We highlight the importance of randomisation bias, a situation where the process of participation in a social experiment has been affected by randomisation per se. We illustrate how this has happened in the case of the UK Employment Retention and Advancement (ERA) experiment, in which over one...

One of the most powerful critiques of the use of randomised experiments in the social sciences is the possibility that individuals might react to the randomisation itself, thereby rendering the causal inference from the experiment irrelevant for policy purposes. In this paper we set out a...

The low unemployment rates traditionally enjoyed by Sweden have often been attributed to the country s extensive system of active labour market programmes, which have thus often been regarded as a model for other countries to emulate. The paper investigates the presence of short- and long-term...

The paper evaluates the differential performance of the six main types of Swedish programmes that were available to adult unemployed workers entitled to unemployment benefits in the 1990s: labour market training, workplace introduction, work experience placement, relief work, trainee replacement...

Randomised controlled or clinical trials (RCTs) are generally viewed as the most reliable method to draw causal inference as to the effects of a treatment, as they should guarantee that the individuals being compared differ only in terms of their exposure to the treatment of interest. This...

This paper assesses the impact of Swedish welfare-to-work programmes on labour market performance including wages, labour market status, unemployment duration and future welfare-to-work participation. We develop a structural dynamic model of labour supply which incorporates detailed...

In this paper we study the impact of misreported treatment status on the estimation of causal treatment effects. We characterise the bias introduced by misclassification on the average treatment effect on the treated under the assumption of selection on observables. Although the bias of...