The Exact Likelihood Function for an Empirical Job Search Model
分析了典型求职搜索模型的精确似然函数，通过动态规划的最优性条件识别出工作机会到达概率与接受概率，并探讨了有限样本下似然函数的几何性质及最大似然估计的渐近性质。
The exact likelihood function for a prototypal job search model is analyzed. The optimality condition implied by the dynamic programming framework is fully imposed. Using the optimality condition allows identification of an offer arrival probability separately from an offer acceptance probability. The estimation problem is nonstandard. The geometry of the likelihood function in finite samples is considered, along with asymptotic properties of the maximum likelihood estimator.