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Consistent estimator of nonparametric structural spurious regression model for high frequency data

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  • Jeong, Minsoo

Abstract

We propose a new nonparametric estimator for continuous-time regression models with nonstationary error terms. While other conventional nonparametric estimators such as the Nadaraya–Watson and local linear estimators are not consistent, our estimator achieves consistency and asymptotic normality.

Suggested Citation

  • Jeong, Minsoo, 2018. "Consistent estimator of nonparametric structural spurious regression model for high frequency data," Economics Letters, Elsevier, vol. 162(C), pages 18-21.
  • Handle: RePEc:eee:ecolet:v:162:y:2018:i:c:p:18-21
    DOI: 10.1016/j.econlet.2017.10.007
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    References listed on IDEAS

    as
    1. Kim, Jihyun & Park, Joon Y., 2017. "Asymptotics for recurrent diffusions with application to high frequency regression," Journal of Econometrics, Elsevier, vol. 196(1), pages 37-54.
    2. Badi H. Baltagi & Chihwa Kao & Long Liu, 2017. "Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 85-102, March.
    3. Choi, Chi-Young & Hu, Ling & Ogaki, Masao, 2008. "Robust estimation for structural spurious regressions and a Hausman-type cointegration test," Journal of Econometrics, Elsevier, vol. 142(1), pages 327-351, January.
    4. Aït-Sahalia, Yacine & Park, Joon Y., 2016. "Bandwidth selection and asymptotic properties of local nonparametric estimators in possibly nonstationary continuous-time models," Journal of Econometrics, Elsevier, vol. 192(1), pages 119-138.
    5. Trapani, Lorenzo, 2012. "On the asymptotic t-test for large nonstationary panel models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3286-3306.
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    More about this item

    Keywords

    Nonparametric regression; Nonstationary error term; Structural spurious regression; Consistency; High frequency data;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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