Retrospective Impact Assessment

While the prospective IA and accompanying IA assess anticipated impacts, the retrospective impact assessment is primarily used to determine the impacts of legislation that have actually occurred. It involves retrospectively evaluating the degree to which the goal of a piece of legislation has been achieved on the basis of a piece of legislation that has entered into force. The main questions thereby raised are

• Have the goals been achieved with the legislation in force?
• What side effects and effects have occurred? Are these significant?
• What burden and relieving of burdens have actually taken place?
• Have the provisions proved to be practicable, that is, can those addressed comply with them and can the administrative authorities enforce them?
• Is there a need for revision or indeed repeal?

In terms of method, these questions are mostly answered using tried and tested procedures and tools from empirical field research and legal sociology.

As a rule, retrospective IAs are not carried out by the administrative authorities themselves but as research contracts at research institutes. In deciding on the award of the research contract, the administration should bear the following points in mind from the point of view of the gender perspective:

Firstly, it should be made clear at tender invitation stage for the award of the project that the retrospective IA must be carried out in a way that is oriented to gender equality by means of implementing Gender Mainstreaming. In the concrete choice of research institutes or researchers it must be ensured that gender competence is taken into account as a selection criterion.

In the work of the research institute in terms of content, too, attention must be paid to gender aspects in all three phases of the retrospective IA, the conception, review and evaluation phases. The following concentrates on the conception phase because it is particularly important to integrate gender into the working stages of the conception phase. Errors in this phase are carried forward as defects into all subsequent phases and can hardly be rectified any more.

The following working stages should be run through in the conception phase.

• determination of the central review criteria, such as degree to which goal has been achieved, development of costs, acceptance of the legislation, practicability and side-effects;
• description of the impact model on which the piece of legislation under review is based;
• definition of the scope of evaluation;
• formation of hypotheses by formulating measurable assumptions related to the review criteria;
• determination of data collection and of the evaluation process.
  

In the central review criterion of acceptance of the provision, the differentiation of the target group should be kept in view from the gender perspective. Are there discrepancies in the acceptance of a piece of legislation for instance between older women with a high level of education as distinguished from younger men with an immigration background, etc.? The same applies to the side-effects point. Side-effects of a piece of legislation can be very different depending on the person’s life situation. For instance, an increase in kindergarten charges will affect a single parent with a low income differently than a married couple with children with a good income.

In general, it can be said that good empirical research is characterized by its avoidance of systematic bias effects (gender bias), which distort knowledge and perception and thus have a detrimental effect with regard to the social use of the findings of the research. The inclusion of the findings of Women’s Studies and Gender Studies helps to avoid such bias.

This is of course also true in the formation of hypotheses which should also be done in this phase. Gender-specific bias in the development of testable assumptions greatly impair the results of research and therefore their continued usability.

In determining the collection of data and the evaluation process, it should be noted that good data offer information on the target group that is as differentiated as possible. Quality of data exists when they adequately record the lives of women and of men in different life situations. You can find out more about gender equality-oriented data here.

A current example of retrospective IA is the evaluation of the Hartz social security laws [German], which is being carried out taking Gender Mainstreaming into account.


Please click here if you are interested in prospective IA.