SabaRanjbar

This paper estimates models of the evolution of cognitive and noncognitive skills and studies the role of family environment in shaping these skills in teenage years. I estimate a dynamic factor model to solve the issue of endogeneity of inputs and multiplicity of inputs relative to instruments. The model is estimated once for the 1988 sample between the ages of 14 to 16, and a second time, for high school graduates only, in both 1988 and 2009 cohorts between the ages of 14 and 18. This paper differs from others in the literature by looking at the evolution of skill production technology in teenagers and young adults over a span of 20 years instead of estimating the production function only for one cohort and in early childhood. The results show that parental investments (both in terms of time and money) improved noncognitive skills but not cognitive skills for the 1988 cohort. The effect on cognitive skills has increased in the later cohort.

KeywordsChild Development · Human Capital · Cognitive Skills · Noncognitive Skills · Parental Investments

I estimate a dynamic model of schooling on two longitudinal datasets (the National Education Longitudinal Study of 1988 and the High School Longitudinal Study of 2009) and find that the effect of relative family income on education has decreased between the early 1990s and the early 2010s. After taking into account a cognitive ability measure (a math test score), family background variables and unobserved heterogeneity, the marginal effects of relative income on grade progression in college have become smaller for the younger cohort. After substituting the math test score quartiles as measures of cognitive ability by an estimated cognitive factor, the effect of relative family income in the two cohorts becomes smaller and the differences between the two cohorts are not statistically significant. Meanwhile, in the same period, the effect of unobserved heterogeneity in explaining the variation in educational attainment has increased significantly.

KeywordsInequality · Education · Family Income · Cognitive Ability · Unobserved Heterogeneity

Students' participation in the labor force is the norm for a large proportion of high school students in many countries including the US. Data from the National Education Longitudinal Study of 1988 (NELS:88) show that in 1990, around 56 percent of 10th grade students in the US were working during school days, while this number for the same cohort had increased to almost 70 percent in 1992 when most of the students were in 12th grade. Around 20 years later, data from the High School Longitudinal Study of 2009 (HSLS:09) show that although the number of students working while in school has decreased, the proportion is still high — between 46 and 50 percent of students in 9th and 12th grades work for pay during school days.

Using data from these two American surveys, this paper examines the effect of school year employment and participation in extracurricular activities on academic performance, specifically the grade point average. Since the decision to work or participate in extracurricular activities is endogenous, several methods were used in this paper to overcome this issue. The results show that in 1990, working while in school had no significant impact on students' GPAs, but in 1992, when most students in the cohort were in 12th grade, working decreased their GPAs. In 2009, working had a negative impact on GPAs among grade 9 students. Working in 2012, when most students were in 12th grade, also had a negative impact on their GPAs. Contrary to the effect of working, participating in extracurricular activities significantly improves academic performance.

KeywordsStudent Employment · Extracurricular Activities · After-School Activities · Educational Performance · GPA

Purpose

This paper examines immigrant earnings trajectories and labour-market positioning across industries and employment arrangements in six Canadian provinces, and how industry patterns relate to digital intensity, telework feasibility, and productivity-relevant allocation.

Design / Methodology / Approach

Canadian Census microdata, 1971–2021, compare immigrant and native-born earnings across ten arrival cohorts by gender and age at arrival. For two recent cohorts, an earnings-based positioning measure combines industry mean annual earnings with full-time or part-time status; multinomial-logit average marginal effects are estimated. The study also maps 2021 industry employment shares to external digital-intensity and telework-feasibility classifications. Individual productivity, artificial-intelligence (AI) adoption, ICT use, and remote-work uptake are not observed.

Findings

Entry earnings gaps and incomplete cohort convergence persist, especially among women and recent cohorts. Across the two positioning cohorts, immigrants are less likely than comparable native-born workers to hold full-time jobs in higher-earnings industries; gaps vary by source region and do not uniformly narrow. Education is associated with better positioning but does not eliminate gaps. Immigrant employment is more concentrated in many digitally intensive categories but less concentrated in several higher-earnings, high-telework-feasibility industries; digital intensity is not systematically related to immigrant employment shares.

Originality / Value

The paper combines five decades of earnings evidence across ten cohorts with a two-cohort positioning measure and descriptive digital and telework mapping. It complements individual-level careers research by identifying structural differences in opportunity access with possible, unmeasured productivity implications.

KeywordsImmigrant Earnings Assimilation · Labour-Market Allocation · Industry Positioning · Remote Work and Digital Intensity · Labour-Market Inequality

We examine the wage earnings of employed immigrants in Canada. Using IMDB linked with LAD data, a sample of immigrants is compared to a matched sample of native-born workers. Employing recentered influence function (RIF) quantile regressions to wage earnings, the industry-based Oaxaca–Blinder decomposition approach tries to show whether immigrants perform better than natives at certain quantiles of the wage, controlling for individual and industry characteristics.

This study develops a discrete choice dynamic programming model to examine immigrants' labour supply, schooling investment, and home-production decisions in Canada from arrival to retirement. Following a Keane–Wolpin-style optimal stopping framework, the model captures how immigrants dynamically trade off current earnings against the long-term returns to Canadian human capital. Using rich post-landing data, the estimation quantifies the role of skill transferability, labour market uncertainty, and education investment in shaping long-run economic assimilation. The results shed light on how policy can accelerate productive integration through targeted human capital support.