摘要翻译:
本文讨论了存在未知形式的横截面依赖性和时间依赖性的大型面板数据模型中的推理问题。我们感兴趣的是作出不依赖于选择任何平滑参数的推论,就像对协方差矩阵经常使用的“HAC”估计量一样。为此,我们提出了一个估计量渐近协方差的聚类估计器和有效的bootstrap方案,该方案不需要选择带宽或平滑参数,并适应时间和截面相关性的非参数性质。我们的方法是基于固定效应面板数据模型的光谱表示是这样的观察,误差变得近似时间不相关。我们提出的自举方案可以看作是频域中的野生自举。我们给出了一些蒙特卡罗模拟,以说明我们的推理过程的小样本性能。
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英文标题:
《Inference without smoothing for large panels with cross-sectional and
temporal dependence》
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作者:
J. Hidalgo and M. Schafgans
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最新提交年份:
2020
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分类信息:
一级分类:Economics 经济学
二级分类:Econometrics 计量经济学
分类描述:Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论,微观计量经济学,宏观计量经济学,通过新方法发现的经济关系的实证内容,统计推论应用于经济数据的方法论方面。
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一级分类:Mathematics 数学
二级分类:Statistics Theory 统计理论
分类描述:Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计:例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类:Statistics 统计学
二级分类:Statistics Theory 统计理论
分类描述:stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近,贝叶斯推论,决策理论,估计,基础,推论,检验。
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英文摘要:
This paper addresses inference in large panel data models in the presence of both cross-sectional and temporal dependence of unknown form. We are interested in making inferences that do not rely on the choice of any smoothing parameter as is the case with the often employed "HAC" estimator for the covariance matrix. To that end, we propose a cluster estimator for the asymptotic covariance of the estimators and valid bootstrap schemes that do not require the selection of a bandwidth or smoothing parameter and accommodate the nonparametric nature of both temporal and cross-sectional dependence. Our approach is based on the observation that the spectral representation of the fixed effect panel data model is such that the errors become approximately temporally uncorrelated. Our proposed bootstrap schemes can be viewed as wild bootstraps in the frequency domain. We present some Monte-Carlo simulations to shed some light on the small sample performance of our inferential procedure.
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PDF链接:
https://arxiv.org/pdf/2006.14409