satisfaction, turnover and promotions, and (employee perceptions of) organizational performance (see e.g. Pitts, 2009; Choi & Rainey, 2010). All in all, the evidence for the effectiveness of diversity policies is not overwhelming. Often the findings seem to be contradictory which is probably partly due to the specific contexts under research. In addition, the effectiveness of diversity policies is dependent on other variables, such as the underlying motivation (Kirton & Greene, 2005; Wrench, 2007), the translation into substantive policy practices (Hoque & Noon, 2004) and their actual implementation (Pitts, 2007; Pitts, Hicklin, Hawes & Melton, forthcoming). Hoque & Noon (2004) evaluate the incidence of equal opportunity policies in the UK and assess whether the policies are substantive or merely ‘empty shells’. Their evidence suggests that equal opportunity policies are not so often followed by substantive equal opportunity practices as could be expected. For some organizations having a policy could be a goal in itself. Its symbolic function is valued, because it contributes to the organization’s legitimacy, or it is simply imposed to the organization by legislation. Policies that are empty shells will not have a direct impact on

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the representation of ethnic minorities in the organizations. Their study, however, leaves open to question whether having substantive equal opportunity policy practices actually results in their implementation and improves the representation of ethnic minorities in employment. If improving the representation of ethnic minorities is important for reaching the organization’s economic goals, it will be more likely that diversity management is a voluntary management action. As a consequence, policies will be more supported by top management. The commitment of (top) management to the adoption and implementation of diversity policies is an important prerequisite for their success (Kellough & Naff, 2004). The more support from top management and the more resources devoted to diversity policies, the more likely that they are implemented (Pitts, 2007). As can be learned from the policy implementation literature, policy success very much depends on its implementation. Differences between public and private sector organizations Policies based on economic motives and that are voluntary actions of management are assumed to be more wholeheartedly implemented and –as a result- will be more successful compared to policies that are grounded in non-economic motives and are legally imposed. It can be expected that compared to public organizations in private sector organizations diversity policies will be driven by economic motives to a greater extent. In the end, private sector organizations’ survival is dependent on their economic success or failure. In addition to the expectation that private sector organizations will relatively more often adopt managing diversity policies, it can therefore also be hypothesized that diversity policies are more effective in the private than in the public sector. Furthermore, managing diversity policies in private sector organizations will be most effective. As in public sector organizations diversity policies are relatively more often conducted for reasons of legitimacy, the symbolic function of having policies at all is more important. Therefore, it was hypothesized in the previous section that public sector organization will relatively more often adopt equal opportunity and affirmative action policies. In addition to this, it can be expected that equal opportunity and affirmative action policies in public sector organizations are the least effective. Hoque & Noon (2004) however, find that there is no greater likelihood of public sector organizations having equal opportunity policies, and where they do so, they are less likely to be empty shells. In other words, public sector organizations relatively speaking develop and implement more substantive EO policy practices. But, as is said, the authors do not assess the implementation and effectiveness of these practices. Based on the above, the following hypothesis can be formulated: Hypothesis 3: The effectiveness of diversity policies in improving the representation of ethnic minorities depends on the combination of sector and policy type. Managing diversity programs in private sector organizations will be most effective.

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3 Data and method 3.1 Data The research material consists of thousands of annual reports that were filed in the context of the Dutch Act Stimulation Labor Market Participation of Ethnic Minorities (Wet SAMEN 1998-2003).4 These reports contain information on the labor market participation of ethnic minorities on four different job levels as well as information on organizational policies aimed at this group. The law applied to organizations employing 35 or more employees. The data used in this paper were imported from the original database, which was created by the different authorities involved in the implementation of the law, using information supplied by individual employers. Unfortunately, the original Wet SAMEN database was incomplete and many annual reports had to be deleted because of their poor quality. In many reports, crucial information is missing and in many others, different pieces of information contradict each other. In order to create a dataset as reliable as possible, an intensive filtering process was undertaken. In each annual report, for example, we checked whether the total number of employees equaled the number of employees working at the different functional levels, whether the ethnic minority employees did not outnumber the total number of employees, whether the number of full-time employees made sense compared with the total number of employees, et cetera. All reports that were judged inconsistent in their own terms were removed from the analysis.5 For the analysis reported in this paper, some further reductions of the sample were necessary. We restricted the analyses to the years 2001 and 2002. The most important reason for this reduction is the fact that the information on organizational policies is not comparable throughout the years: in earlier years, employers were more or less free to formulate the kind of policies they were implementing, whereas from 2000 onwards, they could also choose from a range of different individual policy actions (as in a closed survey). The list of policy types changed in 2001. Besides, the primary sector (agriculture, fishing, minerals, utilities) was deleted from the analysis in its entirety, because the percentage of primary sector organizations in the sample was only about two percent (creating a problem of ‘uneven split’, see Tabachnick & Fidell, 2007, p. 73). Finally, in preparation of the regression analysis a number of outliers had to be removed, even though the transformation of some of the variables led to a significant reduction of the number of outliers. Cases with absolute Z-scores equal to or greater than 3.29 were removed from the

4 The Wet SAMEN came into force on the first of January 1998 and ended on the first of January 2004. The

Central Wet SAMEN Database, however, contains a sizable number of comparable reports that were filed in

1997, i.e. in the context of its predecessor (the Wet BEAA, the ‘act promotion proportional labor participation

ethnic minorities’). Probably due to administrative reasons, very few annual reports from the year 2003 were

entered into the database – if they were filed at all. 5 The organizations in the final sample may be considered ‘most likely cases’ to a certain extent: if diversity

policies are ineffective in these organizations, it is unlikely that they were implemented successfully in the

other organizations, who reported inconsistently or never even bothered to file a report at all.

