Perceptions of intergroup bias : the roles of social projection and meta-stereotypes

Underlying intergroup perceptions include processes of social projection (perceiving personal traitslbeliefs in others, see Krueger 1998) and meta-stereotyping (thinking about other groups' perceptions of one's own group, see Vorauer et aI., 1998). Two studies were conducted to investigate social projection and meta-stereotypes in the domain of White-Black racial relations. Study 1, a correlational study, examined the social projection of prejudice and 'prejudiced' meta-stereotypes among Whites. Results revealed that (a) Whites socially projected their intergroup attitudes onto other Whites (and Blacks) [i.e., Whites higher in prejudice against Blacks believed a large percentage of Whites (Blacks) are prejudiced against Blacks (Whites), whereas Whites low in prejudice believed a smaller percentage of Whites (Blacks) are prejudiced]; (b) Whites held the meta:..stereotype that their group (Whites) is viewed by Blacks to be prejudiced; and (c) prejudiced meta-stereotypes may be formed through the social projection of intergroup attitudes (result of path-model tests). Further, several correlates of social projection and meta-stereotypes were identified, including the finding that feeling negatively stereotyped by an outgroup predicted outgroup avoidance through heightened intergroup anxiety. Study 2 replicated and extended these findings, investigating the social projection of ingroup favouritism and meta- and other-stereotypes about ingroup favouritism. These processes were examined experimentally using an anticipated intergroup contact paradigm. The goal was to understand the experimental conditions under which people would display the strongest social projection of intergroup attitudes, and when experimentally induced meta-stereotypes (vs. other-stereotypes; beliefs about the group 11 preferences of one's outgroup) would be most damaging to intergroup contact. White participants were randomly assigned to one of six conditions and received (alleged) feedback from a previously completed computer-based test. Depending on condition, this information suggested that: (a) the participant favoured Whites over Blacks; (b) previous White participants favoured Whites over Blacks; (c) the participant's Black partner favoured Blacks over Whites; (d) previous Black participants favoured Blacks over Whites; (e) the participant's Black partner viewed the participant to favour Whites over Blacks; or (£) Black participants previously participating viewed Whites to favour Whites over Blacks. In a defensive reaction, Whites exhibited enhanced social projection of personal intergroup attitudes onto their ingroup under experimental manipulations characterized by self-concept threat (i.e., when the computer revealed that the participant favoured the ingroup or was viewed to favour the ingroup). Manipulated meta- and otherstereotype information that introduced intergroup contact threat, on the other hand, each exerted a strong negative impact on intergroup contact expectations (e.g., anxiety). Personal meta-stereotype manipulations (i.e., when the participant was informed that her/ his partner thinks s/he favours the ingroup) exerted an especially negative impact on intergroup behaviour, evidenced by increased avoidance of the upcoming interracial interaction. In contrast, personal self-stereotype manipulations (i.e., computer revealed that one favoured the ingroup) ironically improved upcoming intergroup contact expectations and intentions, likely due to an attempt to reduce the discomfort of holding negative intergroup attitudes. Implications and directions for future research are considered.

Traité de géométrie descriptive, suivi de la méthode des pl ans cotés et de la théorie des engrenages cylindriques et c oniques, avec une collection d'épures, composée de 71 planc hes

UANL

Méthode pour l'exercise de l'Heure Sainte demandé par N.S. a la Bienheureuse Marguerite-Marie.

UANL

Évaluation d'un projet de modernisation; par la méthode des effets et celle des prix de référence.

Rapport de recherche

Statistical Inference for Computable General Equilibrium Models with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

Finite-Sample Inference Methods for Simultaneous Equations and Models with Unobserved and Generated Regressors

We propose finite sample tests and confidence sets for models with unobserved and generated regressors as well as various models estimated by instrumental variables methods. The validity of the procedures is unaffected by the presence of identification problems or \"weak instruments\", so no detection of such problems is required. We study two distinct approaches for various models considered by Pagan (1984). The first one is an instrument substitution method which generalizes an approach proposed by Anderson and Rubin (1949) and Fuller (1987) for different (although related) problems, while the second one is based on splitting the sample. The instrument substitution method uses the instruments directly, instead of generated regressors, in order to test hypotheses about the \"structural parameters\" of interest and build confidence sets. The second approach relies on \"generated regressors\", which allows a gain in degrees of freedom, and a sample split technique. For inference about general possibly nonlinear transformations of model parameters, projection techniques are proposed. A distributional theory is obtained under the assumptions of Gaussian errors and strictly exogenous regressors. We show that the various tests and confidence sets proposed are (locally) \"asymptotically valid\" under much weaker assumptions. The properties of the tests proposed are examined in simulation experiments. In general, they outperform the usual asymptotic inference methods in terms of both reliability and power. Finally, the techniques suggested are applied to a model of Tobin’s q and to a model of academic performance.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.