scholarly journals From Partisan Media to Misperception: Affective Polarization as Mediator

2019 ◽  
Vol 69 (5) ◽  
pp. 490-512 ◽  
Author(s):  
R Kelly Garrett ◽  
Jacob A Long ◽  
Min Seon Jeong
Keyword(s):  
Fixed Effects ◽  
Regression Models ◽  
Presidential Elections ◽  
Major Party ◽  
Cross Sectional ◽  
Presidential Candidates ◽  
Nationally Representative ◽  
Using Data ◽  
Conservative Media ◽  
Fixed Effects Regression

Abstract This article provides evidence that affective polarization is an important mechanism linking conservative media use to political misperceptions. Partisan media’s potential to polarize is well documented, and there are numerous ways in which hostility toward political opponents might promote the endorsement of inaccurate beliefs. We test this mediated model using data collected via nationally representative surveys conducted during two recent U.S. presidential elections. Fixed effects regression models using three-wave panel data collected in 2012 provide evidence that conservative media exposure contributes to more polarized feelings toward major-party presidential candidates, and this growing favorability gap is associated with misperceptions critical of the Democrats. Further, these effects are more pronounced among Republicans than among Democrats. Cross-sectional analyses using data collected in 2016 provide additional evidence of the mediated relationship. The theoretical and real-world significance of these results are discussed.

What Goes Up Might Not Come Down: Modeling Directional Asymmetry with Large-N, Large-T Data

2021 ◽  
pp. 008117502110463
Author(s):  
Ryan P. Thombs ◽  
Xiaorui Huang ◽  
Jared Berry Fitzgerald
Keyword(s):  
Fixed Effects ◽  
Directional Asymmetry ◽  
Cross Sectional ◽  
Monte Carlo Experiments ◽  
Long Run ◽  
Large N ◽  
Fixed Effects Estimator ◽  
Cross Sectional Dependence ◽  
Using Data ◽  
Heterogeneous Panel

Modeling asymmetric relationships is an emerging subject of interest among sociologists. York and Light advanced a method to estimate asymmetric models with panel data, which was further developed by Allison. However, little attention has been given to the large- N, large- T case, wherein autoregression, slope heterogeneity, and cross-sectional dependence are important issues to consider. The authors fill this gap by conducting Monte Carlo experiments comparing the bias and power of the fixed-effects estimator to a set of heterogeneous panel estimators. The authors find that dynamic misspecification can produce substantial biases in the coefficients. Furthermore, even when the dynamics are correctly specified, the fixed-effects estimator will produce inconsistent and unstable estimates of the long-run effects in the presence of slope heterogeneity. The authors demonstrate these findings by testing for directional asymmetry in the economic development–CO2 emissions relationship, a key question in macro sociology, using data for 66 countries from 1971 to 2015. The authors conclude with a set of methodological recommendations on modeling directional asymmetry.

scholarly journals Interactions in Fixed Effects Regression Models

2020 ◽  
pp. 004912412091493
Author(s):  
Marco Giesselmann ◽  
Alexander W. Schmidt-Catran
Keyword(s):  
Monte Carlo ◽  
Time Constant ◽  
Fixed Effects ◽  
Regression Models ◽  
Time Varying ◽  
Unit Level ◽  
Monte Carlo Experiments ◽  
Product Term ◽  
Fixed Effects Regression ◽  
Effect Heterogeneity

An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, algebraic transformations reveal that this strategy does not yield a within-unit estimator. Instead, the standard FE interaction estimator reflects unit-level differences of the interacted variables. This property allows interactions of a time-constant variable and a time-varying variable in FE to be estimated but may yield unwanted results if both variables vary within units. In such cases, Monte Carlo experiments confirm that the standard FE estimator of x ⋅ z is biased if x is correlated with an unobserved unit-specific moderator of z (or vice versa). A within estimator of an interaction can be obtained by first demeaning each variable and then demeaning their product. This “double-demeaned” estimator is not subject to bias caused by unobserved effect heterogeneity. It is, however, less efficient than standard FE and only works with T > 2.