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analysis, implying that scores with a probability lower than .001 are outliers. Visual inspection of all univariate distributions showed that most outliers identified in this way were also detached from the other cases, which is another relevant criterion (Cohen et al., 2003). After the transformations and removal of outliers, all continuous variables were either normally distributed or very close to normality. Had the law been perfectly complied with, then the total number of Wet SAMEN reports in 2001 and 2002 would have been 32,452. In reality, 22,024 of these reports were actually filed and for the reasons outlined above, 13,741 reports were removed from the analysis. Hence, the final sample contains 8,283 reports (25.5%). 3.2 Method A Lagged Dependent Variable (LDV) model was used (compare Naff & Kellough, 2003), which is a good option in situations with many cases, few waves, and a presumed need to take into account the initial (‘pre-test’) score on the dependent variable (Menard, 2002; Van der Kamp & Bijleveld, 1998: 37-40). The LDV model is fairly simple: it just means adding a pre-test score on the dependent variable as a control variable into the regression analysis. The reasoning behind this is elegant, capturing a distinguishing feature of longitudinal studies: it allows each case to serve as its own control (Hedeker & Gibbons, 2006: xiv). The idea is that all previous influences on the dependent variable are crystallized at the beginning of the study – the ‘pre-treatment’ score in experimental terms. Subsequently, groups of cases receive various treatments. This design enables strong causal inferences, as differential post-treatment scores can be related more reliably to the treatment.6 In this study, the ‘treatments’ of interest are the three different policy types. Measurement of the dependent variable The dependent variable in this study is ‘end of year ethnic minority representation’. It is based on the proportion of ethnic minority workers employed by the organization at the 31st of December of the reporting year. In this sample, the distribution of the dependent variable strongly deviated from normality. In order to meet one of the assumptions of the statistical model, it was transformed using the logit function, i.e. by calculating odds instead of proportions and then

6 Statistically, there are other optional models to analyse the effects of independent variables on a single

continuous dependent variable (Yt) over a single unit of time. For example: regressing Yt on Xt-1 or using

Change Scores as dependent variables (Yt minus Yt-1). Change Scores, however, are typically less reliable

than the scores of the variables from which they are calculated (Cronbach & Furby, 1970, in Menard, 2002:

71).

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taking the natural logarithm of these odds. Odds are defined as the proportion of ethnic minority employees divided by the proportion not from that group (proportion/(1 – proportion)).7

Measurement of diversity policies The measurement of diversity policies in this study is based on the original Wet SAMEN database, which contains information on a high number of policy actions reported by the organizations that were subject to the law. In 2001 and 2002, employers were sent a detailed manual with instructions on how to comply with the law. The booklet as well as the floppy disk contained a form with 29 policy actions (as in a closed survey) and ample space for the employer to report additional measures. On receipt, regulators would interpret and categorize the latter items before adding the official report to the database. Hence, the total number of policy items in the dataset is even higher (56, see Appendix 1). Some policy actions, however, are mentioned far more often than others. The three most frequently occurring items are mentioned by almost 40% of organizations. 16 policy actions are reported by at least 10% of organizations. 31 out of 56 policy actions are mentioned by at least 1% of organizations. The remaining 25 items are very uncommon; most of these items were not pre-formulated in the manual. By clustering the high number of items in three policy types, it was possible to use all available policy-relevant information. The process of clustering was informed by both theoretical and empirical concerns, i.e. the opportunities and constraints of the data. As it turned out, the vast majority of policy items (45) could be categorized on the basis of the theoretical distinction between affirmative action/equal opportunity approaches on the one hand and managing diversity approaches on the other hand. Consistent with the general aim of the Wet SAMEN, most policy actions mentioned in the database (31) are designed to improve the influx of ethnic minorities in work organizations. In fact, the most popular policy action in the dataset is in the domain of ‘inflow, recruitment, and selection’: ‘making available internships (also) for ethnic minorities’. Other popular policy actions aimed at increasing aggregate participation rates of ethnic minorities in work organizations include ‘preferring ethnic minorities over other job applicants, if they are equally qualified’, ‘formulating target figures for inflow of ethnic minorities’, ‘using subsidized jobs (also) for ethnic minorities’, ‘using specialized recruitment and selection agency’, and ‘using media channels

7 At proportions of 0 or 1 (no ethnic minority employees or only ethnic minority employees), the logit

transformation does not work. Following Kalev et al. (2006: 598), 0 was substituted with 1/2v and 1 with 1-

1/2v, where v is the denominator of the counted fraction (see Cohen et al., 2003: 243 and Fox, 2008 for

comparable solutions). This is arbitrary to some extent, but from an employment equity perspective perhaps

not completely. In larger groups, zero participation of ethnic minorities yields ‘worse’ scores and conversely,

larger groups that completely consist of ethnic minority employees (proportion: 1) yield ‘better’ scores.

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aimed at ethnic minorities’. Just like traditional EO/AA approaches these policy actions are primarily aimed at increasing diversity and characterized by an emphasis on quantitative goals, a focus on (target) groups rather than individuals, and a high degree of formality. The second largest group consists of 14 policy actions that are commonly categorized as managing diversity instruments. These policy actions are not primarily designed to increase the diversity of the organizational workforce, but rather to manage and retain the diversity that is already there. This typically involves creating and nourishing a diversity-friendly organizational culture that values intercultural and interethnic differences between employees. In such an anti-discriminatory work environment, individual career development is a central issue. Concomitantly, talented ethnic minority employees should experience no difficulties in reaching the higher echelons of the organization. In the dataset, this type of policy is measured most frequently by policy items on labor relations and career development: ‘developing code of conduct against discrimination and sexual harassment’, ‘appointing a confidential adviser or a confidential advisory committee’, ‘education of employees (also) from ethnic minority groups’, and ‘offering (job-related) language courses’. In the domain of ‘communication and support’, this type of policy may for example also involve ‘multicultural personnel policy training for managers, personnel specialists and/or members of the works council’. Generally speaking, managing diversity approaches are not only characterized by a ‘qualitative’ focus on the existing workforce, but also by a concern with effectively reconciling organizational interests with the interests of individual employees. After creating the first two clusters, 11 policy items remained. Two of them could not be categorized because their content was either unknown or unspecific (policy items number 14 and number 32 in Appendix 1). The remaining nine policy actions could all be categorized as policies designed to analyze the situation with regard to ethnic diversity in the organization. With this type of policy, work organizations aim at gaining insight into the representation of ethnic minorities and possible explanations for their underrepresentation. The presence of these policy items in the manual for employers is not surprising, since one of the central aims of the law was to raise awareness in Dutch work organizations of the inequitable labor market participation of ethnic minorities. Furthermore, the fact that several policy actions aimed at analysis and research were reported by the organizations in the dataset shows that in these years, organizations were indeed starting to explore the issue. One of the most popular policy actions in this cluster is ‘having exit conversations with employees (also) from ethnic minority groups’ (mentioned in 38% of the Wet SAMEN reports). Intuitively, asking why people leave seems an effective and efficient way of gaining knowledge about inter-ethnic relations at the shop floor and perceived obstacles for the equitable participation of minorities. ‘Comparing experiences with other organizations’ is also part of the third cluster, as well as ‘using the Helpdesk Minorities/Wet SAMEN’. Some organizations reported a so-called ‘diversity audit’: ‘to determine the starting point (to what extent are (ethnic) diversity and multicultural personnel policy already a reality)’. To test hypothesis 1 and 2, the analysis focuses on the number of policy actions reported in the three domains. In the multivariate analysis testing hypothesis 3, the analysis is based on the

