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?
correlation matrix set-up helpI'm trying to create a correlation matrix using the 'correlate var1 var2 var3...' command. I've got…
Identifying variables that serve as unique identifiersHello everyone I want to write a program that accepts numeric and string variables as input, that …
Interpreting VEC output with ranks higher than 1Dear STATA users, Although it feels like a simple question, I have spent a lot of time reading STAT…
Estimate coefficients to predict out of sample for the excluded quarter.Hi, I want to evaluate the model’s (reg lnUnmprate lnInflation lnFedfunds) ability to predict out of…
Hausman-Taylor estimator for binary dependent variableHi all, I am a business student who has had some introductory econometirc courses and has some basi…
Subscribe to:
Post Comments (Atom)
0 Response to VAR models on raw or filtered/smoothed data?
Post a Comment