Dear Statalisters,
Please help me clarify my understanding in the correct procedure
to use seasonal variables in time-series regressions. My very
basic understanding of the correct use of the seasonal
differencing technique (time series operator _S._ in Stata) is in
the autoregressive integrated moving average (ARIMA) models. For
other regression techniques in analyzing time-series, and panel
data, the seasonal dummy variables are used.
Hamilton (my much dogged-eared version for Stata 7) explains how
to use _S._ in Stata, but not the ?why,? or the ?when? to use it.
Harvey explains briefly both procedures and says that the
differencing is used when the seasonal pattern changes over time.
Thus, in this sense, the differencing would cause the seasonal
pattern to become stationary.
Is there ever an appropriate situation to use the _S._ time-series
operator outside of an ARIMA model? In answering this specific
Stata question, I ask that you extend your answer to an
explanation, and possible reference that I could research, in
controlling seasons (and cycles) in time-series data that goes
beyond the usual econometric textbook treatment. An example, which
does not necessarily need to be economic, would be very much
appreciated.
Thanks,
Yvonne
M. Yvonne Reinertson
University of Florida, PhD Candidate
[email protected]
Version: Stata 7 (final update)
OS: WindowsXP
References Used:
Hamilton, L., 2003, ?Statistics with Stata,? (Duxbury-Thomson
Learning, Belmont).
Harvey, A, 1999, ?The Econometric Analysis of Time Series,? 2nd
ed., (MIT Press, Cambridge).
--
REINERTSON,M YVONNE
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
