scholarly journals The fixed effects approach as an alternative to multilevel analysis for cross-national analyses

2021 ◽  
Author(s):  
Katja Moehring
Keyword(s):  
Multilevel Modeling ◽  
Fixed Effects ◽  
Regression Models ◽  
Macro Level ◽  
Multilevel Regression ◽  
Country Level ◽  
Omitted Variable Bias ◽  
Fixed Effects Models ◽  
Variable Bias ◽  
Cross National

Multilevel models that combine individual and contextual factors are increasingly popular in comparative social science research; however, their application in country-comparative studies is often associated with several problems. First of all, most data-sets utilized for multilevel modeling include only a small number (N<30) of macro-level units, and therefore, the estimated models have a small number of degrees of freedom on the country level. If models are correctly specified paying regard to the small, level-2 N, only a few macro-level indicators can be controlled for. Furthermore, the introduction of random slopes and cross-level interaction effects is then hardly possible. Consequently, (1) these models are likely to suffer from omitted variable bias regarding the country-level estimators, and (2) the advantages of multilevel modeling cannot be fully exploited.The fixed effects approach is a valuable alternative to the application of conventional multilevel methods in country-comparative analyses. This method is also applicable with a small number of countries and avoids the country-level omitted variable bias through controlling for country-level heterogeneity. Following common practice in panel regression analyses, the moderator effect of macro-level characteristics can be estimated also in fixed effects models by means of cross-level interaction effects. Despite the advantages of the fixed effects approach, it is rarely used for the analysis of cross-national data.In this paper, I compare the fixed effects approach with conventional multilevel regression models and give practical examples using data of the International Social Survey Programme (ISSP) from 2006. As it turns out, the results of both approaches regarding the effect of cross-level interactions are similar. Thus, fixed effects models can be used either as an alternative to multilevel regression models or to assess the robustness of multilevel results.

scholarly journals Income Inequality and Population Health: A Global Gradient?

2018 ◽  
Vol 59 (4) ◽  
pp. 536-553 ◽  
Author(s):  
Michaela Curran ◽  
Matthew C. Mahutga
Keyword(s):  
Economic Development ◽  
Income Inequality ◽  
Population Health ◽  
Fixed Effects ◽  
Harmful Effect ◽  
Fixed Effects Models ◽  
Two Measures ◽  
The Relationship ◽  
Lower Population ◽  
Cross National

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.

scholarly journals Asymmetric Fixed Effects Models for Panel Data

2018 ◽  
Author(s):  
Paul D Allison
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Opposite Direction ◽  
Difference Method ◽  
Fixed Effects ◽  
Regression Models ◽  
Social Phenomena ◽  
Logistic Regression Models ◽  
Fixed Effects Models ◽  
The Difference

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.

Relative supervisor education and worker well-being

2018 ◽  
Vol 39 (5) ◽  
pp. 731-745
Author(s):  
Benjamin Artz
Keyword(s):  
Fixed Effects ◽  
Design Methodology ◽  
Well Being ◽  
Longitudinal Survey ◽  
Content Type ◽  
Omitted Variable Bias ◽  
Worker Education ◽  
Education Levels ◽  
Variable Bias ◽  
The Relationship

Purpose Less educated supervisors create worker status incongruence, a violation of social norms that signals advancement uncertainty and job ambiguity for workers, and leads to negative behavioral and well-being outcomes. The purpose of this paper is to compare education levels of supervisors with their workers and measure the correlation between relative supervisor education and worker job satisfaction. Design/methodology/approach Using the only wave of the 1979 National Longitudinal Survey of Youth that identifies education levels of both supervisor and worker, a series of ordered probit estimates describe the relationship between supervisor education levels and subordinate worker well-being. Extensive controls, sub-sample estimates and a control for sorting confirm the estimates. Findings Worker well-being is negatively correlated with having a less educated supervisor and positively correlated with having a more educated supervisor. This result is robust to a number of alternative specifications. In sub-sample estimates, workers highly placed in an organization’s hierarchy do not exhibit reduced well-being with less educated supervisors. Research limitations/implications A limitation is the inability to control for worker fixed effects, which may introduce omitted variable bias into the estimates. Originality/value The paper is the first to introduce relative supervisor–worker education level as a determinant of worker well-being.

