Personality at Face Value: Facial Appearance Predicts Self and Other Personality Judgments among Strangers and Spouses

Character judgments, based on facial appearance, impact both perceivers’ and targets’ interpersonal decisions and behaviors. Nonetheless, the resilience of such effects in the face of longer acquaintanceship duration is yet to be determined. To address this question, we had 51 elderly long-term married couples complete self and informant versions of a Big Five Inventory. Participants were also photographed, while they were requested to maintain an emotionally neutral expression. A subset of the initial sample completed a shortened version of the Big Five Inventory in response to the pictures of other opposite sex participants (with whom they were unacquainted). Oosterhof and Todorov’s (in Proc Natl Acad Sci USA 105:11087–11092, 2008) computer-based model of face evaluation was used to generate facial trait scores on trustworthiness, dominance, and attractiveness, based on participants’ photographs. Results revealed that structural facial characteristics, suggestive of greater trustworthiness, predicted positively biased, global informant evaluations of a target’s personality, among both spouses and strangers. Among spouses, this effect was impervious to marriage length. There was also evidence suggestive of a Dorian Gray effect on personality, since facial trustworthiness predicted not only spousal and stranger, but also self-ratings of extraversion. Unexpectedly, though, follow-up analyses revealed that (low) facial dominance, rather than (high) trustworthiness, was the strongest predictor of self-rated extraversion. Our present findings suggest that subtle emotional cues, embedded in the structure of emotionally neutral faces, exert long-lasting effects on personality judgments even among very well-acquainted targets and perceivers.     

Accuracy of Inferring Self- and Other-Preferences from Spontaneous Facial Expressions

Participants?? faces were covertly recorded while they rated the attractiveness of people, the decorative appeal of paintings, and the cuteness of animals. Ratings employed a continuous scale. The same participants then returned and tried to guess ratings from 3-s videotapes of themselves and other targets. Performance was above chance in all three stimulus categories, thereby replicating the results of an earlier study (North et al. in J Exp Soc Psychol 46(6):1109?C1113, 2010) but this time using a more sensitive rating procedure. Across conditions, accuracy in reading one??s own face was not reliably better than other-accuracy. We discuss our findings in the context of ??simulation?? theories of face-based emotion recognition (Goldman in The philosophy, psychology, and neuroscience of mindreading. Oxford University Press, Oxford, 2006) and the larger body of accuracy research.     

Logratio approach to statistical analysis of 2×2 compositional tables

Compositional tables represent a continuous counterpart to well-known contingency tables. Their cells contain quantitatively expressed relative contributions of a whole, carrying exclusively relative information and are popularly represented in proportions or percentages. The resulting factors, corresponding to rows and columns of the table, can be inspected similarly as with contingency tables, e.g. for their mutual independent behaviour. The nature of compositional tables requires a specific geometrical treatment, represented by the Aitchison geometry on the simplex. The properties of the Aitchison geometry allow a decomposition of the original table into its independent and interactive parts. Moreover, the specific case of 2×2 compositional tables allows the construction of easily interpretable orthonormal coordinates (resulting from the isometric logratio transformation) for the original table and its decompositions. Consequently, for a sample of compositional tables both explorative statistical analysis like graphical inspection of the independent and interactive parts or any statistical inference (odds-ratio-like testing of independence) can be performed. Theoretical advancements of the presented approach are demonstrated using two economic applications.     

The Realized Laplace Transform of Volatility

We introduce and derive the asymptotic behavior of a new measure constructed from high‐frequency data which we call the realized Laplace transform of volatility. The statistic provides a nonparametric estimate for the empirical Laplace transform function of the latent stochastic volatility process over a given interval of time and is robust to the presence of jumps in the price process. With a long span of data, that is, under joint long‐span and infill asymptotics, the statistic can be used to construct a nonparametric estimate of the volatility Laplace transform as well as of the integrated joint Laplace transform of volatility over different points of time. We derive feasible functional limit theorems for our statistic both under fixed‐span and infill asymptotics as well as under joint long‐span and infill asymptotics which allow us to quantify the precision in estimation under both sampling schemes.     

