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英文文献：Indirect inference with time series observed with error-用误差观察时间序列的间接推理
英文文献作者：Eduardo Rossi,Paolo Santucci de Magistris
英文文献摘要：
We analyze the properties of the indirect inference estimator when the observed series are contaminated by measurement error. We show that the indirect inference estimates are asymptotically biased when the nuisance parameters of the measurement error distribution are neglected in the indirect estimation. We propose to solve this inconsistency by jointly estimating the nuisance and the structural parameters. Under standard assumptions, this estimator is consistent and asymptotically normal. A condition for the identification of ARMA plus noise is obtained. The proposed methodology is used to estimate the parameters of continuous-time stochastic volatility models with auxiliary specifications based on realized volatility measures. Monte Carlo simulations shows the bias reduction of the indirect estimates obtained when the microstructure noise is explicitly modeled. Finally, an empirical application illustrates the relevance of a realistic specification of the microstructure noise distribution to match the features of the observed log-returns at high frequencies.
分析了观测序列受测量误差污染时间接推理估计器的性质。当间接估计中忽略测量误差分布的有害参数时，间接推断估计是渐近有偏的。我们建议通过联合估计结构参数和妨害来解决这种不一致性。在标准假设下，该估计量是一致的，渐近正态的。得到了ARMA加噪声识别的条件。该方法用于基于已实现波动测度的带辅助规范的连续时间随机波动模型的参数估计。蒙特卡洛模拟表明，当微观结构噪声明确建模时，间接估计得到的偏差减少。最后，一个经验的应用说明了一个切合实际的微观结构噪声分布规范，以匹配在高频率的观测对数回报的特征。
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