Fully Modified HP Filter

Muhammad Hanif, Javed Iqbal and Ali Choudhary

No 88, SBP Working Paper Series from State Bank of Pakistan, Research Department

Abstract: Business cycle estimation is core of macroeconomics research. Hodrick-Prescott (1997) filter, (or HP filter), is the most popular tool to extract cycle from a macroeconomic time series. There are certain issues with HP filter including fixed value of ? across the series/countries and end points bias (EPB). Modified HP filter (MHP) of McDermott (1997) attempted to address the first issue. Bloechl (2014) introduced a loss function minimization approach to address the EPB issue but keeping lambda fixed (as in HP filter). In this study we marry the endogenous lambda approach of McDermott (1997) with loss function minimization approach of Bloechl (2014) to analyze EPB in HP filter, while intuitively changing the weighting scheme used in the latter. We contribute by suggesting an endogenous weighting scheme along with endogenous smoothing parameter to resolve EPB issue of HP filter. We call this fully modified HP (FMHP) filter. Our FMHP filter outperforms a variety of conventional filters in a power comparison (simulation) study as well as in observed real data (univariate and multivariate) analytics for a large set of countries.

Keywords: Business Cycle; Time Series; Fully Modified HP Filter; End Point Bias in HP Filter; Simulation; Cross Country Study. (search for similar items in EconPapers)
JEL-codes: C18 E32 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2017-04
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mac
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Citations: View citations in EconPapers (1)

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