Causes and consequences of early-life health

We examine the consequences of child health for economic and health outcomes in adulthood, using height as a marker of childhood health. After reviewing previous evidence, we present a conceptual framework that highlights data limitations and methodological problems that complicate the study of this topic. We then present estimates of the associations between height and a range of outcomes—including schooling, employment, earnings, health, and cognitive ability—measured in five data sets from early to late adulthood. These results indicate that, on average, taller individuals attain higher levels of education. Height is also positively associated with better economic, health, and cognitive outcomes. These associations are only partially explained by the higher average educational attainment of taller individuals. We then use data from the National Longitudinal Survey of Youth 1979 Children and Young Adults survey to document the associations between health, cognitive development, and growth in childhood. Even among children with the same mother, taller siblings score better on cognitive tests and progress through school more quickly. Part of the differences found between siblings arises from differences in their birth weights and lengths attributable to mother’s behaviors while pregnant. Taken together, these results support the hypothesis that childhood health influences health and economic status throughout adulthood.     

Bayesian autoregressive spectral analysis

The article describes an operational Bayesian approach to making inferences for the spectral density function for univariate autoregressive processes and for the AR operator of multivariate autoregressive processes. The derivation of the approach is described. Numerical examples, including the Wolfer Sunspot numbers, are used to demonstrate the practical usefulness of the approach.     

The Economic Efficiency of Sampling Size: The Case of Beef Trim

The economically optimal sample size in a food safety test balances the marginal costs and marginal benefits of increasing the sample size. We provide a method for selecting the sample size when testing beef trim for Escherichia coli O157:H7 that equates the averted costs of recalls and health damages from contaminated meats sold to consumers with the increased costs of testing while allowing for uncertainty about the underlying prevalence rates of contamination. Using simulations, we show that, in most cases, the optimal sample size is larger than the current sample size of 60 and, in some cases, it exceeds 120. Moreover, lots with a lower prevalence rate have a higher expected damage because contamination is more difficult to detect. Our simulations indicate that these lots have a higher optimal sampling rate.     

Bayesian analysis of threshold autoregressions

A nonasymptotic Bayesian approach is developed for analysis of data from threshold autoregressive processes with two regimes. Using the conditional likelihood function, the marginal posterior distribution for each of the parameters is derived along with posterior means and variances. A test for linear functions of the autoregressive coefficients is presented. The approach presented uses a posterior p-value averaged over the values of the threshold. The one-step ahead predictive distribution is derived along with the predictive mean and variance. In addition, equivalent results are derived conditional upon a value of the threshold. A numerical example is presented to illustrate the approach.     

Bayesian autoregressive filter and squared gain estimation

This article describes a Bayesian small sample approach to making inferences for the operator (or filter) and squared gain of a p — th order Gaussian univariate autoregressive process. Simultaneous pos¬terior probability bands are developed for the real and the imaginary parts of the frequency-response function of an autoregressive operator as well as for the squared gain of an autoregressive process.     

Stochastic Learning Dynamics and Speed of Convergence in Population Games

We study how long it takes for large populations of interacting agents to come close to Nash equilibrium when they adapt their behavior using a stochastic better reply dynamic. Prior work considers this question mainly for 2 × 2 games and potential games; here we characterize convergence times for general weakly acyclic games, including coordination games, dominance solvable games, games with strategic complementarities, potential games, and many others with applications in economics, biology, and distributed control. If players' better replies are governed by idiosyncratic shocks, the convergence time can grow exponentially in the population size; moreover, this is true even in games with very simple payoff structures. However, if their responses are sufficiently correlated due to aggregate shocks, the convergence time is greatly accelerated; in fact, it is bounded for all sufficiently large populations. We provide explicit bounds on the speed of convergence as a function of key structural parameters including the number of strategies, the length of the better reply paths, the extent to which players can influence the payoffs of others, and the desired degree of approximation to Nash equilibrium.     

A bayesian analysis of the mixed linear model

The mixed model is defined. The exact posterior distribution for the fixed effect vector is obtained. The exact posterior distribution for the error variance is obtained. The exact posterior mean and variance of a Bayesian estimator for the variances of random effects is also derived. All computations are non-iterative and avoid numerical integrations.     

Income and child development

We examine how income is associated with the home environments and the cognitive and behavioral development of pre-school children using data from a birth cohort study of children born at the end of the 20th century. Lower-income 3-year-old children are more likely than wealthier children to live in homes with inadequate physical environments and to have mothers who are more likely to be stressed, depressed, harsh and unresponsive. Additionally, low income children have lower PPVT scores, more mother-reported aggressive, withdrawn, and anxious behavior problems, and also more interviewer-reported problems with behavior, than more affluent children. A key policy question is whether increases in the incomes of poor families would result in improvements in children's outcomes, at least in part through improvements in the home environment. This question is difficult to answer using observational data. However, we argue that, even under the most generous interpretation of the associations we estimate, large income transfer programs would have relatively small effects on children's cognitive and behavioral outcomes.     

Orphans in Africa: parental death,poverty, and school enrollment

We examine the impact of orphanhood on children's school enrollment in 10 sub-Saharan African countries. Although poorer children in Africa are less likely to attend school, the lower enrollment of orphans is not accounted for solely by their poverty. We find that orphans are less likely to be enrolled than are nonorphans with whom they live. Consistent with Hamilton's rule, the theory that the closeness of biological ties governs altruistic behavior, outcomes for orphans depend on the relatedness of orphans to their household heads. The lower enrollment of orphans is largely explained by the greater tendency of orphans to live with distant relatives or unrelated caregivers.