Education Economics最新文献

{"title":"The over-education wage penalty among PhD holders: a European perspective","authors":"Loredana Cultrera, François Rycx, Giulia Santosuosso, Guillaume Vermeylen","doi":"10.1080/09645292.2023.2277120","DOIUrl":"https://doi.org/10.1080/09645292.2023.2277120","url":null,"abstract":"ABSTRACTUsing a unique pan-European dataset, we rely on two alternative measures of over-education and control stepwise for four groups of covariates in order to interpret the over-education wage penalty in light of theoretical models. Firstly, it appears that a significant fraction (i.e. between 1/5 and 1/3) of PhD holders in Europe are genuinely over-educated. Secondly, these genuinely over-educated PhD holders are found to face a substantial wage penalty (ranging from 15 to almost 30%) with respect to their well-matched counterparts. Finally, unconditional quantile regressions highlight that the over-education wage penalty among PhD holders increases greatly along the wage distribution.KEYWORDS: Phd graduatesover-educationover-skillingjob satisfactionwagesEuropeJEL CODES: J21J24 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 In the European Union, the statistics point in the same direction: the number of newly enrolled doctoral students aged between 24 and 35 increased by almost 27% between 2013 and 2018 (from around 71,000 to almost 90,000), while the number of doctoral students rose from around 735,000 to 779,000 between 2013 and 2019 (European Commission Citation2020; Eurostat, Citation2023). Furthermore, in 2019, the number of new doctorate holders was around 121,000 in the EU-28 (Eurostat, Citation2023).2 This said, it should be noted that a significant number of people embark on a thesis for reasons other than obtaining a job requiring a PhD. Intrinsic motivation and intellectual development are also important drivers (Hnatkova et al. Citation2022). In addition, studies show that many PhD graduates, despite holding jobs for which a PhD is not essential (and for which they are therefore likely to be over-educated), can nevertheless leverage their degree to improve their career prospects. More specifically, as Boman et al. (Citation2021) point out, in many jobs, a doctorate, even if not required, is desired or valued, so that the person with a doctorate has a more interesting and rewarding job, which also makes it easier to access more responsibility, promotion or other benefits (pecuniary or otherwise).3 The term ‘voluntary’ should be interpreted with caution as it may obviously be a constrained choice.4 The study by Ermini, Papi, and Scaturro (Citation2017), based on four cohorts of Italian doctoral graduates (relating to the years 2004, 2006, 2008 and 2010), also finds that jobs held by doctoral graduates in academia and the research sector are more often associated with a successful match. The analysis by Boman et al. (Citation2021), which is based on a career tracking survey of doctoral graduates between 2006 and 2020 in nine European universities, concludes that almost half of doctoral graduates are employed in jobs that do not require a doctorate, but also that overeducation is most prevalent outside universities and research institutions.5 By relying on the WA method, over-education is co","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"8 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can teachers learn online? – evidence from Armenia during the COVID-19 pandemic","authors":"Naneh Hovanessian, Gevorg Minasyan, Armen Nurbekyan, Mattias Polborn, Tigran Polborn","doi":"10.1080/09645292.2023.2273224","DOIUrl":"https://doi.org/10.1080/09645292.2023.2273224","url":null,"abstract":"ABSTRACTThe COVID-19 pandemic has forced a shift from traditional face-to-face instruction to online learning. We analyze how this shift has affected learning outcomes, using a rich data set from a financial literacy training of schoolteachers in Armenia. Online training worked well for relatively simple skills (acquiring theoretical financial knowledge) but less well than in-person training for more complex tasks (learning how to teach financial literacy to students). We also found that the deterioration of training success in the online cohort is stronger among social studies teachers than among math teachers. AcknowledgementsWe are very thankful to the editor and two anonymous referees whose comments helped us to substantially improve this paper. We are also grateful to Andrew Dustan, Kayleigh McCrary, Pedro Sant'Anna and Zaruhi Sahakyan, as well as attendees at the 2022 meeting of the Armenian Economic Association for helpful discussions, and to the staff of the Consumer Rights Protection and Financial Education Center, in particular Araks Manucharyan, for providing the data used in this article. The views expressed in this paper are those of the authors and do not necessarily represent the views or policies of the Central Bank of Armenia.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Even after the pandemic ends, online learning will have an important role in the future, as it can be more cost-effective (OECD Citation2020), or meet diverse learning needs (UNESCO Citation2020).2 Armenia has about 1420 primary and secondary schools, so each cohort consists of about 355 schools. The average school in Armenia is much smaller than in the United States, serving around 270 students in the relevant age range, and sending about 4 teachers to the financial literacy training.3 Almost all teachers also participated in the pre-test before the training took place. Those who did not (<10 across both years combined) were dropped from the dataset.4 The test questions contain a ‘don't know’ answer option.5 The 2020 Covid death rate was 1180 per million population in Armenia as a whole (1572 per million population in Yerevan). The 2021 Covid death rate was 1810 per million population in Armenia as a whole, and 2400 per million in Yerevan. Measured by these death rates, the pandemic was approximately 50% more severe in the in-person year 2021 than in the online year.6 Approximately 50 percent of our sample are ‘rich’ under this definition. Because teacher salaries are relatively flat, this variable depends mostly on the teacher's partner's income.7 For example, some