event history analysis
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COVID-19 has sickened and killed millions of people globally. Conventional non-pharmaceutical interventions, particularly stay-at-home orders (SAHOs), though effective for limiting the spread of disease have significantly disrupted social and economic systems. The effects also have been dramatic in Africa, where many states are already vulnerable due to their developmental status. This study is designed to test hypotheses derived from the public health policymaking literature regarding the roles played by medical and political factors as well as social, economic, and external factors in African countries’ issuance of SAHOs in response to the early stages of the COVID-19 pandemic. Using event history analysis, this study analyzed these five common factors related to public health policy to determine their impact on African states’ varying decisions regarding the issuance of SAHOs. The results of this analysis suggest that medical factors significantly influenced decisions as did factors external to the states, while the role of political factors was limited. Social and economic factors played no discernible role. Overall, this study suggests how African leaders prioritized competing factors in the early stages of a public health crisis.

Plant population ecologists regularly study soil seed banks with seed bag burial and seed addition experiments. These experiments contribute crucial data to demographic models, but we lack standard methods to analyze them. Here, we propose statistical models to estimate seed mortality and germination with observations from these experiments. We develop these models following principles of event history analysis, and analyze their identifiability and statistical properties by algebraic methods and simulation. We demonstrate that seed bag burial, but not seed addition experiments, can be used to make inferences about age-dependent mortality and germination. When mortality and germination do not change with seed age, both experiments produce unbiased estimates but seed bag burial experiments are more precise. However, seed mortality and germination estimates may be inaccurate when the statistical model that is fit makes incorrect assumptions about the age-dependence of mortality and germination. The statistical models and simulations that we present can be adopted and modified by plant population ecologists to strengthen inferences about seed mortality and germination in the soil seed bank.

Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.

Abstract Although a growing literature explores the relationship between migration and fertility, far less scholarship has examined how migrant childbearing varies over time, including across migrant cohorts. I extend previous research by exploring migrant-cohort differences in fertility and the role of changing composition by education and type of family migration. Using 1984–2016 German Socio-Economic Panel data, I investigate the transition into first, second, and third birth among foreign-born women in West Germany. Results from an event-history analysis reveal that education and type of family migration—including marriage migration and family reunions—contribute to differences in first birth across migrant cohorts. Specifically, more rapid entry into first birth among recent migrants from Turkey stems from a greater representation of marriage migrants across arrival cohorts, while increasing education is associated with reduced first birth propensities among recent migrants from Southern Europe. I also find variation in the risk of higher parity transitions across migrant cohorts, particularly lower third birth risks among recent arrivals from Turkey, likely a result of changing exposures within origin and destination contexts. These findings suggest that as political and socioeconomic circumstances vary within origin and destination contexts, selection, adaptation, and socialization processes jointly shape childbearing behavior.

We question why some state legislatures responded to public discourse promptly while other state legislatures resist change. We use the choice of performance-based budgeting (PBB) to set the stage in answering this compelling question. We employ a logit model as a discrete event history analysis (EHA). We use the EHA to determine how and what variables influence the probability of an organization’s qualitative change (or “event”) at a given point in time. In this study, the organizations are states, and the event to be analyzed is the enactment of PBB law. Our data set is a modified panel of 50 states between the years 1993 and 2008. We study the factors that would influence state legislators to pass PBB laws across the nation. While our empirical result shows that political preferences are not statistically significant factors for states to pass PBB law, state legislators seem to favor the factors associated with the financial management explanation to adopt PBB. Also, the factors of path dependence and mimicking influence states to adopt PBB.

AbstractThis chapter provides a summary and a systematic synopsis of the theoretical approaches and the empirical results. It gives a comparative overview over the temporal and spatial pattern of the diffusion process and critically reflects the theoretical approaches and the applied methods. A basic insight of this comparative conclusion is that the macro-quantitative approach of network diffusion event history analysis has great benefits for global studies on social policy diffusion, but in-depth case studies still remain important for revealing the diffusion mechanisms. Future research should more systematically combine both perspectives.

AbstractThe introductory chapter to the volume by Mossig, Windzio, Seitzer and Besche-Truthe defines the core concepts, such as diffusion and contagion, and gives an example of an application diffusion and contagion in epidemiology. The most important underlying functions, namely the logistic density and cumulative logistic density function, are explained, followed by a very brief introduction to the core concepts of event history analysis. In the network diffusion model, contagion, or, in other words, the adoption of information or innovation, is based on the concept of exposure which will be elaborated in this chapter. Finally, after describing and visualizing the four different networks and their correlations, exponential random graph models are used to analyze structural and substantive properties of these networks. The introduction concludes with a brief overview of the chapters.

Diffusion models explore the reasons policies transfer across governments. In this study, we focus on U.S. state level efforts in affordable housing. Drawing predominately from policy diffusion literature, our research examines the determinants of the creation of state Housing Trust Funds (HTFs). We utilize event history analysis with logit regressions and survival modeling to examine how problem severity, neighbor adoption, economic standing, elected leadership, housing investment, and demographics predict state HTF adoption. Results indicate that both problem severity and elected leadership predict the adoption of HTFs. This work improves our understanding of state policy diffusion and efforts in housing affordability.

AbstractRecent research suggests that the increasing complexity of family life could be a factor in declines in internal migration (long-distance moves within countries). As many separated parents continue to share childcare responsibilities or have visiting arrangements, their mobility is naturally constrained. However, the relationship between family complexity and individual migration behaviour has never been studied explicitly. We compare separated parents with parents in two-parent families in their likelihood of migrating within the Netherlands. We use detailed records of parents’ partnership status and children’s residential situation. An event-history analysis was performed using register-based population data (N = 442,412). We find that separated, single parents are more likely to migrate than those in two-parent families. The same is true for repartnered mothers, while repartnered fathers are about as likely to migrate as fathers in two-parent families. Separated parents’ migration behaviour depends on where their children live. Having non-resident children who live some distance away is associated with a much higher likelihood of migrating than having resident children or non-resident children who live nearby. Having both resident and non-resident children who live nearby—shared residence (i.e. joint physical custody) is likely common in this situation—is associated with a considerably lower likelihood of migrating than having resident children only. Based on our findings, one would expect family complexities stemming from parental separation to be associated with higher rather than lower levels of migration. However, potential future increases in the number of parents who share physical custody after separation might lead to lower migration levels.