scholarly journals Analysing Transitions in Intimate Relationships with Panel Data

2021 ◽  
Vol 46 ◽  
Author(s):  
Michael Feldhaus ◽  
Richard Preetz
Keyword(s):  
Panel Data ◽  
Intimate Relationships ◽  
Union Formation ◽  
Special Issue ◽  
Cross Sectional ◽  
Demographic Research ◽  
Longitudinal Methods ◽  
Causal Mechanisms ◽  
Over Time

Panel data on intimate relationships are becoming increasingly available, enabling a closer examination and deeper understanding of why and how they develop over time. The aim of this review is to illustrate to what extent demographic research has made progress in understanding the dynamics of intimate relationships by examining panel data. We focus on hypotheses about key transitions throughout the progression of intimate relationships, ranging from union formation up to cohabitation, marriage, divorce and repartnering. For every hypothesis, we will present findings from cross-sectional data and illustrate whether the use of panel data and longitudinal methods modified the previous understandings of transitions in intimate relationships. * This article belongs to a special issue on "Identification of causal mechanisms in demographic research: The contribution of panel data".

Are Millennials Really Particularly Selfish? Preliminary Evidence From a Cross-Sectional Sample in the Philanthropy Panel Study

2019 ◽  
Vol 63 (14) ◽  
pp. 1965-1982 ◽  
Author(s):  
Peter Koczanski ◽  
Harvey S. Rosen
Keyword(s):  
Multivariate Analysis ◽  
Panel Data ◽  
Prosocial Behavior ◽  
Panel Study ◽  
Preliminary Evidence ◽  
Demographic Variables ◽  
Cross Sectional ◽  
Charitable Donations ◽  
Causal Mechanisms

We use panel data on charitable donations to analyze how the philanthropic behavior of Millennials (born between 1981 and 1996) compares with that of earlier generations. On the basis of a multivariate analysis with a rich set of economic and demographic variables, we find that conditional on making a gift, one cannot reject the hypothesis that Millennials donate more than members of earlier generations. However, Millennials are somewhat less likely to make any donations at all than their generational predecessors. While our data do not allow us to explore causal mechanisms, our findings suggest a more nuanced view of the Millennials’ prosocial behavior than is depicted in popular accounts.

Human, social and cultural predictors of productive activities in later life

2018 ◽  
Vol 40 (2) ◽  
pp. 328-347 ◽  
Author(s):  
Seoyoun Kim
Keyword(s):  
Panel Data ◽  
Social Life ◽  
Later Life ◽  
Activity Level ◽  
Productive Activity ◽  
Cross Sectional ◽  
Care Giving ◽  
Productive Activities ◽  
Baseline Activity ◽  
Over Time

AbstractWhile considerable scholarly attention has been given to factors influencing productive activity, less is known about how multiple forms of resources predict the maintenance or initiation of such activity over time. Using two-wave panel data of older adults from the National Social Life, Health, and Aging Project (NSHAP), the study investigated the relationship between measures of capital and changes in multiple types of productive activity. Findings showed that all three types of capital were associated with volunteering in cross-sectional analyses, but only education, neighbourhood socialisation and religious service attendance remain significant predictors of continued volunteerism. Human capital strongly influenced employment both cross-sectionally and over time. Aspects of social capital – marital status and network size – were linked to participation and initiation of care-giving activities. The findings demonstrate that different patterns emerge in cross-sectional and two-wave panel data of multiple productive activities, adjusting for baseline activity level and selective attrition. The project also suggests factors that promote or hinder continued engagement in productive activity.

Modeling Behavior as Dynamic Sequential States: Introduction to the Special Issue

2021 ◽  
Vol 44 (1) ◽  
pp. 3-8
Author(s):  
Brian P. Flaherty ◽  
Lawrence M. Scheier
Keyword(s):  
Latent Class ◽  
Dynamic Change ◽  
Qualitative Change ◽  
Response Patterns ◽  
Special Issue ◽  
Cross Sectional ◽  
Transition Analysis ◽  
Modeling Behavior ◽  
Discrete Change ◽  
Over Time

This special issue of Evaluation and The Health Professions focuses on applications and extensions of latent transition analysis (LTA), a longitudinal parameterization of the latent class (LC) model. LTA is a model of discrete or qualitative change over time among potentially complex states (e.g., patterns of recent drug use or abuse experiences), commonly referred to as latent classes, latent profiles, or latent statuses. Frequently, researchers will distinguish the term “classes” for cross-sectional studies and with LTA use “statuses” to indicate the concept of “dynamic change” with individuals shifting in their response patterns and associated statuses over time. It goes without saying that LTA models are underutilized, although quite flexible. This special issue showcases articles that apply LTA and extend the capabilities of this approach to modeling discrete change in new ways.

How do relationship desire and sociability relate to each other among singles? Longitudinal analysis of the Pairfam survey

2020 ◽  
Vol 37 (8-9) ◽  
pp. 2634-2650
Author(s):  
Elyakim Kislev
Keyword(s):  
Longitudinal Analysis ◽  
Intimate Relationships ◽  
Lower Degree ◽  
Panel Analysis ◽  
Relative Importance ◽  
Cross Sectional ◽  
Never Married ◽  
Longitudinal Methods ◽  
Social Satisfaction ◽  
Social Lives

This study examines the effect of relationship desire on singles’ social lives and vice versa. Based on the German-based Panel Analysis of Intimate Relationships and Family Dynamics study, never-married singles and divorced singles were analyzed. Cross-sectional results showed a correlation between the extent to which singles desire relationship and both the relative importance of friendships and overall social satisfaction. Further analysis, using longitudinal methods, showed that the move to a lower degree of relationship desire had a significant effect on the relative importance of friends. Furthermore, both higher levels of the relative importance of friends and social satisfaction are negatively correlated with relationship desire. These results clarify previous studies and point to the fact that singles with low relationship desire are more social and derive greater support from their friends.

scholarly journals Does Marriage Increase Couples’ Life Satisfaction?

