Low-Frequency Econometrics

Ulrich K. Müller and Mark Watson

No 21564, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Many questions in economics involve long-run or trend variation and covariation in time series. Yet, time series of typical lengths contain only limited information about this long-run variation. This paper suggests that long-run sample information can be isolated using a small number of low-frequency trigonometric weighted averages, which in turn can be used to conduct inference about long-run variability and covariability. Because the low-frequency weighted averages have large sample normal distributions, large sample valid inference can often be conducted using familiar small sample normal inference procedures. Moreover, the general approach is applicable for a wide range of persistent stochastic processes that go beyond the familiar I(0) and I(1) models.

JEL-codes: C12 C22 C32 (search for similar items in EconPapers)
Date: 2015-09
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: TWP
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Citations: View citations in EconPapers (5)

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