Skills, earnings, and employment: exploring causality in the estimation of returns to skills

Hampf, Franziska; Wiederhold, Simon; Woessmann, Ludger

doi:10.1186/s40536-017-0045-7

Cited by 49 publications

(43 citation statements)

References 56 publications

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“…Based on the German PIAAC data, it can be seen that the students affected by the two short school years have indeed received a total of three quarters of a year less instruction ( (Hampf, 2019 [26]) Table 3). This loss can also be seen in the long-term skills of the pupils concerned: even in the age group from early 50s to late 60s, the maths skills are still about a quarter of a standard deviation lower because of the two years of short schooling ( (Hampf, 2019 [26]), Table 4).…”

Section: The Experience Of the German "Short School Years"mentioning

confidence: 99%

The economic impacts of learning losses

2020

OECD Education Working Papers

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This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. 2  EDU/WKP(2020)13 THE ECONOMIC IMPACTS OF LEARNING LOSSES Unclassified OECD EDUCATION WORKING PAPERS SERIES OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed herein are those of the author(s). Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcome, and may be sent to the Directorate for Education and Skills, OECD,

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Section: The Experience Of the German "Short School Years"mentioning

confidence: 99%

The economic impacts of learning losses

2020

OECD Education Working Papers

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“…At the macro level, growth of a country's national gross domestic product (GDP) has been associated with increasing levels of literacy and numeracy proficiency (Schwerdt and Wiederhold 2018). Franziska Hampf et al (2017) have provided various kinds of converging evidence that the observed relationships between proficiencies and economic outcomes are causal in nature.…”

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confidence: 99%

Practice makes perfect: Practice engagement theory and the development of adult literacy and numeracy proficiency

2020

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Practice engagement theory (PET) posits that individuals' literacy proficiencies develop as a by-product of their engagement in everyday reading and writing practices and, reciprocally, that literacy proficiencies affect levels of engagement in reading and writing practices. This suggests that literacy training which increases engagement in meaningful practices might generate proficiency growth. Research has shown that this approach does indeed seem to be effective in improving (adult) learners' literacy proficiency. A number of cross-sectional comparisons of participants' and non-participants' performance in various training activities, as well as quantitative modelling of adults' proficiency growth in longitudinal studies have confirmed the theoretical assumptions of PET. The authors of this article describe the first application of PET to literacy and numeracy development in a longitudinal study of a nationally representative adult population. Their investigation followed a sample of adults initially interviewed and assessed in the German component of the Programme for the International Assessment of Adult Competencies (PIAAC), adding longitudinal data from three additional waves of the national extension study (PIAAC-L), which included repeated assessments of literacy and numeracy proficiency over a period of three years. The authors' quantitative modelling of the growth of literacy and numeracy proficiency over time provides strong support for PET. Their comparisons of how various practice engagement indexes predict growth of literacy and numeracy proficiencies indicate that reading engagement is the strongest predictor of literacy growth and maths engagement is the strongest predictor of numeracy growth. The authors conclude their article by considering their findings' implications for sustainable development, lifelong learning policy and future research into the development of adult literacy and numeracy proficiency.

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“…A number of authors have attempted to circumvent these difficulties either through methodologies for combining data from repeated cross-sectional surveys (Gustafsson 2013) or through linking different surveys in order to follow specific cohorts (Kaplan 2009;Kaplan and McCarty 2013;Chmielewski 2015). See the review by Chmielewski and Dhuey (2017), as well as recent work by Hampf et al (2017) and by Bind and Rubin (2017). Hampf et al investigated a number of different approaches to establishing the causal linkage between skills and wages, concluding there was compelling evidence for such an inference.…”

Section: Summary and Limitationsmentioning

confidence: 99%

How long is the shadow? The relationships of family background to selected adult outcomes: results from PIAAC

Braun

2018

Large-scale Assess Educ

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Background: Ongoing interest in the relationships between family background and adult outcomes is motivated by concerns regarding the intergenerational transmission of advantage/disadvantage. Currently all countries are far from achieving the ideal that all individuals, irrespective of their starting points or their demographic characteristics, are able to accumulate sufficient human capital so that they can achieve success in the workplace and fulfill their responsibilities as family members and as citizens. This study quantifies the length of the shadow cast by family background and personal characteristics on an individual's prospects in the labor market. It also examines the extent to which these relationships are mediated by factors more proximal to labor market entry. Methods:This study uses data for 21 OECD countries from the first round of PIAAC. It employs descriptive statistics, correlations and logistic regression. Two dichotomous variables are derived from each country's national annual income distribution: Q1 = 1 if the individual's income is in the first (lower) quartile and Q4 = 1 if the individual works full-time and whose income is in the fourth (upper) quartile. For each country, a nested sequence of logistic regression models are fit to ascertain the role of more proximal factors in mediating the impact of family background and demographic characteristics on these labor market outcomes.

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Skills, earnings, and employment: exploring causality in the estimation of returns to skills

Cited by 49 publications

References 56 publications

The economic impacts of learning losses

The economic impacts of learning losses

Practice makes perfect: Practice engagement theory and the development of adult literacy and numeracy proficiency

How long is the shadow? The relationships of family background to selected adult outcomes: results from PIAAC

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