Investigating demographic processes using innovative combinations of remotely sensed and demographic data

Population and Environment -     

Correction to: Assessing recall bias and measurement error in high-frequency social data collection for human-environment research

Population and Environment - The original version of this article unfortunately contained a mistake. The name of “Md. Ehsanul Haque Tamal” is now corrected in the author group of this...     

On the estimation of multidimensional demographic models with population registration data

In this paper the estimation of multidimensional demographic models is investigated in situations where population registration data are available. With this kind of aggregate data, estimation by traditional methods is not possible. We look at two versions of the multidimensional model: the constant intensities model and the linear integration model. Some logical inconsistencies in the derivation of the latter are discussed. In particular, we argue that the linear integration model is not compatible with a Markov process. A new algorithm for the estimation of the constant intensities model with population registration data is proposed. Some preliminary results on the mathematical and statistical properties of this method are given. The algorithm is applied to Dutch nuptiality data.     

Correction to: Horizontal Inequality and Data Challenges

Inequality and social exclusion receive considerable contemporary policy attention. In the field of international development, inequality—both vertical (between individuals and households) and horizontal (between groups)—is a core concern in the 2030 Agenda for Sustainable Development. Despite considerable attention to horizontal inequality in both research and policy, there are notable gaps and weaknesses in our empirical knowledge about how it manifests within and across countries and over time. This has implications not only for the rigour with which we can build and test theories in this area, but also for informing policy, monitoring trends, and evaluating the impact of interventions. This article probes what more can be learned from existing survey and census data to address empirical gaps. It argues that key methodological, conceptual, and—in particular—political issues pose persistent challenges for such survey and census data on topics relating to ‘ethnicity’ broadly defined. These challenges imply not only real limits in the so-called data revolution for sustainable development, but also risks to ‘evidence-based’ policy making in this area when it relies too heavily on quantitative data. This article serves also as the introductory and framing paper for this special issue.

     

Growth and inequality: a demographic explanation

This paper investigates the relationship between growth and inequality from a demographic point of view. In an extended model of the accidental bequest with endogenous fertility, we analyze the effects of a decrease in old-age mortality rate on the equilibrium growth rate as well as on the income distribution. We show that the relationship between growth and inequality is at first positive and then may be negative in the process of population aging. The results are consistent with the empirical evidence in some developed countries.

Propensity to adopt innovative housing: Development of knowledge indexes

The process by which energy efficient housing alternatives is diffused through society in relation to the information flow is relatively unknown. The major purpose of this study was to validate a continuum of the propensity to adopt alternative housing (passive and active solar, earth sheltered and retrofitted) based on knowledge level. Findings indicate knowledge indices are valid predictors of consumer acceptance of energy efficient housing alternatives. A greater level of knowledge was correlated with respondents willing to adopt an alternative housing type.     

Fertility decline in the modern world and in the original demographic transition: Testing three theories with cross-national data

This study uses aggregate data on a large number of the world's societies to test three theories of fertility decline in the modern world and in the original demographic transition. One prominent theory relates fertility decline to the changing economic value of children. With industrialization and overall modernization the economic value of children's labor shifts from positive to negative. This interpretation has been challenged by those who claim that the flow of wealth in preindustrial societies is always from parent to child rather than from child to parent. An alternative interpretation is that fertility levels reflect people's efforts to promote their reproductive success, and that this requires the careful tracking of infant and child mortality. Fertility rates are adjusted to the rate of infant and child survival, and will be high when survival rates are low and low when survival rates are high. A third theory emphasizes female empowerment. Fertility will be high when women are highly subordinated to men, but as women gain more autonomy and control over their own lives they reduce their fertility levels because, among other possibilities, higher levels of fertility present them with serious burdens. We tested all three theories through multiple regression analyses performed on two samples of societies, the first a large sample of the world's nation-states during the period between 1960 and 1990, and the second a sample of now-developed societies between 1880 and 1940. Our findings showed that infant mortality was an excellent predictor of fertility, and that female empowerment was a good predictor. However, there was only weak support for the argument that the economic value of children's labor plays an important role in fertility decisions. The findings were discussed in the context of a broader interpretation of fertility behavior in societies with high levels of industrialization and modernization.     

