Distributions of the Duration and Value of Job Search with Learning
针对带学习的求职搜索，提出将概率重新表达为不动点，从而直接计算搜索持续时间和接受报价的概率，并计算自适应搜索的期望值，附有示例和比较静态分析。
Expected value maximizing sequential search rules can be expressed in terms of reservation values. In search with learning the reservation value at any stage of the search is unknown until that stage is reached. Thus calculating ex ante (and subsequent) probabilities of search duration and the offer accepted is difficult if these probabilities are expressed in terms of reservation values. This paper shows, for a wide class of learning procedures, how re-expressing these probabilities in terms of fixed points allows their direct calculation and, thereby, calculation of the expected value of adaptive search. Examples and comparative statics results are presented.