引导自适应套索求解路径单位根检验

Martin C. Arnold, Thilo Reinschlüssel
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引用次数: 0

摘要

我们对 Arnold 和 Reinschl\"ussel (2024) 的自适应拉索解路径单位根检验提出了筛子式自举类似方法,以改进有限样本属性,并将其适用性扩展到广义框架,允许非平稳波动。数值证据表明,自举法提高了检验的精确度,因为误差过程会导致对单位根零值的虚假拒绝,这取决于去趋势过程。当数据的无条件方差随时间变化时,自举法可减轻有限样本的偏差并恢复渐近有效的推断。我们对欧元区前六大经济体的实际住宅物业价格进行了自举检验,发现静止性的证据是特定时期的,这支持了住房市场的繁荣是近期欧元区住宅物业价格发展特点的猜想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bootstrap Adaptive Lasso Solution Path Unit Root Tests
We propose sieve wild bootstrap analogues to the adaptive Lasso solution path unit root tests of Arnold and Reinschl\"ussel (2024) arXiv:2404.06205 to improve finite sample properties and extend their applicability to a generalised framework, allowing for non-stationary volatility. Numerical evidence shows the bootstrap to improve the tests' precision for error processes that promote spurious rejections of the unit root null, depending on the detrending procedure. The bootstrap mitigates finite-sample size distortions and restores asymptotically valid inference when the data features time-varying unconditional variance. We apply the bootstrap tests to real residential property prices of the top six Eurozone economies and find evidence of stationarity to be period-specific, supporting the conjecture that exuberance in the housing market characterises the development of Euro-era residential property prices in the recent past.
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