Knox meets Cox: Adapting epidemiological space-time statistics to demographic studies

Many important questions and theories in demography focus on changes over time, and on how those changes differ over geographic and social space. Space-time analysis has always been important in studying fertility transitions, for example. However, demographers have seldom used formal statistical methods to describe and analyze time series of maps. One formal method, used widely in epidemiology, criminology, and public health, is Knox’s space-time interaction test. In this article, we discuss the potential of the Knox test in demographic research and note some possible pitfalls. We demonstrate how to use familiar proportional hazards models to adapt the Knox test for demographic applications. These adaptations allow for nonrepeatable events and for the incorporation of structural variables that change in space and time. We apply the modified test to data on the onset of fertility decline in Brazil over 1960–2000 and show how the modified method can produce maps indicating where and when diffusion effects seem strongest, net of covariate effects.     

Transfers to the old,government debt and demographic change

In this paper we take the view that policy makers (representing the interests of the living generations in one way or another) take the relationship between (explicit) intergenerational transfer systems (including public pension schemes) and government deficits into account. It is assumed that policy makers are behaving altruistically towards past and future generations. Given the behavioral model, an analysis is made of the effects of demographic changes (such as the baby-boom of the 1940s and 1950s and the decline of birth rates in the 1970s) on the decisions to be taken with respect to the tax rate of the public pension system and the size of government debt. From the analysis it appears that, with the assumption of altruistic decision-makers, periods of increasing or decreasing debt can occur alternately in periods of demographic change.     

Options and sequences: Europe’s demographic patterns

It is argued in this lecture that Ryder’s approach to the study of the role of the cohort in social change is too narrow. Cohorts do not only permit change; they actively create the options succeeding cohorts have to choose from. Through its own choice from amongst the options perceived, each cohort both limits and enriches the options of the next. It is through the choice people make with regard to life shaping demographic events that they group themselves into ‘mental’ cohorts. The course of demographic events in Western Europe in the postwar period is difficult to understand if one does not appreciate that these events form a sequence. A sequence generated by the quite specific option(s) each ‘mental’ cohort, through its own choice, created for the next. Current demographic patterns in Europe have to be interpreted in terms of differences in social and cultural heritage of the countries concerned, and in terms of the differences in options perceived and selected.     

Biosocial models of demographic behavior: An introduction

A workshop on biosocial models of demographic behavior was organized to provide information to members of the Social Sciences and Population Study Section (SSP), the group entrusted by the National Institutes of Health (NIH) with the responsibility for conducting the first level of peer review of demographic applications submitted to NIH for possible funding. Some of the variables studies by demographers are biological, e.g., fertility, fecundity, morbidity, and mortality, so demographers are not unaware of biological variables. However, they tend to treat biological variables as something to be explained by social, economic, and psychological factors rather than to be integrated into an explanatory paradigm. This workshop contains papers that focus upon various stages of the life cycle and explore the importance of biosocial variables in explaining selected aspects of human behavior.This introduction presents an overview of the topics covered by the authors of the papers presented and the workshop, and is based upon opening remarks at the DRG Workshop on Biosocial Models of Demographic Behavior, Bethesda, MD, 12 October 1994.     

The role of demographic data in the operation of public policy: a case study of the job training partnership act

To work at the state and local levels, the Job Training Partnership Act (JTPA) requires specific kinds of demographic data. Unemployment figures, poverty information, occupational supply and demand data, wage structure, and many other types of data are used in planning and operating JTPA programs, and in modifying the performance standards by which the programs are evaluated. The decennial census provides some key data and thus some significant types of information become less timely as the decade progresses. Furthermore, the framers of the Act had little or no knowledge of the forms in which data are collected and thus definitions given in the Act do not always agree with definitions used in the demographic data which are available. The policymakers for future government benefit programs could learn from this mistake: before writing legislation which is so heavily dependent on demographic data, they should ascertain what types of data are available or can be generated for use in the program.