The Impact of Demographic Change on Intergenerational Transfers via Bequests

Transfers in the form of bequests have important implications for the intergenerational transmission of inequality. Demographic change has relevant consequences for the timing and size of bequests. For example, longer life implies that people receive bequests when they are older. Conversely, increasing generational length reduces the average age at which people are given bequests. We analyze the consequences of demographic change in the United States for the timing over the life course when individuals receive an inheritance and for the size of bequests. We evaluate trends in life expectancy at the mean age at childbearing as a proxy for timing at receipt of bequests. We complement formal demographic analysis with empirical estimates from the Panel Study of Income Dynamics (PSID) inheritance data for 1987-2010. We find that the long-term trend of increasing age at receipt of bequests and of increasing size of per-capita bequests received might have stalled, mainly because of changes in the timing of fertility. In the long term, the upward trend in age at which people receive bequests may resume as the expected linear gains in life expectancy would more than counteract recent increases in the mean age at childbearing. We showed that demographic change affects the size of bequests and the timing over the life course at which people receive them. As the need for economic resources varies over the life cycle, changes in the timing at receipt of bequests may have a differential impact on wealth inequality and affect patterns of multigenerational transfers of resources

The advantages of demographic change after the wave: Fewer and older, but healthier, greener, and more productive?

Population aging is an inevitable global demographic process. Most of the literature on the consequences of demographic change focuses on the economic and societal challenges that we will face as people live longer and have fewer children. In this paper, we (a) briefly describe key trends and projections of the magnitude and speed of population aging; (b) discuss the economic, social, and environmental consequences of population aging; and (c) investigate some of the opportunities that aging societies create. We use Germany as a case study. However, the general insights that we obtain can be generalized to other developed countries. We argue that there may be positive unintended side effects of population aging that can be leveraged to address pressing environmental problems and issues of gender inequality and intergenerational ties

Studying Migrant Assimilation Through Facebook Interests

Migrants' assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook's data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address.Comment: Accepted as a short paper at Social Informatics 2018 (https://socinfo2018.hse.ru/). Please cite the SocInfo versio

Bowling Together: Scientific Collaboration Network of Demographers at European Population Conferences.

Exploiting a unique database of metadata for papers presented at six European Population Conferences (EPC) for the years 2006-2016, this paper explores: 1) development of research in population studies; 2) trends and patterns of scientific collaboration networks among demographers; and 3) gender differences in demographic research. The data are organised in a panel format whereby each author, institution and country are linked across the six conferences. We find that collaboration among demographers has increased substantially over the past ten years. While there is no gender disparity in the likelihood of co-authoring a paper, men are significantly more likely than women to collaborate with authors from other institutions. Likewise, the fields of research vary considerably by gender where women are particularly over represented in the subfield ‘fertility and family’ whereas men dominate the subfield ‘data and methods’. Compared to other subfields, research on ‘data and methods’ is more likely to involve collaboration across multiple institutions. With respect to collaboration patterns at the institutional level, a chord diagram plot shows that scientific collaborations across institutions are more common between institutions sharing geographical proximity. Finally, using network centrality measures, we identify key demographic research institutes which play a role in driving demographic research in Europe

Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data

Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide a general framework for converting digital trace data into estimates of migration transitions and for systematically analyzing their variation along a quasi-continuous time scale, analogous to a survival function. From migration theory, we develop two simple hypotheses regarding how we expect our estimated migration transition functions to behave. We then test our hypotheses on simulated data and empirical data from three platforms in two internal migration contexts: geotagged Tweets and Gowalla check-ins in the United States, and cell-phone call detail records in Senegal. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research. At the same time, however, common patterns across our three empirical data sets point to an emergent research agenda using digital trace data to study the specific functional relationship between estimates of migration and time and how this relationship varies by geography and population characteristics

Little-Italy: an Agent-Based Approach to the Estimation of Contact Patterns. Fitting Predicted Matrices to Serological Data.

Knowledge of social contact patterns still represents the most critical step for understanding the spread of directly transmitted infections. Data on social contact patterns are, however, expensive to obtain. A major issue is then whether the simulation of synthetic societies might be helpful to reliably reconstruct such data. In this paper, we compute a variety of synthetic age-specific contact matrices through simulation of a simple individual-based model (IBM). The model is informed by Italian Time Use data and routine socio-demographic data (e.g., school and workplace attendance, household structure, etc.). The model is named “Little Italy” because each artificial agent is a clone of a real person. In other words, each agent's daily diary is the one observed in a corresponding real individual sampled in the Italian Time Use Survey. We also generated contact matrices from the socio-demographic model underlying the Italian IBM for pandemic prediction. These synthetic matrices are then validated against recently collected Italian serological data for Varicella (VZV) and ParvoVirus (B19). Their performance in fitting sero-profiles are compared with other matrices available for Italy, such as the Polymod matrix. Synthetic matrices show the same qualitative features of the ones estimated from sample surveys: for example, strong assortativeness and the presence of super- and sub-diagonal stripes related to contacts between parents and children. Once validated against serological data, Little Italy matrices fit worse than the Polymod one for VZV, but better than concurrent matrices for B19. This is the first occasion where synthetic contact matrices are systematically compared with real ones, and validated against epidemiological data. The results suggest that simple, carefully designed, synthetic matrices can provide a fruitful complementary approach to questionnaire-based matrices. The paper also supports the idea that, depending on the transmissibility level of the infection, either the number of different contacts, or repeated exposure, may be the key factor for transmission

