In the presence of intersectoral linkages, sector-specific carbon tax changes can have complex general equilibrium effects. In particular, a carbon tax on the emissions of a sector can lead to an increase in aggregate emissions. We analytically characterise how incremental taxes on the emissions of any set of sectors affect aggregate emissions. We show that carbon tax reforms that target sectors based on their position in the production network can achieve a greater reduction in aggregate emissions than reforms that target sectors based on their direct emissions alone. We illustrate the effects of carbon tax reforms by calibrating our intersectoral network model to the economies of two countries.

In the presence of intersectoral linkages, sector-specific carbon tax changes can have complex general equilibrium effects. In particular, a carbon tax on the emissions of a sector can lead to an increase in aggregate emissions. We analytically characterise how incremental taxes on the emissions of any set of sectors affect aggregate emissions. We show that carbon tax reforms that target sectors based on their position in the production network can achieve a greater reduction in aggregate emissions than reforms that target sectors based on their direct emissions alone. We illustrate the effects of carbon tax reforms by calibrating our intersectoral network model to the economies of two countries.

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We show that the playing sequence-the order in which players update their actions-is a crucial determinant of whether the best-response dynamic converges to a Nash equilibrium. Specifically, we analyze the probability that the best-response dynamic converges to a pure Nash equilibrium in random n-player m-action games under three distinct playing sequences: clockwork sequences (players take turns according to a fixed cyclic order), random sequences, and simultaneous updating by all players. We analytically characterize the convergence properties of the clockwork sequence best-response dynamic. Our key asymptotic result is that this dynamic almost never converges to a pure Nash equilibrium when n and m are large. By contrast, the random sequence bestresponse dynamic converges almost always to a pure Nash equilibrium when one exists and n and m are large. The clockwork best-response dynamic deserves particular attention: we show through simulation that, compared to random or simultaneous updating, its convergence properties are closest to those exhibited by three popular learning rules that have been calibrated to human game-playing in experiments (reinforcement learning, fictitious play, and replicator dynamics).