'Better Choices, Decent Work' - Using Behavioral Design to Improve Labor Market Programs in Low- and Middle-Income Countries

Author(s)
Aibana, K. , Barofsky, J. , Datta, S. , Jean-Francois, J. & Martin, J.
Publication language
English
Pages
25pp
Date published
01 Mar 2020
Publisher
Ideas42
Type
Research, reports and studies
Keywords
Markets, Livelihoods, Poverty, Urban

Decent work—or work that is “productive and delivers a fair income, security and social protection” for individuals and their families—is widely acknowledged to be critical for access to basic needs, poverty reduction, social cohesion, and the promotion of political stability. As a result, programs and policies that seek to create decently paid and secure jobs, improve rates of labor market participation, and reduce unemployment rates are priorities for governments around the world. Historically, governments have intervened directly to connect workers to more and better employment opportunities using a class of programs known as active labor market policies, (ALMPs), which research shows have a mixed record in terms of impact. In particular, their impact is severely curtailed by two common problems: low take-up and low persistence rates. These problems are often even starker for historically vulnerable groups, such as women and those with the lowest incomes.3

In this paper, we argue that cognitive and behavioral phenomena can help explain and potentially address these shortcomings and patterns of impact. Specifically, we identify three broad classes of behavioral bottlenecks;

  1. The long-term benefits of education and vocational training are hidden from view;
  2. Assumptions about employment opportunities are more accessible than facts about employment; and 
  3. The benefits of ALMPs come in months and years while the costs are felt immediately.

After reviewing each bottleneck, we use insights from behavioral science to provide design recommendations for addressing each barrier as well as examples from research studies on some of the recommendations. 

Authors: 
Aibana, K. , Barofsky, J. , Datta, S. , Jean-Francois, J. & Martin, J.