Dynamic Congressional Approval: An ALT-ernative Approach

Past research studies congressional approval at the aggregate level and explains fluctuations as a function of macro-level political factors. This paper provides new insight into the variability and stability of congressional approval at the individual-level through a novel panel survey data set that collects individual-level congressional approval data over a period of 60 months. We test longstanding hypotheses regarding the role presidential approval, partisan control, and policy congruence have in relation to congressional approval using hierarchical measurement modeling techniques. This methodological approach estimates random intercepts and random slopes, permitting each individual in the sample to have her own trajectory of approval over time. Our modeling strategy ensures the results are not a function of measurement error but instead a function of systematic change over the period under investigation. The results demonstrate that even at the individual level the approval of both the president and Congress are tightly connected and that the relationship between approval and policy preferences is tenuous