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question, whether an organization reported a certain type of policy (at least once) or not. Hence, in the OLS regression models the three types of policy are entered as dummy variables. Given some deviations from normality in the original constructs, this strategy increased the robustness of the multivariate analysis. Measurement of sector The measurement of sector is also based on the original Wet SAMEN database, as it categorizes all work organizations according to the European NACE system (Nomenclature générale des Activités économiques dans les Communautés Européennes) (Kamer van Koophandel, 2005). Using these codes, it was possible to cluster the organizations in the dataset in three main groups: industry, commercial services, and non-commercial services. Non-commercial services include government, education, and care. In the European context, all organizations in the non-commercial services are commonly referred to as the ‘collective’ or ‘public’ sector, for two related reasons. Firstly, education and care are seen as collective goods, just like the services offered by government agencies. Secondly, turnover rates in the public sector are mostly determined by budgeting – and thus by political decision-making processes. Around the turn of the century, approximately 30% of all jobs in the Netherlands were in the public sector (CWI, 2006: 28). Public sector organizations are the reference group in the multivariate analysis. The most important Dutch industries in December 2001 (in terms of added value and number of jobs) were the food, chemical, metallurgical, machine, electrical, publishing, and motor vehicle industry (Berkhout et al., 2002). The commercial services sector (the ‘tertiary’ sector) is the biggest sector as it includes (almost) all other economic activities: construction, cultural/recreational/other services, retail trade, financial institutions, wholesale trade, hotel/catering, transport/storage/communication, and business services. The two biggest ‘subsectors’ within the commercial services sector (in terms of the number of jobs) are the business services sector (including, amongst others, ICT services, legal services, accountancy, security, and cleaning) and retail trade. As mentioned earlier, primary sector organizations only made up about 2% of all cases, creating a problem of 'uneven split’. Hence, this sector was deleted from the analysis in its entirety. It is likely that the number of primary sector organizations was relatively small due to the fact that the law only applied to organizations with 35 or more employees. In agriculture and fishing, most organizations are probably smaller. Conversely, the fields of minerals and utilities are the domain of a small number of very large organizations. Within the commercial services sector, the size criterion probably impacts the representation of subsectors to a certain extent. The catering industry for example (including hotels, bars, and restaurants) contains a relatively high number of small work organizations. The results of the current analysis do therefore not generalize to small organizations.

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Measurement of the control variables The control variables are all based on the official Wet SAMEN reports, unless stated otherwise. − Year (2001): a dummy variable to control for macro trends and events. The reference group

is formed by all annual reports filed in 2002. − Major city: a dummy variable to control for a possible pro-diversity climate in the four largest

cities in the Netherlands: Amsterdam, Rotterdam, The Hague, and Utrecht. All other Dutch municipalities together form the reference group.

− Ethnic minority representation on the regional labor market: a continuous variable to control for the supply-side on the regional labor market. This measurement is based on the official percentages published each year, to support the implementation of the Wet SAMEN. The proportions were transformed using the logit function (see dependent variable); substitutions were not required.

− Job level: a continuous variable to control for the average job level in organizations (on a scale from 1 to 4).

− Size: a continuous variable to control for the organization size, as measured by the total number of employees at the end of the year. This measurement was transformed by taking the natural logarithm (compare Kalev et al., 2006). Still, 92 reports of very large organizations (more than 1,650 employees) had to be removed (46% of all outliers). 90% of all reports in the final sample features between 35 and 295 employees. The results reported here may therefore not generalize to very large work organizations.

− Full-time/part-time ratio: a continuous variable to control for the share of full-time and part-time jobs in an organization. This measurement was transformed using the logit function. Some substitutions were necessary for cases with no full-time jobs or only full-time jobs (see dependent variable).

− Growth: a continuous variable to control for the general health of an organization, as measured by its growth rate, i.e. the difference between the total number of employees at the beginning of the year and the total number of employees at the end of the year (in percentages). Taking the natural logarithm greatly improved the shape of the distribution.

− Beginning of year ethnic minority representation: a continuous variable to control for the share of ethnic minority workers at the beginning of the year. This variable was calculated in the same way as the dependent variable, except for the fact that it expresses the situation a year earlier, using the information on the inflow and outflow of ethnic minority employees and other employees.

Table 1 shows the descriptive statistics of all variables, for the total sample and by sector. Correlations can be found in appendix 2. On average 7.9 percent of the employees at the end of the year are ethnic minorities. Public sector organizations show the lowest percentage of ethnic minorities at the end of the year (5.7 percent) compared to industrial organizations (10.5 percent) and commercial service organizations (7.5 percent).

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Table 1: Descriptive statistics, total sample and by sector Total (n=8,283) Industry (n=2,036) Commercial

services (n=4,814) Public sector

(n=1,433) mean stddev mean stddev mean stddev mean stddev End of year ethnic minority representation*

0.079 0.097 0.105 0.103 0.075 0.098 0.057 0.070

Policies designed to analyse ethnic minority representation (dummy)

0.521 0.500 0.506 0.500 0.518 0.500 0.552 0.497

Policies designed to improve the influx of ethnic minorities in organizations (dummy)

0.698 0.459 0.660 0.474 0.695 0.460 0.760 0.427

Managing diversity instruments designed to improve the management of a diverse workforce in organizations (dummy)

0.577 0.494 0.591 0.492 0.551 0.497 0.646 0.479

Industry 0.246 0.431 Commercial services

0.581 0.493

Public sector 0.173 0.378 Year (2001) (dummy)

0.510 0.500 0.531 0.499 0.502 0.500 0.505 0.500

Major city (dummy) 0.111 0.314 0.043 0.202 0.138 0.345 0.114 0.318 Regional labor market ethnic minority representation**

0.098 0.040 0.090 0.038 0.102 0.041 0.095 0.039

Average job level*** 2.615 0.618 2.449 0.474 2.572 0.637 2.991 0.580 Size** 146.694 192.634 145.854 180.259 120.967 154.976 234.318 278.935 Full-time/part-time ratio**

0.686 0.291 0.866 0.123 0.703 0.278 0.376 0.257

Growth** 0.024 0.117 0.001 0.103 0.024 0.125 0.058 0.098 Beginning of year ethnic minority representation**

0.076 0.096 0.102 0.101 0.072 0.098 0.054 0.068

*This continuous variable was transformed before being entered into the regression analysis. **These continuous variables were transformed and standardized before being entered into the regression analysis. ***This continuous variable was standardized before being entered into the regression analysis.

