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Selecting the tuning parameter of the ℓ 1 trend filter

Selecting the tuning parameter of the ℓ 1 trend filter Abstract The ℓ 1 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 ℓ 1 trend filter and its generalization. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Studies in Nonlinear Dynamics & Econometrics de Gruyter

Selecting the tuning parameter of the ℓ 1 trend filter

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Publisher
de Gruyter
Copyright
Copyright © 2016 by the
ISSN
1081-1826
eISSN
1558-3708
DOI
10.1515/snde-2014-0089
Publisher site
See Article on Publisher Site

Abstract

Abstract The ℓ 1 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 ℓ 1 trend filter and its generalization.

Journal

Studies in Nonlinear Dynamics & Econometrics – de Gruyter

Published: Feb 1, 2016

References

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    Tibshirani
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    Kim
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    Rappoport
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    Reeves
  • Regression Biased Estimation for Nonorthogonal Problems
    Hoerl
  • Postwar Cycles An Empirical Investigation of and
    Hodrick
  • Adaptive Piecewise Polynomial Estimation via Trend Filtering of
    Tibshirani
  • Blinder Macroeconomics Principles Policy th ed South Western
    Baumol
  • On the LASSO and its Dual of and
    Osborne
  • Note on Band - Pass Filters Based on the Hodrick Prescott Filter and the OECD System of Composite Leading Indicators of Cycle and
    Yamada
  • Measuring Cycles Approximate Band - Pass Filters for Economic Time Series of and
    Baxter
  • Why are the Unobserved - Components Decompositions of GDP so Different of and
    Morley
  • The Filter Generalization New Procedure for Extracting an Empirical Cycle From a Series in Nonlinear Dynamics and
    Reeves
  • The Great Crash the Oil Price Shock and the Unit Root Hypothesis
    Perron
  • Regression Shrinkage and Selection via the Lasso of the
    Tibshirani
  • Japan s Output Gap Estimation andℓ Trend Filtering Empirical
    Yamada
  • Convex Princeton Princeton University
    Rockafellar
  • Regression Biased Estimation for Nonorthogonal Problems
    Hoerl
  • When meet Linear Trends in Primary Commodity Prices of and
    Yamada
  • ℓ Trend Filtering
    Kim
  • Regression Shrinkage and Selection via the Lasso of the
    Tibshirani
  • The Filter Special Case of Penalized Smoothing Electronic of
    Paige
  • The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series of and
    Gómez
  • The Solution Path of the Generalized Lasso of
    Tibshirani
  • Let s Take a break : Trend and Cycles in US Real GDP of
    Perron
  • When meet Linear Trends in Primary Commodity Prices of and
    Yamada
  • The Great Crash the Oil Price Shock and the Unit Root Hypothesis
    Perron
  • Time Series Princeton Princeton University
    Hamilton
  • Low Frequency Filtering and Real Cycles of Economic Dynamics and
    King
  • Blinder Macroeconomics Principles Policy th ed South Western
    Baumol
  • Segmented Trends and Non - Stationary Time Series
    Rappoport
  • Convex Princeton Princeton University
    Rockafellar
  • Low Frequency Filtering and Real Cycles of Economic Dynamics and
    King