Impact of Financial Risks on the Profitability of Systematically Important Banks in Nigeria

Paradigm ◽  
2019 ◽  
Vol 23 (2) ◽  
pp. 117-129
Author(s):  
Olufemi Adewale Aluko ◽  
Funso Tajudeen Kolapo ◽  
Patrick Olufemi Adeyeye ◽  
Patrick Olajide Oladele
Keyword(s):  
Interest Rate ◽  
Fixed Effects ◽  
Positive Impact ◽  
Financial Risks ◽  
Cross Sectional ◽  
Bank Profitability ◽  
Alternative Measures ◽  
Cross Sectional Dependence ◽  
Fixed Effects Regression ◽  
The Impact

This study examines the impact of financial risks in form of credit, interest rate and liquidity risk on the profitability of systematically important banks in Nigeria over the period from 2010 to 2016. The fixed effects regression model is estimated with Driscoll–Kraay standard errors in order to produce results that are robust to heteroscedaticity, autocorrelation, cross-sectional dependence and temporal dependence. After controlling for some bank-specific, industry-specific, macroeconomic and institutional factors, the empirical results show that credit and liquidity risks have a positive impact on bank profitability while interest rate does not have an impact. The results are robust to alternative measures of profitability.

scholarly journals Personality Factors and Sick Leave Days. Evidence from a Nationally Representative Longitudinal Study in Germany.

2020 ◽  
Vol 17 (3) ◽  
pp. 1089
Author(s):  
Yulia I. Raynik ◽  
Hans-Helmut König ◽  
André Hajek
Keyword(s):  
Sick Leave ◽  
Representative Sample ◽  
Fixed Effects ◽  
Personality Factors ◽  
Cross Sectional ◽  
Private Households ◽  
Longitudinal Association ◽  
Nationally Representative ◽  
Underlying Mechanisms ◽  
The Relationship

Background: The question of whether employees’ sickness absence from the workplace depends on personality has been researched. Existing evidence mostly stems from cross-sectional studies, mainly showing that personality factors were not associated with the number of sick leave days, except for neuroticism, which was positively associated with sick leave days. Based on the above, it remains an under researched question whether intraindividual changes in personality factors are associated with changes in sick leave days. Thus, based on a nationally representative sample, the current study aimed to investigate the relationship between personality factors and sick leave days longitudinally based on a nationally representative sample of individuals in Germany. Methods: The present study used data from the German Socio-Economic Panel (GSOEP), a longitudinal survey of private households in Germany. Information from the years 2005, 2009, 2013 were used. The Big Five Inventory-GSOEP (BFI-S) was used to measure personality. Sick leave days in the preceding year were recorded. Poisson fixed effects regressions were used. Results: Adjusting for potential confounders, regressions showed that increases in neuroticism were associated with increased sick leave days. The longitudinal association between extraversion and sick leave days was marginally significant (p < 0.10). Other personality factors were not significantly associated with sick leave days. In addition, sick leave days increased with worsening self-rated health, presence of severe disability and increasing age. Conclusions: The findings of the current study highlight the association between neuroticism and sick leave days longitudinally. Further research is required to elucidate the underlying mechanisms.

scholarly journals Religious Heterogamy and the Intergenerational Transmission of Religion: A Cross-National Analysis

Religions ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 109 ◽  
Author(s):  
Brian McPhail
Keyword(s):  
Fixed Effects ◽  
Negative Impact ◽  
National Level ◽  
Religious Attendance ◽  
Social Survey ◽  
Using Data ◽  
Fixed Effects Regression ◽  
National Analysis ◽  
The Relationship ◽  
Cross National

This study examines the effect of religious heterogamy on the transmission of religion from one generation to the next. Using data from 37 countries in the 2008 Religion III Module of the International Social Survey Programme (ISSP), I conduct a cross-national analysis of the relationship between parents’ religious heterogamy and their adult childrens’ religious lives. By estimating fixed effects regression models, I adjust for national-level confounders to examine patterns of association between having interreligious parents during childhood and level of adult religiosity as measured by self-rated religiousness, belief in God, and frequencies of religious attendance and prayer. The results indicate that having religiously heterogamous parents or parents with dissimilar religious attendance patterns are both associated with lower overall religiosity in respondents. Parents’ religious attendance, however, mediates the relationship when each parent has a different religion. Having one unaffiliated parent is associated with lower religiosity regardless of parents’ levels of religious attendance. The negative impact of parents’ religious heterogamy on religious inheritance is independent of national-level factors and has implications for anticipating changes in the religious landscapes of societies characterized by religious diversity and growing numbers of interreligious marriages.