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52.1 percent of the organizations report the presence of policies designed to analyze ethnic minority representation. Policies designed to improve the influx of ethnic minorities in organizations are present more frequently: almost 70 percent of the organizations report this kind of policy. 57.7 percent of the organizations report managing diversity instruments designed to improve the management of a diverse workforce in organizations. Correlations show that in several organizations the three policy types go hand in hand (see appendix 2). The correlation coefficients vary between .42 and .59, values that do not yield problems of multicollinearity in the regression model. All in all, 80 percent of the organizations report some sort of diversity management policy. As a consequence, 20 percent do not (percentages not in the table). 55.2 percent of the public sector organizations report the presence of policies designed to analyze ethnic minority representation, compared to 50.6 percent of the industrial organizations and 51.8 percent of the commercial service organizations. For the policies designed to improve the influx of ethnic minorities in organizations the difference between public and private sector organizations is larger: 76.0 percent of the public sector organizations report the presence of one or more policies designed to improve the influx of ethnic minorities in organizations, compared to 66.0 percent of the industrial organizations and 69.5 percent of the commercial service organizations. The public sector also shows the highest share of organizations reporting managing diversity instruments designed to improve the management of a diverse workforce in organizations: 64.6 percent of the public sector organizations report the presence of managing diversity instruments, compared to 59.1 percent of the industrial organizations and 55.1 percent of the commercial service organizations. For all three sectors the share of organizations reporting a type of policy is the highest for policies designed to improve the influx of ethnic minorities in the organization. 84 percent of the public sector organizations report some sort of diversity policy (16 percent do not), compared to 80 percent of commercial service organizations and industrial organizations (percentages not in the table). 4 Results 4.1 Diversity policies in the public and private sector In the previous section it was shown that relatively speaking public sector organizations more frequently report the presence of some sort of diversity management policy. To test hypotheses 1 and 2 however, we also need to know the number of policies that are reported by the organizations. Table 2 shows the average number of diversity policies by sector. Public sector organizations report on average 5.34 policies compared to on average 4.25 policies reported by private sector organizations. Public sector organizations report more policies designed to improve the influx of ethnic minorities and more managing diversity instruments designed to improve the management of a diverse workforce than private sector organizations. For both sectors the average number of policies designed to improve the influx of ethnic minorities is higher than the average number of managing diversity instruments. However, the

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sector differences in the average number of policies are relative large with respect to policies designed to improve the influx of ethnic minorities. Table 2: Number and type of diversity policies by sector, 2001/2002

Public sector

(n=1,433)

Private sector

(n= 6,850)

t

Policies designed to analyze ethnic minority

representation

1.06 1.03 0.757

Policies designed to improve the influx of ethnic

minorities in organizations

2.29 1.61 12.596***

Managing diversity instruments designed to improve

the management of a diverse workforce in

organizations

1.84 1.48 6.997***

Total 5.34 4.25 8.824***

* p<.05; ** p<.01; *** p<.001 All in all, hypotheses 1 and 2 are confirmed: public sector organizations report more and different types of diversity management compared to private sector organizations.8 The greater emphasis of public sector organizations on policies designed to improve the influx of ethnic minorities can be explained by their more formalized and symbolic character. In addition, public sector organizations report more often policies designed to improve the influx of ethnic minorities probably because the representation of ethnic minorities in public sector organizations is lower compared to private sector organizations. 4.2 Effectiveness of diversity policies To test hypothesis 3 the effectiveness of the three types of diversity policies is estimated. Table 3 presents the findings of an OLS regression analysis. The dependent variable is ethnic minority representation by the end of the year in logit form (a transformed variable with a mean of -3.022 and a standard deviation of 1.252). In the first model only the three types of diversity policies are adopted as independent variables. Controlling for the presence of the two other policy types policies designed to analyze ethnic minority representation are positively associated with ethnic minority representation in the organization. The effect of the presence of managing diversity instruments on ethnic minority representation is also positive and statistically significant. In contrast, policies designed to improve the influx of ethnic minorities are negatively associated with ethnic minority representation.

8 The differences between public and private sector organizations in the number of policies designed to

improve the influx of ethnic minorities in organizations and in the number of managing diversity policies are

statistically significant, also after controlling for the control variables mentioned in section 3.

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In model 2 two sector dummies are added as independent variables. Public sector organizations are the reference category. As was shown in the previous section, private sector organizations have higher shares of ethnic minority employees than public sector organizations. The coefficients of the three policy types only change slightly after adding sector to the model. Model 3 shows that controlling for sector and other economic factors does not change the conclusions with respect to the association of the three policy types with ethnic minority representation. The model also shows that controlling for economic circumstances and average job level the ethnic minority representation is still lower in public sector than in private sector organizations. Compared to the sector and several control variables, the policy variables play a relatively modest role in predicting ethnic minority representation at the end of the year. Comparing the beta coefficients, industrial sector, major city and the representation of ethnic minorities on the regional labor market have the greatest positive impact on the representation of ethnic minorities in the organization. The effect of average job level is negative and also relatively large, which is not surprising given the fact that the ethnic minorities are on average less educated than the native Dutch: the higher the average job level in an organization, the less ethnic minorities are represented. Finally, the representation of ethnic minorities is higher in larger and growing organizations and organizations with a relatively high number of part-time jobs. By controlling for ethnic minority representation at the beginning of the year, model 4 estimates the effects of the three policy types on the changes in ethnic minority participation rates in the course of a year, using the Lagged dependent variable (LDV) method. The results show that policies designed to analyze ethnic minority representation and policies designed to improve the influx of ethnic minorities in organizations do not affect the annual developments in numerical employment equity. The unstandardized coefficients of these policy variables are close to zero and no longer significant. By contrast, managing diversity instruments have a positive impact on changes in ethnic minority representation in the course of a year. The effects of the sector variables are still statistically significant. The average improvements in ethnic minority representation in the course of a year were better in the industrial sector and commercial services than in the public sector in these particular years. This effect can not be attributed to the effects of the different policy types, as they are controlled for. In addition, all control variables in the longitudinal model still contribute to the prediction of the dependent variable. Moreover, the effect of ‘year’ is significant now: average improvements in ethnic minority participation rates were better in 2001 than in 2002 (controlling for the other variables). This may be explained by macro political-economic trends and events: the end of the economic boom, September 11th, and the Dutch electoral turmoil (the rise and murder of Pim Fortuyn). In addition, the coefficients of the growth variable now indicate a small negative effect rather than a small positive effect. Apparently, whilst ethnic minority representation is higher in growing organizations, in these particular years ethnic minorities were underrepresented in the net inflow of workers.

