Dear all,
I just started to learn time series analysis and I'm reading Becketti's book at the moment. One general question that I didn't catch an answer to was, do I apply VAR models (as well as other models) on raw data or smoothen/filtered data? To be more precise, do I want to, for instance, de-trend, fix autocorrelation, and/or make my series stationarity prior to applying VAR models?
In general, I find it very hard to extract any general steps of how time series analysis proceeds, that is, what are the first steps, second, third? Are they any general "ways" how one analysis time series, I mean, maybe it makes way more sense to first test stationarity, autocorrelation than checking trend, cycle, etc?
Hope my question is not too confusingly written.
Thank you for your answers!
Related Posts with VAR models on raw or filtered/smoothed data?
Not able to convert string to date using date()Hi, I am having trouble converting a string to a date. I have imported an excel file, and have a v…
Missing values while using fixed effects model I have household-level panel data from two time periods. I found out that a good portion of my ho…
how to do a maximum simulated likelihood estimation?Dear statlist: I want to do a MSLE for the following equation systems: the choice function: Dit = 1 …
Generate time from date+time variableHello All, I am a beginner with Stata, and I have a Time variable that looks like this: Time 31dec…
Testing overidentification with categorical covariatesHi everyone, I am using Stata Version 14.2 and currently run a 2SLS Regression using the ivprobit c…
Subscribe to:
Post Comments (Atom)
0 Response to VAR models on raw or filtered/smoothed data?
Post a Comment