scholarly journals Effect of changes in green spaces on mental health in older adults: a fixed effects analysis

2019 ◽  
Vol 74 (1) ◽  
pp. 48-56 ◽  
Author(s):  
J Mark Noordzij ◽  
Marielle A Beenackers ◽  
Joost Oude Groeniger ◽  
Frank J Van Lenthe
Keyword(s):  
Mental Health ◽  
Fixed Effects ◽  
Green Space ◽  
Residential Environment ◽  
Green Spaces ◽  
Cross Sectional ◽  
Urban Green Spaces ◽  
Using Data ◽  
Sectional Analysis

BackgroundUrban green spaces have been linked to different health benefits, but longitudinal studies on the effect of green spaces on mental health are sparse and evidence often inconclusive. Our objective was to study the effect of changes in green spaces in the residential environment on changes in mental health using data with 10 years of follow-up (2004–2014).MethodsData from 3175 Dutch adults were linked to accessibility and availability measures of green spaces at three time points (2004/2011/2014). Mental health was measured with the Mental Health Inventory-5. Fixed effects analyses were performed to assess the effect of changes in green spaces on mental health.ResultsCross-sectional analysis of baseline data showed significant associations between Euclidean distances to the nearest green space and mental health, with an increase of 100 m correlating with a lower mental health score of approximately 0.5 (95% CI −0.87 to −0.12) on a 0–100 scale. Fixed effects models showed no evidence for associations between changes in green spaces and changes in mental health both for the entire sample as well as for those that did not relocate during follow-up.ConclusionsDespite observed cross-sectional correlations between the accessibility of green space in the residential environment and mental health, no evidence was found for an association between changes in green spaces and changes in mental health. If mental health and green spaces are indeed causally linked, then changes in green spaces in the Eindhoven area between 2004 and 2014 are not enough to produce a significant effect.

scholarly journals Functional Hearing Loss and Social Engagement Among Medicare Beneficiaries

2019 ◽  
Vol 76 (1) ◽  
pp. 195-200 ◽  
Author(s):  
Aishwarya Shukla ◽  
Thomas K M Cudjoe ◽  
Frank R Lin ◽  
Nicholas S Reed
Keyword(s):  
Older Adults ◽  
Hearing Loss ◽  
Social Engagement ◽  
Social Activity ◽  
Medicare Beneficiaries ◽  
Cross Sectional ◽  
The Past ◽  
Hearing Ability ◽  
Nationally Representative ◽  
Using Data

Abstract Objectives Hearing loss is common in older adults and limits communication. We investigated the independent association between functional hearing loss and social engagement in a nationally representative sample of older adults. Methods Using data from the 2015 Medicare Current Beneficiaries Survey, we modeled the cross-sectional association between self-reported hearing ability and limitation in social activity over the past month using multivariable logistic regression. Results The majority of the study population was female (54.8%) and non-Hispanic white (74.3%). Participants (40.4%) reported “a little trouble” hearing and 7.4% reported “a lot of trouble” hearing. Those who reported any trouble hearing had higher odds of limited social engagement in the past month. After adjustment for demographic, clinical, and functional covariates, those who reported “a lot of trouble” hearing had 37% higher odds of limited social activity in the past month compared to those with normal hearing. Discussion These results suggest that hearing loss may be an important risk factor for limited social engagement and downstream negative health consequences, independent of other disability and health conditions.

