Maria Laura Sanchez Puerta

Intragenerational Income Mobility in Latin America

Economic mobility has not been widely studied in developing countries until very recently owing to the lack of suitable data. Studying mobility requires longitudinal data tracking economic units (that is, individuals, households, or firms) over time. Collecting this type of data is expensive, and historically few Latin American countries carried it out. Now, however, such data sets are available for a number of Latin American and Caribbean countries; table A-1 in the appendix provides a list of available panel data sets that can be used for income mobility studies for these countries. In this paper, we discuss how the knowledge gleaned from mobility studies differs from comparable cross-sectional analysis. The structure of the paper is as follows. The next section discusses what mobility is, how it can be measured, and how it differs from inequality. The subsequent section reviews previous mobility studies in Latin American countries. The paper then summarizes the contributions of our own recent work, and the final section discusses what lies ahead in mobility research for Latin American economies.

Accounting for Mismatch in Low- and Middle-Income Countries

To stimulate economic advancement, low- and middle-income countries need well-educated and trained workforces to fill the types of skilled jobs that drive economic growth. Improving educational quality and attainment and providing better training are all rightly put forth as policy recommendations to leverage economic growth and job creation. However, new findings based on large scale surveys of adult skills fromthe World Bank Group’s STEP (Skills Toward Employment and Productivity) Skills Measurement Program suggest that many workers are over qualified for their current jobs (based on the education those jobs require). The results of this study suggest that countries may not reap as much benefit from their investments in quality education and training if weak job creation leaves workers’ skills under utilized. Most of the literature on mismatch focuses on higher-income countries and rates of over-education among college graduates. Accounting for Mismatch in Low- and Middle-Income Countries uses new STEP Skills Survey data from 12 low- and middle-income countries, representing a range of economic and educational and training climates, to better understand the scope and patterns of education and skills mismatch. STEP collects information not only on workers’ level of education and employment status, but also on the types,frequency, and durations of tasks they carry out at their jobs as well as some of the cognitive skills they use.The study also explores additional factors such as gender, health, career stage, and participation in the informal labor sector that may help explain the degree of mismatch rates. The study’s findings indicate thatover-education is common in low and middle income countries with both lower and higher rates of educational attainment. There is also evidence that over-educated tertiary workers do not use all of theirskills, potentially wasting valuable human capital and educational resources. Aimed at policy makers, business and education leaders, and employers, Accounting for Mismatch in Low- and Middle-Income Countries suggests that job growth must go hand-in-hand with investments in education and training.

Taking stock of programs to develop socioemotional skills : a systematic review of program evidence

Possessing a range of cognitive, socioemotional, and technical skills is important for individuals to maximize their chances of success in many aspects of life. In particular, a growing body of research highlights the effects that socioemotional skills have on a variety of outcomes, from wages and academic performance to health. Programs to help participants develop such skills continue to expand in both high-income and lower-income countries, targeting individuals of almost all ages and life stages. Socioemotional skills development is embedded in programs as diverse as early-childhood nutrition programs for adolescent mothers, K-12 academic curricula, and workforce training programs for vulnerable adults. However, the characteristics that make some programs more successful than others, or even what types of outcomes programs use to measure ‘success’, are less clear in the literature. This analysis seeks to fill this knowledge gap through a systemic review of socioemotional skills development programs. To categorize the wide range of socioemotional program objectives, this analysis breaks down programs by where they occur, program characteristics, participant characteristics, and outcomes measured. Only programs with randomized or quasi-randomized evaluations are included. The programs in this review are divided into three categories, on the basis of when they are implemented in the life cycle: (a) before-school programs (infants and young children), (b) school-based programs (preschool to secondary education), and (c) out-of-school programs (usually targeted, vulnerable populations). Next, the review assesses programs by their specific characteristics: objectives, components and complementary elements, setting, and quality.

Employer survey - Snapshot - 2016 : highlights from six low and middle-income countries

The Employer Survey Snapshot features a descriptive analysis of the data collected during the first two waves of the Skills Towards Employment and Productivity (STEP) Employer Surveys. Key objectives of the Snapshot are (1) to explain the motivation and relevance behind the implementation of employer skills surveys and (2) to highlight some of the observed cross-country patterns from six participating countries, namely, Armenia, Azerbaijan, Georgia, Sri Lanka, Vietnam and China (Yunnan Province). The Snapshot provides information on how employers view jobs mismatch and how they identify and value worker skills sets. In addition, it includes insights from innovative firms and examples of training provisions. A section on survey methodology has also been included as an annex.

Do cognitive and noncognitive skills explain the gender wage gap in middle-income countries ? an analysis using STEP data

Gender-based wage discrimination is a highly researched area of labor economics. However, most studies on this topic have focused on schooling and paid limited attention to the mechanisms through which cognitive and noncognitive skills influence wages. This paper uses data from adults in seven low- and middle-income countries that participated in the STEP Skills Measurement Survey to conduct a comparative analysis of gender wage gaps. The paper uses schooling and skills measures, including reading proficiency and complexity of on-the-job computer tasks to proxy cognitive skills, and personality and behavioral measures to proxy for noncognitive skills in wage decompositions. The analysis finds that years of school explain most of the gender wage gap. The findings also suggest that cognitive and noncognitive skills affect men’s and women’s earnings in different ways, and that the effects of these skills vary across the wage distribution and between countries.