Incorrect code: I couldn't run a panel VAR using monthly data in R

Hi RStudio Community!
I am trying to run a panel VAR in R using a monthly data. I usually don't have any issue with the code if it is a yearly data. But whenever I run the code, I will get the "Error in xtfrm.data.frame(x) : cannot xtfrm data frames".

This is the code I use when I'm running a yearly data.

varone <-pvargmm(
dependent_vars = c("SP", "IDV"),
lags = 1,
transformation = "fod",
data = Olu,
panel_identifier = c("Bank", "Year"),
steps = c("twostep"),
system_instruments = FALSE,  # System GMM estimator
max_instr_dependent_vars = 99,
min_instr_dependent_vars = 2L,
collapse = FALSE
)
summary(varone)
#Some Diagnostics
Andrews_Lu_MMSC(varone)
stab_varone <- stability(varone)
print(stab_varone)
plot(stab_varone)
#Generating IRFs
varone_oirf <- oirf(varone, n.ahead = 4)
varone_girf <- girf(varone, n.ahead = 4, ma_approx_steps = 4)
varone_bs <- bootstrap_irf(varone, typeof_irf = c("GIRF"), n.ahead = 4, nof_Nstar_draws = 10, confidence.band = 0.95)
plot(varone_girf, varone_bs)```


Here's my monthly data format >>
```Date	Firm	SP	IDV
17/5/2008	1	41.55	78.1671764
17/6/2008	1	41.55	88.71156551
17/7/2008	1	41.55	94.62386639
17/8/2008	1	41.55	90.25628369
17/9/2008	1	41.55	167.8154374
17/10/2008	1	41.55	206.0425319
17/11/2008	1	41.55	143.4637941
17/12/2008	1	41.55	145.8841294
17/1/2009	1	40.56	146.2989599
17/2/2009	1	40.56	147.8324335
17/3/2009	1	40.56	132.3191329
17/4/2009	1	40.56	103.6057804
17/5/2009	1	40.56	103.6464375
17/6/2009	1	40.56	109.9066284
17/7/2009	1	40.56	101.2797006
17/8/2009	1	40.56	98.25295428
17/9/2009	1	40.56	99.4154606
17/10/2009	1	40.56	86.35406984
17/11/2009	1	40.56	99.45631204
17/12/2009	1	40.56	98.41018199
17/1/2010	1	36.17	113.0533892
17/2/2010	1	36.17	111.374998
17/3/2010	1	36.17	107.5623321
17/4/2010	1	36.17	103.8260152
17/5/2010	1	36.17	146.9229145
17/6/2010	1	36.17	134.131418
17/7/2010	1	36.17	141.9443299
17/8/2010	1	36.17	121.069976
17/9/2010	1	36.17	132.6676209
17/10/2010	1	36.17	122.8472654
17/11/2010	1	36.17	127.5586595
17/12/2010	1	36.17	130.4620766
17/1/2011	1	32.73	110.5378187
17/2/2011	1	32.73	93.99837031
17/3/2011	1	32.73	127.251416
17/4/2011	1	32.73	115.8967363
17/5/2011	1	32.73	89.15496195
17/6/2011	1	32.73	117.6272763
17/7/2011	1	32.73	156.7766995
17/8/2011	1	32.73	215.0422942
17/9/2011	1	32.73	190.5246478
17/10/2011	1	32.73	166.4254173
17/11/2011	1	32.73	198.1231932
17/12/2011	1	32.73	182.7998454
17/1/2012	1	31.48	161.9961291
17/2/2012	1	31.48	142.6191284
17/3/2012	1	31.48	134.6995838
17/4/2012	1	31.48	127.5277319
17/5/2012	1	31.48	160.4464483
17/6/2012	1	31.48	189.4425436
17/7/2012	1	31.48	160.2275403
17/8/2012	1	31.48	123.0971093
17/9/2012	1	31.48	152.0809791
17/10/2012	1	31.48	159.5541814
17/11/2012	1	31.48	173.7342532
17/12/2012	1	31.48	168.511748
17/1/2013	1	31.31	167.8918869
17/2/2013	1	31.31	125.5674663
17/3/2013	1	31.31	141.5396622
17/4/2013	1	31.31	133.6297578
17/5/2013	1	31.31	106.2872956
17/6/2013	1	31.31	119.5215531
17/7/2013	1	31.31	108.3500438
17/8/2013	1	31.31	118.5749171
17/9/2013	1	31.31	132.7210016
17/10/2013	1	31.31	158.6930179
