The short answer is yes, they have a seemingly small, but significant positive impact on the likelihood to find work. This is what a recent so-called “meta-study” finds, summarizing the evidence of 207 different evaluations. Crucially, the evidence suggests that the impact of ALMPs depends on the time horizon one looks at. The effects become much larger with longer time horizons. In the short run, program participants only have a 1.6 percentage point higher probability of finding work within the first year when compared to non-participants. For example, if out of 100 non-participants, 30 had a job after one year, 31.6 had a job among the participants—a small difference indeed. However, in the medium term, between one and two years after program completion, the difference grows to 5.4 percentage points, and after two years, to 8.7 percentage points. So, if after two years, 50 out of 100 non-participants had a job, 58.7 had a job among the participants—a much bigger difference than within the first year.
Figure 1 plots the effect estimates (and their confidence intervals) by program for the short, medium, and long term. Clearly, one can observe a shift towards higher impact when going from short to long run. The various programs are “stacked” above each other, ranked from the programs with the least impact at the bottom all the way up the program with the highest impact at the top. The red diamond represents the actual effect estimate for that program, and the blue line the confidence interval around the point estimate. For example, the least well-performing program for the short term estimated an average effect of about -0.06, corresponding to a negative effect of about 6 percentage points. The confidence interval for that estimate ranges from about -0.11 to -0.01, making this estimate statistically significant because it is entirely left to zero. On the other hand, the best-performing program in the short run had an estimated effect of more than +0.2 (20 percentage points), with a confidence interval ranging from about 0.1 to 0.3 (also statistically significant as the confidence interval is entirely to the right of zero). As one goes from short to long run, one can observe how the estimates and their confidence intervals start moving towards the right, implying that programs have higher impact in the long run.