clusters outside Yerevan are composed of schools from relatively urban areas, e.g. from the second-largest city, while other clusters contain primarily rural schools.8 Both the predicted and the actual pre-scores in 2021 are also quite close to the average pre-score of the 2020 cohort (46.3).9 Since teachers receive a salary that varies only slightly with ","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135271454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Are dreams contagious? Peer effects of undocumented college students","authors":"Federick Ngo","doi":"10.1080/09645292.2023.2272591","DOIUrl":"https://doi.org/10.1080/09645292.2023.2272591","url":null,"abstract":"","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134910256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Which college types increase earnings? Estimates from geographic proximity","authors":"Jennifer L. Steele","doi":"10.1080/09645292.2023.2265594","DOIUrl":"https://doi.org/10.1080/09645292.2023.2265594","url":null,"abstract":"ABSTRACTThe question of why postsecondary institutions produce different labor market outcomes is difficult to answer due to unobserved student characteristics. Here, I leverage students' geographic proximity to three classifications of postsecondary institutions – earnings-enhancing, competitive, and Historically Black Colleges and Universities (HBCUs). Using a nationally representative sample, I estimate attainment and earnings effects of first attending each type. Attending an institution classified as earnings-enhancing increases humanities credit completion, degree attainment, and early-career wages. Among underrepresented students, living closest to an HBCU strongly predicts HBCU enrollment. This yields higher STEM credit completion but lower early-career wages, suggesting possible labor market bias.Abbreviations: Competitive: Barron's Top 3 Selectivity Tier Institution; HBCU:Historically Black College or University; HSI: High-Success Institution; STEM: Science; Technology; Engineering; and Mathematics; Underrepresented Minority (URM): Black; Indigenous; or Hispanic/LatinxHIGHLIGHTSNearest-college attributes predict college choice for many high school students, especially those living near HBCUs.Colleges previously linked to students' wage mobility yield higher earnings by students' mid-20s.Higher earnings effects coincide with higher humanities credit completion, bachelor's completion, and postbaccalaureate training.HBCU attendance relative to other options yields higher STEM credit completion, but lower early-career wages.HBCU attendance relative to no college also increases humanities credit completion and bachelor's degree completion.KEYWORDS: Human capitalsalary wage differentialsinstitutional effectsinstrumental variablescollege proximity Disclosure statementNo potential conflict of interest was reported by the author.Notes1 Chetty et al. (Citation2017) also found high variation in the ‘mobility rates’ of institutions, which they defined as the product of institutions' success rates and the fraction of bottom-quintile students enrolled in them.2 ELS:2002 provides cross-sectional base-year weights for each school and student to reflect both the inverse probability of selection, which is known from the sampling design, and the probability of nonresponse, which is estimated from student and school attributes at baseline. The dataset also includes panel weights for use in longitudinal analyzes across the other survey waves. I do not employ the ELS weights in this analysis because my identification strategy, instrumental variables analysis, in effect assigns greater weight to respondents who are sensitive to the set of geographic instrumental variables. Applying sampling and non-response weights may therefore distort the internal validity of the IV analysis (Solon, Haider, and Wooldridge Citation2015).3 The four HBCUs also classified as high-success institutions are Howard University, Morehouse College, Spelman College, and Xavier Universi","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135854503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spillover effects of maternal education in elementary classroom: evidence from Vietnam","authors":"My Nguyen","doi":"10.1080/09645292.2023.2266591","DOIUrl":"https://doi.org/10.1080/09645292.2023.2266591","url":null,"abstract":"ABSTRACTThis paper examines the spillover effects of maternal education in elementary classrooms in the context of Vietnam. Drawing from the sample of students who are randomly assigned to classrooms, we find that exposure to classmates whose mothers are well-educated positively influences student achievement. The heterogeneity analyses reveal that the magnitude of the effects tends to be larger for students from advantaged backgrounds. Exploring the mechanisms, we find that higher academic aspiration and motivation as well as an improved learning environment are potential pathways to the favorable impacts of peers’ maternal education.KEYWORDS: Peer effectmaternal educationlearningstudent achievement Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Changes in teachers’ and mothers’ behavior can also be potential pathways (Wang Citation2021; Chung and Zou Citation2023). These are mentioned in Section 5.5 but unfortunately the lack of data makes it impossible for us to empirically test these pathways.2 School data were only collected for the younger cohort3 Vietnam is categorized into eight socioeconomic regions: North-West, North-East, Red River Delta, North Central Coast, South Central Coast, South-East, Central Highlands, and Mekong River Delta. Furthermore, all major urban centers (Hanoi, Ho Chi Minh City, Da Nang, Hai Phong, and Ba Ria-Vung Tau) are regarded as a new region – the Cities region (Nguyen Citation2008). Five regions were selected for the YLP study, based on the following criteria: (i) regions in the North, Central and South, (ii) regions consisting of urban, rural, and mountainous areas, (iii) regions having a larger (than the national average) poor population, and (iv) regions reflecting some unique factors of the country, such as natural disaster and war consequences. The Young Lives team then selected one province from each region: Lao Cai (North-East