17/11/2013	1	31.31	96.36528748
17/12/2013	1	31.31	119.3385261
17/1/2014	1	30.47	111.0462013
17/2/2014	1	30.47	98.21535362
17/3/2014	1	30.47	113.5682659
17/4/2014	1	30.47	101.6973428
17/5/2014	1	30.47	104.1855346
17/6/2014	1	30.47	86.67951839
17/7/2014	1	30.47	93.17936195
17/8/2014	1	30.47	99.6378978
17/9/2014	1	30.47	123.5690457
17/10/2014	1	30.47	119.2752895
17/11/2014	1	30.47	114.062693
17/12/2014	1	30.47	111.5614839
17/1/2015	1	32.18	136.2074457
17/2/2015	1	32.18	113.0624447
17/3/2015	1	32.18	103.9277457
17/4/2015	1	32.18	102.1256079
17/5/2015	1	32.18	106.3849656
17/6/2015	1	32.18	117.341851
17/7/2015	1	32.18	128.4748616
17/8/2015	1	32.18	131.1165349
17/9/2015	1	32.18	174.3628331
17/10/2015	1	32.18	125.1895271
17/11/2015	1	32.18	101.8232681
17/12/2015	1	32.18	113.0718169
17/1/2016	1	34.85	149.5762644
17/2/2016	1	34.85	155.8688966
17/3/2016	1	34.85	166.2577496
17/4/2016	1	34.85	144.6225879
17/5/2016	1	34.85	132.8261068
17/6/2016	1	34.85	243.3254
17/7/2016	1	34.85	236.1954322
17/8/2016	1	34.85	143.8483186
17/9/2016	1	34.85	149.0530404
17/10/2016	1	34.85	134.166564
17/11/2016	1	34.85	251.402222
17/12/2016	1	34.85	222.4529313
17/1/2017	1	33.19	265.8841234
17/2/2017	1	33.19	202.1854423
17/3/2017	1	33.19	235.4675576
17/4/2017	1	33.19	181.3023623
17/5/2017	1	33.19	165.9753869
17/6/2017	1	33.19	169.6574743
17/7/2017	1	33.19	149.1325767
17/8/2017	1	33.19	141.123693
17/9/2017	1	33.19	157.4284091
17/10/2017	1	33.19	150.614683
17/11/2017	1	33.19	155.8565075
17/12/2017	1	33.19	149.5420948
17/1/2018	1	31.37	151.6560698
17/2/2018	1	31.37	124.8380554
17/3/2018	1	31.37	168.4881679
17/4/2018	1	31.37	157.7025835
17/5/2018	1	31.37	175.9046381
17/6/2018	1	31.37	178.3403237
17/7/2018	1	31.37	223.6561374
17/8/2018	1	31.37	180.0526114
17/9/2018	1	31.37	195.988825
17/10/2018	1	31.37	221.7969141
17/11/2018	1	31.37	247.3147665
17/12/2018	1	31.37	270.8802303
17/1/2019	1	33.77	263.3453307
17/2/2019	1	33.77	205.6982687
17/3/2019	1	33.77	250.9757905
17/4/2019	1	33.77	191.5888773
17/5/2019	1	33.77	241.4707898
17/6/2019	1	33.77	316.5279056
17/7/2019	1	33.77	262.0162952
17/8/2019	1	33.77	317.8178408
17/9/2019	1	33.77	273.8698727
17/10/2019	1	33.77	258.4812378
17/11/2019	1	33.77	253.4914123
17/12/2019	1	33.77	266.1575394
17/1/2020	1	45.59	228.0170478
17/2/2020	1	45.59	230.5792029
17/3/2020	1	45.59	356.976704
17/4/2020	1	45.59	359.027983
17/5/2020	1	45.59	431.6293151
17/6/2020	1	45.59	328.6724979
17/7/2020	1	45.59	352.1057149
17/8/2020	1	45.59	301.6853032
17/9/2020	1	45.59	290.0191396
17/10/2020	1	45.59	307.8081476
17/11/2020	1	45.59	368.4571564
17/12/2020	1	45.59	295.6825498
17/1/2021	1	43.73	280.6170065
17/2/2021	1	43.73	215.4135632
17/3/2021	1	43.73	215.2704288
17/4/2021	1	43.73	199.4371476
17/5/2021	1	43.73	190.319996
17/6/2021	1	43.73	178.801245
17/7/2021	1	43.73	205.5256264
17/8/2021	1	43.73	216.4920911
17/9/2021	1	43.73	205.3888224
17/10/2021	1	43.73	195.2901747
17/11/2021	1	43.73	228.0767047
17/12/2021	1	43.73	266.1702001
17/1/2022	1	44.13	232.0608158
17/2/2022	1	44.13	191.9002698
17/3/2022	1	44.13	330.0518633
17/4/2022	1	44.13	303.0238944
17/5/2022	1	44.13	291.2759018
17/6/2022	1	44.13	275.2200013