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When the LDV model is estimated for the three sectors separately (see appendix 3), only the effect of managing diversity instruments in the commercial services is statistically significant. Whereas in the commercial services managing diversity policies positively affect the annual change in ethnic minority representation, in the industrial sector and in the public sector there is no such an effect. The incidence of managing diversity policies is the lowest in the commercial services (see section 3), but when these organizations have such policies, they turn out to be effective. To test for sector differences in the effects of diversity policies model 5 is estimated (see again table 3). In this model the interactions of the three policy types and sector are adopted. None of the interaction effects is statistically significant. In other words, there is no evidence for sector differences in the effectiveness of diversity policies. Hypothesis 3 must be rejected.

Table 3: effectiveness of three types of diversity policy on ethnic minority representation (OLS regression analysis) Model 1 Model 2 Model 3 Model 4 Model 5 B se beta B se beta B se beta B se beta B se beta

Constant -3.11*** .026 -3.50*** .040

-3.63*** .042 -3.11*** .013 -3.11*** .019

Policies designed to analyze ethnic minority representation

.175*** .034 .070 .180*** .034 .072

.135*** .031 .054 .007 .009 .003 .009 .022 .004

Policies designed to improve the influx of ethnic minorities in organizations

-.327*** .034 -.120 -.287*** .033 -.105

-.259*** .031 -.095 -.008 .009 -.003 .003 .024 .001

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

.384*** .036 .151 .371*** .035 .147

.350*** .032 .138 .036*** .010 .014 .030 .024 .012

Industry .785*** .042 .270

.951*** .046 .327 .068*** .014 .023 .091*** .024 .031

Commercial services .307*** .036 .121

.312*** .039 .123 .047*** .011 .018 .045* .021 .018

Year (2001)

.032 .025 .013 .033*** .007 .013 .033*** .007 .013

Major city

.835*** .043 .209 .064*** .013 .016 .064*** .013 .016

Regional labor market ethnic minority representation

.261*** .013 .208

.017*** .004 .014 .017*** .004 .014

Average job level

-.196*** .013 -.155 -.012** .004 -.010 -.012** .004 -.010

Size

.101*** .013 .081 .012** .004 .009 .012** .004 .009

Full-time/part-time ratio

-.118*** .014 -.094 -.022*** .004 -.017 -.022*** .004 -.017

Growth

.031* .012 .025 -.014*** .004 -.011 -.014*** .004 -.011

Beginning of year ethnic minority representation

1.190*** .004 .951 1.190*** .004 .951

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23

Policies designed to analyze ethnic minority representation * Industry

.001 .028 .000

Policies designed to analyze ethnic minority representation * Commercial services

-.003 .025 -.001

Policies designed to improve the influx of ethnic minorities in organizations * Industry

-.024 .030 -.007

Policies designed to improve the influx of ethnic minorities in organizations * Commercial services

-.008 .027 -.003

Managing diversity instruments designed to improve the management of a diverse workforce in organizations * Industry

-.012 .030 -.003

Managing diversity instruments designed to improve the management of a diverse workforce in organizations * Commercial services

.016 .026 .006

R2 .030 .074 .212 .932 .932 N 8,283 8,283 8,283 8,283 8,283 * p<0.05; ** p<0.01; *** p<0.001 F changes are statistically significant at the 0.001 level except for model 5.

5 Discussion and conclusion This paper examined sector differences in diversity policies and in their effectiveness. It was hypothesized that compared to private sector organizations public sector organizations report more diversity policies (hypothesis 1) and more often emphasize visible policies that refer to measurable goals (hypothesis 2). Moreover, it was expected that the effectiveness of diversity policies depend on the combination of sector and policy type (hypothesis 3). More specifically, it was hypothesized that managing diversity policies in private sector organizations would be the most effective. The research material consisted of 8,283 annual reports that were filed in the context of the Dutch Act Stimulation Labor Market Participation of Ethnic Minorities (Wet SAMEN 1997-2002). First, it was shown that Dutch public sector organizations report more policies than private sector organizations. What is more, they are relatively more focused on the policies designed to improve the influx of ethnic minorities. These results are in concordance with the hypotheses. Second, the findings in this paper suggest that managing diversity policies are not only positively associated with ethnic minority representation, but also have a positive impact on the representation of ethnic minorities in Dutch organizations in the short run. Policies designed to analyze ethnic minority representation are positively associated with ethnic minority representation too, but they do not affect the annual change in ethnic minority representation. Policies designed to improve the influx of ethnic minority representation are negatively associated with ethnic minority representation and do not affect the annual change in ethnic minority representation neither. The absence of effects of these policies is also found in the literature. There are several explanations for their failure. They may never be implemented at all or have opposite effects, in the sense that they attract ethnic minority employees, but do not succeed in their retention. The positive impact of managing diversity instruments on the annual change in ethnic minority representation is only found for commercial services organizations. For industrial and public sector organizations this impact is not found. Having said this, the sector differences in the effectiveness of diversity policies are not statistically significant. Therefore, the third hypothesis must be rejected. Our findings leave several questions unanswered. First, the findings in the cross sectional analyses point at possible reverse causality (Hoque & Noon, 2004; Naff & Kellough, 2003). Policies may reflect participation rates rather than cause them. As far as the policies designed to improve the influx of ethnic minorities are concerned, this opposite relationship could be straightforward: organizations with relatively few ethnic minority workers set numerical targets to improve representation, but do not yet feel a need to adjust internal managerial practice with the help of managing diversity policies. What is more, they probably want to send out a strong symbolic message which these ‘hard policies’ exactly do (Verbeek, forthcoming). Previous research on these data indicated that many organizations report the policies of formulating target

