Allais for the poor: Relations to ability,information processing,and risk attitudes

This paper complements evidence on the Allais paradox from advanced countries and educated people by a novel investigation in a poor rural area. The share of Allais-type behavior is indeed high and related to indicators of “lacking ability,” such as poor education, unemployment, and little financial sophistication. Based on prospective reference theory, we extend these characteristics by biased processing of probabilistic information. Finally, we reveal that Allais-type behavior is linked to risk-related characteristics, such as risk tolerance and optimism. This indicates a potential problem as exactly the more dynamic among the poor tend to make inconsistent decisions under uncertainty.     

Are the poor worse at dealing with ambiguity?

This paper studies the relationship between people’s ambiguity attitudes and income in the field using language as a natural source of ambiguity. It shows that the method of Baillon et al. (2017b) can be adapted for field studies, providing ambiguity measurement tasks that are more comprehensible for nonacademic subjects. Ambiguity attitudes were elicited in two groups of Chinese adolescents (poor rural and rich urban), among whom the income variation is big. In the rural group the poorer are both more ambiguity averse and more a-insensitive, whereas in the urban group the richer are more a-insensitivite. On average, the poor rural adolescents are worse at dealing with ambiguity than their urban counterparts. A-insensitivity, which measures people’s understanding of an ambiguous situation, is an important but sometimes neglected component of ambiguity attitude. Policies aiming to help people improve decisions may focus more on reducing a-insensitivity as this cognitive bias is more likely to be influenced by intervention than people’s intrinsic aversion towards ambiguity.     

Loss aversion leading to advantageous selection

Some insurance markets are characterized by “advantageous selection”, that is, ex-post risk and coverage are negatively correlated. We show that expectation-based loss aversion as in K?szegi and Rabin (Quarterly Journal of Economics, 121(4), 1133–1165, 2006; The American Economic Review, 97(4), 1047–1073, 2007) provides a natural explanation for this phenomenon in environments in which risk aversion models do not, e.g., when agents face modest-scale risks and/or in absence of moral hazard. More exposure to risk has two competing effects on an agent’s willingness to pay for insurance: a positive effect, as in standard expected utility models; and a negative one, due to a reference effect. We determine conditions under which an insurance provider optimally sets a high price at which only low risk agents buy.     

Giving in the face of risk

Decisions about how to share resources with others often need to be taken under uncertainty regarding its allocational consequences. Although risk preferences are likely important, existing research is silent about how social and risk preferences interact in such situations. In this paper we provide experimental evidence on this question. In a first experiment givers are not exposed to risk while beneficiaries’ final earnings may be larger or smaller than the allocation itself, depending on the realized state of the world. In a second experiment, risk affects the earnings of givers but not of beneficiaries. We find that individuals’ risk preferences are predictive for giving in both experiments. Increased risk exposure of beneficiaries tends to decrease giving whereas increased risk exposure of givers has no effect. We propose a simple non-linear generalization of a model allowing for other-regarding preferences, ex-post and ex-ante fairness, and risk aversion. We find some support for it in our data when risk is on the beneficiaries’ side but less so when risk is on the givers’ side. Our results point to the importance of the further development of models of social preferences that also incorporate risk preferences.     

Influence of Proximity to Kin on Residential Mobility and Destination Choice: Examining Local Movers in Metropolitan Areas

A growing body of research has examined how family dynamics shape residential mobility, highlighting the social—as opposed to economic—drivers of mobility. However, few studies have examined kin ties as both push and pull factors in mobility processes or revealed how the influence of kin ties on mobility varies across sociodemographic groups. Using data on local residential moves from the Panel Study of Income Dynamics (PSID) from 1980 to 2013, we find that location of noncoresident kin influences the likelihood of moving out of the current neighborhood and the selection of a new destination neighborhood. Analyses of out-mobility reveal that parents and young adult children living near each other as well as low-income adult children living near parents are especially deterred from moving. Discrete-choice models of neighborhood selection indicate that movers are particularly drawn to neighborhoods close to aging parents, white and higher-income households tend to move close to parents and children, and lower-income households tend to move close to extended family. Our results highlight the social and economic trade-offs that households face when making residential mobility decisions, which have important implications for broader patterns of inequality in residential attainment.     

Paternal Incarceration and Adolescent Social Network Disadvantage

Previous research has suggested that adolescent peers influence behavior and provide social support during a critical developmental period, but few studies have addressed the antecedents of adolescent social networks. Research on the collateral consequences of incarceration has explored the implications of parental incarceration for children’s behavioral problems, academic achievement, health, and housing stability, but not their social networks. Using network data from the National Longitudinal Study of Adolescent Health, I find that adolescents with recently incarcerated fathers are in socially marginal positions in their schools and befriend more-marginal peers than other adolescents: their friends are less advantaged, less academically successful, and more delinquent than other adolescents’ friends. Differences in network outcomes are robust to a variety of specifications and are consistent across race and gender subgroups. This study advances the social networks literature by exploring how familial characteristics can shape adolescent social networks and contributes to the collateral consequences of incarceration literature by using network analysis to consider how mass incarceration may promote intergenerational social marginalization.     

Fertility and Life Satisfaction in Rural Ethiopia

Despite recent strong interest in the link between fertility and subjective well-being, the focus has centered on developed countries. For poorer countries, in contrast, the relationship remains rather elusive. Using a well-established panel survey—the Ethiopian Rural Household Survey (ERHS)—we investigate the empirical relationship between fertility and life satisfaction in rural Ethiopia, the largest landlocked country in Africa. Consistent with the fertility theories for developing countries and with the sociodemographic characteristics of rural Ethiopia, we hypothesize that this relationship varies by gender and across life stages, being more positive for men and for parents in old age. Indeed, our results suggest that older men benefit the most in terms of life satisfaction from having a large number of children, while the recent birth of a child is detrimental for the subjective well-being of women at reproductive ages. We address endogeneity issues by using lagged life satisfaction in ordinary least squares regressions, through fixed-effects estimation and the use of instrumental variables.     

The Network Survival Method for Estimating Adult Mortality: Evidence From a Survey Experiment in Rwanda

Adult death rates are a critical indicator of population health and well-being. Wealthy countries have high-quality vital registration systems, but poor countries lack this infrastructure and must rely on estimates that are often problematic. In this article, we introduce the network survival method, a new approach for estimating adult death rates. We derive the precise conditions under which it produces consistent and unbiased estimates. Further, we develop an analytical framework for sensitivity analysis. To assess the performance of the network survival method in a realistic setting, we conducted a nationally representative survey experiment in Rwanda (n = 4,669). Network survival estimates were similar to estimates from other methods, even though the network survival estimates were made with substantially smaller samples and are based entirely on data from Rwanda, with no need for model life tables or pooling of data from other countries. Our analytic results demonstrate that the network survival method has attractive properties, and our empirical results show that this method can be used in countries where reliable estimates of adult death rates are sorely needed.