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Random Deviations Improve Micro–Macro Predictions: An Empirical Test

机译:随机偏差改善了微观宏观预测:一项经验检验

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摘要

Many sociological theories make critically different macropredictions when their microassumptions are implemented stochastically rather than deterministically. Deviations from individuals’ behavioral patterns described by microtheories can spark cascades that change macrooutcomes, even when deviations are rare and random. With two experiments, we empirically tested whether macrophenomena can be critically shaped by random deviations. Ninety-six percent of participants’ decisions were in line with a deterministic theory of bounded rationality. Despite this impressive microlevel accuracy, the deterministic model failed to predict the observed macrooutcomes. However, a stochastic version of the same microtheory largely improved macropredictions. The stochastic model also correctly predicted the conditions under which deviations mattered. Results also supported the hypothesis that nonrandom deviations can result in fundamentally different macrooutcomes than random deviations. In conclusion, we echo the warning that deterministic microtheories can be misleading. Our findings show that taking into account deviations in sociological theories can improve explanations and predictions.
机译:当许多社会学理论的微观假设是随机而不是确定性地实施时,它们会做出截然不同的宏观预测。微观理论所描述的与个人行为模式的偏差会引发级联,从而改变宏观结果,即使偏差很少且是随机的。通过两个实验,我们通过经验测试了宏观现象是否可以由随机偏差严格地塑造。 96%的参与者的决定符合有限理性的确定性理论。尽管具有令人印象深刻的微观水平准确性,但是确定性模型无法预测观察到的宏观结果。但是,同一微观理论的随机版本在很大程度上改善了宏观预测。随机模型还可以正确预测偏差影响的条件。结果也支持以下假设:非随机偏差可能导致宏结果与随机偏差根本不同。总之,我们回响警告,即确定性微观理论可能会误导人们。我们的发现表明,将社会学理论中的偏差纳入考量可以改善解释和预测。

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