Analyzing macro-political processes is complicated by four interrelated problems: model scale, endogeneity, persistence, and specification uncertainty. These problems are endemic in the study of political economy, public opinion, international relations, and other kinds of macro-political research. We show how a Bayesian structural time series approach addresses them. Our illustration is a structurally identified, nine equation model of the U.S. politicaleconomic system. It combines key features of Erikson, MacKuen and Stimson's model of the American macropolity (2002) with those of a leading macroeconomic model of U.S. Zha 1998 andLeeper, Sims, andZha 1996). This structural model, with a loose informed prior, yields the best performance in terms of a mean squared error loss criterion and new insights into the dynamics of the American political economy. The model 1) captures the conventional wisdom about the countercyclical nature of monetary policy (Williams 1990) 2) reveals informational sources of approval dynamics: innovations in information variables affect consumer sentiment and approval and the impacts on consumer sentiment feed-forward into subsequent approval changes, 3) finds that the real economy does not have any major impacts on key macropolity variables and 4) concludes that macropartisanship does not depend on the evolution of the real economy in the short or medium term and only very weakly on informational variables in the long term.