17/7/2022	1	44.13	317.1823114
17/8/2022	1	44.13	257.1827253
17/9/2022	1	44.13	281.92513
17/10/2022	1	44.13	301.3202716
17/11/2022	1	44.13	332.5035624
17/12/2022	1	44.13	263.563725
17/1/2023	1	45.13	247.3790651
17/2/2023	1	45.13	243.441932
17/3/2023	1	45.13	310.6251426
17/4/2023	1	45.13	231.7783697
17/5/2023	1	45.13	228.3557885
17/5/2008	2	41.55	78.1671764
17/6/2008	2	41.55	88.71156551
17/7/2008	2	41.55	94.62386639
17/8/2008	2	41.55	90.25628369
17/9/2008	2	41.55	167.8154374
17/10/2008	2	41.55	206.0425319
17/11/2008	2	41.55	143.4637941
17/12/2008	2	41.55	145.8841294
17/1/2009	2	40.56	146.2989599
17/2/2009	2	40.56	147.8324335
17/3/2009	2	40.56	132.3191329
17/4/2009	2	40.56	103.6057804
17/5/2009	2	40.56	103.6464375
17/6/2009	2	40.56	109.9066284
17/7/2009	2	40.56	101.2797006
17/8/2009	2	40.56	98.25295428
17/9/2009	2	40.56	99.4154606
17/10/2009	2	40.56	86.35406984
17/11/2009	2	40.56	99.45631204
17/12/2009	2	40.56	98.41018199
17/1/2010	2	36.17	113.0533892
17/2/2010	2	36.17	111.374998
17/3/2010	2	36.17	107.5623321
17/4/2010	2	36.17	103.8260152
17/5/2010	2	36.17	146.9229145
17/6/2010	2	36.17	134.131418
17/7/2010	2	36.17	141.9443299
17/8/2010	2	36.17	121.069976
17/9/2010	2	36.17	132.6676209
17/10/2010	2	36.17	122.8472654
17/11/2010	2	36.17	127.5586595
17/12/2010	2	36.17	130.4620766
17/1/2011	2	32.73	110.5378187
17/2/2011	2	32.73	93.99837031
17/3/2011	2	32.73	127.251416
17/4/2011	2	32.73	115.8967363
17/5/2011	2	32.73	89.15496195
17/6/2011	2	32.73	117.6272763
17/7/2011	2	32.73	156.7766995
17/8/2011	2	32.73	215.0422942
17/9/2011	2	32.73	190.5246478
17/10/2011	2	32.73	166.4254173
17/11/2011	2	32.73	198.1231932
17/12/2011	2	32.73	182.7998454
17/1/2012	2	31.48	161.9961291
17/2/2012	2	31.48	142.6191284
17/3/2012	2	31.48	134.6995838
17/4/2012	2	31.48	127.5277319
17/5/2012	2	31.48	160.4464483
17/6/2012	2	31.48	189.4425436
17/7/2012	2	31.48	160.2275403
17/8/2012	2	31.48	123.0971093
17/9/2012	2	31.48	152.0809791
17/10/2012	2	31.48	159.5541814
17/11/2012	2	31.48	173.7342532
17/12/2012	2	31.48	168.511748
17/1/2013	2	31.31	167.8918869
17/2/2013	2	31.31	125.5674663
17/3/2013	2	31.31	141.5396622
17/4/2013	2	31.31	133.6297578
17/5/2013	2	31.31	106.2872956
17/6/2013	2	31.31	119.5215531
17/7/2013	2	31.31	108.3500438
17/8/2013	2	31.31	118.5749171
17/9/2013	2	31.31	132.7210016
17/10/2013	2	31.31	158.6930179
17/11/2013	2	31.31	96.36528748
17/12/2013	2	31.31	119.3385261
17/1/2014	2	30.47	111.0462013
17/2/2014	2	30.47	98.21535362
17/3/2014	2	30.47	113.5682659
17/4/2014	2	30.47	101.6973428
17/5/2014	2	30.47	104.1855346
17/6/2014	2	30.47	86.67951839
17/7/2014	2	30.47	93.17936195
17/8/2014	2	30.47	99.6378978
17/9/2014	2	30.47	123.5690457
17/10/2014	2	30.47	119.2752895
17/11/2014	2	30.47	114.062693
17/12/2014	2	30.47	111.5614839
17/1/2015	2	32.18	136.2074457
17/2/2015	2	32.18	113.0624447
17/3/2015	2	32.18	103.9277457
17/4/2015	2	32.18	102.1256079
17/5/2015	2	32.18	106.3849656
17/6/2015	2	32.18	117.341851
17/7/2015	2	32.18	128.4748616
17/8/2015	2	32.18	131.1165349
17/9/2015	2	32.18	174.3628331
17/10/2015	2	32.18	125.1895271
17/11/2015	2	32.18	101.8232681
17/12/2015	2	32.18	113.0718169
17/1/2016	2	34.85	149.5762644
