scholarly journals Selection into Identification in Fixed Effects Models, with Application to Head Start

2021 ◽  
pp. 0520-10930R1
Author(s):  
Douglas L. Miller ◽  
Na’ama Shenhav ◽  
Michel Grosz
2021 ◽  
pp. 095001702110042
Author(s):  
Aleksander Å Madsen ◽  
Idunn Brekke ◽  
Silje Bringsrud Fekjær

This study explores women’s attrition from male-dominated workplaces based on Norwegian public administrative records, covering individuals born 1945–1983, in the period between 2003 and 2013. It examines sex differences in rates of attrition and tests the significance of two commonly proposed explanations in the literature, namely the degree of numerical minority status and motherhood. It also investigates whether these explanations vary by occupational class. Selection into male-dominated workplaces is accounted for by using individual fixed effects models. The results show that attrition rates from male-dominated workplaces are considerably higher among women than among men. Moreover, the risk of female attrition to sex-balanced workplaces increases, regardless of occupational class, with increases in the percentage of males. Childbirth is associated with an increased risk of attrition to female-dominated workplaces, while having young children (⩽ 10 years old) lowered the risk. This association, however, was primarily evident among working-class women in manual occupations.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xujia Liu ◽  
Zehua Jiang ◽  
Guihua Zhang ◽  
Tsz Kin Ng ◽  
Zhenggen Wu

Abstract Background Genetic association of uncoupling proteins (UCPs) variants with the susceptibility of diabetic retinopathy (DR) in diabetes mellitus (DM) patients has been reported but with controversy. Here we aimed to conduct a meta-analysis to confirm the association of different UCPs variants with DR. Methods Three databases (Medline Ovid, Embase Ovid and CENTRAL) were applied in the literature search. Five genetic models, including allelic, homozygous, heterozygous, dominant and recessive models, were evaluated. Odds ratios (OR) were estimated under the random or fixed-effects models. Subgroup analyses, publication bias and sensitivity analyses were also conducted. Results Eleven studies on 2 UCPs variants (UCP1 rs1800592 and UCP2 rs659366) were included. Our meta-analysis showed that UCP1 rs1800592 was not associated with DR in type-2 DM patients, and UCP2 rs659366 also showed no association with DR. In the subgroup analyses on the stage of DR, allele G of UCP1 rs1800592 significantly increased the susceptibility of proliferative diabetic retinopathy (PDR) in type-2 DM patients in the allelic (OR = 1.26, P = 0.03) and homozygous models (OR = 1.60, P = 0.04). Subgroup analysis on ethnicity did not found any significant association of rs1800592 and rs659366 with DR. Conclusion Our meta-analysis confirmed the association of UCP1 rs1800592 variant with PDR in patients with type-2 DM, suggesting its potential as a genetic marker for PDR prediction in population screening.


2021 ◽  
pp. 001041402199717
Author(s):  
Charles T. McClean

How can incumbent governments benefit when they control the timing of elections? The conventional wisdom is that incumbents gain an advantage by timing elections to coincide with favorable economic conditions. An alternative mechanism that has received less attention is the element of surprise: the incumbent’s ability to exploit the opposition’s lack of election preparedness. I theorize and empirically test this surprise mechanism using candidate-level data from Japanese House of Representatives elections (1955–2017). The results show that in surprise elections, opposition parties recruit fewer, lower-quality candidates, spend less money campaigning, coordinate their candidates less effectively, and ultimately receive fewer votes and seats. Evidence from fixed effects models and exogenously timed by-elections further suggest that surprise matters more in shorter, competitive election campaigns and helps incumbents more with confronting inter-party as opposed to intra-party electoral competition. These findings add to our understanding of how strategic election timing can undermine electoral accountability.


10.3982/qe59 ◽  
2011 ◽  
Vol 2 (2) ◽  
pp. 211-249 ◽  
Author(s):  
Rachel Griffith ◽  
Sokbae Lee ◽  
John Van Reenen

2018 ◽  
Vol 59 (4) ◽  
pp. 536-553 ◽  
Author(s):  
Michaela Curran ◽  
Matthew C. Mahutga

Cross-national empirical research about the link between income inequality and population health produces conflicting conclusions. We address these mixed findings by examining the degree to which the income inequality and health relationship varies with economic development. We estimate fixed-effects models with different measures of income inequality and population health. Results suggest that development moderates the association between inequality and two measures of population health. Our findings produce two generalizations. First, we observe a global gradient in the relationship between income inequality and population health. Second, our results are consistent with income inequality as a proximate or conditional cause of lower population health. Income inequality has a 139.7% to 374.3% more harmful effect on health in poorer than richer countries and a significantly harmful effect in 2.1% to 53.3% of countries in our sample and 6.6% to 67.6% of the world’s population but no significantly harmful effect in richer countries.


2018 ◽  
Author(s):  
Paul D Allison

Standard fixed effects methods presume that effects of variables are symmetric: the effect of increasing a variable is the same as the effect of decreasing that variable but in the opposite direction. This is implausible for many social phenomena. York and Light (2017) showed how to estimate asymmetric models by estimating first-difference regressions in which the difference scores for the predictors are decomposed into positive and negative changes. In this paper, I show that there are several aspects of their method that need improvement. I also develop a data generating model that justifies the first-difference method but can be applied in more general settings. In particular, it can be used to construct asymmetric logistic regression models.


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