I prove some theorems for competitive equilibria in the presence of distortionary taxes and other restraints of trade, and use those theorems to motivate an algorithm for (exactly) computing and empirically evaluating competitive equilibria in dynamic economies. Although its economics is relatively sophisticated, the algorithm is so computationally economical that it can be implemented with a few lines in a spreadsheet. Although a competitive equilibrium models interactions between all sectors, all consumer types, and all time periods, I show how my algorithm permits separate empirical evaluation of these pieces of the model and hence is practical even when very little data is available. For similar reasons, these evaluations are not particularly sensitive to how data is partitioned into "trends" and "cycles." I then compute a real business cycle model with distortionary taxes that fits aggregate U.S. time series for the period 1929-50 and conclude that, if it is to explain aggregate behavior during the period, government policy must have heavily taxed labor income during the Great Depression and lightly taxed it during the war. In other words, the challenge for the competitive equilibrium approach is not so much why output might change over time, but why the marginal product of labor and the marginal value of leisure diverged so much and why that wedge persisted so long. In this sense, explaining aggregate behavior during the period has been reduced to a public finance question - were actual government policies distorting behavior in the same direction and magnitude as government policies in the model?
Game theory is both at the heart of economics and without a definitive solution. This paper proposes a solution. It is argued that a dominance criterion generates a, and perhaps the, generalized equilibrium solution for game theory. First we provide a set theoretic perspective from which to view game theory, and then present and discuss the proposed solution.