PMG: PMG
In PooledMeanGroup: Pooled Mean Group Estimation of Dynamic Heterogenous Panels
Description
Usage
Arguments
Details
Value
Author(s)
References
Examples
Description
Having particular long-run parameters (exp. start values) estimates parameters of short-run relationships as well as standard errors of estimations, Student's t-distribution type statistics, probs, confidence intervals. Also performs diagnostic tests of error terms, such as autocorrelation, heteroscedasticity and normality
Usage
1
PMG(paramTeta, vecSR, vecLR, dataset, quantity, const)
Arguments
paramTeta
the vector of parameters of long-run relationships, as outlined in Equation 7 (Pesaran, Shin and Smith, 1999)
vecSR
a list of vectors containing the column numbers of variables in short-run relationships for each group (alternatively a list of vectors containing the variables names instead of column numbers). In each vector of the list the first number must indicate dy (i.e., the dependant variable)
vecLR
a vector containing the column numbers of variables in long-run relationships (alternatively a vector containing the variables names instead of column numbers). The first number must indicate ly (i.e., the lagged dependant variable)
dataset
a panel data set in the form of stacked time series, containing variables of long-run and short-run relationships (i.e., including differentiated and lagged variables)
quantity
a vector of the number of time series observations in each group; in practice, it takes the form c(T1,...,Tn) since the PMG allows the numbers of time series observations to differ freely across groups (if the number of time series observations in each group is the same, then c(T,...,T) and T=T1=T2=...=Tn
const
logical. If TRUE (the default value), the intercept term is added to the model (i.e., to the short-run relationship)
Details
Having particular long-run parameters estimates parameters of short-run relationships. Also estimates the information matrix as well as standard errors of estimations, as indicated in Equation 13 (Pesaran, Shin and Smith, 1999). Calculates Student's t-distribution type statistics, probs and confidence intervals. Also performs diagnostic tests of error terms, such as the Breusch-Godfrey autocorrelation test, the Goldfeld-Quandt heteroscedasticity test and the Conover nonparametric test of homogeneity of variance and the Jarque-Bera normality test
Value
$LogL
the concentrated log-likelihood function
$LR
parameters of long-run relationships
$SR
the estimated parameters of short-run relationships
$DiagTests
results of diagnostic tests
$residuals
residuals
Author(s)
Lech Kujawski, Piotr Zientara
References
Pesaran, Shin and Smith (1999) <doi:10.1080/01621459.1999.10474156>
Examples
1
2
3
4
5
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8
9
10
11
12
13
14
15
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17
18
19
20
21
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# first import DataExp, i=1...9, T1=T2=...T9=35
data(DataExp)
DataExp[1:5,]
# then prepare lags and diffs using LagPanel and DiffPanel
y10=data.frame(y10=DataExp[,1], row.names=row.names(DataExp))
cpi=data.frame(cpi=DataExp[,7], row.names=row.names(DataExp))
dy10=DiffPanel(variable=y10, quantity=rep(35,9))
dopeness=DiffPanel(variable=DataExp[,6], quantity=rep(35,9))
ly10=LagPanel(variable=y10, quantity=rep(35,9))
diip=DiffPanel(variable=DataExp[,11], quantity=rep(35,9))
dcrisk=DiffPanel(variable=DataExp[,9], quantity=rep(35,9))
ldcrisk=LagPanel(variable=dcrisk, quantity=rep(35,9))
dcpi=DiffPanel(variable=DataExp[,7], quantity=rep(35,9))
ddcpi=DiffPanel(variable=dcpi, quantity=rep(35,9))
ldebt=LagPanel(variable=DataExp[,4], quantity=rep(35,9))
