Topic
Counterfactual thinking
About: Counterfactual thinking is a research topic. Over the lifetime, 4784 publications have been published within this topic receiving 125801 citations.
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TL;DR: Supporting this analysis, research shows that the various distances are cognitively related to each other, that theySimilarly influence and are influenced by level of mental construal, and that they similarly affect prediction, preference, and action.
Abstract: People are capable of thinking about the future, the past, remote locations, another person's perspective, and counterfactual alternatives. Without denying the uniqueness of each process, it is proposed that they constitute different forms of traversing psychological distance. Psychological distance is egocentric: Its reference point is the self in the here and now, and the different ways in which an object might be removed from that point-in time, in space, in social distance, and in hypotheticality-constitute different distance dimensions. Transcending the self in the here and now entails mental construal, and the farther removed an object is from direct experience, the higher (more abstract) the level of construal of that object. Supporting this analysis, research shows (a) that the various distances are cognitively related to each other, (b) that they similarly influence and are influenced by level of mental construal, and (c) that they similarly affect prediction, preference, and action.
4,114 citations
TL;DR: In this article, a theory of norms and normality is presented and applied to some phenomena of emotional responses, social judgment, and conversations about causes, such as emotional response to events that have abnormal causes, the generation of predictions and inferences from observations of behavior and the role of norms in causal questions and answers.
Abstract: A theory of norms and normality is presented and applied to some phenomena of emotional responses, social judgment, and conversations about causes. Norms are assumed to be constructed ad hoc by recruiting specific representations. Category norms are derived by recruiting exemplars. Specific objects or events generate their own norms by retrieval of similar experiences stored in memory or by construction of counterfactual alternatives. The normality of a stimulus is evaluated by comparing it to the norms that it evokes after the fact, rather than to precomputed expectations. Norm theory is applied in analyses of the enhanced emotional response to events that have abnormal causes, of the generation of predictions and inferences from observations of behavior, and of the role of norms in causal questions and answers. This article is concerned with category norms that represent knowledge of concepts and with stimulus norms that govern comparative judgments and designate experiences as surprising. In the tradition of adaptation level theory (Appley, 1971; Helson, 1964), the concept of norm is applied to events that range in complexity from single visual displays to social interactions. We first propose a model of an activation process that produces norms, then explore the role of norms in social cognition. The central idea of the present treatment is that norms are computed after the event rather than in advance. We sketch a supplement to the generally accepted idea that events in the stream of experience are interpreted and evaluated by consulting precomputed schemas and frames of reference. The view developed here is that each stimulus selectively recruits its own alternatives (Garner, 1962, 1970) and is interpreted in a rich context of remembered and constructed representations of what it could have been, might have been, or should have been. Thus, each event brings its own frame of reference into being. We also explore the idea that knowledge of categories (e.g., "encounters with Jim") can be derived on-line by selectively evoking stored representations of discrete episodes and exemplars. The present model assumes that a number of representations can be recruited in parallel, by either a stimulus event or an
2,910 citations
TL;DR: In this article, the authors propose an elaboration of the Diamond model that permits multiple, locally stable stationary states, and this multiplicity is due to increasing social returns to scale in the accumulation of human capital.
Abstract: Standard one-sector growth models often have the counterfactual implication that economies with access to similar technologies will converge to a common balanced growth path. We propose an elaboration of the Diamond model that permits multiple, locally stable stationary states. This multiplicity is due to increasing social returns to scale in the accumulation of human capital.
2,070 citations
TL;DR: A review of recent advances in causal inference can be found in this article, where a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a) is presented.
Abstract: This review presents empiricalresearcherswith recent advances in causal inference, and stresses the paradigmatic shifts that must be un- dertaken in moving from traditionalstatistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that un- derly all causal inferences, the languages used in formulating those assump- tions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coher- ent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: (1) queries about the effects of potential interven- tions, (also called "causal effects" or "policy evaluation") (2) queries about probabilities of counterfactuals, (including assessment of "regret," "attri- bution" or "causes of effects") and (3) queries about direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both.
1,661 citations
TL;DR: The developments in mediation analysis for nonlinear models within the counterfactual framework within the psychology audience is brought to an accessible format and the types of inferences about mediation that are allowed by a variety of software macros are compared.
Abstract: Mediation analysis is a useful and widely employed approach to studies in the field of psychology and in the social and biomedical sciences. The contributions of this article are several-fold. First we seek to bring the developments in mediation analysis for nonlinear models within the counterfactual framework to the psychology audience in an accessible format and compare the sorts of inferences about mediation that are possible in the presence of exposure-mediator interaction when using a counterfactual versus the standard statistical approach. Second, the work by VanderWeele and Vansteelandt (2009, 2010) is extended here to allow for dichotomous mediators and count outcomes. Third, we provide SAS and SPSS macros to implement all of these mediation analysis techniques automatically, and we compare the types of inferences about mediation that are allowed by a variety of software macros.
1,499 citations