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The impact of a job search planning intervention on job search efficiency and employment among youth in South Africa

Location: South Africa
Sample: 1,097 unemployed youth
Timeline:
2015
Target Group: 
Job seekers
Youth
Outcome of Interest: 
Employment
Intervention Type: 
Behavioral economics
Nudges and reminders
Job counseling
Partners:

While many factors contribute to high unemployment in South Africa, the time it takes for job seekers and employers to find good employment matches is one important component. In particular, job seekers often procrastinate in their job searches or are slowed down by the complexity of application processes. Yet, there is little rigorous evidence about how to make job searches more effective. Researchers tested the impact of a job search planning intervention on job search efficiency and employment among unemployed youth in South Africa. The planning intervention improved participants’ job search intensity and efficiency, leading to higher rates of employment.   

Policy Issue 

In 2015, 5.5 percent of the global labor force was unemployed, meaning they lacked employment despite being available for and actively seeking work.1 Job seekers and employers may have difficulty identifying the right employment match—job seekers must dedicate significant time to identifying opportunities that suit their interests and skills, preparing job application materials, meeting deadlines, and following up on job leads. Yet, research indicates that job seekers often procrastinate in their job search efforts or are slowed down by the complexity of application processes. Job search plans might help bridge the gap between job seekers’ intentions and actual actions by breaking down tasks and helping them follow through on their plans. To understand how to make job searches more effective, researchers tested the impact of a plan-making intervention on job search efficiency and employment among unemployed youth in South Africa.

Context of the Evaluation 

South Africa’s unemployment rate in 2015 was 25 percent—five times the international rate.2  Unemployment among youth in South Africa was even higher, at 50 percent.3 While many factors contribute to unemployment in South Africa, recent research documented that the time it takes for job seekers and employers to find good employment matches is one component. The South African Department of Labor (DoL) has attempted to address this challenge through a range of cost-effective and scalable employment services such as job counseling and job referrals.

This study took place in the Gauteng province areas of Krugersdorp, Sandton/Alexandra, and Soweto. Unemployed job seekers between the ages of 18 and 35 who registered with the Employment Services of South Africa database in the 18 months prior to the evaluation and who lived within traveling distance from three participating Labour Centers were eligible to take part in the study. The youth who participated were relatively educated, averaging twelve years of education, and 79 percent had previously held a job. Study participants reported being able to dedicate sufficient time to their job search, yet they faced barriers to following through on meeting their intended targets for submitting job applications. For example, they reported submitting an average of 4.4 applications per month, which amounted to 6.6 fewer job applications per week than they intended.  

Young people in a class in South Africa

Photo: Sunshine Seeds | Shutterstock.com

Details of the Intervention 

In 2015, researchers partnered with the DoL to evaluate the effect of a plan-making intervention on job search behavior and employment. Researchers randomly assigned 1,097 unemployed youth to three treatment arms:

  1. The workshop only group received the DoL’s standard ninety-minute career counseling workshop consisting of topics such as job search strategies, CV creation, interview techniques, and access to information and resources for the job search.
  2. The workshop plus planning group received the standard workshop along with a job search planning intervention. The research team designed and provided job seekers with a template in order to develop their own job search plans. The template asked respondents to think about the time they had available in a typical week and fill out a chart with the job search tasks they planned to perform. Respondents also provided specific details regarding how, when, and where they planned to carry out their proposed tasks. To understand the role of peer support, some participants in this treatment arm were randomly assigned to provide a friend’s contact information who would be updated about the participants’ job search goals.
  3. The comparison group received neither the counseling workshop nor the job search planning intervention. 

To understand the importance of reminders, researchers also randomly assigned some participants in the workshop only and the workshop plus planning groups to receive weekly text message reminders about meeting their job search goals.

Researchers conducted two follow-up surveys with all participants five and twelve weeks after the intervention to document job search activities and employment status. Researchers also sent all participants a text message informing them of an actual job vacancy, inviting them to submit an application to a specific e-mail address. This allowed them to observe the quality of applications along with proactive job seeking behavior across the three treatment arms.

Results and Policy Lessons 

While the workshop alone did not lead to any improved employment outcomes, the workshop plus planning intervention improved participants’ job search intensity and efficiency, leading to higher rates of employment.

The workshop plus planning intervention increased the number of applications that job seekers submitted. Although there was no change in the number of hours spent looking for a job, participants in this group reported submitting an average of 0.7 more applications, 15 percent more than the workshop only group and 18 percent more than the comparison group. They were also more likely to submit applications in response to the researchers’ text message regarding a job vacancy. 

Developing a job search plan helped job seekers optimize their job search strategies, leading to higher rates of employment. Participants in both groups had similar quality job applications. Yet, the workshop plus planning group secured more job offers than those in the workshop only group by diversifying their job search strategies. These strategies included visiting employment agencies, dropping off CVs at locations where there were openings, answering advertisements, and searching online.  Job seekers that received the workshop plus planning intervention were also 3.9 percentage points (26 percent) more likely to have received a job offer and 3 percentage points (22 percent) more likely to be employed following the intervention than job seekers who only received the workshop.

The peer support and text message reminders had no impact on the job search or employment outcomes.

These results suggest that a simple and low-cost programmatic tweak such as adding a plan-making activity can boost the effectiveness of existing government unemployment programs.  

 Abel, Martin, Rulof Burger, Eliana Carranza, and Patrizio Piraino. 2019. "Bridging the Intention-Behavior Gap? The Effect of Plan-Making Prompts on Job Search and Employment." American Economic Journal: Applied Economics  11 (2): 284–301.

1The World Bank. 2018. “Unemployment, total (% of total labor force) (modeled ILO estimate).” Accessed October 18, 2018. https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS.

The International Labour Organization. 2018. “Labour underutilization.” Accessed July 5, 2018.  http://www.ilo.org/global/statistics-and-databases/statistics-overview-and-topics/WCMS_470306/lang--en/index.htm

2The World Bank. 2018. “Unemployment, total (% of total labor force) (modeled ILO estimate).” Accessed October 18, 2018. https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS.

3The World Bank. 2018. “Unemployment, youth total (% of total labor force) (modeled ILO estimate).” Accessed October 18, 2018. https://data.worldbank.org/indicator/SL.UEM.1524.ZS?locations=ZA.