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    題名: Constructing Smooth Tests without Estimating the Eigen-pairs of the Limiting Process
    作者: Hsu, Shih-Hsun;Kuan, Chung-Ming
    貢獻者: 經濟系
    關鍵詞: Data-driven method;Eigenpairs;Fourier representation;Karhunen–Loève expansion;Smooth test
    日期: 2014.01
    上傳時間: 2014-03-26 16:32:26 (UTC+8)
    摘要: Based on the well known Karhunen–Loève expansion, it can be shown that many omnibus tests lack power against “high frequency” alternatives. The smooth tests of Neyman (1937) may be employed to circumvent this power deficiency problem. Yet, such tests may be difficult to compute in many applications. In this paper, we propose a more operational approach to constructing smooth tests. This approach hinges on a Fourier representation of the postulated empirical process with known Fourier coefficients, and the proposed test is based on the normalized principal components associated with the covariance matrix of finitely many Fourier coefficients. The proposed test thus needs only standard principal component analysis that can be carried out using most econometric packages. We establish the asymptotic properties of the proposed test and consider two data-driven methods for determining the number of Fourier coefficients in the test statistic. Our simulations show that the proposed tests compare favorably with the conventional smooth tests in finite samples.
    關聯: Journal of Econometrics,178, 71-79
    資料類型: article
    顯示於類別:[經濟學系] 期刊論文

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