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AbstractPublic support is central to the emergence of judicial power. Conventional wisdom holds that citizen commitment to democracy and the rule of law sustains this support. An implication is that such commitments should protect courts from partisan backlash following contentious rulings. But this remains largely untested. The Kenyan Supreme Court's historic 2017 elections rulings provide an unusual opportunity to test this expectation. After annulling the incumbent president's victory, the Court upheld his controversial repeat‐election win. With data from a national panel survey—conducted before and after the repeat election—we find important partisan‐based withdrawals/increases in judicial‐power support. There is no evidence that democratic principles attenuated partisan backlash; some were associated with its amplification. However, partisan losers maintain moderately high support despite backlash. Results advance debates about public support for judicial power and provide new evidence about public reactions to assertions of judicial authority in new democracies and electoral autocratic regimes.

Central to traditionalist and revisionist perspectives of individual-level party identification is a debate about the stability of party identification. We revisit the debate about the dynamic properties and processes underlying party identification. We present a conceptual framework that defines heterogeneity and state dependence as endpoints of a continuum underlying partisan stability, which is important in understanding an individual's capacity for updating partisanship. Using panel data from the 1992-1996 National Election Study, we estimate dynamic, random effects multinomial logit models of party identification that distinguish between heterogeneity and 'true state dependence.' In accord with traditionalist perspectives, our evidence suggests that in general, minimal state dependence underlies party identification; party identification is strongly stationary. However, we find that age enhances the magnitude of state dependence, which provides some support for revisionist theories. Overall, our work showcases how explaining individual-level dynamics expands our knowledge of partisan stability. Using panel data from the 1992-1996 National Election Study, we estimate dynamic, random effects multinomial logit models of party identification that distinguish between heterogeneity and 'true state dependence. Minimal state dependence underlies party identification; party identification is strongly stationary. Age enhances the magnitude of state dependence, which provides some support for revisionist theories. [Copyright Elsevier Ltd.]