Enhancing soft skills in active labor market programs

The government spends a considerable amount on active labor market programs to improve the employment and earning capacity of the unemployed. One of the most common of the active labor market programs is the training program (in the traditional classroom or on the job) that provides unemployed people with general skills or specific professional skills to increase their productivity and employment. However, many individuals lack the basic soft skills such as motivation, career aspirations and interpersonal skills that are required to transition from welfare to work and perseverance in employment – skills that strongly predict labor market success.

Indeed, a growing literature in economics and other social sciences emphasizes the importance of soft skills for human capital formation and labor market success (Hackman et al. 2006, Deming 2017, Aghion et al. 2020). Yet, especially in the adult population, scientific evidence about the potential to improve these skills is limited, and little is known about the impact of such improvements on labor market outcomes and welfare dependence.

In a recent study (Schlosser and Shanan 2022), we provide experimental evidence on whether it is possible to develop or improve the soft skills of unemployed income support claimants and improve labor market outcomes. Using a large-scale randomized controlled trial, we evaluate the effectiveness of an Israeli active labor market program that focuses on increasing work-related soft skills such as motivation, work self-efficacy, self-esteem, and interpersonal skills. Individuals who submitted new income support claims and a fraction of existing claimants in the welfare system were randomized to the treatment and control group in each of the 14 employment offices participating in the test. Randomization took place on a weekly basis in each employment office separately for the incoming flow of job seekers (i.e. new claimants) and current job seekers (existing pool of claimants). Individuals in the treatment group received individual coaching and participated in the therapeutic group workshops for two to seven months, as well as job search assistance. Our study examined the effects of the program based on a sample of 6,151 individuals who were randomly assigned to treatment and control groups in the first year of program implementation.

Our study relates to a large body of literature that evaluates the impact of active labor market programs (see recent reviews of Greenberg et al. 2003, Cluve 2010, Crepan and Van Denberg 2016, Card et al. 2018, and Levy Yeti et al. 2019). . Evidence of the effectiveness of these programs is still mixed. Moreover, evidence of the effectiveness of active labor market programs that focus on soft skills enhancement is scarce. A notable exception is Barrera-Osorio et al. (2020), who find positive employment and wage effects from a program implemented among 663 job seekers in Colombia that provides combined training in both technical and soft skills. Our study expands their results by providing experimental evidence based on complementary and a large-scale randomized controlled trial that focuses exclusively on soft skills training.

The impact of the program on labor market outcomes and welfare dependence

Figure 1 shows the impact of the program on employment by estimating its impact on a monthly basis, from three years prior to the random allocation to the program to 12 months after that event. Figure 1a reports the share assigned between treatment and control groups and Figure 1b reports the difference in control versus treatment in employment with the confidence band. The figure shows that there was a uniform employment trajectory before the randomization of treatment and control groups. 36 months before the randomization, their employment rate was about 32%. In general, for the population enrolled in active labor market programs, the employment rate of both groups shows a decline (referred to as ‘Ashenfelter Deep’) that began about 18 months before randomization and accelerated the year before randomization. Twelve months after the randomization, the control group converted to the observed employment rate three years before randomization (approximately 33%) when the treatment group exceeded its pre-programmed employment rate by a record 41%. Overall, the employment rate increased by 24% compared to the control group average.

Figure 1 Impact of the program on employment

Comments: Figure reports the difference in the treatment and employment rates for the control groups (left panel) and the difference in the treatment and employment rates between the treatment and control groups with a 90% confidence interval (right panel) over time. Month zero corresponds to the month of random assignment.

At the same time, we find that the program reduced participants’ income support dependence by 11 percentage points (26% reduction). Our estimates further suggest that the reduction in the income of the treatment group (related to the control group) is greater than the cost of the program within 12 months after the allocation for treatment.

The effects of the program were significantly greater among those with lower labor force and lower employment prospects, such as dropouts from high school and those with a long history of income support dependence. In particular, the program had a greater impact on individuals who were already seeking benefits when allocating programs (stock samples) related to new arrivals of job seekers.

