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Given that my variables exhibit non-stationary (i.e lrgdp and lop) and I intend on estimating a VAR model, would it make sense to correlate them in their first differences instead (dlrgdp and dlop) and how does one then interpret the results? For instance, 5 lags of dlrgdp would mean 6 lags of lrgdp?

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    $\begingroup$ In brief, yes. Correlation between non-stationary series can be problematic. See here for more: stats.stackexchange.com/questions/133155/… What is the reason for doing this correlation analysis? How does it relate to your intention to build a VAR model? $\endgroup$ – ColorStatistics Jan 26 at 17:00
  • $\begingroup$ If your original variables are measured each year, say, then their first-order differenced versions represent year-to-year changes in the values of the original variables. $\endgroup$ – Isabella Ghement Jan 26 at 18:22
  • $\begingroup$ This is because I want to help characterise temporal sequence of influences in VAR and I'm trying to figure this out through cross-correlations and the granger causality analysis. $\endgroup$ – Shan Jan 26 at 18:48

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