17/2/2016	2	34.85	155.8688966
17/3/2016	2	34.85	166.2577496
17/4/2016	2	34.85	144.6225879
17/5/2016	2	34.85	132.8261068
17/6/2016	2	34.85	243.3254
17/7/2016	2	34.85	236.1954322
17/8/2016	2	34.85	143.8483186
17/9/2016	2	34.85	149.0530404
17/10/2016	2	34.85	134.166564
17/11/2016	2	34.85	251.402222
17/12/2016	2	34.85	222.4529313
17/1/2017	2	33.19	265.8841234
17/2/2017	2	33.19	202.1854423
17/3/2017	2	33.19	235.4675576
17/4/2017	2	33.19	181.3023623
17/5/2017	2	33.19	165.9753869
17/6/2017	2	33.19	169.6574743
17/7/2017	2	33.19	149.1325767
17/8/2017	2	33.19	141.123693
17/9/2017	2	33.19	157.4284091
17/10/2017	2	33.19	150.614683
17/11/2017	2	33.19	155.8565075
17/12/2017	2	33.19	149.5420948
17/1/2018	2	31.37	151.6560698
17/2/2018	2	31.37	124.8380554
17/3/2018	2	31.37	168.4881679
17/4/2018	2	31.37	157.7025835
17/5/2018	2	31.37	175.9046381
17/6/2018	2	31.37	178.3403237
17/7/2018	2	31.37	223.6561374
17/8/2018	2	31.37	180.0526114
17/9/2018	2	31.37	195.988825
17/10/2018	2	31.37	221.7969141
17/11/2018	2	31.37	247.3147665
17/12/2018	2	31.37	270.8802303
17/1/2019	2	33.77	263.3453307
17/2/2019	2	33.77	205.6982687
17/3/2019	2	33.77	250.9757905
17/4/2019	2	33.77	191.5888773
17/5/2019	2	33.77	241.4707898
17/6/2019	2	33.77	316.5279056
17/7/2019	2	33.77	262.0162952
17/8/2019	2	33.77	317.8178408
17/9/2019	2	33.77	273.8698727
17/10/2019	2	33.77	258.4812378
17/11/2019	2	33.77	253.4914123
17/12/2019	2	33.77	266.1575394
17/1/2020	2	45.59	228.0170478
17/2/2020	2	45.59	230.5792029
17/3/2020	2	45.59	356.976704
17/4/2020	2	45.59	359.027983
17/5/2020	2	45.59	431.6293151
17/6/2020	2	45.59	328.6724979
17/7/2020	2	45.59	352.1057149
17/8/2020	2	45.59	301.6853032
17/9/2020	2	45.59	290.0191396
17/10/2020	2	45.59	307.8081476
17/11/2020	2	45.59	368.4571564
17/12/2020	2	45.59	295.6825498
17/1/2021	2	43.73	280.6170065
17/2/2021	2	43.73	215.4135632
17/3/2021	2	43.73	215.2704288
17/4/2021	2	43.73	199.4371476
17/5/2021	2	43.73	190.319996
17/6/2021	2	43.73	178.801245
17/7/2021	2	43.73	205.5256264
17/8/2021	2	43.73	216.4920911
17/9/2021	2	43.73	205.3888224
17/10/2021	2	43.73	195.2901747
17/11/2021	2	43.73	228.0767047
17/12/2021	2	43.73	266.1702001
17/1/2022	2	44.13	232.0608158
17/2/2022	2	44.13	191.9002698
17/3/2022	2	44.13	330.0518633
17/4/2022	2	44.13	303.0238944
17/5/2022	2	44.13	291.2759018
17/6/2022	2	44.13	275.2200013
17/7/2022	2	44.13	317.1823114
17/8/2022	2	44.13	257.1827253
17/9/2022	2	44.13	281.92513
17/10/2022	2	44.13	301.3202716
17/11/2022	2	44.13	332.5035624
17/12/2022	2	44.13	263.563725
17/1/2023	2	45.13	247.3790651
17/2/2023	2	45.13	243.441932
17/3/2023	2	45.13	310.6251426
17/4/2023	2	45.13	231.7783697
17/5/2023	2	45.13	228.3557885```

Any assistance with the right code and steps to run a panel VAR using monthly datasets would be appreciated.

Thank you.

Hi @Oluwaseyi1954 ,

Could you also share a data frame or tibble that contains yearly data that you know does work? To do that, you would run

dput(yearly_data)

where yearly_data is a data frame or tibble, and post the output here in a code block.

And it would be helpful if you could do the same with the monthly data that you shared above.