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on Education |
| By: | Shure, Nikki (University College London); Zierow, Larissa (Ifo Institute for Economic Research) |
| Abstract: | First-generation university graduates have been found to face a series of disadvantages on their pathway to higher education and the labor market. We use unique, national level data on high achieving university graduates to attempt to disentangle the importance of lower prior attainment from parental educational background on a series of higher education and labor market outcomes. We compare first-generation and non-first-generation graduates who are recipients of a prestigious national scholarship program targeted at the top percentile of the student distribution in Germany. We find the first-generation high achievers are more likely to study at less prestigious institutions and at institutions that are closer to home even though they have the prior attainment to go further afield. They are also less likely to study subjects with high labor market returns and are more likely to work in jobs with high job security. We furthermore find evidence that especially female first- generation high achievers are less likely to see the value of the networking opportunities the scholarship provides. |
| Keywords: | socio-economic gaps, first-generation, higher education |
| JEL: | I24 J24 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16654&r=edu |
| By: | Jan Bietenbeck; Natalie Irmert; Linn Mattisson; Felix Weinhardt |
| Abstract: | We study whether autonomous schools, which are publicly funded but can operate more independently than government-run schools, affect student achievement and school segregation across 15 countries over 16 years. Our triple-differences regressions exploit between-grade variation in the share of students attending autonomous schools within a given country and year. While autonomous schools do not affect overall achievement, effects are positive for high-socioeconomic status students and negative for immigrants. Impacts on segregation mirror these findings, with evidence of increased segregation by socioeconomic and immigrant status. Rather than creating "a rising tide that lifts all boats", autonomous schools increase inequality. |
| Keywords: | autonomous schools, student achievement, school segregation |
| Date: | 2023–12–18 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1968&r=edu |
| By: | DI PIETRO Giorgio (European Commission - JRC) |
| Abstract: | In this report, we conduct a new meta-analysis of papers examining the impact of Covid-19 school related closure on student performance. While we focus only on OECD countries, the present meta-analysis includes, to the best of our knowledge, a larger number of studies (i.e., 55), effect sizes (i.e., 400) and countries (i.e., 21) than previous similar studies. Our results confirm that Covid-19 had, on average, an adverse effect on learning. While the size of the overall learning loss is estimated to be between 0.11 and 0.17 standard deviations of student achievement, learning losses are found to be smaller for pupils in OECD EU countries than for their peers in OECD non-EU countries. The periods of physical school closure were shorter in OECD EU countries than in OECD non-EU countries and this may provide a possible explanation for our finding. Additionally, our study shows that, overall, students seem to have fallen behind in their learning more in the later stages of the pandemic compared with the earlier stages. This finding is at variance with the outcome of earlier meta-analyses concluding that students did not lose any additional ground but failed to rebound. Our result is driven by the inclusion of recent studies showing that pandemic-related learning deficits have accelerated over time. Consequently, our findings suggest that particular attention should continue to be paid towards ensuring that students are able to catch up on what they have missed while schools have been closed. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc134506&r=edu |
| By: | David Cesarini; Erik Lindqvist; Robert Östling; Christofer Schroeder |
| Abstract: | There is a well-established negative gradient between economic status and crime, but its underlying causal mechanisms are not well understood. We use data on four Swedish lotteries matched to data on criminal convictions to gauge the causal effect of financial windfalls on player’s own crime and their children’s delinquency. We estimate a positive but statistically insignificant effect of lottery wealth on players’ own conviction risk. Our estimates allow us to rule out effects one fifth as large as the cross-sectional gradient between income and crime. We also estimate a less precise null effect of parental lottery wealth on child delinquency. |
| JEL: | K0 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31962&r=edu |
| By: | Klauser, Roman (RWI); Tamm, Marcus (Hochschule der Bundesagentur für Arbeit (HdBA)) |
| Abstract: | Do returns to training differ if training is accompanied by technological innovations at the workplace? We analyze this potential heterogeneity of returns based on panel data from Germany that provide a unique measure for individuals' adoption of new technology at the workplace. In the preferred analysis we run fixed effects estimations. As a robustness test we also allow for individual time trends. The findings indicate positive wage effects and more job stability for training participants in general but no effects on wages and job mobility for new technology adoption. Furthermore, the combined occurrence of new technology adoption and of training participation does not make individuals better off in terms of wages or job stability compared with individuals experiencing neither training nor new technology adoption. |
| Keywords: | returns to education, training, technology |
| JEL: | I26 J24 J62 M53 O33 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16659&r=edu |
| By: | James J. Heckman; Rodrigo Pinto; Azeem Shaikh |
| Abstract: | This paper considers the problem of making inferences about the effects of a program on multiple outcomes when the assignment of treatment status is imperfectly randomized. By imperfect randomization we mean that treatment status is reassigned after an initial randomization on the basis of characteristics that may be observed or unobserved by the analyst. We develop a partial identification approach to this problem that makes use of information limiting the extent to which randomization is imperfect to show that it is still possible to make nontrivial inferences about the effects of the program in such settings. We consider a family of null hypotheses in which each null hypothesis specifies that the program has no effect on one of many outcomes of interest. Under weak assumptions, we construct a procedure for testing this family of null hypotheses in a way that controls the familywise error rate--the probability of even one false rejection--in finite samples. We develop our methodology in the context of a reanalysis of the HighScope Perry Preschool program. We find statistically significant effects of the program on a number of different outcomes of interest, including outcomes related to criminal activity for males and females, even after accounting for imperfections in the randomization and the multiplicity of null hypotheses. |
| JEL: | C31 I21 J13 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31982&r=edu |