Modelling heterogeneity and dynamics in the volatility of individual wages
提出一个模型，同时刻画个体工资的条件均值和条件方差的异质性与动态性，使用偏差校正似然方法估计，发现方差动态主要由工作流动驱动，并解释了工资数据的非正态性。
Abstract This paper presents a model for the heterogeneity and dynamics of the conditional mean and conditional variance of individual wages. A bias‐corrected likelihood approach, which reduces the estimation bias to a term of order 1/ T 2 , is used for estimation and inference. The small‐sample performance of the proposed estimator is investigated in a Monte Carlo study. The simulation results show that the bias of the maximum likelihood estimator is substantially corrected for designs calibrated to the data used in the empirical analysis, drawn from the PSID. The empirical results show that it is important to account for individual unobserved heterogeneity and dynamics in the variance, and that the latter is driven by job mobility. The model also explains the non‐normality observed in log‐wage data. Copyright © 2010 John Wiley & Sons, Ltd.