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Efficient estimation in dynamic conditional quantile models

机译:动态条件分位数模型中的有效估计

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In this paper we consider the problem of semiparametric efficient estimation in conditional quantile models with time series data. We construct an M-estimator which achieves the semiparametric efficiency bound recently derived by Komunjer and Vuong (forthcoming). Our efficient M-estimator is obtained by minimizing an objective function which depends on a nonparametric estimator of the conditional distribution of the variable of interest rather than its density. The estimator is new and not yet seen in the literature. We illustrate its performance through a Monte Carlo experiment.
机译:本文考虑具有时间序列数据的条件分位数模型中半参数有效估计的问题。我们构造了一个M估计器,该估计器实现了Komunjer和Vuong(即将推出)最近得出的半参数效率范围。我们的有效M估计量是通过最小化目标函数获得的,该目标函数取决于关注变量的条件分布而不是其密度的非参数估计量。估算器是新的,尚未在文献中看到。我们通过蒙特卡洛实验说明其性能。

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