Family size,father's education,and children's educational attainment in intact white families

One body of previous research has documented a negative relationship between family size and educational attainment (Blau and Duncan 1967; Sewell et al. 1980; Coleman 1988). Another body of research has argued that because parents are likely to act as potential equalizers of attainment gaps among their children, this relationship is likely to vary depending on the level of parental education (Johnson 1972; Zajonc 1976; Griliches 1979). In an attempt to integrate these two bodies of research, this study examines recent GSS data on white men and women from intact families and aged 25 and over. This research finds support for both arguments. The findings suggest that although there is a direct negative relationship between family size and educational attainment, it varies across levels of father's education. The effect of family size on educational attainment turns positive for men when the father's education is at least high school. For women, it is positive only when the father's education is at least a B.A. Additionally, this relationship holds for men born after 1950 and for women born before 1950. This study rationalizes that changing labor market conditions and cultural pressures to be educated have contributed to such differential impacts of father's education on children's educational attainment across cohorts.     

The accessibility and applicability of knowledge: predicting context effects in national surveys

Using data from the National Health Interview Survey on Disability from 1994 and 1995, this research demonstrates that the size of accessibility effects (increased likelihood of using information activated by initial questions in responding to subsequent questions) can be modeled as a function of the applicability of the initial to the subsequent questions. When respondents reported a disability and were asked about the main condition causing the disability, they were more likely to report conditions they had been asked about earlier in the interview than alternative conditions. This accessibility effect was inversely related to the effect on reports of "other" or unclassifiable conditions. The more reports of primed conditions, the fewer reports of unclassifiable conditions. A log-linear model of the accessibility bias fit the data for all disabilities. For reports of specific conditions, a measure of the applicability of context accounted for 74.4 percent of the variance of the accessibility bias; for unclassifiable or "other" conditions, it accounted for 61 percent. When limited to "well-defined" disabilities, applicability accounted for 91.9 percent of the variance (a multiple correlation of.96). Finally, models of the context effects derived from the 1994 data were tested against the actual effects for the 1995 data. The correlation between predicted and actual effects was.80 across disabilities. The theoretical and the practical implications of the findings are discussed.     

Another Look at Reasoning Experiments: Rationality, Normative Models and Conversational Factors

In many studies, human reasoning has been depicted as "biased" or deviating from normative models in both areas of deductive and inductive reasoning. Two criteria for evaluation of reasoning studies are proposed in this paper. The first criterion concerns the selection and application of normative models against which human performance is assessed. The second criterion concerns the role of conversational factors in the differential selection of information used in the subsequent judgment. These two criteria were applied to studies on two tasks from the fields of deductive and inductive reasoning, the Wason selection task and the base rate fallacy. In view of alternative normative systems, control of the application of the normative models used and the perceived conversational relevance of the information presented in the experimental tasks, the alleged biases have been demonstrated to be largely unsupported. The analysis is consistent with the notion that human reasoning is optimal and rational. The implications of the present account for reasoning experiments are discussed.     

Estimation of Jump Tails

We propose a new and flexible nonparametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple‐to‐implement set of estimating equations associated with the compensator for the jump measure, or its intensity, that only utilizes the weak assumption of regular variation in the jump tails, along with in‐fill asymptotic arguments for directly estimating the “large” jumps. The procedure assumes that the large‐sized jumps are identically distributed, but otherwise allows for very general dynamic dependencies in jump occurrences, and, importantly, does not restrict the behavior of the “small” jumps or the continuous part of the process and the temporal variation in the stochastic volatility. On implementing the new estimation procedure with actual high‐frequency data for the S&P 500 aggregate market portfolio, we find strong evidence for richer and more complex dynamic dependencies in the jump tails than hitherto entertained in the literature.     

Classical and robust orthogonal regression between parts of compositional data

The different parts (variables) of a compositional data set cannot be considered independent from each other, since only the ratios between the parts constitute the relevant information to be analysed. Practically, this information can be included in a system of orthonormal coordinates. For the task of regression of one part on other parts, a specific choice of orthonormal coordinates is proposed which allows for an interpretation of the regression parameters in terms of the original parts. In this context, orthogonal regression is appropriate since all compositional parts – also the explanatory variables – are measured with errors. Besides classical (least-squares based) parameter estimation, also robust estimation based on robust principal component analysis is employed. Statistical inference for the regression parameters is obtained by bootstrap; in the robust version the fast and robust bootstrap procedure is used. The methodology is illustrated with a data set from macroeconomics.