Real-Time vs. Full-Sample Performance of One-Sided and Two-Sided HP Filters. An Application to 27 EU Member States' GDP Data
The paper makes a comparison of the results of the application of two-sided and one-sided versions of the Hodrick-Prescott filter on GDP data concerning 27 EU Member States. Based on the results, the overall finding is that, contrary to its assumed advantages, the one-sided filter does not help overcome endpoint unbiasedness. Quite the opposite, it rather spreads and consolidates the endpoint bias that plagues the two-sided version over the entire filtered data. In addition, regression-based results on the influence of the second, third, and fourth moments of the GDP acceleration rates on the differences between onesided and two-sided HP trends are presented. (original abstract)
-  Cogley T., Nason J. M., (1995), Effects of the Hodrick-Prescott Filter on Trend and Difference Stationary Time Series. Implications for Business Cycle Research, Journal of Economic Dynamics and Control 19, 253-278.
-  Hamilton J., (2018), Why You Should Never Use the Hodrick-Prescott Filter, Review of Economics and Statistics 100(5), 831-843.
-  Harvey A. C., Jaeger A., (1993), Detrending, Stylized Facts, and the Business Cycle, Journal of Applied Econometrics 8(3), 231-247.
-  Hodrick R. J., Prescott E. C., (1997-), Postwar U.S. Business Cycles: An Empirical Investigation, Journal of Money, Credit and Banking 29(1), 1-16.
-  Manning W. G., Mullahy J., (2001), Estimating Log Models: To Transform or Not to Transform? Journal of Health Economics 20, 461-494.
-  Mehra Y. P., (2004), The Output Gap, Expected Future Inflation and Inflation Dynamics: Another Look, Topics in Macroeconomics 4(1),
-  Ravn M. O., Uhlig H., (2002), On Adjusting the Hodrick-Prescott Filter for the Frequency of Observations, The Review of Economics and Statistics 84(2), 371-376.
-  Stock J. H., Watson M. W., (1999), Forecasting Inflation, Journal of Monetary Economics 44, 293-335.
-  Thadewald T., Büning H., (2007), Jarque-Bera Test and its Competitors for Testing Normality - A Power Comparison, Journal of Applied Statistics 34(1), 87-105.