Thank you for your prompt response!
Below, I copied the gretl syntax (restrictions and bootstrap). I also copied the gretl output. And yes, I installed the latest version from the gretl site.
Sincerely,
Jay


BQModel = SVAR_setup("C", X, exog, maxlag)
BQModel["horizon"]=20

SVAR_restrict(&BQModel, "lrC", 1,2,0)
SVAR_restrict(&BQModel, "lrC", 1,3,0)
SVAR_restrict(&BQModel, "lrC", 1,4,0)
SVAR_restrict(&BQModel, "lrC", 1,5,0)

SVAR_restrict(&BQModel, "C", 1,3,0)
SVAR_restrict(&BQModel, "C", 1,4,0)
SVAR_restrict(&BQModel, "C", 1,5,0)
SVAR_restrict(&BQModel, "C", 3,5,0)
SVAR_restrict(&BQModel, "C", 4,5,0)
SVAR_restrict(&BQModel, "C", 5,3,0)

SVAR_cumulate(&BQModel, 1)
SVAR_cumulate(&BQModel, 2)
SVAR_cumulate(&BQModel, 3)
SVAR_cumulate(&BQModel, 4)
SVAR_cumulate(&BQModel, 5)

SVAR_estimate(&BQModel)

bfail = SVAR_boot(&BQModel, 2000, 0.9, 0)

? SVAR_estimate(&BQModel)
 
Unconstrained Sigma:
     0.00004     0.00000     0.00071     0.00059     0.00014
     0.00000     0.00000     0.00010     0.00364     0.00000
     0.00071     0.00010     0.11088     0.24597     0.00347
     0.00059     0.00364     0.24597   159.92282    -0.00971
     0.00014     0.00000     0.00347    -0.00971     0.00084
 
Long-run matrix C(1) =
      0.7736     -1.5321      0.0135      0.0001      0.1158
      0.1695      1.4970      0.0076      0.0001      0.0254
    -72.3749    -90.8705      2.9837      0.0254     15.0368
    305.4149  -1451.6624    -17.4910      0.7748    -14.4628
     -0.4012    -13.7671      0.0605      0.0006      1.6212
 
Optimization method = Scoring algorithm
 
              coefficient    std. error       z        p-value 
  --------------------------------------------------------------
  C[ 1; 1]     0.00520873    0.000629939     8.269     1.36e-016 ***
  C[ 2; 1]    -0.000263129   0.000231818    -1.135     0.2563  
  C[ 3; 1]     0.223805      0.0378243       5.917     3.28e-09  ***
  C[ 4; 1]     1.58688       1.62616         0.9758    0.3291  
  C[ 5; 1]     0.0237545     0.00304730      7.795     6.43e-015 ***
  C[ 1; 2]    -0.00320062    0.000292175   -10.95      6.33e-028 ***
  C[ 2; 2]    -0.000529455   0.000225448    -2.348     0.0189    **
  C[ 3; 2]     0.141552      0.0290911       4.866     1.14e-06  ***
  C[ 4; 2]     2.39856       1.60483         1.495     0.1350  
  C[ 5; 2]    -0.00460859    0.00209923     -2.195     0.0281    **
  C[ 1; 3]     0.00000       0.00000        NA        NA       
  C[ 2; 3]     0.000120530   0.000476143     0.2531    0.8002  
  C[ 3; 3]     0.114847      0.0437330       2.626     0.0086    ***
  C[ 4; 3]   -11.2260        1.65104        -6.799     1.05e-011 ***
  C[ 5; 3]     0.00000       0.00000        NA        NA       
  C[ 1; 4]     0.00000       0.00000        NA        NA       
  C[ 2; 4]     0.00131884    0.000186939     7.055     1.73e-012 ***
  C[ 3; 4]     0.166040      0.0362217       4.584     4.56e-06  ***
  C[ 4; 4]     5.06246       3.24872         1.558     0.1192  
  C[ 5; 4]    -0.00717976    0.00194941     -3.683     0.0002    ***
  C[ 1; 5]     0.00000       0.00000        NA        NA       
  C[ 2; 5]     0.00107498    9.81318e-05    10.95      6.33e-028 ***
  C[ 3; 5]     0.00000       0.00000        NA        NA       
  C[ 4; 5]     0.00000       0.00000        NA        NA       
  C[ 5; 5]     0.0142210     0.00129819     10.95      6.33e-028 ***
 
  Log-likelihood = 413.11
 
 
? bfail = SVAR_boot(&BQModel, 2000, 0.9, 0)
 
Bootstrapping model (2000 iterations)
 
errcode = 32
errcode = 32
errcode = 32
errcode = 32
errcode = 32
errcode = 32
errcode = 32
errcode = 32
Warning: couldn't improve criterion (gradient = 2.25191)
errcode = 32
errcode = 32
errcode = 32
errcode = 32
errcode = 32
Bootstrap results (2000 replications, 0 failed)
 
             coefficient    std. error       z       p-value
  ----------------------------------------------------------
  C[ 1; 1]    0.00153498    0.00411606     0.3729     0.7092
  C[ 2; 1]    2.14368e-05   0.000533545    0.04018    0.9680
  C[ 3; 1]    0.0748155     0.171772       0.4356     0.6632
  C[ 4; 1]    2.02507       1.62786        1.244      0.2135
  C[ 5; 1]    0.00678030    0.0184051      0.3684     0.7126
  C[ 1; 2]   -0.000957296   0.00313491    -0.3054     0.7601
  C[ 2; 2]    4.25591e-05   0.000707832    0.06013    0.9521
  C[ 3; 2]    0.0331823     0.101026       0.3285     0.7426
  C[ 4; 2]    2.80113       2.28712        1.225      0.2207
  C[ 5; 2]   -0.00259911    0.00885520    -0.2935     0.7691
  C[ 1; 3]    0.00000       0.00000       NA         NA    
  C[ 2; 3]   -0.000110869   0.000565895   -0.1959     0.8447
  C[ 3; 3]    0.0287889     0.143152       0.2011     0.8406
  C[ 4; 3]   -7.72066       3.47706       -2.220      0.0264 **
  C[ 5; 3]    0.00000       0.00000       NA         NA    
  C[ 1; 4]    0.00000       0.00000       NA         NA    
  C[ 2; 4]    0.000248349   0.000768865    0.3230     0.7467
  C[ 3; 4]    0.0170406     0.147616       0.1154     0.9081
  C[ 4; 4]    5.01946       3.53079        1.422      0.1551
  C[ 5; 4]   -0.00276044    0.00696356    -0.3964     0.6918
  C[ 1; 5]    0.00000       0.00000       NA         NA    
  C[ 2; 5]    0.000545628   0.000746872    0.7306     0.4651
  C[ 3; 5]    0.00000       0.00000       NA         NA    
  C[ 4; 5]    0.00000       0.00000       NA         NA    
  C[ 5; 5]    0.0114515     0.00396175     2.891      0.0038 ***



On Tuesday, August 2, 2016 7:01 PM, Sven Schreiber <svetosch@gmx.net> wrote:


Am 03.08.2016 um 00:16 schrieb jayeryu:

> 2. There is a red flag for the short and long run restrictions, though.
> I put the two restrictions simultaneously but the results are widely
> different from what my coauthor obtained from RATS and GAUSS.

Thanks for reporting your case.


>
> The result from gretl shows a C matrix that looks like one that just
> superimposed short and long run matrices in a way that any 0 values in
> either of the two matrices replaced the relevant element of the C.

>

It would be useful if you could copy&paste your restrictions and the C
matrix that gretl shows.

In case you're not using the latest gretl version please also add that
information.

Thanks,
sven
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