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Re: st: unconventional lag length in VAR model?
From
Robert A Yaffee <[email protected]>
To
[email protected]
Subject
Re: st: unconventional lag length in VAR model?
Date
Mon, 4 Mar 2013 13:30:10 -0500
Jason,
The varsoc, varlmar, and varwle are generally used for this purpose.
Bob Yaffee
On Fri, Mar 1, 2013 at 1:48 PM, Jason R Franken <[email protected]> wrote:
> I want to determine the appropriate lag structure for a VAR of 3 price series - C, F1, and E. A prior study used these variables and determined the structure using Akaiki's Final Prediction Error (FPE), which can be obtained with the below commands.
>
> My problem is that the prior study was able to ascertain how the lag length differed for each variable and in each equation (that is 4 lags of each variable in each equation might not be appropriate), and I'm not sure how to investigate this with the below commands. Specifically, the prior study finds (for a shorter time period) that the F1 equation has lag 1 of F1 and lags 1 and 2 of C; the E equation has only lags 1 through 4 of C; and the C equation has only lag1 of F1.
>
> Can I examine this by estimating a VAR with commands for seemingly unrelated regression (reg3, sur; suest; sureg)?
>
> Thanks in advance,
> Jason Franken
>
> RESULTS:
> . var C F1 E, lags(1/4)
>
> Vector autoregression
>
> Sample: 1976q1 2010q3 No. of obs = 139
> Log likelihood = -1096.43 AIC = 16.33712
> FPE = 2502.717 HQIC = 16.6717
> Det(Sigma_ml) = 1425.583 SBIC = 17.16046
>
> Equation Parms RMSE R-sq chi2 P>chi2
> ----------------------------------------------------------------
> C 13 5.20584 0.5664 181.5755 0.0000
> F1 13 4.50839 0.6138 220.9116 0.0000
> E 13 3.64389 0.7331 381.8178 0.0000
> ----------------------------------------------------------------
> ------------------------------------------------------------------------------
> | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> C |
> C |
> L1. | .8522103 .1119234 7.61 0.000 .6328444 1.071576
> L2. | -.2105517 .1371686 -1.53 0.125 -.4793972 .0582938
> L3. | .4614619 .1400664 3.29 0.001 .1869368 .735987
> L4. | -.0850031 .1404678 -0.61 0.545 -.360315 .1903088
> F1 |
> L1. | .1405764 .136883 1.03 0.304 -.1277093 .4088621
> L2. | -.3039644 .1454131 -2.09 0.037 -.5889687 -.01896
> L3. | .0981597 .1456564 0.67 0.500 -.1873216 .383641
> L4. | .0081719 .1410511 0.06 0.954 -.2682833 .284627
> E |
> L1. | -.1111197 .1855016 -0.60 0.549 -.4746961 .2524566
> L2. | .0254513 .1867506 0.14 0.892 -.3405732 .3914758
> L3. | -.2986691 .1875468 -1.59 0.111 -.6662541 .068916
> L4. | .0016383 .1617178 0.01 0.992 -.3153227 .3185994
> _cons | 18.8637 4.441675 4.25 0.000 10.15818 27.56923
> -------------+----------------------------------------------------------------
> F1 |
> C |
> L1. | .728714 .0969286 7.52 0.000 .5387376 .9186905
> L2. | -.221222 .1187916 -1.86 0.063 -.4540491 .0116052
> L3. | .5090438 .1213011 4.20 0.000 .271298 .7467896
> L4. | -.3071865 .1216488 -2.53 0.012 -.5456138 -.0687593
> F1 |
> L1. | .3239146 .1185442 2.73 0.006 .0915722 .5562569
> L2. | .0113203 .1259315 0.09 0.928 -.2355008 .2581414
> L3. | .0733694 .1261422 0.58 0.561 -.1738648 .3206036
> L4. | .3028863 .1221539 2.48 0.013 .063469 .5423036
> E |
> L1. | -.3247369 .1606491 -2.02 0.043 -.6396034 -.0098704
> L2. | -.225406 .1617309 -1.39 0.163 -.5423927 .0915807
> L3. | -.0965215 .1624204 -0.59 0.552 -.4148596 .2218166
> L4. | -.2100509 .1400518 -1.50 0.134 -.4845473 .0644455
> _cons | 19.94553 3.846605 5.19 0.000 12.40632 27.48473
> -------------+----------------------------------------------------------------
> E |
> C |
> L1. | .5893907 .0783421 7.52 0.000 .435843 .7429384
> L2. | -.3047364 .0960128 -3.17 0.002 -.492918 -.1165548
> L3. | .3976193 .0980411 4.06 0.000 .2054622 .5897763
> L4. | .0127413 .0983221 0.13 0.897 -.1799665 .2054491
> F1 |
> L1. | .4016804 .0958129 4.19 0.000 .2138907 .5894702
> L2. | -.3147535 .1017836 -3.09 0.002 -.5142457 -.1152614
> L3. | -.1558412 .1019539 -1.53 0.126 -.3556671 .0439848
> L4. | .0926355 .0987304 0.94 0.348 -.1008726 .2861435
> E |
> L1. | -.023602 .129844 -0.18 0.856 -.2780915 .2308876
> L2. | .2505328 .1307183 1.92 0.055 -.0056704 .5067359
> L3. | -.0338416 .1312756 -0.26 0.797 -.2911371 .2234539
> L4. | -.1952189 .1131963 -1.72 0.085 -.4170795 .0266417
> _cons | 12.52217 3.109002 4.03 0.000 6.428634 18.6157
> ------------------------------------------------------------------------------
>
> . varsoc
>
> Selection order criteria
> Sample: 1976q1 2010q3 Number of obs = 139
> +---------------------------------------------------------------------------+
> |lag | LL LR df p FPE AIC HQIC SBIC |
> |----+----------------------------------------------------------------------|
> | 0 | -1236.7 11201.5 17.8374 17.8632 17.9008 |
> | 1 | -1146.61 180.18 9 0.000 3488.08 16.6707 16.7736 16.924* |
> | 2 | -1125.79 41.648 9 0.000 2942.99 16.5006 16.6807 16.9439 |
> | 3 | -1111.73 28.119 9 0.001 2737.7 16.4278 16.6851 17.0611 |
> | 4 | -1096.43 30.599* 9 0.000 2502.72* 16.3371* 16.6717* 17.1605 |
> +---------------------------------------------------------------------------+
> Endogenous: C F1 E
> Exogenous: _cons
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
--
Robert A. Yaffee, Ph.D.
Research Professor
Silver School of Social Work
New York University
Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf
CV: http://homepages.nyu.edu/~ray1/vita.pdf
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/