How can we measure the causal effects of social networks using observational data? Evidence from the diffusion of family planning and AIDS worries in South Nyanza District, Kenya

This study presents estimates that social networks exert causal and substantial influences on individuals’ attitudes and behaviors. The study explicitly allows for the possibility that social networks are not chosen randomly, but rather that important characteristics such as unobserved preferences and unobserved community characteristics determine not only the outcomes of interest but also the informal conversational networks in which they are discussed. Longitudinal survey data from rural Kenya on family-planning and AIDS are used to estimate the impact of social networks while controlling for their unobserved determinants. There are four major findings: First, the endogeneity of social networks can substantially distort the usual cross-sectional estimates of network influences. Second, social networks have significant and substantial effects even after controlling for unobserved factors that may determine the nature of the social networks. Third, these network effects generally are nonlinear and asymmetric. In particular, they are relatively large for individuals who have at least one network partner who is perceived to be using contraceptives or or to be at high risk of HIV/AIDS, which is consistent with S-shaped diffusion models that have been emphasized in the literature. Fourth, the effects of networks are not confined to the use of family planning by women, the focus of much of the literature on networks in demography, but appear to be more general, influencing responses to HIV/AIDS, and influencing men as well as women. (AUTHORS)

Childhood health-care practices among Italians and Jews in the United States, 1910-1940

This paper examines attitudes toward childhood health-care practices among urban Italian and Jewish families in the United States in the first part of the twentieth century. Although women in both groups were concerned about their children’s health, Italian and Jewish respondents differed in their attitudes toward home remedies, doctors, and medical advice literature. Jewish women were more likely to turn rapidly to professional medical assistance, typically from Jewish doctors, whereas Italian women were more likely to rely longer on common sense before eventually seeking professional medical intervention outside the family and ethnic group. These differences are evident both in the respondents’ recollections of their mothers’ and their own child-care practices, and suggest persistent ethnic cultures. That differences in child care are consistent with the mortality differences documented in other sources supports previous speculations about the importance of child care, and thus the role of culture in health transitions

Social Networks and HIV/AIDS Risk Perceptions

Understanding the determinants of individuals\u27 perceptions of their risk of becoming infected with HIV and their perceptions of acceptable strategies of prevention is an essential step toward curtailing the spread of this disease. We focus in this article on learning and decision-making about AIDS in the context of high uncertainty about the disease and appropriate behavioral responses. We argue that social interactions are important for both. Using longitudinal survey data from rural Kenya and Malawi, we test this hypothesis. We investigate whether social interactions—and especially the extent to which social network partners perceive themselves to be at risk—exert causal influences on respondents\u27 risk perceptions and on one approach to prevention, spousal communication about the threat of AIDS to the couple and their children. The study explicitly allows for the possibility that important characteristics, such as unobserved preferences or community characteristics, determine not only the outcomes of interest but also the size and composition of networks. The most important empirical result is that social networks have significant and substantial effects on risk perceptions and the adoption of new behaviors even after we control for unobserved factors

Attrition in longitudinal household survey data

Longitudinal household data can have considerable advantages over much more widely used cross-sectional data. The collection of longitudinal data, however, may be difficult and expensive. One problem that has concerned many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be particularly severe in areas where there is considerable mobility because of migration between rural and urban areas. Many analysts share the intuition that attrition is likely to be selective on characteristics such as schooling and that high attrition is likely to bias estimates made from longitudinal data. This paper considers the extent of and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high per-year attrition rates between survey rounds. Our estimates indicate that (1) the means for a number of critical outcome and family background variables differ significantly between attritors and nonattritors; (2) a number of family background variables are significant predictors of attrition; but (3) nevertheless, the coefficient estimates for “standard” family background variables in regressions and probit equations for the majority of the outcome variables considered in all three data sets are not affected significantly by attrition. Therefore, attrition apparently is not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to results for developed economies, suggest that for these outcome variables—despite suggestions of systematic attrition from univariate comparisons between attritors and nonattritors, multivariate estimates of behavioral relations of interest may not be biased due to attrition.Household surveys Methodology ,

Attrition in longitudinal household survey data

Longitudinal household data can have considerable advantages over much more widely used cross-sectional data. The collection of longitudinal data, however, may be difficult and expensive. One problem that has concerned many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be particularly severe in areas where there is considerable mobility because of migration between rural and urban areas. Many analysts share the intuition that attrition is likely to be selective on characteristics such as schooling and that high attrition is likely to bias estimates made from longitudinal data. This paper considers the extent of and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high per-year attrition rates between survey rounds. Our estimates indicate that (1) the means for a number of critical outcome and family background variables differ significantly between attritors and nonattritors; (2) a number of family background variables are significant predictors of attrition; but (3) nevertheless, the coefficient estimates for “standard” family background variables in regressions and probit equations for the majority of the outcome variables considered in all three data sets are not affected significantly by attrition. Therefore, attrition apparently is not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to results for developed economies, suggest that for these outcome variables—despite suggestions of systematic attrition from univariate comparisons between attritors and nonattritors, multivariate estimates of behavioral relations of interest may not be biased due to attrition.Household surveys Methodology ,

Attrition in longitudinal household survey data - some tests for three developing-country samples

For capturing dynamic demographic relationships, longitudinal household data can have considerable advantages over more widely used cross-sectional data. But because the collection of longitudinal data may be difficult and expensive, analysts must assess the magnitudes of the problems, specific to longitudinal, but not to cross-sectional data. One problem that concerns many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be especially severe where there is considerable migration between rural, and urban areas. And attrition is likely to be selective on such characteristics as schooling, so high attrition is likely to bias estimates. The authors consider the extent, and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high annual attrition rates between survey rounds. Their estimates indicate that: 1) the means for a number of critical outcome, and family background variables differ significantly between those who are lost to follow-up, and those who are re-interviewed. 2) A number of family background variables are significant predictors of attrition. 3) Nevertheless, the coefficient estimates for standard family background variables in regressions, and probit equations for the majority of outcome variables in all three data sets, are not significantly affected by attrition. So attrition is apparently not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to those for industrial countries, suggest that multivariate estimates of behavioral relations may not be biased because of attrition. This wold support the collection of longitudinal data.Statistical&Mathematical Sciences,Public Health Promotion,Health Monitoring&Evaluation,Scientific Research&Science Parks,Educational Sciences,Science Education,Scientific Research&Science Parks,Health Monitoring&Evaluation,Poverty Assessment,Statistical&Mathematical Sciences

The causes of stalling fertility transitions

An examination of fertility trends in countries with multiple DHS surveys found that in the 1990s fertility stalled in mid-transition in seven countries: Bangladesh, Colombia, Dominican Republic, Ghana, Kenya, Peru, and Turkey. An analysis of trends in the determinants of fertility revealed a systematic pattern of leveling off or near leveling in a number of determinants, including contraceptive use, the demand for contraception, and wanted fertility. Findings suggest no major deterioration in contraceptive access during the stall, but levels of unmet need and unwanted fertility are relatively high and improvements in access to family planning methods would therefore be desirable. No significant link was found between the presence of a stall and trends in socioeconomic development, but at the onset of the stall the level of fertility was low relative to the level of development in all but one of the stalling countries