Dear Stata users,
I'm relatively new to the VAR model and have been using Sean Becketti's 'Introduction to Time Series Using State' as reference and wanted to check if I am on the right track.
As of now, I have 5 variables in the VAR Model. [GDP, Oil prices, Exchanged rates (Expressed in Logs)] , [Inflation Rate and Unemployment Rate (Expressed in percentages)]
I performed the Unit Root tests and all of them proved to be non-stationary and did the Johansen Cointegration tests using
the results show that the variables do not have any cointegrating relationships.
However,
the variables contain a unit root, I don't know if I should estimate the VAR using the variables in their first differences or in levels.
I did it in levels
but I'm not sure if it should be that or
These are my variables
Please help me out as I don't know how to approach this. Thank you.
I'm relatively new to the VAR model and have been using Sean Becketti's 'Introduction to Time Series Using State' as reference and wanted to check if I am on the right track.
As of now, I have 5 variables in the VAR Model. [GDP, Oil prices, Exchanged rates (Expressed in Logs)] , [Inflation Rate and Unemployment Rate (Expressed in percentages)]
I performed the Unit Root tests and all of them proved to be non-stationary and did the Johansen Cointegration tests using
vecrank lrgdp lop lexc inf unp, max ic
However,
the variables contain a unit root, I don't know if I should estimate the VAR using the variables in their first differences or in levels.
I did it in levels
varbasic lrgdp lop lexc inf unp, lags (1 2 3 4 5)
varbasic dlrgdp dlop dlexc dinf dunp, lags (1 2 3 4 5)
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(lrgdp lop lexc) double(unp inf) float(Dlrgdp Dlop Dlexc Dunp Dinf) 12.733817 3.571784 1.598734 1.5 7.74278215223094 . . . . . 12.690648 3.568123 1.5978713 1.4 10.2464332036316 -.04316902 -.0036604404 -.0008628368 -.1 2.503651 12.661692 3.487579 1.5771695 2.1 12.291933418694 -.028956413 -.08054447 -.020701766 .7 2.0455003 12.745687 3.6658666 1.614704 1.6 13.1147540983606 .08399487 .17828774 .03753448 -.5 .8228207 12.734313 3.6188145 1.6771152 1.8 14.7381242387332 -.01137352 -.04705215 .06241119 .2 1.62337 12.7117 3.512739 1.7375907 2 14 -.022613525 -.10607576 .06047547 .2 -.7381243 12.695962 3.4593616 1.805854 2.4 13.5689851767389 -.015737534 -.05337715 .06826341 .4 -.4310148 12.754564 3.5122416 1.7645824 1.8 12.3745819397994 .05860233 .05288005 -.04127169 -.6 -1.1944033 12.734605 3.423394 1.7836152 2 11.8895966029724 -.01995945 -.08884788 .019032836 .2 -.48498535 12.70936 3.469064 1.8045276 2.4 11.0423116615067 -.025244713 .04567003 .02091241 .4 -.8472849 12.699594 3.459676 1.893353 2.8 10.8433734939759 -.009765625 -.009387732 .08882523 .4 -.19893816 12.762194 3.4528406 1.9665668 3.2 11.6071428571428 .06259918 -.00683546 .073213935 .4 .7637694 12.752794 3.372798 1.961493 3.6 9.77229601518024 -.009399414 -.0800426 -.005073905 .4 -1.834847 12.759803 3.383712 1.9698684 3.7 9.1078066914498 .007008553 .010914087 .0083755255 .1 -.6644893 12.74189 3.411038 2.0019078 3.8 7.78985507246374 -.017912865 .02732563 .032039404 .1 -1.3179516 12.807036 3.365225 2.015254 2.6 7.28888888888891 .065146446 -.04581285 .013346195 -1.2 -.5009662 12.81646 3.37531 2.0397863 3.2 6.30942091616251 .00942421 .010084867 .02453232 .6 -.979468 12.796157 3.3780425 2.0465481 