region), Hung Yen (Red River Delta), Da Nang (Cities), Phu Yen (South Central Coast), and Ben Tre (Mekong River Delta).4 In the full sample that includes students who are randomly assigned to classrooms and students who are not randomly assigned to classrooms, there are 3,284 students and 176 classrooms (Table 1, Columns 4-6).5 On average, a student in our sample misses around 1.15 days of class during the academic year while the maximum of absent days each student has is 9 days. Approximately 15% of students have the number of absences greater than the class average.","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135147214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economies of scale and scope, merger effects, and ownership difference: an empirical analysis of universities in Japan","authors":"Fumitoshi Mizutani, Tomoyasu Tanaka, Noriyoshi Nakayama","doi":"10.1080/09645292.2023.2260574","DOIUrl":"https://doi.org/10.1080/09645292.2023.2260574","url":null,"abstract":"ABSTRACTThis paper evaluates economies of scale and scope, and the merger effect among national universities in Japan. We apply SUR for the total translog cost function in FY2014 and FY2018. The main results are: (i) there exist economies of scale as a whole university; (ii) but there exist no clear economies of scope except for in research; (iii) there are cost saving effects with mergers among single colleges, but not in the case of mergers of general universities and medical colleges, (iv) both the costs of a public and a private university are higher than those of a national university.KEYWORDS: Higher educationEconomies of scaleEconomies of scopeMerger of universities Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 In Table A1 (Appendix), studies of the stochastic cost frontier approach, which estimates economies of scale and scope, are listed. Other studies using this approach to estimate the efficiency level of universities are Stevens (Citation2005), McMillan and Chan (Citation2006), Agasisti and Salerno (Citation2007), Lenton (Citation2008), Kempkes and Pohl (Citation2008, Citation2010), Yamasaki and Itaba (Citation2009, Citation2010), Johnes and Johnes (Citation2009), Johnes and Schwarzenberger (Citation2011), Mamun (Citation2012), Suhara (Citation2014), Johnes and Johnes (Citation2016), Gralka (Citation2018), Agasisti and Gralka (Citation2019), Fu et al. (Citation2019), Maeda (Citation2020).2 As we note in the literature review, it is reasonable and common that three university output measures be used—undergraduate education, graduate education, and research. In fact, as for types of education, education for undergraduate and graduate students differs because graduate education is more related to research, an activity distinct from education. The main goal of research is the production of papers, patents, etc. Therefore, we use these three output measures.3 According to Christensen and Greene (Citation1976), estimating cost function alone leads to multicollinearity problems because the information of the input share equations cannot be used. As a result, the explanatory variables in a translog cost function are inaccurate parameter estimates. As the simultaneous method of the cost function and the input share equations as a system increases the degree of freedom, the accuracy of the estimates increases, compared to a case of a single estimation method using the cost function only.4 As for output measure, universities of more than 95% in undergraduate education, of more than 93% in graduate education and of more than 96% in research satisfy the monotonicity condition. As for input factor price, universities of 100% in both labor and material and other prices, and of more than 98% in capital price satisfy the monotonicity condition.5 The partial derivatives of input prices are stable with little variation across models. As for university type, the partial derivatives of labor prices are higher i","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134885414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gender differences in grading: teacher bias or student behaviour?","authors":"David Contreras","doi":"10.1080/09645292.2023.2252620","DOIUrl":"https://doi.org/10.1080/09645292.2023.2252620","url":null,"abstract":"This paper examines the presence of systematic differences in teachers' grading behaviour across gender and whether these can be attributed to teacher bias. This study measures these differences by comparing teachers' grades with national exams, which are externally and anonymously marked. Consistent with the literature, the gender gap in teacher grading is against boys. Using a dataset with gender gaps at class-subject level – which allows to follow teachers in different classes over time – this study shows that teachers' grading behaviour is not persistent across classes. Results suggest that gender grading gaps are explained by differences in students' behaviour.","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135939224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of a large-scale program for the construction of daycare and preschool centers on cognitive skills and female employment","authors":"Marcelo Castro, Breno da Cruz","doi":"10.1080/09645292.2023.2254516","DOIUrl":"https://doi.org/10.1080/09645292.2023.2254516","url":null,"abstract":"","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135982209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the spatial impact of educational attainment on poverty reduction in Thailand","authors":"Katikar Tipayalai, Chayaton Subchavaroj","doi":"10.1080/09645292.2023.2244702","DOIUrl":"https://doi.org/10.1080/09645292.2023.2244702","url":null,"abstract":"","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49303907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Home computer ownership and educational outcomes of adolescents in Greece","authors":"Vladana Djinovic, N. Giannakopoulos","doi":"10.1080/09645292.2023.2243550","DOIUrl":"https://doi.org/10.1080/09645292.2023.2243550","url":null,"abstract":"","PeriodicalId":46682,"journal":{"name":"Education Economics","volume":" ","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48395150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}