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Publication Does a Small Country Have Meaningful Regional Personality Differences? The Case of Estonia(2025-02)ABSTRACT Background Regional differences in the Big Five personality domains have been observed in several countries at different geographical granularities, often correlating with regional political, economic, social, and health (PESH) indicators. Objective We examined the extent of regional personality differences in Estonia and whether these differences were meaningfully correlated with PESH indicators. Methods Using data from the Estonian Biobank (N = 72,268; 7% of the adult population, providing unprecedented representativeness), we tested regional personality differences and their relations with PESH indicators with and without spatial smoothing. Results We found that regional Big Five scores varied by 1.19 (extraversion) to 2.78 (openness) T‐score units across counties (N = 15) and by 2.80 (extraversion) to 4.74 (openness) units across municipalities (n = 74). Also, the correlations with the PESH indicators at the county and municipality levels persisted even after controlling for gender, age, and spatial dependency, and were moderately consistent with our predictions (r = 0.23 to 0.30) and between the county and municipality levels (r = 0.41). Conclusions Estonian residents tended to be similar in personality traits regardless of their location, replicating results from other countries. Yet, small regional personality domain differences could represent valid and possibly consequential psychological variation. - Some of the metrics are blocked by yourconsent settings
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Publication Natural experiments: Missed opportunities for causal inference in psychology(2024-01)Knowledge about causal effects is essential for building useful theories and designing effective interventions. The preferred design for learning about causal effects is randomized experiments (i.e., studies in which the researchers randomly assign units to treatment and control conditions). However, randomized experiments are often unethical or unfeasible. On the other hand, observational studies are usually feasible but lack the random assignment that renders randomized experiments causally informative. Natural experiments can sometimes offer unique opportunities for dealing with this dilemma, allowing causal inference on the basis of events that are not controlled by researchers but that nevertheless establish random or as-if random assignment to treatment and control conditions. Yet psychological researchers have rarely exploited natural experiments. To remedy this shortage, we describe three main types of studies exploiting natural experiments (standard natural experiments, instrumental-variable designs, and regression-discontinuity designs) and provide examples from psychology and economics to illustrate how natural experiments can be harnessed. Natural experiments are challenging to find, provide information about only specific causal effects, and involve assumptions that are difficult to validate empirically. Nevertheless, we argue that natural experiments provide valuable causal-inference opportunities that have not yet been sufficiently exploited by psychologists.Type:Journal:Volume:Issue:
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