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Selecting the tuning parameter of the ℓ1 trend filter

Author

Listed:
  • Yamada Hiroshi

    (Department of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan)

  • Yoon Gawon

    (Department of Economics, Kookmin University, 136–702, S. Korea)

Abstract

The ℓ1 trend filter, which is similar to the popular Hodrick–Prescott (HP) filter, seems to be very promising because it enables us to estimate a piecewise linear trend without specifying the location and number of kink points a priori. Such a trend may be regarded as a result of occasional permanent shocks to the growth rate. Similarly to the HP filter, the value of the tuning parameter needs to be selected in applying this filter. This paper proposes a method for selecting the tuning parameter of the ℓ1 trend filter and its generalization.

Suggested Citation

  • Yamada Hiroshi & Yoon Gawon, 2016. "Selecting the tuning parameter of the ℓ1 trend filter," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 97-105, February.
    • Handle: RePEc:bpj:sndecm:v:20:y:2016:i:1:p:97-105:n:5
    DOI: 10.1515/snde-2014-0089
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    References listed on IDEAS

    as
    1. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Hiroshi Yamada & Ruixue Du, 2018. "Some Results on ℓ 1 Polynomial Trend Filtering," Econometrics, MDPI, vol. 6(3), pages 1-10, July.

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    More about this item

    Keywords

    Hodrick–Prescott filter; lasso; ℓ1 trend filter; sparsity; tuning parameter;
    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

    Statistics

    Access and download statistics

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