More evidence: what effects do economic policy measures have? Guest contribution from Prof Dr Claudia Buch and Regina T. Riphahn published in the Süddeutsche Zeitung

Education policy, labour market policy or housing policy – in many areas, time and again measures are initiated without full knowledge of their impact and of whether they will bring us closer to our avowed goals. How can public funds be used more effectively in order to achieve policy objectives? Systematic evaluations can shed some light on this question. However, Germany lags behind other countries when it comes to using evidence to systematically review the impact of policy measures.
A constructive dialogue between academia and policy-makers can help improve the necessary infrastructures. 

Improved information base for policy decisions

Evidence-based policy follows a continuous, facts-based learning process: it defines objectives, implements projects, assesses their efficacy, adapts and learns for future actions. This is how policy effectiveness can be improved: measures that are ineffective and have adverse side effects are undone, while those which are successful are reinforced.

However, there are practical impediments to this ideal: policy actions are taken under pressure to deliver quick results, and bureaucratic protocol has to be observed. Policy often tends more to be the "art of the possible" than the outcome of an evidence-based process. And yet there is much to be gained by taking measures based on evidence – regarding both their costs and effectiveness.

When searching for evidence, it is important to make a distinction between correlation and causation. Correlation is when two events happen simultaneously, while causation implies a cause-and-effect relationship. It is not enough to observe the coincidence of two events: it’s not raining "because" people are carrying umbrellas (causation) but only "while" they’re carrying umbrellas (correlation).

Policy measures are often assessed by polling participants as to their satisfaction or reviewing whether funds have been spent. These metrics say nothing about whether the desired effects have been achieved, however. The question of causation can be answered using the right methods and data. This enables us to improve both the diagnosis and the therapy of economic ills.

Considerable progress has been made in the past few years: research and teaching now provide superior tools with which we can examine the efficacy of policy action. Initiatives in the political and administrative spheres are afoot to harness these findings. Moreover, a higher quantity and a higher quality of data are available.

Two examples of evidence-based policy

In the 1990s, contributions to unemployment insurance running into the billions were invested in active labour market policy, job creation schemes or "one-euro jobs". As analysis after analysis showed the negative impact of these programmes, they were scaled back and replaced by more effective measures.

Family policy measures relating to objectives such as the work-life balance or the social participation of families have been studied since 2009. Only one measure did not involve a trade-off: the public funding of child day-care achieved its objective of improving the work-life balance without having to make compromises regarding other objectives.

Intensify dialogue between academia and policy-makers

Academically sound analyses cannot take the place of the political decision-making process, though they do provide a basis for better-informed decisions. This calls for an intensified interdisciplinary dialogue between policy-makers and academia. The two examples of successful transfers mentioned in the section above are just the beginning, and others should follow in the same vein.

First, the political and administrative spheres need to be convinced of the added value of evidence-based decision-making. Measures evaluated positively can be continued, while those receiving a negative assessment can be improved upon. The evaluation process requires the creation of a legal basis, the definition of objectives and the identification of milestones for achieving the objective. There are already some highly promising initiatives out there. In the United Kingdom, for instance, the "What Works" programme was created, a network of centres which systematically gather empirical evidence on the efficacy of policy measures. At the international level, last year the G20 under the German presidency adopted a framework for the evaluation of financial market reforms.

Second, the exchange of information between academia and policy-makers needs to be facilitated, such as by using digital platforms. They can enable research findings to be communicated in a more understandable manner and enhance the transparency of administrative processes.

Third, the necessary data have to be available. It can be very expensive or even impossible to collect data retrospectively. Pilot studies can help identify the data requirements before implementing a measure. Broad access to data can boost the quality of evaluation studies – and this does not run counter to the central role of data protection.

Fourth, incentives to support policy through good evidence should be enhanced in the academic community.

Fifth, Germany, of all countries, with its independent research institutions and research data centres, has an excellent infrastructure which can be used even better as an interface between academia and practitioners.

Incorporating "more evidence" into political decision-making processes is a key societal goal. It requires increased commitment, openness and a willingness on the part of academia and policy-makers alike to engage in dialogue. The better the available structures are used and evaluations embedded into ongoing processes, the lower the costs of evaluations – and the more we can learn from experience.