Psychology Implies Paternalism? Bounded Rationality may Reduce the Rationale to Regulate Risk-Taking

Behavioral economists increasingly argue that violations of rationality axioms provide a new rationale for paternalism – to “de-bias” individuals who exhibit errors, biases and other allegedly pathological psychological regularities associated with Tversky and Kahneman’s (in Science 185:1124–1131, 1974) heuristics-and-biases program. The argument is flawed, however, in neglecting to distinguish aggregate from individual rationality. The aggregate consequences of departures from normative decision-making axioms may be Pareto-inferior or superior. Without a well-specified theory of aggregation, individual-level biases do not necessarily imply losses in efficiency. This paper considers the problem of using a social-welfare function to decide whether to regulate risk-taking behavior in a population whose individual-level behavior may or may not be consistent with expected utility maximization. According to the social-welfare objective, unregulated aggregate risk distributions resulting from non-maximizing behavior are often more acceptable (i.e., lead to a weaker rationale for paternalism) than population distributions generated by behavior that conforms to the standard axioms. Thus, psychological theories that depart from axiomatic decision-making norms do not necessarily strengthen the case for paternalism, and conformity with such norms is generally not an appropriate policy-making objective in itself.     

Relational Aggression in Middle Childhood: Predictors and Adolescent Outcomes

This study examined gender differences in the level and developmental course of relational aggression in middle childhood, as well as early predictors and outcomes of relational aggression, after controlling for concurrent physical aggression. Relational (RAgg) and Physical aggression (PAgg) scores for 558 boys and 545 girls at the ages of eight to 11 in the NICHD Study of Early Child Care and Youth Development (SECCYD) were created by combining the highest rating for each item across mother and teacher reports. Longitudinal analyses were conducted using latent curve models of RAgg with PAgg as a time‐varying covariate, with all parameters allowed to vary by gender. Boys and girls had different growth parameters of RAgg. Girls' RAgg intercept was higher, and the slope was not different from zero; boys' RAgg intercept was lower, and the slope declined. Mother–child conflict in early childhood predicted RAgg intercept for both boys and girls, but maternal harsh control and sensitivity were also uniquely predictive for girls whereas center care was uniquely predictive for boys. RAgg intercept predicted adolescent self‐reports of depression for girls and delinquency and risk‐taking for both boys and girls; the magnitude of the association with risk taking was significantly greater for boys.     

A cumulative ecological–transactional risk model of child maltreatment and behavioral outcomes: Reconceptualizing early maltreatment report as risk factor

The current analysis was designed to critically examine the tendency to focus on child maltreatment as a unique risk factor and test the resulting assumption of a direct causal relationship between early maltreatment and later behavioral problems. The variation seen in behavioral outcomes among children reported for maltreatment early in life led us to hypothesize that the cumulative level of risk facing children and their families can, at least in part, account for that variation in outcome. Participants were 242 mothers of predominantly at-risk newborn infants who were interviewed shortly after giving birth. The State Central Registry of Maltreatment was then reviewed over each child's first four years of life to assess for early maltreatment. Following the neonatal interviews, mothers completed the Child Behavior Checklist when their children were 4, 6, 8, 10 and 12 years-of-age. Although early maltreatment report does appear to be important to early child functioning, the cumulative level of risk more strongly predicts long-term clinical behavioral difficulty. High-risk children who were not reported for maltreatment by age 4 demonstrate greater behavioral problem trajectories than did low-risk children with a maltreatment report. Maltreatment itself may be best conceptualized as an important, but not singularly so, risk factor for later behavioral problems. In focusing directly on reported maltreatment, our child protective systems may be paying too little attention to what else is going wrong in the lives of children and targeting intervention efforts in the wrong direction. When it comes to early maltreatment our child protective policy and practice need to broaden their lenses to include greater emphasis on overall family functioning, stress and well-being. Early maltreatment, it seems, may be a symptom of more profound problems in the early environments of our most vulnerable children, rather than the problem itself.     

A lofistic rlgression analysis of response-time data where the hazard function is time dependent

A logistic-exponential model for analyzing response-time data involving regressor variables is modified to allow for non-consrarey of the hazard function. For the discrete observation case illustrated the logit of the probability of responding in a time interval cf arbitrary length is taken as the sum of a function of resressor variables and a function of the time variable. The particular functions chosen in the two medical examples analyzed are linear in the parameters involved. A polynomial function of time is employed in the absence of knowledge as to a more appropriate form. Various issues arising in the analysis made are discussed.     

In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?

It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this paper, we question this interpretation. Our analysis shows that neither data mining nor dynamic misspecification of the model under the null nor unmodelled structural change under the null are plausible explanations of the observed tendency of in-sample tests to reject the no-predictability null more often than out-of-sample tests. We provide an alternative explanation based on the higher power of in-sample tests of predictability in many situations. We conclude that results of in-sample tests of predictability will typically be more credible than results of out-of-sample tests.     

THE McMASTER FAMILY ASSESSMENT DEVICE: RELIABILITY AND VALIDITY*

This paper reports a series of studies investigating the reliability and validity of the McMaster Family Assessment Device (FAD). The results indicated that the FAD has: (a) adequate test-retest reliability, (b) low correlations with social desirability, (c) moderate correlations with other self-report measures of family functioning, and (d) differentiates significantly between clinician-rated healthy and unhealthy families. Cut-off scores for identifying healthy and unhealthy families also were developed which have adequate sensitivity and specificity. Additionally, the relationships between the FAD, Family Unit Inventory, and FACES-II suggests that the cohension and adaptability scales from the FACES-II have a linear relationship with health/pathology.     

On the momentum of population growth

If age-specific birth rates drop immediately to the level of bare replacement the ultimate stationary number of a population will be given by (9): $$\left( {{\textstyle{{b\mathop e\limits^ \bullet {}_0} \over {r\mu }}}} \right)\left( {\frac{{R_0 - 1}}{{R_0 }}} \right)$$ multiplied by the present number, where b is the birth rate, r the rate of increase, \(\mathop e\limits^ \bullet _0 \) the expectation of life, and R ₀ the Net Reproduction Rate, all before the drop in fertility, and μ the mean age of childbearing afterwards. This expression is derived in the first place for females on the stable assumption; extension to both sexes is provided, and comparison with real populations shows the numerical error to be small where fertility has not yet started to drop. The result (9) tells how the lower limit of the ultimate population depends on parameters of the existing population, and for values typical of underdeveloped countries works out to about 1. 6. If a delay of 15 years occurs before the drop of the birth rate to replacement the population will multiply by over 2. 5 before attaining stationarity. The ultimate population actually reached will be higher insofar as death rates continue to improve. If stability cannot be assumed the ultimate stationary population is provided by the more general expression (7), which is still easier to calculate than a detailed projection.     

On structure-dependent grammars: A reply to Mabry

The Analysis of Verbal Behavior - In a recent paper, Mabry (1993) examines various aspects of Skinner’s (1957) treatment of grammar, and he compares it with cognitivist approaches. Mabry...