Letter from 3 ministers, April 2021
Images of the original letter (written in Dutch) can be found here: https://afkomstdata.medium.com/tekst-van-de-brief-van-3-ministers-april-2021-81a3ee1972a6
Also on behalf of the Ministers of Justice and Security and the Interior Business and Kingdom Relations, thank you very much for your letter with recommendations on the way in which Dutch government organisations report on crime rates and migration backgrounds. Hereby I am sending you my response to the letter, with apologies for the long delay.
First of all, I would like to state that in the Netherlands, in a general sense, we find it unacceptable that someone’s place of birth — or that of his or her parents — determines one’s possibilities, opportunities and social position. This applies no less to persons with a migration background.
In your letter you indicate that since the 1990s in several government publications, figures on criminal behaviour are linked to the country of origin of the inhabitants of the Netherlands, also broken down according to generations (first, second and third generation). In addition, you have also studied this form of categorisation in relation to crime figures in government publications. As part of this study you have spoken to a number of administrators and researchers of organisations that publish such figures. You indicate that questions about necessity, proportionality, falsifiability and division of responsibilities have been met with unsatisfactory and at times incomplete answers. Finally, you call for a re-evaluation and modification of the way in which government organisations communicate about the migrant background of suspects of crime. You state that with continuation of government communication about crime and migrant background, a number of conditions should be met. Among other things, the government should try to include some other relevant variables in (data) analyses, such as the extent to which networks (families and/or friends) play a role, ethnic profiling and the educational level of parents.
Reading Guide
With this letter I answer — also on behalf of the Minister of JenV and the Minister of the Interior and Kingdom Relations — your letter. I would like to address the following points:
1. The need to break down crime figures according to countries of origin;
2. the objective of government policies and the role of categorisation by countries of origin;
3. the importance of explanatory analyses for the deployment of effective policies.
The necessity of a breakdown of crime figures by countries of origin
After careful consideration of the pros and cons I come to the conclusion that crime figures broken down by countries of origin per population group are necessary for an effective and efficient policy.
I do think it is important, as you indicate in your letter, to always make a critical assessment of whether and when these figures are really necessary, and only in those situations when this is really the case, to put them together. As far as I am concerned, the necessity may lie in policy and in political-social considerations. As for the latter, I want in this context refer to the motion of MP Van der Staaij. In this motion it is observed that the crime figures still a show a worrying overrepresentation of people with a non-western migration background and therefore requests the government to acknowledge and investigate the problem and develop a targeted approach develop to reduce crime in these groups as well as in its entirety.
Although the descriptive statistics containing a categorisation based on ethnic background are therefore necessary for policy making, and more in particular for evidence-based policy making, I realise well that they can have the unintended side effect that they confirm and reinforce stereotypes and prejudices. In addition to descriptive statistics, also police registrations are an important source for policy information. Actually, these registrations themselves contain no country-of-origin data, as this is sensitive data that only under strict conditions (such as subsidiarity and purpose limitation) may be registered, but by enrichment with country-of-origin data from the Personal Records Database (BRP) it is — within the legal preconditions of privacy legislation — possibly to compile anonymised statistics that provide a reliable basis forms for policy development and evaluation.
Your letter of 8 April 2019 has prompted further reflection, specifically on crime rates in relation to ethnic background. After all, such data can contribute to a self-reinforcing mechanism through the possible confirmation of stereotypical images. At the same time, a further explanation of figures actually contribute to disproving stereotypes, because then it turns out that overrepresentation of certain ethnic groups can often be traced back to generic background features.
Therefore, based on your recommendations, I intend to combine descriptive insights as much as possible with analyses that provide insight into the factors that can explain any over- or explain underrepresentation of groups in crime.
A good example of this are the so-called decomposition analyses that have recently been carried out by Statistics Netherlands and published in the Annual Integration Report 2020. After all, they showed that for almost all origin groups the overrepresentation of young adults with a second-generation migration background in the conviction for crimes can be traced back to generic background characteristics such as education, parental and family structure, material prosperity of the parents, living environment and (previous) convictions of parents. If these categories with a migration background are compared with Dutch people without a migration background with the same background characteristics, the overrepresentation in conviction rates disappears. In other words, for those categories no (origin) specific factors play a role in crime. For the instrumentation of policy, these kinds of insights are fundamental: after all, when this is the case, it means that for the policy goal of equal positions (as outlined later in this letter) no specific (target group) policy is needed, but that a generic approach is sufficient. I intend to put this insight in the spotlight more clearly, in future government communication.
Objective of government policy and the role of categorisation by origin
Since the 1980s, the Dutch government has conducted a policy aimed at combatting inequalities in opportunities and in social positions. The ultimate goal of the policy consists of equal positions for all Dutch people, regardless of background. However, because Dutch people with a migration background are on average less educated than the group without a migration background, it is unrealistic to assume, for example, that they can realise an equal position on the labor market. That is why the policy has an intermediate objective, namely proportional positions. There is proportionality when the different origin groups with similar background characteristics (e.g. age, gender and education) take a comparable position in society. In that case, the difference in factual position can be fully explained with these background factors — just as with the group without a migration background — and origin therefore no longer plays an independent role.
In order to monitor the progress of this policy, the Ministry of Social Affairs and Employment (SZW), among others through the Central Bureau of Statistics (CBS), periodically collect data about the position of population groups with different (migration) backgrounds, about the differences in those positions compared to each other, and about how these differences develop over time.
For the purpose of monitoring this policy, this descriptive information about the actual positions that groups take in relation to each other are indispensable. The insight into the extent to which differences decrease over the course of time and the degree to which positions get closer to each other provides information about target range and the effects of the policy pursued. This is true for areas such as labor and income, education and housing, but also in in the field of crime, this kind of information is important unabatedly. This provides an important insight into the position of individuals and groups.
In doing so, data collection in relation to the position of people with a migration background is limited to the first and second generations. Data on the third generation are not being collected in this context.Importance of explanatory analyses for the deployment of effective policy
At the same time, it should be noted that although these statistics play an indispensable role in a policy process, they ‘only’ provide descriptive information. For policy development, adjustments and instrumentation, there is also need for explanatory analyses that offer insight into the ‘how and why’ of the developments as observed. This could, for example, provide insight into whether generic policy instruments are sufficient to achieve the policy goals, or whether specific instrumentation is useful. The former is the case if there there is proportionality: after all, generic background characteristics then fully explain — just as with the group without a migration background — the differences in position. If this is not the case, on the contrary, there is a reason for specific attention. A good example of this can be found on the labor market: background characteristics such as education, age, gender and work experience explained only part of the unfavourable position that groups with a non-western migration background held on the labor market. Specific attention to ethnic background in data collection is needed in this case to explain the difference in position. This insight was the direct reason for the development and implementation of the policy program Further Integration on the Labor Market (VIA).
In conclusion
In closing, I would like to pass along that considerations regarding which data are support policies are not static. Using scientific research and analysis we shape our policies, these can be generic or group-specific policies. As stated above, I’m committed to provide explanatory background characteristics more clearly into the spotlight in future government communication about crime figures. As the policy goal of equal or proportional positions regardless of origin is more within reach, the need for such data classification will diminish.
That is why I, with my colleagues in this cabinet, will continue to fight hard for equal opportunities to enable full social participation of everyone in our diverse society. Should the need arise, I am happy to involve various civil society organisations in a dialogue about the use and necessity for such categorisation of data in the future.
