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二元响应相关随机系数面板模型AI 解读

In this paper, we consider binary response correlated random coefficient (CRC) panel data models which are frequently used in the analysis of treatment effects and demand of products. We focus on the nonparametric identification and estimation of panel data models under unobserved heterogeneity which is captured by random coefficients and when these random coefficients are correlated with regressors. Our identification conditions and estimation are based on the framework of…

非参数与半参数固定效应面板模型的渐近理论AI 解读

In this paper, we investigate the problem of estimating nonparametric and semiparametric panel data models with fixed effects. We focus on establishing the asymptotic results for estimators using smooth backfitting methods. We consider two estimators for the smooth unknown function in nonparametric panel regressions. One is a local linear estimator constructed similar as the one in Mammen et al. (2009) which was proposed for the additive nonparametric panel model. The other…

半参数变系数模型中的协整关系检验AI 解读

In this paper, we develop two cointegration tests for two varying coefficient cointegration regression models, respectively. Our test statistics are residual based. We derive the asymptotic distributions of test statistics under the null hypothesis of cointegration and show that they are consistent against the alternative hypotheses. We also propose a wild bootstrap procedure companioned with the continuous moving block bootstrap method proposed in Paparoditis and Politis…

含时间趋势的函数系数回归模型AI 解读

We consider the problem of estimating a varying coefficient regression model when regressors include a time trend. We show that the commonly used local constant kernel estimation method leads to an inconsistent estimation result, while a local polynomial estimator yields a consistent estimation result. We establish the asymptotic normality result for the proposed estimator. We also provide asymptotic analysis of the data-driven (least squares cross validation) method of…