Improved output gap estimates and forecasts using a local linear regression

Marlon Fritz

International Economics, 2022, issue 172, 157-167

Abstract: The output gap, the difference between potential and actual output, has a direct impact on policy decisions, e.g., monetary policy. Due to methodological problems, estimating this gap and its further analysis remains the subject of many debates. We propose a local polynomial regression and its forecasting extension for a systematic output gap estimation. Further, the local polynomial regression is proposed for the (multivariate) OECD production function approach, and its reliability is demonstrated in forecasting output growth. Comparing the proposed gap to the Hodrick-Prescott filter and to estimations by experts from the FED and OECD shows a higher correlation of our output gap with those from economic institutions. Furthermore, it sometimes happens that gaps with different magnitudes and different positions above or below the trend are observed between different methods. This may cause competing policy implications which can be improved with our results.

Keywords: Business cycles; Nonparametric methods; Output gap; Trend identification (search for similar items in EconPapers)
JEL-codes: C14 C22 E31 E52 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:cii:cepiie:2022-q3-172-10

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