scholarly journals NEIGHBORHOOD AGE COMPOSITION AND SELF-RATED HEALTH: FINDINGS FROM A NATIONALLY REPRESENTATIVE STUDY

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S64-S64
Author(s):  
Amanda Lehning ◽  
Amanda J Lehning ◽  
Nicole Mattocks ◽  
Kyeongmo Kim ◽  
Richard J Smith
Keyword(s):  
Older Adults ◽  
Regression Models ◽  
Neighborhood Change ◽  
Age Composition ◽  
Logistic Regression Models ◽  
Self Rated Health ◽  
Representative Study ◽  
Nationally Representative ◽  
Using Data ◽  
Conceptual Work

Abstract Neighborhood age composition is an understudied area. Furthermore, existing empirical and conceptual work is conflicting, with some indicating neighborhoods with more older adults are beneficial and other scholarship suggesting it can be detrimental. Using data from 7,197 older adults from the first wave (2011) of the National Health & Aging Trends Study combined with census tract data from the National Neighborhood Change Database, we examined the association between neighborhood age composition and self-rated health. Findings from logistic regression models indicate those living in neighborhoods with a growing concentration of older residents are significantly more likely to report lower self-rated health compared to those living in a neighborhood in which older adults overall are declining (β=1.51, p &lt; .05) or are becoming diluted by younger residents (β=.66, p &lt; .05). Results have implications for interventions promoting aging in place, particularly for those who may be stuck in place in age-concentrated neighborhoods.

Twin and Sibling Attachment in a Nationally Representative Sample

2012 ◽  
Vol 38 (3) ◽  
pp. 308-316 ◽  
Author(s):  
R. Chris Fraley ◽  
Caroline M. Tancredy
Keyword(s):  
Older People ◽  
Representative Sample ◽  
Inclusive Fitness ◽  
Identical Twins ◽  
Cross Sectional ◽  
Attachment Figure ◽  
Nationally Representative ◽  
Using Data

The objective of this research was to evaluate the hypothesis that twin relationships are attachments, using data from a nationally representative sample. The results indicated that twin siblings were more likely than nontwin siblings to be attached to their siblings. Moreover, analyses indicated that both attachment theoretical and inclusive fitness perspectives are necessary for explaining these findings. Namely, twins were more likely to be attached than nontwin siblings, as expected from an attachment perspective. But identical twins were more likely than fraternal twins to be attached to one another, as might be expected from an inclusive fitness perspective. Cross-sectional analyses indicated that older people are less likely than younger people to use their sibling as an attachment figure compared to younger people and that married adults are less likely to use their sibling as an attachment figure than nonmarried people.

scholarly journals Language Variation Suite: A theoretical and methodological contribution for linguistic data analysis

2016 ◽  
Vol 1 ◽  
pp. 29 ◽  
Author(s):  
Olga Scrivner ◽  
Manuel Díaz-Campos
Keyword(s):  
Fixed Effects ◽  
Regression Models ◽  
Quantitative Methods ◽  
Language Variation ◽  
Mixed Effects ◽  
Logistic Regression Models ◽  
Linguistic Data ◽  
Diachronic Study ◽  
Phonetic Context ◽  
Fixed Effects Regression

In recent years there has been growing interest in quantitative methods for analyzing linguistic data.  Advanced multifactorial statistical analyses, such as inferential trees and mixed-effects logistic regression models, have become more accessible for linguistic research as a result of the availability of an open source programming environment provided by the statistical software R. In the present paper, we introduce a novel toolkit, Language Variation Suite, a software program that offers a friendly environment for conducting quantitative analyses. We demonstrate how theory built on traditional monofactorial analysis can be extended to macro and micro multifactorial approaches allowing for a deeper understanding of language variation. The focus of the analysis is based on intervocalic /d/ deletion in Spanish from the Diachronic Study of the Speech of Caracas 1987 and 2004-2010. In contrast to traditional methodological approaches we have treated intervocalic /d/ as a continuous dependent variable according to the intensity ratio measurements obtained. Furthermore, we have integrated various syntactic, phonetic and sociolinguistic factors. Non-parametric and fixed-effects regression models revealed that overall age (younger speakers), sex (male speakers), phonetic context (low vowels), token frequency and morphosyntactic category (past participles) have a significant effect on the lenition of intervocalic /d/. In contrast, the mixed-effects model selected only phonetic context, frequency and category, showing that individual speaker variation is higher than group variation.

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