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Previous research has focused on estimating the causal effect of incarceration on communities. Incarceration has been found to be negatively associated with community outcomes such as physical and mental health, employment prospects, sexual disease transmission, and relationship stability. However, a key challenge in prior research is identifying the causal effect of solely incarceration. Typically, the most disadvantaged and violent neighborhoods also experience the highest rates of incarceration. Thus, socioeconomic disadvantage and violence represent profound confounding challenges in modeling. Using yearly county-level incarceration data from the Vera Institute, crime and homicide data from the Uniform Crime Report and CDC Vitality data, and socioeconomic data from the Census, I propose using cross-lagged panel models (a form of Structural Equation Modeling) to discern the temporal causal order of these variables. Preliminary results suggest higher rates of incarceration lead to a long-term worsening of socioeconomic neighborhood health and simultaneous short-term improvements but a long-term worsening in neighborhood rates of violence.