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A trend filtering method closely related to $$\ell _{1}$$ ℓ 1 trend filtering

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  • Hiroshi Yamada

    (Hiroshima University)

Abstract

The filtering method developed by Kim et al. (SIAM Rev 51:339–360, 2009), $$\ell _{1}$$ ℓ 1 trend filtering, is attractive because it enables us to estimate a continuous piecewise linear trend. This paper introduces a new filtering method closely related to $$\ell _{1}$$ ℓ 1 trend filtering in order to contribute to the accumulation of knowledge on $$\ell _{1}$$ ℓ 1 trend filtering. We show that the piecewise linearity, which is the key feature of $$\ell _{1}$$ ℓ 1 trend filtering, is derived from the new filtering. For this reason, we refer to the filtering as ‘pure’ $$\ell _{1}$$ ℓ 1 trend filtering. We also demonstrate some other miscellaneous results concerning the new filtering.

Suggested Citation

  • Hiroshi Yamada, 2018. "A trend filtering method closely related to $$\ell _{1}$$ ℓ 1 trend filtering," Empirical Economics, Springer, vol. 55(4), pages 1413-1423, December.
  • Handle: RePEc:spr:empeco:v:55:y:2018:i:4:d:10.1007_s00181-017-1349-8
    DOI: 10.1007/s00181-017-1349-8
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    References listed on IDEAS

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    1. Sato, Kazuo, 2002. "From fast to last: the Japanese economy in the 1990s," Journal of Asian Economics, Elsevier, vol. 13(2), pages 213-235.
    2. Yamada, Hiroshi & Yoon, Gawon, 2014. "When Grilli and Yang meet Prebisch and Singer: Piecewise linear trends in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 193-207.
    3. Harchaoui, Z. & Lévy-Leduc, C., 2010. "Multiple Change-Point Estimation With a Total Variation Penalty," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1480-1493.
    4. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    5. Hiroshi Yamada, 2018. "Why does the trend extracted by the Hodrick–Prescott filtering seem to be more plausible than the linear trend?," Applied Economics Letters, Taylor & Francis Journals, vol. 25(2), pages 102-105, January.
    6. Rappoport, Peter & Reichlin, Lucrezia, 1989. "Segmented Trends and Non-stationary Time Series," Economic Journal, Royal Economic Society, vol. 99(395), pages 168-177, Supplemen.
    7. Hiroshi Yamada, 2017. "Estimating the trend in US real GDP using the trend filtering," Applied Economics Letters, Taylor & Francis Journals, vol. 24(10), pages 713-716, June.
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    More about this item

    Keywords

    $$ell _{1}$$ ℓ 1 trend filtering; Generalized lasso regression; Hodrick–Prescott filtering; Ridge regression; Penalized least squares; 1d fused lasso; Total variation denoising;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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