Hodrick-Prescott (hp) filter: EViews tutorial

Hodrick-Prescott (hp) filter: EViews tutorial. In this video I teach you how to use the Hodrick-Prescott (hp) filter in Eviews step-by-step. In this video, we will apply the HP filter option in EViews to real data (GDP of USA).

What is the Hodrick-Prescott (hp) filter? And, How do you use an HP Filter?
The Hodrick-Prescott (hp) filter is a smoothing method used in macroeconomics to decompose a time series into trend and cyclical components. Although the filter appeared more frequently in the '80s, it became widely popular by the end of the 90s after Hodrick and Prescott published a paper in 1997 entitled: Postwar U.S. Business Cycles: An Empirical Investigation.

Technically, the Hodrick-Prescott (HP) filter computes the smoothed series of "y" by minimizing the variance of "y" around the trend. The trend component is generally non-stationary (stochastic or deterministic). wOn the other hand, the cyclical part is stationary (you can run the Augmented dickey fuller - option: no trend and no intercept - in the cyclical component).

We can obtain the cyclical (GAP) and trend component when applied to Real GDP. The HP-Filter smoothing parameter is commonly set to 1600 for quarterly data, 100 for yearly data and 14,400 for monthly data.

Are you ready? Let's get into it!

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🕘 Timestamps:
🎬 In this video the following analysis is performed:
👋 Introduction 0:00
📊 HP Filter Introduction 0:28
📊 HP Filter Overview 1:20
📊 HP Filter - USA Example 2:21
📊 HP Filter in EViews 4:00
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