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AN EQUILIBRIUM THEORY OF LEARNING, SEARCH, AND WAGES

机译:学习,搜索和工资的均衡理论

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We examine the labor market effects of incomplete information about the workers' own job-finding process. Search outcomes convey valuable information, and learning from search generates endogenous heterogeneity in workers' beliefs about their job-finding probability. We characterize this process and analyze its interactions with job creation and wage determination. Our theory sheds new light on how unemployment can affect workers' labor market outcomes and wage determination, providing a rational explanation for discouragement as the consequence of negative search outcomes. In particular, longer unemployment durations are likely to be followed by lower reem-ployment wages because a worker's beliefs about his job-finding process deteriorate with unemployment duration. Moreover, our analysis provides a set of useful results on dynamic programming with optimal learning.
机译:我们研究了有关工人自己的找工作过程的不完整信息对劳动力市场的影响。搜索结果传达了有价值的信息,而从搜索中学到的知识会在工人对找到工作的可能性的信念中产生内生的异质性。我们对这一过程进行了表征,并分析了其与创造就业机会和确定工资的相互作用。我们的理论为失业如何影响工人的劳动力市场结果和工资确定提供了新的思路,为因负搜索结果而产生的沮丧情绪提供了合理的解释。特别是,较长的失业时间可能会导致较低的重新安置工资,因为工人对其找工作过程的信念会随着失业时间而恶化。此外,我们的分析为动态编程和最佳学习提供了一组有用的结果。

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