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figures and tiebreak preferential treatment without assigning responsibility for their implementation which is an indication for their possible symbolic character (Verbeek & Groeneveld, 2010). The possible symbolic character of these policies – in public and private sector organizations - could be the reason that we do not find causal effects. Organizations with relatively many ethnic minority employees on the other hand have a need to devise managing diversity policies to deal with or even strategically benefit from the ethnic differences amongst their staff. This is what ‘managing diversity’ is all about and could be a strong incentive to actual implement these policies. That – in turn - could be the reason for finding effects of managing diversity policies on the change of ethnic minority representation even in the short timeframe of one year. Naff & Kellough (2003) argue that in particular the effects of managing diversity policies must be studied over a longer period, whereas the results of numerical policies could be observed in the short run. In future research diversity policies should be studied in a longer timeframe to be able to disentangle causal relationships (Verbeek & Groeneveld, 2010) and detect the effects of the actual implementation of policies over time (Pitts, 2007; Pitts, et al., forthcoming). In addition, we did not analyze the effects of combinations of policy types. Equal opportunity and affirmative action policies and managing diversity can be considered as complementary. Organizations that complement equal opportunity and affirmative action policies with managing diversity will probably be most effective (Wrench, 2007; Kirton & Greene, 2005)? Research on combinations of policy types and the actual implementation of policy measure could also reveal the possible symbolic character of policies. Then, it could also be examined whether diversity policies in public sector organizations are more often symbolic or ‘empty shells’ than in the private sector. Furthermore, changes in the representation of ethnic minorities in employment are the result of both recruitment and turnover of ethnic minority and native employees that are probably differently affected by different policy types. Future research is needed to examine whether equal opportunity and affirmative action are successful in attracting ethnic minority employees, but perhaps fail in their retention. And managing diversity, does it both attract (see Ng & Burke, 2005) and retain ethnic minorities (Pitts, 2009; Choi, 2009)? Or do (some sorts of) diversity policies repel natives which by definition enhances ethnic minority representation? To conclude, more than in the private sector, in public sector organizations policies designed to improve the influx of ethnic minorities are emphasized. Managing diversity policies, however, appear to be the only policy type that positively affects the annual change in ethnic minority representation. Managing diversity policies probably not only attract new employees, but also succeed in managing the diversity that is already there. It appears that public sector organizations relatively speaking put emphasis on policies that are relatively less effective, possibly for symbolic reasons.

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Verbeek, S.R. (2010a). The Business Case for Diversity or Discrimination? Labour Market Shortages, Diversity Management, and Ethnic Minority Representation in Dutch Organisations. Maastricht: Paper to be presented at the Netherlands Institute of Government (NIG) Annual Work Conference, 25-26 November 2010.

Verbeek, S.R. (2010b). Exclusionary and Inclusionary Discrimination: An Exploratory Factor Analysis of Ethnic Minority Representation in Large Dutch Organisations. Paris: Paper presented at the ESF/QMSS2 Seminar on Measuring Integration and Discrimination, 5-6 July 2010.

Verbeek, S. R. and Penninx, R. (2009). Employment Equity Policies in Work Organizations, in Equal Opportunities and Ethnic Inequality in European Labor Markets. Discrimination, Gender and Policies of Diversity, eds. K. Kraal, J. Roosblad, and J. Wrench, Amsterdam: IMISCOE/Amsterdam University Press, 69-93.

Verbeek, S. and S. Groeneveld (under review). The Effectiveness of Diversity Management Policies in Improving the Representation of Ethnic Minorities in Dutch Organizations.

Wise, L. R. and M. Tschirhart (2000). Examining empirical evidence on diversity effects: How useful is diversity research for public-sector managers? Public Administration Review 60(5). 386-394.

Wrench, J. (2007). Diversity Management and Discrimination: Immigrants and Ethnic Minorities in the EU, Aldershot: Ashgate.

28

Appendix 1: diversity policies: policy types and percentages of organizations reporting the policy 2001, 2002 (1) policies designed to analyze ethnic minority representation (2) policies designed to improve the influx of ethnic minorities in organizations (3) managing diversity instruments designed to improve the management of a diverse workforce in organizations Item no.

Policy Policy type

Tota

l sam

ple

(n=8

283)

Indu

stry

(n=2

036)

Com

m. s

ervi

ces

(n=4

814)

Priv

ate

sect

or (n

=685

0)

Publ

ic s

ecto

r (n=

1433

)

1 Current policy action inflow, recruitment, and selection: making available internships (also) for ethnic minorities

2 40 33 39 37 52

2 Current policy action outflow: having exit conversations with employees (also) from ethnic minority groups

1 38 38 38 38 41

3 Current career policy action: education of employees (also) from ethnic minority groups

3 37 40 35 37 41

4 Current labor relations policy action: developing code of conduct against discrimination and sexual harassment

3 31 29 29 29 43

5 Current labor relations policy action: appointing a confidential adviser or a confidential advisory committee

3 31 29 28 28 44

6 Current policy action analysis/research: turnover employees 1 26 26 28 27 21

7 Current policy action inflow, recruitment, and selection: preferring ethnic minorities over other job applicants, if they are equally qualified

2 26 21 24 23 39

8 Current policy action inflow, recruitment, and selection: formulating target figures for inflow of ethnic minorities

2 21 18 21 20 26

9 Current career policy action: offering (job-related) language courses 3 20 28 18 21 20

10 Current policy action inflow, recruitment, and selection: appointing mentors for coaching new employees (also) from ethnic minority groups

2 17 14 16 15 22

11 Current policy action inflow, recruitment, and selection: using subsidized jobs (also) for ethnic minorities

2 17 10 12 11 44

12 Current policy action: comparing experiences with other companies 1 14 15 14 14 14

13 Selection policy aimed at quality 2 14 17 15 16 6

14 Alternative current policy action [content unknown, SG & SV] n/a 12 13 11 12 14

29

Item no.