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics

The legacy of Corrado Gini in population studies

This volume contains 12 papers that range over many different research subjects, taking in many of the population questions that, directly or indirectly, absorbed Corrado Gini as demographer and social scientist over several decades. They vary from the analysis of the living conditions and behaviours of the growing foreign population (measurements and methods of analysis, socio-economic conditions and health, ethnic residential segregation, sex-ratio at birth), to studies on the homogamy of couples; from population theories (with reference to the cyclical theory of populations) to the modelling approach to estimating mortality in adult ages or estimating time transfers, by age and sex, related to informal child care and adult care; from historical studies that take up themes dear to Gini (such as the estimates of Italian military deaths in WWI), to the application of Gini’s classical measurements to studying significant phenomena today (transition to adulthood and leaving the parental home, health care, disabled persons and social integration). The subjects and measurements that appear here are not intended to exhaust the broad spectrum of Gini’s research work in the demographic and social field (nor could they), but they can make up a part of the intersection between his vast legacy and some interesting topics in current research, some of which were not even imaginable in the mid twentieth century. Looking at the many contributions that celebrated Gini in Treviso and thinking about his legacy, it seems possible to identify at least two typologies of approach, to be found in this issue of the journal, too. On the one hand, there are contributions that aim to retrieve and discuss themes, methodologies and measurements dealt with or used by Gini so as to evaluate their present relevance and importance in the current scholarly debate. On the other, there are contributions that deal with topics that are far from Gini’s work, as they study very recent phenomena, but actually, among other things, make use of methods and indicators devised by Gini that are now so much part of the common currency of methodology, so they don’t require explicit reference to their Author

The Leverage of Demographic Dynamics on Carbon Dioxide Emissions: Does Age Structure Matter?

This article provides a methodological contribution to the study of the effect of changes in population age structure on carbon dioxide (CO2) emissions. First, I propose a generalization of the IPAT equation to a multisector economy with an age-structured population and discuss the insights that can be obtained in the context of stable population theory. Second, I suggest a statistical model of household consumption as a function of household size and age structure to quantitatively evaluate the extent of economies of scale in consumption of energy-intensive goods, and to estimate age-specific profiles of consumption of energy-intensive goods and of CO2 emissions. Third, I offer an illustration of the methodologies using data for the United States. The analysis shows that per-capita CO2 emissions increase with age until the individual is in his or her 60s, and then emissions tend to decrease. Holding everything else constant, the expected change in U.S. population age distribution during the next four decades is likely to have a small, but noticeable, positive impact on CO2 emissions

Estimating the impact of school closure on social mixing behaviour and the transmission of close contact infections in eight European countries

BACKGROUND: Mathematical modelling of infectious disease is increasingly used to help guide public health policy. As directly transmitted infections, such as influenza and tuberculosis, require contact between individuals, knowledge about contact patterns is a necessary pre-requisite of accurate model predictions. Of particular interest is the potential impact of school closure as a means of controlling pandemic influenza (and potentially other pathogens). METHODS: This paper uses a population-based prospective survey of mixing patterns in eight European countries to study the relative change in the basic reproduction number (R0--the average number of secondary cases from a typical primary case in a fully susceptible population) on weekdays versus weekends and during regular versus holiday periods. The relative change in R0 during holiday periods and weekends gives an indication of the impact collective school closures (and prophylactic absenteeism) may have during a pandemic. RESULTS: Social contact patterns differ substantially when comparing weekdays to the weekend and regular to holiday periods mainly due to the reduction in work and/or school contacts. For most countries the basic reproduction number decreases from the week to weekends and regular to holiday periods by about 21% and 17%, respectively. However for other countries no significant decrease was observed. CONCLUSION: We use a large-scale social contact survey in eight different European countries to gain insights in the relative change in the basic reproduction number on weekdays versus weekends and during regular versus holiday periods. The resulting estimates indicate that school closure can have a substantial impact on the spread of a newly emerging infectious disease that is transmitted via close (non sexual) contacts