2021 ◽  
Vol 46 ◽  
Author(s):  
Alexander Gattig ◽  
Lara Minkus
Keyword(s):  
Life Satisfaction ◽  
Panel Data ◽  
Fixed Effects ◽  
Unobserved Heterogeneity ◽  
Married Couples ◽  
Social Mechanisms ◽  
Special Issue ◽  
Demographic Research ◽  
Analytical Strategies ◽  
Lower Effect

Many contemporary studies find that married couples are more satisfied with life than unmarried people. However, whether marriage makes people more satisfied with life or whether more satisfied couples are more likely to marry remains a debated question. We reassess this relationship with panel data from the German Family Panel (pairfam) and extend previous analyses by adding individual trajectories (slopes) to standard fixed-effects regressions (FEIS). We are thereby able to distinguish – controlling for time-constant unobserved heterogeneity – whether there is in fact an effect of marriage on life satisfaction, whether people who are simply happier in their relationship are more likely to get married, or whether people whose development in life satisfaction is more positive are more likely to get married. We translate these different social mechanisms into different analytical strategies and find that OLS regression – due to its confounding effects between and within persons – overestimates the effect of marriage on life satisfaction. A fixed-effects estimator reveals a much lower effect of marriage on life satisfaction for couples who marry compared to those who continue to live apart together or cohabitate. Additionally, using a FEIS estimator and adjusting for – non-linear – development of individual life satisfaction over time, suggests that this effect is in fact causal. * This article belongs to a special issue on "Identification of causal mechanisms in demographic research: The contribution of panel data".

scholarly journals xtoaxaca - Extending the Kitagawa-Oaxaca-Blinder Decomposition Approach to Panel Data

2020 ◽  
Author(s):  
Hannes Kröger ◽  
Jörg Hartmann
Keyword(s):  
Panel Data ◽  
Gender Pay Gap ◽  
Group Level ◽  
Decomposition Techniques ◽  
Cross Sectional ◽  
Pay Gap ◽  
Decomposition Approach ◽  
Research Questions ◽  
Changes Over Time ◽  
Over Time

The Kitagawa-Oaxaca-Blinder decomposition approach has been widely used to attribute group-level differences in an outcome to differences in endowment, coefficients, and their interactions. The method has been implemented for Stata in the popular oaxaca program for cross-sectional analyses. In the last decades, however, research questions have been more often focused on the decomposition of group-based differences in change over time, e.g. diverging income trajectories, as well as decomposition of change in differences between groups, e.g. change in the gender pay gap over time. We review five existing methods for the decomposition of changes in group means and contribute a complementing interventionist perspective, which is suitable for applications with a clear before-after comparison. These decompositions of levels and changes over time can be implemented using a first version of the program {\tt xtoaxaca}, which works as a postestimation command for different regression commands in Stata. It is built to maximize flexibility in modeling and implements all decomposition techniques presented in this paper.

scholarly journals Does social capital affect wages? A panel data analysis of causal mechanisms

2020 ◽  
Author(s):  
Gerhard Krug ◽  
Paul Schmelzer ◽  
Mark Trappmann
Keyword(s):  
Social Capital ◽  
Panel Data ◽  
Job Search ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Positive Association ◽  
Job Interviews ◽  
Cross Sectional ◽  
Causal Mechanisms ◽  
Panel Data Regression

Many studies document the positive association between accessed social capital and wages. It is widely accepted that the underlying relationship is causal. However, most studies use cross-sectional data, and only a few test causal mechanisms. In our analysis, we first test a broad range of social capital indicators by applying fixed-effects panel data regression to a sample of currently employed and a sample of newly employed individuals. Second, we test reservation wages, network search, being offered a job without prior job search, and the number of job interviews as some of the theoretical mechanisms put forward to explain positive social capital effects. Overall, we find no empirical evidence for wage effects of the social capital measure and no evidence that any of the proposed mechanisms are empirically relevant.

The Size Imperative? Longitudinal Tests

1989 ◽  
Vol 10 (1) ◽  
pp. 83-95 ◽  
Author(s):  
Robert M. Marsh ◽  
Hiroshi Mannari
Keyword(s):  
Panel Data ◽  
School Districts ◽  
Manufacturing Firms ◽  
Mirror Image ◽  
Ratchet Effect ◽  
Causal Inferences ◽  
Cross Sectional ◽  
Over Time ◽  
Organization Research

The theory of size as a cause of administrative intensity (the A/P ratio) is perhaps the most heavily researched topic in the study of organizations. Blau's version of this theory, like most others, is based on cross-sectional data. Using new panel data collected from 48 heterogeneous Japanese manufacturing firms in 1976 and 1983, this paper shows that prior size and complexity explain little of the variance in 1983 administrative intensity. We also find that in Japanese factories, as in U.S. school districts studied over time by previous researchers, changes in A/P ratios in declining size organizations are not simply the mirror image of what happens to personnel components in growing organizations. We conclude with a discussion of power versus efficiency explanations of this 'ratchet effect' and with a strong appeal that causal inferences in organization research be based more on longitudinal and panel data.

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