QUANTITATIVE METHODS
4 Matching methods
Pauline Givord
Abstract
Matching is a quantitative method for ex-post evaluation in which, in the absence of direct experimentation, a counterfactual situation is reconstructed by comparing the situations of beneficiaries of an intervention with those of non-beneficiaries with very similar characteristics. This method is particularly useful for evaluating the impact of a programme on a whole population, when sufficiently precise data exist to compare beneficiaries and non-beneficiaries.
Keywords: Quantitative methods, ex post evaluation, causal effect, propensity score, common support
I. What does this method consist of?
Matching methods are among the main quantitative methods for ex-post evaluation, aiming to measure the effect of a public policy tool or programme (e.g. a training programme for jobseekers, or localised aids in certain territories) on the situation of the beneficiaries. As with most quantitative evaluation methods, the aim is to estimate the causal effect of the intervention on the situation of the beneficiaries (for example, a return to employment after training, or the economic activity of the targeted territory). The objective of matching methods is to estimate this causal effect by comparing the situation of beneficiaries of the programme with that of people who have not benefited from it, but whose characteristics are so similar that it would have been possible for them to benefit from it. The observation of these non-beneficiaries is supposed to give an idea of the “counterfactual” situation, that which the beneficiaries would have experienced in the absence of the programme.
The challenge here is to reduce the selection effects that can occur when one wishes to estimate the effect of an intervention. In general, the beneficiaries have not been designated by chance, and they have specific characteristics that can explain by themselves a more or less favourable evolution, even in the absence of the programme being evaluated. For example, the evaluation of a training programme aimed at people furthest from employment cannot be done simply by comparing the chances of return to employment of beneficiaries before and after the training, at the risk of underestimating the effect of the programme for the most disadvantaged public. Nor is it possible to compare the return-to-work rates of trainees with those of the non-trained population as a whole: the latter are too different for their employment situation to be a likely reflection of what the trainees would have experienced in the absence of training.
The principle of matching methods is to restrict the comparison of trainees to comparable non-trainees. Specifically, each beneficiary of the programme being evaluated is matched with one or more “twin” non-beneficiaries, in the sense that they have very similar individual characteristics in all dimensions that may influence both benefiting from the programme and their subsequent situation. I