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MCMC Estimation of Extended Hodrick-Prescott (HP) Filtering Models

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  • Wolfgang Polasek

    (Institute for Advanced Studies, Austria; University of Porto, Portugal; The Rimini Centre for Economic Analysis (RCEA), Italy)

Abstract

The Hodrick-Prescott (HP) method was originally developed to smooth time series, i.e. to get a smooth (long-term) component. We show that the HP smoother can be viewed as a Bayesian linear model with a strong prior for the smoothness component. Extending this Bayesian approach in a linear model set-up is possible by a conjugate and a non-conjugate model using MCMC. The Bayesian HP smoothing model is also extended to a spatial smoothing model. We have to define spatial neighbors for each observation and we can use in a similar way a smoothness prior as for the HP filter in time series. The new smoothing approaches are applied to the (textbook) airline passenger data for time series and to the problem of smoothing spatial regional data. This new approach can be used for a new class of model-based smoothers for time series and spatial models.

Suggested Citation

  • Wolfgang Polasek, 2011. "MCMC Estimation of Extended Hodrick-Prescott (HP) Filtering Models," Working Paper series 25_11, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:25_11
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    File URL: http://www.rcea.org/RePEc/pdf/wp25_11.pdf
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    References listed on IDEAS

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    1. Danthine, Jean-Pierre & Girardin, Michel, 1989. "Business cycles in Switzerland : A comparative study," European Economic Review, Elsevier, vol. 33(1), pages 31-50, January.
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    Cited by:

    1. Wolfgang Polasek, 2012. "MCMC Estimation of Extended Hodrick-Prescott (HP) Filtering Models," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 1, pages 25-52, March.
    2. Wolfgang Polasek, 2011. "The Extended Hodrick-Prescott (HP) Filter for Spatial Regression Smoothing," Working Paper series 45_11, Rimini Centre for Economic Analysis.
    3. Wolfgang Polasek, 2011. "The Hodrick-Prescott (HP) Filter as a Bayesian Regression Model," Working Paper series 46_11, Rimini Centre for Economic Analysis, revised Jan 2012.

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    More about this item

    Keywords

    Hodrick-Prescott (HP) smoothers; Spatial econometrics; MCMC estimation; Airline passenger time series; Spatial smoothing of regional data; NUTS: nomenclature of territorial units for statistics;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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