scholarly journals Asymmetric Fixed-effects Models for Panel Data

2019 ◽  
Vol 5 ◽  
pp. 237802311982644 ◽  
Author(s):  
Paul D. Allison
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Opposite Direction ◽  
Difference Method ◽  
Fixed Effects ◽  
Regression Models ◽  
Social Phenomena ◽  
Logistic Regression Models ◽  
Fixed Effects Models ◽  
The Difference

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 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 article, 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.

scholarly journals Cross-national Attitudes about Paid Parental Leave Offerings for Fathers

2021 ◽  
Author(s):  
Qi Li ◽  
Chris Knoester ◽  
Richard Petts
Keyword(s):  
Parental Leave ◽  
Multilevel Regression ◽  
Social Survey ◽  
Public Opinions ◽  
Separate Spheres ◽  
Country Level ◽  
Self Interest ◽  
Paid Parental Leave ◽  
National Attitudes ◽  
Cross National

Using cross-national data from the 2012 International Social Survey Programme (N = 33,273), this study considers institutional, self-interest, and ideational factors in analyzing public opinions about the provision, length, and source of paid parental leave offerings for fathers. We find substantial support for generous leave offerings. Multilevel regression results reveal that being a woman, supporting dual-earning expectations, and realizing more family strains lead to support for more generous leave offerings. Endorsing separate spheres and intensive mothering attitudes reduces support for more generous leave offerings; although, gendered attitudes interact with one another in predicting leave preferences, too. Finally, country-level indicators of female empowerment and father-specific leave offerings are positively associated with preferences for more generous leave offerings. Overall, public opinions about fathers’ leave offerings across OECD countries largely support policies that provide opportunities for more involved fathering, but preferences continue to be gendered and linked to family strains and country-level contexts.

scholarly journals Female on boards and the risk-taking of microfinance institutions: The moderating role of outreach

2020 ◽  
Vol 16 (2) ◽  
pp. 19-34
Author(s):  
Michael Adusei
Keyword(s):  
Risk Taking ◽  
Fixed Effects ◽  
Positive Impact ◽  
Microfinance Institutions ◽  
Female Representation ◽  
Return On Assets ◽  
Omitted Variable Bias ◽  
Variable Bias ◽  
Moderating Role

This study examines the effect of female on boards on risk-taking with data from 401 microfinance institutions (MFIs) drawn from 64 countries. The study also investigates whether the effect is sensitive to the outreach performance of MFIs. The MFIs sampled for this study are spread across the six MFI regions. The study measures MFI risk by its risk-taking Z-score and risk-adjusted return on assets. The fixed effects estimation technique, known to overcome the omitted variable bias, is deployed to analyze the data. The results show that female representation in the boardroom increases the risk-taking of MFIs. However, when female on boards interacts with the depth of outreach performance of an MFI, its positive impact on MFI risk is observed. It suggests that female directors are more likely to be beneficial to risk management in MFIs that lend more to indigent clients. Several tests, including an instrumental variable test for endogeneity, have been conducted to confirm the robustness of these results.

Statistical Methods for Analyzing Collapsibility in Regression Models

1992 ◽  
Vol 17 (1) ◽  
pp. 51-74 ◽  
Author(s):  
Clifford C. Clogg ◽  
Eva Petkova ◽  
Edward S. Shihadeh
Keyword(s):  
Linear Regression ◽  
Statistical Methods ◽  
Regression Models ◽  
Linear Models ◽  
Reduced Model ◽  
Interval Estimates ◽  
Omitted Variable Bias ◽  
Regression Problems ◽  
The Common ◽  
Variable Bias

