Re: [Gretl-users] Discrepancy between R and Gretl in Johansen cointegration

Am 01.02.2019 um 04:15 schrieb Allin Cottrell: I have now used Reynaldo's original example and turned it into a script. The data are attached in gretl format for convenience. (Note that I had difficulties getting the exogenous variable into tsDyn's rank.test, I believe there may be a small bug there. Hence my workaround with as.matrix and drop=F.) <hansl> open CI_testdata.gdt coint2 6 GDP NDB; Bdum --quiet # Bdum dummy renamed from bnprivfinance foreign language=R --send-data require(tsDyn) cidat <- gretldata[, c("GDP","NDB")] exo <- as.matrix(gretldata[, c("Bdum")], drop=F) # bnprivfinance ve <- VECM(cidat, lag=5, estim="ML", include="const", exogen=exo) ve_test0 <- rank.test(ve, r_null=0, type="trace") ve_test0 ve_test1 <- rank.test(ve, r_null=1, type="trace") ve_test1 require(urca) test2 <- ca.jo(cidat, type="trace", K=6, ecdet=c("none"), dumvar=exo) summary(test2) end foreign </hansl> Here's (parts of) the output: Gretl (German, but I guess it's obvious): Rang Eigenwert Trace-Test p-Wert Lmax-Test p-Wert 0 0.30870 26.346 [0.0006] 20.674 [0.0033] 1 0.096321 5.6718 [0.0172] 5.6718 [0.0172] tsDyn: Test of rank 0 versus 2 (trace test), p-value: 0.0005827881. Test of rank 1 versus 2 (trace test), p-value: 0.01724008. urca: test 10pct 5pct 1pct r <= 1 | 5.67 6.50 8.18 11.65 r = 0 | 26.35 15.66 17.95 23.52 So that's the differing conclusions from the OP, and Gretl and tsDyn again agree, urca doesn't. (And BTW, I'm speculating that a comparison of 26.35 with urca's 1% crit. value 23.5 wouldn't give a p-value below .001, but who knows). Finally, let me add that this is just a comparison of the mechanical workings of the tools. All those results are likely invalid because the test is not valid in general with such an unrestricted exogenous variable which is not an impulse dummy, but is modeling some breaks or thresholds. cheers, sven