Low-Frequency Econometrics / Ulrich K. Müller, Mark W. Watson.

Format:

Book

Author/Creator:

Müller, Ulrich K.

Contributor:

National Bureau of Economic Research.

Watson, Mark W.

Series:

Working Paper Series (National Bureau of Economic Research) no. w21564.

NBER working paper series no. w21564

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2015.

Summary:

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.

Notes:

Print version record

September 2015.