Policy Policy type

Tota

l sam

ple

(n=8

283)

Indu

stry

(n=2

036)

Com

m. s

ervi

ces

(n=4

814)

Priv

ate

sect

or (n

=685

0)

Publ

ic s

ecto

r (n=

1433

)

15 Current policy action analysis/research: obstacles inflow and promotion policy (also) for ethnic minorities

1 12 10 12 11 12

16 Current policy action inflow, recruitment, and selection: trainee program (also) for ethnic minorities

2 11 10 11 11 10

17 Current policy action communication and support: assigning responsibility for the implementation of multicultural personnel policy

3 9 8 10 9 9

18 Current career policy action: developing/implementing objective performance and assessment systems

3 9 11 8 9 7

19 Current policy action inflow, recruitment, and selection: using specialized recruitment and selection agency

2 8 10 9 9 6

20 Current policy action: using the Helpdesk Minorities/Wet SAMEN 1 6 5 6 6 8

21 Current policy action communication and support: formulating plan/strategy for multicultural personnel policy

3 5 3 5 4 6

22 Current policy action communication and support: (implementation of) multicultural personnel policy as standard item on the agenda

3 5 4 4 4 6

23 Current policy action inflow, recruitment, and selection: using media channels aimed at ethnic minorities

2 4 3 3 3 9

24 Current policy action analysis/research: diversity audit to determine the starting point (to what extent are (ethnic) diversity and multicultural personnel policy already a reality)

1 4 4 5 4 4

25 Current policy action communication and support: multicultural personnel policy training for managers, personnel specialists and/or members of the works council

3 4 3 4 3 4

26 Current career policy action: formulating target figures for promotion of ethnic minorities to higher functions

3 3 3 3 3 3

27 Recruitment using temp agency 2 3 5 3 4 1

28 Current policy action: calling in Corporate Minority Consultants of the Employment Offices

1 3 2 3 2 5

29 Current policy action inflow, recruitment, and selection: being present on job fairs for ethnic minorities

2 3 2 3 2 4

30 Employment Office contacts 2 2 2 2 2 3

31 Aiming at equitable participation rates 2 1 1 1 1 2

32 Taking notice of the Wet SAMEN n/a 1 1 1 1 1

30

31

Item no.

Policy Policy type

Tota

l sam

ple

(n=8

283)

Indu

stry

(n=2

036)

Com

m. s

ervi

ces

(n=4

814)

Priv

ate

sect

or (n

=685

0)

Publ

ic s

ecto

r (n=

1433

)

33 Current policy action inflow, recruitment, and selection: using tests that have been specially developed for estimating the capacities of job applicants from ethnic minority groups

2 1 1 1 1 1

34 Current policy action inflow, recruitment, and selection: screening tests for effects of cultural aspects

2 1 1 1 1 1

35 Current policy action inflow, recruitment, and selection: building a network with students` unions of ethnic minorities

2 1 0 1 1 1

36 Target figure retaining ethnic minorities 2 1 1 1 1 1

37 Network current workforce 2 1 1 1 1 0

38 Job advertisement aimed at target group 2 0 0 0 0 1

39 Hiring employees target group 2 0 0 0 0 1

40 Selecting [the ethnic minority candidate, SG & SV] if equally qualified 2 0 0 0 0 0

41 Additional training possibilities 3 0 0 0 0 0

42 Special projects 2 0 0 0 0 0

43 Open information meetings 2 0 0 0 0 0

44 Trainee posts policy more ethnic minorities 2 0 0 0 0 0

45 Career planning 3 0 0 0 0 0

46 Formulating target figure 2 0 0 0 0 0

47 Work experience jobs 2 0 0 0 0 0

48 Calling in Helpdesk Wet SAMEN and Corporate Minority Consultants of the Employment Offices

1 0 0 0 0 0

49 Analyzing supply and demand labor market 1 0 0 0 0 0

50 Incorporating the topic of intercultural management in all internal training

3 0 0 0 0 0

51 Employment project Working Together 2 0 0 0 0 0

52 Preferential treatment minorities 2 0 0 0 0 0

53 Employment project I/D jobs 2 0 0 0 0 0

54 Workshop intercultural management 3 0 0 0 0 0

55 Specialized recruitment 2 0 0 0 0 0

56 Law engagement job seekers WIW 2 0 0 0 0 0

32

Appendix 2: correlation matrix (Pearson correlations) 1 2 3 4 5 6 7 8 9 10 11 12 13 1) End of year ethnic minority representation (dependent variable)

1.000

2) Policies designed to analyze ethnic minority representation (dummy)

0.108*** 1.000

3) Policies designed to improve the influx of ethnic minorities in organizations (dummy)

-0.020* 0.429** 1.000

4) Managing diversity policies designed to improve the management of a diverse workforce in organizations (dummy)

0.137*** 0.591*** 0.464*** 1.000

5) Commercial services (dummy) -0.070*** -0.007 -0.007 -0.062*** 1.000 6) Industry (dummy) 0.195*** -0.017 -

0.047***0.016 -0.673*** 1.000

7) Year (2001) (dummy) -0.007 -0.064***

-0.027** -0.079*** -0.018 0.024* 1.000

8) Major city (dummy) 0.249*** 0.039*** -0.007 0.030** 0.103*** -0.124***

0.002 1.000

9) Regional labour market ethnic minority representation

0.260*** 0.069*** 0.003 0.042*** 0.117*** -0.103***

-0.085***

0.382*** 1.000

10) Average job level -0.136*** 0.070*** 0.049*** 0.084*** -0.080*** -0.153***

-0.030** 0.155*** 0.090*** 1.000

11) Size 0.094*** 0.111*** 0.084*** 0.146*** -0.198*** 0.015 -0.007 0.054*** 0.016 0.082*** 1.000 12) Full-time/part-time ratio 0.036** 0.001 -

0.059***-0.009 0.066*** 0.327*** 0.025* -0.007 0.039*** -

0.110*** -0.120*** 1.000

13) Growth -0.005 -0.007 0.022* -0.003 -0.011 -0.112***

0.067*** -0.002 -0.010 0.050*** 0.057*** -0.168*** 1.000

14) Beginning of year ethnic minority representation

0.965*** 0.102*** -0.026* 0.129*** -0.076*** 0.199*** -0.018* 0.241*** 0.255*** -0.134***

0.088*** 0.044*** 0.006

* p<0.05; ** p<0.01; *** p<0.001 (one-tailed test) N=8,283

Appendix 3: regression analyses on subsets Table 3.1: effectiveness of three diversity policies on ethnic minority representation (OLS regression analysis) (subset industry)

Unstandardized Coefficients

Stand. Coeff.

