Abstract
Revolutions rarely achieve their expressed goals, which often include greater economic prosperity, a more egalitarian distribution of rewards, ending corruption, and a less oppressive state. Yet there is no single reason for this, as revolutions of many types—violent and non-violent, radical and moderate—can produce similar outcomes. We explain this by treating revolutionary outcomes as the result of a decision tree process, in which outcomes are reached by a series of steps in which only the initial state of each step and the events at that junction determine the subsequent step. This simplification allows us to identify numerous pathways by which revolutions can unfold. However, relatively few such trajectories lead to stable constitutional regimes.
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Notes
This independence of prior conditions in determining the outcome at each step is known as the “Markov property,” and makes this model a Markov decision tree (Sheskin, 2016). In a Markov decision tree, actions or events acting on a system in state So produce a transition to one or more states S1, S2 … with probabilities p1, p 2 …. These probabilities may be fixed or stochastic. In the Markov decision tree, the probabilities for each outcome depend jointly on the condition at Sn and an event or action occurring at that point. Thus, the outcomes of the decision tree can be generated by the events (that occur with varying probabilities) and/or choices made by groups or individuals at each step. This model therefore allows for the interaction of actions (choices) and events at multiple points in the post-revolutionary process to shape outcomes in a sequence of steps that can diverge at the specified decision tree points. In the model developed here, the next outcome at each step is fully determined by the conditions and actions at that step, so the probabilities are deterministic at each step. Thus, at step 1, if radicals take power we assume the result is always a radical authoritarian regime. At step 4, we assume that if a moderate revolutionary regime faces major crises, but does not control a well-organized and loyal national army, it will always be replaced by a radical revolutionary regime. Of course, one could further refine the model by estimating probabilities or specifying a stochastic probability regime, but we leave that complication aside in this paper. Setting the probabilities at each step to 1 allows us to simply map out the range of possible trajectories that can be produced from the decision tree.
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Goldstone, J.A. You can’t always get what you want: why revolutionary outcomes so often diverge from revolutionary goals. Public Choice (2023). https://doi.org/10.1007/s11127-023-01092-7
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DOI: https://doi.org/10.1007/s11127-023-01092-7