This paper examines the decline in non-numeric responses to questions about fertility preferences among women in the developing world. These types of responses—such as “don’t know” or “it’s up to God”—have often been interpreted through the lens of fertility transition theory as an indication that reproduction has not yet entered women’s “calculus of conscious choice” (Coale 1973, p. 65), but have yet to be investigated cross-nationally and over time. Using 19 years of data from 32 countries, we find that non-numeric fertility preferences appear to decline most substantially in the early stages of a country’s fertility transition. Using country-specific and multilevel models, we explore the individual- and contextual-level characteristics that are associated with women’s likelihood of providing non-numeric responses to questions about their fertility preferences. Non-numeric fertility preferences are influenced by a host of social factors, with educational attainment and knowledge of contraception being the most robust and consistent predictors.

This paper examines the decline in non-numeric responses to questions about fertility preferences among women in the developing world. These types of response-such as 'don't know' or 'it's up to God'-have often been interpreted through the lens of fertility transition theory as an indication that reproduction has not yet entered women's 'calculus of conscious choice' (Coale 1973, p. 65). However, this has yet to be investigated cross-nationally and over time. Using 19 years of data from 32 countries, we find that non-numeric fertility preferences decline most substantially in the early stages of a country's fertility transition. Using countryspecific and multilevel models, we explore the individual-and contextual-level characteristics associated with women's likelihood of providing a non-numeric response to questions about their fertility preferences. Non-numeric fertility preferences are influenced by a host of social factors, with educational attainment and knowledge of contraception being the most robust and consistent predictors.

BACKGROUND While there is a rich literature on the practice of child fostering in sub-Saharan Africa, little is known about how fostering impacts receiving households, as few studies consider household conditions both before and after fostering. Despite the fact that circumstances surrounding fostering vary, the literature’s key distinction of fostering is often drawn along the simple line of whether or not a household is fostering a child. This paper argues that anticipation of fostering responsibilities, in particular, is a useful dimension to distinguish fostering experiences for receiving households. OBJECTIVE This paper examines the relationship between receiving a foster child and subsequent changes in household wealth. Particular emphasis is placed on how these changes are conditioned by differing levels of anticipation of the fostering event. METHODS This study uses data from Tsogolo la Thanzi (TLT), a longitudinal survey in Balaka, Malawi. Using data from 1754 TLT respondents, fixed effects pooled time-series models are estimated to assess whether and how receiving a foster child changes household wealth. RESULTS This paper demonstrates the heterogeneity of fostering experiences for receiving households. The results show that households that anticipate fostering responsibilities experience a greater increase in household wealth than both households that do not foster and those that are surprised by fostering. CONCLUSION Households that anticipate fostering responsibilities exhibit the greatest increase in household wealth. While fostering households that do not anticipate fostering responsibilities may not experience these gains, there is no evidence to indicate that such households are negatively impacted relative to households that do not foster. This finding suggests that additional childcare responsibilities may not be as detrimental to African households as some researchers have feared.

Summary In a recent article, Regan, Lakhanpal, and Anguiano (2012) highlighted the lack of evidence for different relationship outcomes between arranged and love-based marriages. Yet the sample size (n=58) used in the study is insufficient for making such inferences. Here we discuss and demonstrate how small sample sizes reduce the utility of this research.