3.3 6.47359454855195 -.020303726 .002732754 .00676179 .1 .16417363 12.817017 3.337429 2.1241918 3.6 6.13445378151261 .02085972 -.04061341 .07764363 .3 -.3391408 12.866818 3.313822 2.1803722 2.5 5.96520298260146 .04980183 -.023606777 .05618048 -1.1 -.1692508 12.878362 3.309326 2.237168 3 5.69105691056911 .011543274 -.0044965744 .05679584 .5 -.27414608 12.84228 3.293983 2.1853395 2.3 5.75999999999999 -.036082268 -.015342474 -.05182862 -.7 .06894309 12.861259 3.299288 2.121343 3.1 5.77988915281077 .01897907 .005304575 -.06399655 .8 .019889154 12.929962 3.33482 2.0523486 2 5.62939796716187 .06870365 .035532236 -.06899428 -1.1 -.1504912 12.903667 2.842581 1.9905694 2 5.76923076923076 -.02629471 -.492239 -.06177926 0 .1398328 12.897962 2.521185 2.001881 1.9 6.05143721633889 -.005705833 -.3213961 .01131153 -.1 .28220645 12.89723 2.521185 1.9996946 2.3 8.00898203592812 -.0007314682 0 -.0021862984 .4 1.9575448 12.971673 2.6837575 2.010828 1.7 8.80829015544041 .07444286 .1625726 .011133432 -.6 .7993081 12.92926 2.873941 1.950964 2.4 9.96363636363637 -.04241371 .19018364 -.05986404 .7 1.1553462 12.932686 2.911807 1.9037777 1.8 9.70042796005709 .003426552 .03786588 -.04718626 -.6 -.2632084 12.893644 2.941276 1.906605 2.2 7.90020790020794 -.03904152 .029469013 .0028271675 .4 -1.80022 12.984353 2.876761 1.8676294 1.9 7.41496598639454 .09070873 -.064515114 -.03897548 -.3 -.4852419 12.946301 2.757052 1.8508142 2.5 7.07671957671957 -.0380516 -.11970901 -.016815186 .6 -.3382464 12.911412 2.778198 1.833541 2.9 7.02210663198959 -.03488922 .02114606 -.017273188 .4 -.05461295 12.90235 2.6452286 1.922188 3.4 6.61528580603723 -.009062767 -.13296938 .08864713 .5 -.4068208 12.970265 2.576168 1.88874 3.9 6.01646611779607 .06791592 -.069060326 -.03344822 .5 -.5988197 12.919985 2.834585 1.9055742 4.8 4.69425571340333 -.05028057 .25841665 .016834259 .9 -1.3222104 12.94254 2.916148 1.947119 4.76666666666667 4.67800729040098 .02255535 .08156276 .0415448 -.033333335 -.016248424 12.918333 2.857045 1.951395 5.03333333333333 4.51807228915663 -.024207115 -.05910301 .004276037 .26666668 -.159935 12.99056 2.9295924 1.9239225 4.93333333333333 4.30107526881723 .07222748 .072547674 -.027472496 -.1 -.21699703 12.966217 2.968532 1.876953 5.66666666666667 4.36578171091446 -.02434349 .03893995 -.04696953 .7333333 .064706445 12.940326 2.761275 1.8701546 5.16666666666667 3.83052814857803 -.025891304 -.20725727 -.006798387 -.5 -.5352536 12.928958 3.2448034 1.8171023 5.2 3.80403458213255 -.011367798 .4835284 -.05305231 .033333335 -.026493566 13.01213 3.433987 1.768508 4.83333333333333 4.524627720504 .0831728 .1891837 -.04859436 -.3666667 .7205932 12.980206 2.988204 1.7871656 5.6 3.90050876201245 -.0319252 -.4457831 .018657684 .7666667 -.624119 12.994061 2.908539 1.910165 5.23333333333333 3.80100614868644 .013855934 -.07966495 .12299943 -.3666667 -.09950262 12.965244 2.966475 1.9188864 5.46666666666667 3.49805663520268 -.028817177 .05793595 .008721352 .23333333 -.3029495 13.03053 2.989043 1.8550003 5.5 2.57534246575342 .06528664 .022568226 -.063886166 .033333335 -.9227142 13.03316 2.862582 1.8492314 6.1 2.33949945593033 .00262928 -.1264615 -.005768895 .6 -.235843 13.002828 2.979772 1.8425794 5.96666666666667 2.4232633279483 -.030332565 .1171906 -.006651998 -.13333334 .08376388 13.011215 2.995566 1.7568114 6 2.30686695278971 .008387566 .015793324 -.08576798 .033333335 -.11639638 13.063393 2.9421556 1.8557254 5.63333333333333 2.24358974358973 .05217743 -.05341005 .09891403 -.3666667 -.06327721 13.03319 2.889816 1.9392883 6.26666666666667 2.60499734183944 -.03020191 -.05233955 .08356285 .6333333 .3614076 13.020434 2.890001 1.9237765 6.1 2.41850683491062 -.012756348 .00018525124 -.01551175 -.16666667 -.1864905 13.036485 2.785011 1.981176 6.1 2.14997378080752 .016050339 -.10499 .05739963 0 -.26853305 13.129934 2.705603 1.99125 5.33333333333333 1.98537095088822 .0934496 -.07940865 .01007378 -.7666667 -.16460283 13.086267 2.629728 2.0071983 5.63333333333333 1.2435233160622 -.04366684 -.07587433 .015948415 .3 -.7418476 13.094742 2.789323 1.97535 5.66666666666667 .975359342915802 .00847435 .15959454 -.031848192 .033333335 -.26816398 13.069872 2.83615 1.92342 5.36666666666667 1.54004106776183 -.02486992 .04682732 -.05193007 -.3 .5646817 13.167482 2.8096035 1.907233 4.96666666666667 1.74180327868853 .09761047 -.026546717 -.016186953 -.4 .2017622 13.138304 2.846265 1.8751172 5.53333333333333 2.66120777891503 -.02917862 .036661625 -.032115936 .56666666 .9194045 13.106668 2.9001386 1.8304694 5.2 2.69445856634468 -.031635284 .05387354 -.04464781 -.3333333 .033250786 13.13269 2.7997174 1.8410743 4.8 2.3255813953488 .02602291 -.1004212 .010604978 -.4 -.3688772 13.203746 2.83184 1.8371985 4.2 2.16515609264855 .07105446 .032122374 -.0038758516 -.6 -.1604253 13.192417 2.9076295 1.8587487 5 .897308075772663 -.011328697 .0757897 .02155018 .8 -1.267848 13.162365 2.9697304 1.8772483 5 .990099009900991 -.030052185 .06210089 .018499613 0 .09279093 13.191945 3.026746 1.8584784 4.76666666666667 1.38339920948619 .029580116 .0570159 -.01876986 -.23333333 .3933002 13.232254 3.138244 1.8616062 4.23333333333333 1.77427304090683 .04030895 .11149788 .003127813 -.53333336 .3908738 13.214523 3.048483 1.8915474 4.26666666666667 3.06324110671939 -.017730713 -.08976126 .0299412 .033333335 1.288968 13.248065 2.91723 1.9568384 4.23333333333333 2.69607843137256 .03354168 -.13125277 .06529093 -.033333335 -.3671627 13.222542 2.9262035 2.0096192 3.96666666666667 2.29044834307992 -.025523186 .00897336 .05278087 -.26666668 -.4056301 13.29889 2.935982 1.963833 3.2 2.22760290556901 .0763483 .009778738 -.04578638 -.7666667 -.06284544 13.286092 2.6506565 2.0201964 3.3 2.15723873441995 -.01279831 -.28532577 .05636358 .1 -.07036417 13.259114 2.586259 2.0167592 3.46666666666667 2.2434367541766 -.02697754 -.064397335 -.003437281 .16666667 .08619802 13.23906 2.565206 2.0330641 3.1 2.28680323963794 -.02005291 -.021053314 .01630497 -.3666667 .04336648 13.30432 2.472328 2.0134616 2.5 2.32117479867363 .06525898 -.09287786 -.019602537 -.6 .03437156 13.283984 2.454734 2.0364158 2.8 2.25246363209761 -.02033615 -.017594099 .022954226 .3 -.06871117 13.26049 2.774462 2.0538929 2.96666666666667 2.47432306255837 -.023492813 .3197281 .017477036 .16666667 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4.13333333333333 -1.42682429677945 .014725685 .09015703 -.001775503 .033333335 -2.642757 13.385754 3.5730944 1.9257075 4.33333333333333 .829187396351576 -.03930473 .10330415 -.006779671 .2 2.2560117 13.367247 3.702618 1.9261932 4.5 1.20732722731057 -.018507004 .12952352 .00048577785 .16666667 .3781398 13.447302 3.754901 1.8458267 4.13333333333333 1.24275062137531 .08005524 .05228329 -.0803665 -.3666667 .035423394 end
