Identification and estimation of nonseparable single-index models in panel data with correlated random effects
相关随机效应面板中不可分单指标模型的识别与估计
The identification in a nonseparable single-index models with correlated random effects is considered in panel data with a fixed number of time periods. The identification assumption is based on the correlated random effects structure. Under this assumption, the parameters of interest are identified up to a multiplicative constant and could be estimated by an average difference of derivatives estimator based on the local polynomial smoothing. We suggest to linearly combine…