The existence of links between personality traits, values, and well-being and self-esteem is well established, but the nature and direction of these links have been less clearly understood. This study examines longitudinally the stability of traits and values, their mutual effects, and their effects on affective and cognitive well-being and self-esteem. We analyzed data from a nationally representative panel in The Netherlands, spanning 5 time points spread across 8 years (n = 5,159 to 7,021 per time point, total N = 11,890). We estimated latent state-trait models with autoregression and random-intercepts cross-lagged panel models to account for the trait-like, time-invariant stability of the constructs. Traits were more stable than values. The bidirectional effects tended to be significant, but could be distinguished by their relative size. Traits predicted values more strongly than they were predicted by values, and generally predicted well-being and self-esteem more strongly than values did. Traits predicted broad well-being (especially its affective aspects) more strongly than they were predicted by it; values, by contrast, were predicted by well-being (especially its cognitive aspects and self-esteem) more strongly than they predicted it. The findings highlight the central role of traits for personality functioning, while also supporting the mutual constitution of traits and other personality concepts. The results are discussed in the framework of different theoretical approaches to the composition of the broader personality system. (DIPF/Orig.) [Correction Notice: An Erratum for this article was reported online in Journal of Personality and Social Psychology on Apr 4 2019 (see record 2019-18472-001). In the article, the stability model is referred to incorrectly as trait-state error model in the abstract, twice in the main body of the article, and in the Table 2 Note. Corrected versions of the fourth sentence in the abstract, the first sentence of the Analysis Outline section, and the first sentence of the ...