Labour markets in low-income countries experience many frictions that impair efficient firm-worker matching (Behrman, 1999). Information frictions can hinder firms’ attempts to observe workers’ skills and productivity (Abel et al., 2016; Bassi & Nansamba, 2017; Carranza et al., 2017), spatial frictions can separate firms and workers (Franklin, 2017), regulatory frictions can deter firms from hiring (Freeman, 2010) and norms around gender and other identities can hurt some workers and small firms (Beaman et al., 2017).
These frictions can harm both workers and firms. Information frictions lead firms and workers to make suboptimal matching decisions, lowering output and wages while increasing costly turnover. This reduces total employment if the risk of bad matches lowers firms’ willingness to hire or workers’ willingness to search for jobs. Information frictions can also lead workseekers to make suboptimal human capital investments: acquiring skills firms do not value or acquiring fewer skills because they cannot credibly signal these to firms. Spatial frictions increase the cost of searching for and traveling to jobs, making otherwise profitable viable firm-worker matches loss-making. Gender norms can bar women from the labour force or shift them into self-employment or suboptimal matches that yield lower earnings and lower productivity.
We propose a series of interventions to alleviate search and matching frictions in the labour market in and around Lahore, Pakistan. We build on the successful development of a labour market search platform for the GLM|LIC-funded intervention “Women’s Access to Public Transport and Labour Force Participation: A Randomized Controlled Trial.” In that project, we offer subsidized transport to workers and workseekers and study the effects on labour supply, employment, and earnings. Given the sharp gender differences in labour supply and labour market outcomes, we examine these effects separately by gender and test if the effect of subsidized transport for women depends on whether the transport is gender-segregated or integrated. We developed an innovative job search platform, Job Talash, to measure outcomes of this intervention and help match workseekers and firms. Job Talash generates rich, high-frequency data on both the supply and demand sides of the labour market.
The proposed project will use Job Talash to randomly vary the frictions facing firms and workseekers and hence quantify the importance of these frictions. Specifically:
- We assess workseekers’ skills and randomly vary the information firms observe about workseekers’ skills to understand demand for specific skills.
- We randomly vary the probability of auditing workseekers’ self-reported qualifications and whether firms know this probability to understand workseekers’ incentives to misreport skills and how firms’ respond to the risk of misreporting.
- We randomly the information workseekers observe about job and firm characteristics such as wages and the gender composition of the workforce to understand labour supply responses to job prospects.
- We randomly vary the information workseekers have about firms’ preferences over workseeker attributes to understand how sensitive workers’ decisions to invest in short-term training and internships are to perceived demand for these attributes.
- We contrast centralized firm-worker matching where we make make explicit recommendations about matches to decentralized matching where we facilitate communication between firms and workers but do not make recommendations.
Together, these interventions assess the role of frictions in workseekers’ decisions job search, short-term human capital investments, and skills misreporting as well as firms’ decisions about which and how workseekers to hire when they face better or worse information about those workseekers’ skills.
We will measure effects of alleviating information frictions on job search, job offers, employment, wages, turnover, and productivity using short, high-frequency phone surveys. Manipulating information frictions facing both firms and workers’ allows us to identify effects on demand, supply, and market equilibrium.
Our work speaks to multiple GLM|LIC research areas. We evaluate a specific set of active labour market policies can address labour market frictions arising from limited information on both sides of the labour market. We study how limited information about human capital and labour productivity affects labour market outcomes and incentives for short-term human capital investments. We study a rapidly urbanizing population with extensive rural-to-urban migration, for whom information frictions may be particularly important.
Our work is also relevant to multiple GLM|LIC cross-cutting themes. We study both women and men but emphasize issues around gender in the labour market. Information frictions in hiring are likely to be particularly damaging to women, who are less able to use referral networks that firms facing information frictions may rely on (Beaman et al., 2017). We explicitly test if the gender composition of the specific workplaces affects women’s labour supply decisions. Finally, we offer a model for improving data for labour market research by running a matching platform that directly collects data on firm-worker interactions and matches, which are unobserved in typical labour market surveys.