This paper examines the impact of non-cognitive (socio-emotional) skills on job market outcomes using a randomized control trial implemented in an online job portal in India. Job seekers who registered in the portal were asked to take a Big Five type personality test and, for a random sub-sample of the test takers, the results were displayed to potential employers. Outcomes are measured by whether a potential employer shortlists a seeker by opening (unlocking) his/her application and background information. The results show that the treatment group for whom test results were shown generally enjoyed a higher probability of unlock. That is, employers are more interested in those for whom they can see personality test results. Such a relationship was not seen in the pre-test period, which confirms that the above results are unlikely to be spurious. We also found a significant impact among organized, calm, imaginative and/or quiet applicants (no effect was detected among easy-going, sensitive, realistic and/or out-going applicants), which seems to display employers’ preferences.

This paper examines the impact of noncognitive (socio-emotional) skills on job market outcomes, using a randomized control trial implemented in an online job portal in India. Job seekers who registered in the portal were asked to take a Big-Five type personality test and, for a random subsample of the test takers, the results were displayed to potential employers. The outcomes are measured by whether a potential employer shortlisted a job seeker by opening (unlocking) his/her application and background information. The results show that the treatment group for whom test results were shown generally enjoyed a higher probability of unlock. That is, employers are more interested in those for whom they can see personality test results. Such a relationship was not seen in the pre-test period, which confirms that the results are unlikely to be spurious. The study also finds a significant impact among organized, calm, imaginative, and/or quiet applicants (no effect is detected among easy-going, sensitive, realistic, and/or outgoing applicants), which seems to display employers’ preference.

Ethiopia has long prioritized creating more and better jobs as core to its sustainable and inclusive development. However, steady growth in the gross domestic product and gains in agricultural productivity in recent decades have not translated into better opportunities nor increased earnings for much of the population. The 2021 Labor Force Survey data reveal labor trends since 1999 and underscore these realities. Moreover, COVID-19 and other shocks have reinforced the disconnect between positive macroeconomic trends at a national level and stagnant incomes at the household level. Working Today for a Better Tomorrow in Ethiopia: Jobs for Poor and Vulnerable Households outlines how Ethiopia can leverage its social safety net programs to help poor and vulnerable workers earn more in today’s labor market. The government’s latest development planning policies focus on private sector growth and structural transformation to create more and better jobs. While these long-term reforms take hold, the jobs agenda also must include near-term measures to improve worker productivity in and connect people to jobs that already exist. Complementing cash transfers with capital, training, and other services can help workers earn more in their current work, diversify into new types of employment, or connect to available wage jobs.These investments can have an immediate impact for poor people in Ethiopia while also contributing to sustainable and inclusive development.

Informality remains widespread in South Asia despite decades of economic growth. The low earnings and high vulnerability in the informal sector make this a major development issue for the region. Yet, there is no consensus on its causes and consequences, with the debate polarized between a view that informality is a problem of regulatory evasion and should be eradicated, and another that equates informality with economic exclusion. Recent advances in analyzing informality as the outcome of firm dynamics in distorted economic environments can help reconcile them. Building on these advances, the approach adopted in this volume clarifies that there are different types of informality, with different drivers and consequences. The report has four main messages that underscore the need for a multipronged strategy. First, informality in South Asia is dominated by firms that happen to be outside the purview of regulations because they are small, as opposed to those that remain small to escape regulations. Second, reforms of business regulations tend to have small direct effects on the informal sector, although they could have sizable indirect impacts on it if they succeed in removing major inefficiencies in the broader economy. Third, e-commerce platforms offer new opportunities to informal firms and workers, but many of them lack complementary skills or credit to benefit from such technologies. Fourth, a combination of contributory and non-contributory programs recognizing the heterogenous saving capacities of informal workers may be necessary to achieve more universal coverage of social insurance.

Analyzing the distributions of wages for whites, blacks and Hispanics reveals the existence of a wage gap throughout the distribution. There are also clear cognitive and noncognitive skill differences across groups. Do differences in the distributions of these skills explain differences in the distributions of wages? Do predicted distributions of wages resulting from rewarding blacks and Hispanics as if they were white help explain the observed wage gap? Using data from the NLSY79, I look at the impacts of noncognitive skills on wages for blacks, Hispanics and whites. I estimate the entire distribution of wages conditional on skills for blacks and Hispanics to see if there is a difference in wages individuals with the same level of cognitive and noncognitive skills. I find that all cognitive and noncognitive measures examined are important in explaining the wage penalty paid by blacks and Hispanics and that, for blacks, predicting their wages conditional on skills approximates the distribution of actual wages. Do employers recognize noncognitive skills at the onset (interview) or is there a learning process? How does learning about these noncognitive skills occur over time? This paper uses data from the NLSY79 to incorporate measures of noncognitive skills into a model of employer learning described originally by Altonji Pierret (2001). Measures of noncognitive skills include the Rosenberg Self Esteem Score, the Rotter Locus of Internal Control Score, the Coding Speed Score, and the CES-Depression Scale. I find that employers observe an initial signal of self esteem and schooling and that, over time, employers learn about cognitive skills and motivation, placing less emphasis on these initial observations. Does learning transfer perfectly across employers or is there a degree to which learning resets as employees change jobs throughout their careers? In this paper, I use data from the NLSY79 to look for evidence of asymmetric employer learning. I use tests developed by Schonberg (2007) and Pinkston (2009) to look for asymmetric learning in the model from Altonji Pierret (2001) augmented in Petre (2013b) to incorporate noncognitive skills in addition to cognitive skills. I find mixed evidence that learning done by a prior employer might not transfer completely to a new employer.

We study how employers and job-seekers respond to credible information on skills that are difficult to observe, and how this affects matching in the labor market. We experimentally vary whether certificates on workers' non-cognitive skills are disclosed to both sides of the market during job interviews between young workers and small firms in Uganda. The certificates cause workers to increase their labor market expectations, while high-ability managers revise their assessments of the workers' skills upwards. The reaction in terms of beliefs leads to an increase in positive assortative matching and to higher earnings for workers, conditional on employment.

This paper establishes that a low dimensional vector of cognitive and noncognitive skills explains a variety of labor market and behavioral outcomes. For many dimensions of social performance cognitive and noncognitive skills are equally important. Our analysis addresses the problems of measurement error, imperfect proxies, and reverse causality that plague conventional studies of cognitive and noncognitive skills that regress earnings (and other outcomes) on proxies for skills. Noncognitive skills strongly influence schooling decisions, and also affect wages given schooling decisions. Schooling, employment, work experience and choice of occupation are affected by latent noncognitive and cognitive skills. We study a variety of correlated risky behaviors such as teenage pregnancy and marriage, smoking, marijuana use, and participation in illegal activities. The same low dimensional vector of abilities that explains schooling choices, wages, employment, work experience and choice of occupation explains these behavioral outcomes.