Adaptive Learning and Labor Market Dynamics
研究发现标准理性预期模型无法解释失业和职位空缺的放大效应以及机构短期工资预测特征，而引入适应性学习的简约模型能同时解决这两个问题。
Abstract The standard search and matching model with rational expectations is well known to be unable to generate amplification in unemployment and vacancies. We document a new feature that cannot be replicated: properties of wage forecasts published by institutions in the near term. A parsimonious model with adaptive learning can provide a solution to both of these problems. Firms choose vacancies by forecasting wages using simple autoregressive models; they have greater incentive to post vacancies at the time of a positive productivity shock because of overoptimism about the discounted value of expected profits.