On smoothing macroeconomic time series using HP and modified HP filter
In business cycle research, smoothing data is an essential step in that it can influence the extent to which model-generated moments stand up to their empirical counterparts. To demonstrate this idea, we compare the results of McDermott’s (1997) modified HP-filter with the conventional HP-filter on the properties of simulated and actual macroeconomic series. Our simulations suggest that the modified HP-filter proxies better the true cyclical series. This is true for temporally aggregated data as well. Furthermore, we find that although the autoregressive properties of the smoothed observed series are immune to smoothing procedures, the multivariate analysis is not. As a result, we recommend and hence provide series-, country- and frequency specific smoothing parameters.
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