Impact of the program on soft skills

We surveyed treatment and control group participants 12 to 18 months after randomization to assess their soft skills and self-awareness. We measure:

(1) Self-esteemWhich considers the self-worth and personal values ​​of individuals

(2) Work self-efficacyWhich measures employee confidence in handling workplace situations such as respecting schedules and evaluating co-operation with colleagues

(3) Job-search self-efficacyWhich refers to a person’s confidence in the ability to successfully perform a job search and perform specific job-search tasks

(4) General self-efficacyWhich assesses a person’s confidence in taking action in a wide range of situations

(5) GravelWhich refers to the perseverance and passion of the individual to achieve long term goals.

Figure 2 shows the increasing distribution of these skills for the treatment and control group. We present here the results of stock sampling (i.e. those who were already claiming income support during randomization). The distribution of soft skills among the treated individuals dominates the controls across all levels of soft skills. We noticed that this program increased job-search self-efficacy, job self-efficacy, self-esteem, general self-efficacy, and perseverance. In our work, we also show that these soft skills are associated with higher labor-market outcomes and, as such, mediate a portion of the program’s impact on employment.

Figure 2 Impact of the program on soft skills

Comments: Statistics plot the increasing distribution of soft skills for a sample of individuals who have already claimed income support during the randomization (stock sample). The reported p-values ​​indicate the results of the Stochastic dominance-Whitney test.

Long-term effects and effects during the Covid-19 epidemic

We see that the impact of the program is clear in the long run, even after five to six years of implementation. Individuals who were initially assigned to the treatment group five years after participating in the program, were less likely to claim benefits than those assigned to the control group. These differences persisted during the Covid-19 epidemic, where individuals in the treatment group were less likely to claim benefits than those assigned to the control group. Furthermore, we find that in terms of claiming benefits, treated individuals appear to be more connected to the labor market because they were more likely to be unemployed (instead of welfare) and if unemployed, they were more likely to be in furlough than individuals. Control group.

Conclusion

Our results show that long-term unemployed people can improve their work-related attitudes and self-awareness in an affordable way, which increases their employment and earnings. Moreover, the benefits of such investments are still evident in the long run and even during the Covid-19 epidemic, providing evidence of an effective intervention that has helped disadvantaged groups better cope with adverse labor market shocks.

References

Aghion, P, A Bergeaud, R Blundell and R Griffith (2020), “Premium for Soft Skill Innovation in Low-Skilled Profession”, VoxEU.org, 2 January.

Barrera-Osorio F, A Kugler and M Silliman (2020), “Hard and Soft Skills in Vocational Training: Experimental Evidence from Colombia”, VoxEU.org, 24 October.

Card D, J. Cluve and A. Weber (2018), “What works? A meta-analysis of recent active labor market program evaluations “, Journal of the European Economic Association 16.3: 894-931.

Crépon, B, E Duflo, M Gurgand, R Rathelot and P Zamora (2013), “What are the displacement effects of labor market policy? Evidence from a cluster random test “, Quarterly Journal of Economics 128 (2): 531-580.

Deming, DJ (2017), “The Growing Importance of Social Skills in the Labor Market”, Quarterly Journal of Economics 132 (4): 1593-1640.

Greenberg, DH, C Michalopoulos and PK Robins (2003), “A meta-analysis of government-sponsored training programs”, Review of industrial and labor relations 57 (1): 31-53.

Levy Yeyati, E, M Montane and L Sartorio (2019), “Understanding what work for active labor market policy”, VoxEU.org, 3 September.

Heckman, J. J., J. Sticksrud, and S. Urjua (2006), “The effects of cognitive and cognitive powers on labor market outcomes and social behavior”, Journal of Labor Economics 24 (3): 411-482.

Kluve, J (2010), “Effectiveness of European Active Labor Market Program”, Labor economy 17 (6): 904-918.

Schlosser, A. and Y. Shannan (2022), “Enhancing Soft Skills in Active Labor Market Programs: Evidence from a Large-Scale RCT”, CEPR Discussion Paper No. 17055.