Abstract
There is currently a mismatch between the theoretical expectations of peer effects held by many scholars and the quantitative empirical literature. This paper contributes to the ...understanding of peer effects by highlighting the oft-overlooked conceptual distinction between social influences and a well-defined causal effect; peers may influence one another via several potentially contradicting mechanisms that result in small overall causal peer effects on educational outcomes. We exploit the idiosyncratic variation in gender composition across cohorts within schools to study offsetting mechanisms. Using population-wide Norwegian register and survey data, we find two distinct ways in which the share of girls in lower secondary schools (grades 8–10) affects academic outcomes. First, more girl peers improve the learning environment at school. Simultaneously, however, more girl peers reduce the students’ motivation for schoolwork. Such results suggest that peer effects stem from a complex process where various mechanisms are at odds with one another, and where the influence of peers on academic outcomes is a composite of different mechanisms. Overall, we find that more girl peers lower students’ school grades and reduce students’ likelihood of attending an academic track in upper secondary school (which qualifies for higher education). Supplementary analyses suggest that the achievement level of girls is the main reason for the gender peer effects found in our study.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Unconditional quantile regression has quickly become popular after being introduced by Firpo, Fortin, and Lemieux (2009, Econometrica 77: 953–973) and is easily implemented using the user-written ...command rifreg by the same authors. However, including high-dimensional fixed effects in rifreg is quite burdensome and sometimes even impossible. In this article, I show that when the number of fixed effects is large, the computational speed is massively increased by using xtreg rather than regress to fit the unconditional quantile regression models. I also introduce the xtrifreg command, which should be considered a supplement to rifreg. The xtrifreg command has many of the same features as rifreg but can be used to include a large number of fixed effects, to estimate cluster–robust standard errors, and to estimate cluster–bootstrapped standard errors.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
This paper investigates the effect of attending immigrant-dense schools on student outcomes, which consists of the joint effect of immigrant peers and school context. The sorting of students into ...schools is not random, and a large immigrant peer effect literature uses school fixed effects to eliminate selection bias. However, keeping schools fixed also eliminates the effect of the school context and is accordingly unsuited to estimate the total effect of attending immigrant-dense schools. By using both a value-added approach and by drawing on application data to manage selection bias, this paper demonstrates that attending immigrant-dense upper secondary schools in Norway increases student dropout, even though a school fixed effects model indicates no detectable immigrant peer effects. These findings suggest that immigrant-dense schools affect students in other ways than through mere peer exposure, and that research on the consequences of school segregation should take into account the effect of both school context and peers.
The Fracture Risk Assessment Tool (FRAX) and Garvan Calculator have improved the individual prediction of fracture risk. However, additional bone measurements that might enhance the predictive ...ability of these tools are the subject of research. There is increasing interest in cortical parameters, especially cortical porosity. Neither FRAX nor Garvan include measurements of cortical architecture, important for bone strength, and providing independent information beyond the conventional approaches. We tested the hypothesis that cortical parameters are associated with fracture risk, independent of FRAX and Garvan estimates. This nested case-control study included 211 postmenopausal women aged 54-94 years with nonvertebral fractures, and 232 controls from the Tromsø Study in Norway. We assessed FRAX and Garvan 10-year risk estimates for fragility fracture, and quantified femoral subtrochanteric cortical porosity, thickness, and area from computed tomography images using StrAx1.0 software. Per standard deviation higher cortical porosity, thinner cortices, and smaller cortical area, the odds ratio (95% confidence interval) for fracture was 1.71 (1.38-2.11), 1.79 (1.44-2.23), and 1.52 (1.19-1.95), respectively. Cortical porosity and thickness, but not area, remained associated with fracture when adjusted for FRAX and Garvan estimates. Adding cortical porosity and thickness to FRAX or Garvan resulted in greater area under the receiver operating characteristic curves. When using cortical porosity (>80th percentile) or cortical thickness (<20th percentile) combined with FRAX (threshold >20%), 45.5% and 42.7% of fracture cases were identified, respectively. Using the same cutoffs for cortical porosity or thickness combined with Garvan (threshold >25%), 51.2% and 48.3% were identified, respectively. Specificity for all combinations ranged from 81.0-83.6%. Measurement of cortical porosity or thickness identified 20.4% and 17.5% additional fracture cases that, were unidentified using FRAX alone, and 16.6% and 13.7% fracture cases unidentified using Garvan alone. In conclusion, cortical parameters may help to improve identification of women at risk for fracture.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Immigrant inflows to Europe have changed student compositions in and across schools. Despite the strong intuition that peers matter for student outcomes, a comprehensive literature finds nil ...or moderate effects of immigrant peers. This study explores three reasons for this mismatch. First, it uses quantile regressions to reveal whether estimates on the average of the outcome mask differential effects across the outcome distribution. Second, it estimates the effect of attending schools with different immigrant shares, which is a composite of peer effects and the effects of school traits. Third, it compares the effects on teacher-assigned grades and objective standardized tests to explore whether the effects of immigrant share are influenced by teachers’ grading practices. The results show that high achievers in schools with higher immigrant shares get better grades from their teachers, likely because they are assessed relative to peers with lower academic and socioeconomic levels. However, they show no sign of improved test scores. In contrast, low achievers obtain better test scores when having immigrant peers and this academic improvement is not explained by the general academic and socioeconomic level among peers. The findings demonstrate that effects on the mean outcome mask differential effects across outcome distributions.
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