Paying the Piper: The High Cost of Funerals in South Africa

We analyze funeral arrangements following the deaths of 3,751 people who died between January 2003 and December 2005 in the Africa Centre Demographic Surveillance Area. We find that, on average, households spend the equivalent of a year's income for an adult's funeral, measured at median per capita African (Black) income. Approximately one-quarter of all individuals had some form of insurance, which helped surviving household members defray some fraction of funeral expenses. However, an equal fraction of households borrowed money to pay for the funeral. We develop a model, consistent with ethnographic work in this area, in which households respond to social pressure to bury their dead in a style consistent with the observed social status of the household and that of the deceased. Households that cannot afford a funeral commensurate with social expectations must borrow money to pay for the funeral. The model leads to empirical tests, and we find results consistent with our model of household decision-making.

Well-Being and Social Capital on Planet Earth: Cross-National Evidence from 142 Countries

High levels of social trust and social support are associated with life satisfaction around the world. However, it is not known whether this association extends to other indicators of social capital and of subjective well-being globally. We examine associations between three measures of social capital and three indicators of subjective well-being in 142 low-, middle- and high-income countries. Furthermore, we explore whether positive and negative feelings mirror each other or if they are separate constructs that behave differently in relation to social capital. Data comes from the Gallup World Poll, an international cross-sectional comparable survey conducted yearly from 2005 to 2009 for those 15 years of age and over. The poll represents 95% of the world's population. Social capital was measured with self-reports of access to support from relatives and friends, of volunteering to an organization in the past month, and of trusting others. Subjective well-being was measured with self-reports of life satisfaction, positive affect, and negative affect. We first estimate random coefficient (multi-level) models and then use multivariate (individual-level) Ordinary Least Square (OLS) regression to model subjective well-being as a function of social support, volunteering and social trust, controlling for age, gender, education, marital status, household income and religiosity. We found that having somebody to count on in case of need and reporting high levels of social trust are associated with better life evaluations and more positive feelings and an absence of negative feelings in most countries around the world. Associations, however, are stronger for high- and middle-income countries. Volunteering is also associated with better life evaluations and a higher frequency of positive emotions. There is not an association, however, between volunteering and experiencing negative feelings, except for low-income countries. Finally, we present evidence that the two affective components of subjective well-being behave differently in relation to different indicators of social capital and social support across countries

On Nonstable and Stable Population Momentum

This article decomposes total population momentum into two constituent and multiplicative parts: “nonstable” momentum and “stable” momentum. Nonstable momentum depends on deviations between a population’s current age distribution and its implied stable age distribution. Stable momentum is a function of deviations between a population’s implied stable and stationary age distributions. In general, the factorization of total momentum into the product of nonstable and stable momentum is a very good approximation. The factorization is exact, however, when the current age distribution is stable or when observed fertility is already at replacement. We provide numerical illustrations by calculating nonstable, stable, and total momentum for 176 countries, the world, and its major regions. In short, the article brings together disparate strands of the population momentum literature and shows how the various kinds of momentum fit together into a single unifying framework

Standardized coefficients of social capital on negative feelings score (NFS).

<p>Notes:</p>*<p>p value<5 percent.</p><p>Data source: World Gallup Poll, 2005–2009.</p><p>“<i>γ₁</i>” columns indicate standardized coefficients of a social capital measure (social support, volunteering, or trust) on negative feelings score, estimated using OLS with country fixed effects, also controlling for age, gender, education, household income, marital status, religiosity, and year dummy variables.</p><p>Data is weighted by sampling weights; robust standard errors clustered at country level are estimated.</p

Standardized coefficients of social capital on life evaluation (GLE).

<p>Notes:</p>*<p>p value<5 percent.</p><p>Data source: World Gallup Poll, 2005–2009.</p><p>“<i>γ₁</i>” columns indicate standardized coefficients of a social capital measure (social support, volunteering, or trust) on life evaluation, estimated using OLS with country fixed effects, also controlling for age, gender, education, household income, marital status, religiosity, and year dummies.</p><p>Data is weighted by sampling weights; robust standard errors clustered at country level are estimated.</p

Summary statistics of subjective well-being measures, social capital indicators and socio-demographic variables.

<p>Data source: Gallup World Poll, 2005–2009. Data is weighted by cross-sectional sampling weights.</p

Intra-class correlation coefficients (ICCs) and variances of country level random components in multilevel linear regressions.

*<p>p value<5 percent. “Intercept only” model is a multilevel model with no covariates other than the constant. “ICC” stands for “intraclass correlation coefficient”, which is calculated as the ratio of country-level variance versus total variance in the intercept-only model, and can be interpreted as the proportion of total variance attributed to the country level. The key independent variable in model 1 is “social support”; in model 2 the key independent variable is “volunteering”; in model 3 the key independent variable is “social trust”. All models control for age, gender, education, household income, marital status, religiosity, and year dummy variables.</p

Standardized coefficients of social capital on positive feelings score (PFS).

*<p>p value<5 percent.</p><p>Data source: World Gallup Poll, 2005–2009.</p><p>“<i>γ₁</i>” columns indicate standardized coefficients of a social capital measure (social support, volunteering, or trust) on positive feelings score, estimated using OLS with country fixed effects, also controlling for age, gender, education, household income, marital status, religiosity, and year dummy variables.</p><p>Data is weighted by sampling weights; robust standard errors clustered at country level are estimated.</p