We give a unified treatment of statistical methods for assessing collapsibility in regression problems, including some possible extensions to the class of generalized linear models. Terminology is borrowed from the contingency table area where various methods for assessing collapsibility have been proposed. Our procedures, however, can be motivated by considering extensions, and alternative derivations, of common procedures for omitted-variable bias in linear regression. Exact tests and interval estimates with optimal properties are available for linear regression with normal errors, and asymptotic procedures follow for models with estimated weights. The methods given here can be used to compareβ1 and β2 in the common setting where the response function is first modeled asXβ1(reduced model) and then asXβ2+Zγ(full model), withZ a vector of covariates omitted from the reduced model. These procedures can be used in experimental settings (X= randomly asigned treatments,Z= covariates) or in nonexperimental settings where two models viewed as alternative behavioral or structural explanations are compared (one model withX only, another model withX andZ).

Working After Retirement and Life Satisfaction: Cross-National Comparative Research in Europe

2019 ◽  
Vol 41 (7) ◽  
pp. 648-669 ◽  
Author(s):  
Ellen Dingemans ◽  
Kène Henkens
Keyword(s):  
Life Satisfaction ◽  
Comparative Research ◽  
Fixed Effects ◽  
Positive Relationship ◽  
Financial Resources ◽  
Poor Countries ◽  
Pension Income ◽  
Fixed Effects Models ◽  
Cross National

This study examines differences in life satisfaction between full retirees and working retirees in Europe. We hypothesize that these differences depend on the financial resources of retirees and the resources available in the household and country context. We selected retirees from the “Survey of Health, Ageing and Retirement in Europe” project and estimated country fixed effects models to explain their life satisfaction. The results indicate a positive relationship between working after retirement and life satisfaction for retirees with low pension income without a partner. Additionally, working after retirement seems to be most important for life satisfaction in relatively poor countries.

Taking Innovation to the Streets: Microgeography, Physical Structure, and Innovation

2020 ◽  
Vol 102 (5) ◽  
pp. 912-928 ◽  
Author(s):  
Maria P. Roche
Keyword(s):  
Fixed Effects ◽  
City Planning ◽  
Knowledge Exchange ◽  
Physical Structure ◽  
Set Covering ◽  
Regional Innovation ◽  
Data Set ◽  
Omitted Variable Bias ◽  
Variable Bias ◽  
Block Groups

In this paper, we analyze how the physical layout of cities affects innovation by influencing the organization of knowledge exchange. We exploit a novel data set covering all census block groups in the contiguous United States with information on innovation outcomes, street infrastructure, as well as population and workforce characteristics. To deal with concerns of omitted variable bias, we apply commuting zone fixed effects and construct instruments based on historic city planning. The results suggest that variation in street network density may explain regional innovation differentials beyond the traditional location externalities found in the literature.

scholarly journals Energy – Growth Nexus- A Case of South Asian Countries

2021 ◽  
Vol 8 (2) ◽  
pp. 58-66
Author(s):  
Saddam Hussain ◽  
Chunjiao Yu ◽  
Liu Wan
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
South Asian ◽  
Fixed Effects ◽  
Asian Countries ◽  
Economic Determinants ◽  
Omitted Variable Bias ◽  
Variable Bias ◽  
Macroeconomic Determinants ◽  
The Relationship

The relationship between energy consumption and economic growth is a hot issue in today's society. This paper aims to empirically verify the relationship between energy consumption and economic growth. This article analyzes the relation of energy consumption with the economic growth taking the case of South Asian countries (Afghanistan, Bangladesh, Bhutan, India, Pakistan, Sri Lanka, and Nepal) along with the macroeconomic determinants that affect the total economic growth – FDI growth, CPI rate and population growth in order to avoid omitted variable bias and misleading results. The time span of this study covers the period of 1980–2019. To examine the significant relation of these determinants and impact of energy consumption on economic growth, In-pooled regression, Fixed-effects, Bidirectional fixed effect, Random-effects, and GLS estimation regression model are used. The estimated results show a positive correlation of energy consumption and all other economic determinants with economic growth except CPI, where there is a negative correlation founded.

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