B Std. Error Beta t Sig. (Constant) -2.612 0.047 -55.332 0.000 Policies designed to analyze ethnic minority representation

0.133 0.065 0.057 2.029 0.043

Policies designed to improve the influx of ethnic minorities in organizations

-0.388 0.061 -0.157 -6.334 0.000

1

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.349 0.067 0.146 5.194 0.000

(Constant) -2.832 0.060 -47.423 0.000 Policies designed to analyze ethnic minority representation

0.127 0.061 0.054 2.091 0.037

Policies designed to improve the influx of ethnic minorities in organizations

-0.357 0.057 -0.144 -6.250 0.000

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.389 0.063 0.163 6.190 0.000

Year (2001) 0.050 0.048 0.021 1.039 0.299 Major city 0.357 0.122 0.062 2.928 0.003 Regional labor market ethnic minority representation

0.267 0.025 0.224 10.622 0.000

Average job level -0.418 0.031 -0.272 -13.276 0.000 Size 0.098 0.024 0.082 4.029 0.000 Full-time/part-time ratio 0.137 0.042 0.067 3.295 0.001

2

Growth 0.020 0.026 0.016 0.769 0.442 (Constant) -3.041 0.015 -203.408 0.000 Policies designed to analyze ethnic minority representation

0.011 0.015 0.005 0.718 0.473

Policies designed to improve the influx of ethnic minorities in organizations

-0.014 0.014 -0.005 -0.943 0.346

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.013 0.016 0.006 0.845 0.398

Year (2001) 0.025 0.012 0.011 2.117 0.034 Major city 0.049 0.031 0.008 1.612 0.107 Regional labor market ethnic minority representation

0.023 0.006 0.020 3.623 0.000

Average job level -0.015 0.008 -0.010 -1.828 0.068 Size -0.001 0.006 -0.001 -0.161 0.872 Full-time/part-time ratio 0.008 0.010 0.004 0.808 0.419 Growth 0.005 0.007 0.004 0.789 0.430

3

Beginning of year ethnic minority representation 1.209 0.007 0.964 174.618 0.000

n=2036. R Square Model 1: .032. R Square Model 2: .169. R Square Model 3: .948 (F Changes p< .001)

33

Table 3.2: effectiveness of three diversity policies on ethnic minority representation (OLS regression analysis) (subset commercial services)

Unstandardized Coefficients

Stand. Coeff.

B Std. Error Beta t Sig. (Constant) -3.209 0.034 -95.770 0.000 Policies designed to analyze ethnic minority representation

0.182 0.045 0.072 3.999 0.000

Policies designed to improve the influx of ethnic minorities in organizations

-0.273 0.045 -0.100 -6.117 0.000

1

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.378 0.046 0.150 8.143 0.000

(Constant) -3.302 0.037 -90.111 0.000 Policies designed to analyze ethnic minority representation

0.136 0.042 0.054 3.231 0.001

Policies designed to improve the influx of ethnic minorities in organizations

-0.236 0.041 -0.087 -5.735 0.000

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.331 0.043 0.131 7.697 0.000

Year (2001) 0.024 0.033 0.010 0.739 0.460 Major city 0.775 0.053 0.213 14.692 0.000 Regional labor market ethnic minority representation

0.266 0.018 0.211 14.591 0.000

Average job level -0.139 0.016 -0.114 -8.491 0.000 Size 0.144 0.019 0.103 7.763 0.000 Full-time/part-time ratio -0.157 0.017 -0.120 -9.048 0.000

2

Growth 0.034 0.015 0.029 2.221 0.026 (Constant) -3.070 0.011 -272.591 0.000 Policies designed to analyze ethnic minority representation

0.007 0.013 0.003 0.534 0.594

Policies designed to improve the influx of ethnic minorities in organizations

-0.007 0.013 -0.003 -0.553 0.580

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.046 0.013 0.018 3.511 0.000

Year (2001) 0.042 0.010 0.017 4.097 0.000 Major city 0.060 0.016 0.017 3.669 0.000 Regional labor market ethnic minority representation

0.011 0.006 0.009 2.004 0.045

Average job level -0.005 0.005 -0.004 -0.892 0.373 Size 0.018 0.006 0.013 3.075 0.002 Full-time/part-time ratio -0.030 0.005 -0.023 -5.697 0.000 Growth -0.018 0.005 -0.015 -3.835 0.000

3

Beginning of year ethnic minority representation 1.186 0.005 0.947 215.663 0.000

n=4814. R Square Model 1: .031. R Square Model 2: .183. R Square Model 3: .924 (F Changes p< .001)

34

Table 3.3: effectiveness of three diversity policies on ethnic minority representation (OLS regression analysis) (subset public sector)

Unstandardized Coefficients

Stand. Coeff.

B Std. Error Beta t Sig. (Constant) -3.631 0.065 -55.616 0.000 Policies designed to analyze ethnic minority representation

0.238 0.077 0.099 3.086 0.002

Policies designed to improve the influx of ethnic minorities in organizations

-0.154 0.087 -0.055 -1.771 0.077

1

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.366 0.084 0.147 4.358 0.000

(Constant) -3.728 0.077 -48.211 0.000 Policies designed to analyze ethnic minority representation

0.184 0.069 0.077 2.685 0.007

Policies designed to improve the influx of ethnic minorities in organizations

-0.122 0.077 -0.044 -1.582 0.114

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.323 0.075 0.130 4.310 0.000

Year (2001) 0.040 0.055 0.017 0.726 0.468 Major city 1.212 0.094 0.323 12.917 0.000 Regional labor market ethnic minority representation

0.229 0.030 0.191 7.630 0.000

Average job level -0.204 0.030 -0.160 -6.891 0.000 Size 0.018 0.025 0.017 0.737 0.461 Full-time/part-time ratio -0.102 0.033 -0.072 -3.051 0.002

2

Growth 0.019 0.034 0.013 0.564 0.573 (Constant) -3.086 0.025 -121.356 0.000 Policies designed to analyze ethnic minority representation

0.009 0.022 0.004 0.429 0.668

Policies designed to improve the influx of ethnic minorities in organizations

0.000 0.025 0.000 0.017 0.987

Managing diversity instruments designed to improve the management of a diverse workforce in organizations

0.037 0.024 0.015 1.519 0.129

Year (2001) 0.011 0.018 0.005 0.641 0.521 Major city 0.105 0.032 0.028 3.319 0.001 Regional labor market ethnic minority representation

0.025 0.010 0.021 2.549 0.011

Average job level -0.034 0.010 -0.027 -3.546 0.000 Size 0.010 0.008 0.009 1.223 0.221 Full-time/part-time ratio -0.010 0.011 -0.007 -0.976 0.329 Growth -0.026 0.011 -0.017 -2.318 0.021

3

Beginning of year ethnic minority representation 1.168 0.010 0.935 111.514 0.000

n=1433. R Square Model 1: .037. R Square Model 2: .254. R Square Model 3: .923 (F Changes p< .001)

35