# create homogenous preliminary dataset (containing "NA" as a result of DiffPanel, LagPanel)
dataPanel=cbind(y10, dy10, ly10, DataExp[,6], dopeness, diip,
DataExp[,11], ldcrisk, DataExp[,9], ddcpi, DataExp[,7])
dataPanel=data.frame(dataPanel)
names(dataPanel)=c("y10", "dy10", "ly10", "openess", "dopeness", "diip",
"iip", "ldcrisk", "crisk", "ddcpi", "cpi")
dataPanel[1:5,]
# prepare dataset and quantity for PMG or optimPMG functions using PanelNaOmit
dataPanel=PanelNaOmit(dataset=dataPanel, quantity=rep(35,9))
dataPanel$dataset[1:5,]
dataPanel$quantity
# PMG
PmgExp=PMG(
paramTeta=c(-14.22768, -23.84427, -0.75717, 27.57753),
vecSR=list(SR1=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR2=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR3=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR4=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR5=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR6=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR7=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR8=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR9=c("dy10","dopeness","diip","ldcrisk","ddcpi")),
vecLR=c("ly10","openess","iip","crisk","cpi"),
dataset=dataPanel$dataset,
quantity=dataPanel$quantity,
const=TRUE)
PmgExp
Example output
y10 y10spread riskavers debt deficit openess cpi growth
i=1,t=1,2005q2 4.91 1.78 0.4907953 0.478 -0.0446 0.749 1.001360 0.006
i=1,t=2,2005q3 4.57 1.50 0.5888259 0.468 -0.0436 0.754 0.999384 0.016
i=1,t=3,2005q4 5.16 1.82 0.4938176 0.471 -0.0487 0.776 1.003080 0.012
i=1,t=4,2006q1 4.79 1.15 0.7014965 0.490 -0.0215 0.804 1.002830 0.016
i=1,t=5,2006q2 5.55 1.59 0.6218348 0.494 -0.0430 0.819 1.011460 0.017
crisk urate iip iipnetto cagdp caresvs cds
i=1,t=1,2005q2 74.76667 0.1830 1.079462 0.4271757 -0.018 -0.04051902 16.21965
i=1,t=2,2005q3 74.80000 0.1773 1.093086 0.4364869 -0.028 -0.04921230 15.82511
i=1,t=3,2005q4 76.00000 0.1740 1.117122 0.4430011 -0.027 -0.03684523 16.41765
i=1,t=4,2006q1 76.86667 0.1793 1.113280 0.4436238 -0.036 -0.07054284 17.54188
i=1,t=5,2006q2 76.33333 0.1653 1.085001 0.4320550 -0.035 -0.06876323 23.02218
bidask
i=1,t=1,2005q2 0.000245231
i=1,t=2,2005q3 0.000252121
i=1,t=3,2005q4 0.000385385
i=1,t=4,2006q1 0.000323231
i=1,t=5,2006q2 0.000337833
y10 dy10 ly10 openess dopeness diip iip
i=1,t=1,2005q2 4.91 NA NA 0.749 NA NA 1.079462
i=1,t=2,2005q3 4.57 -0.34 4.91 0.754 0.005 0.013623126 1.093086
i=1,t=3,2005q4 5.16 0.59 4.57 0.776 0.022 0.024036799 1.117122
i=1,t=4,2006q1 4.79 -0.37 5.16 0.804 0.028 -0.003842008 1.113280
i=1,t=5,2006q2 5.55 0.76 4.79 0.819 0.015 -0.028278985 1.085001
ldcrisk crisk ddcpi cpi
i=1,t=1,2005q2 NA 74.76667 NA 1.001360
i=1,t=2,2005q3 NA 74.80000 NA 0.999384
i=1,t=3,2005q4 0.03333333 76.00000 0.005672 1.003080
i=1,t=4,2006q1 1.20000000 76.86667 -0.003946 1.002830
i=1,t=5,2006q2 0.86666667 76.33333 0.008880 1.011460
y10 dy10 ly10 openess dopeness diip iip
i=1,t=3,2005q4 5.16 0.59 4.57 0.776 0.022 0.024036799 1.117122
i=1,t=4,2006q1 4.79 -0.37 5.16 0.804 0.028 -0.003842008 1.113280
i=1,t=5,2006q2 5.55 0.76 4.79 0.819 0.015 -0.028278985 1.085001
i=1,t=6,2006q3 5.48 -0.07 5.55 0.836 0.017 0.020901595 1.105903
i=1,t=7,2006q4 5.14 -0.34 5.48 0.845 0.009 0.057480412 1.163383
ldcrisk crisk ddcpi cpi
i=1,t=3,2005q4 0.03333333 76.00000 0.005672 1.00308
i=1,t=4,2006q1 1.20000000 76.86667 -0.003946 1.00283
i=1,t=5,2006q2 0.86666667 76.33333 0.008880 1.01146
i=1,t=6,2006q3 -0.53333334 77.66667 -0.006170 1.01392
i=1,t=7,2006q4 1.33333334 76.83333 0.000010 1.01639
[1] 33 33 33 33 33 33 33 33 33
$TetaHat
[,1]
openess -14.2276868
iip -23.8442569
crisk -0.7571657
cpi 27.5775415
$LogL
[,1]
[1,] -246.3219
$SR
$SR[[1]]
Coef(i=1) StdErr z P>|z| Low95% High95%
ec1 -0.03252634 0.02202630 -1.4767049 0.13975475 -0.07569708 0.010644406
dopeness 5.78138404 4.10533883 1.4082599 0.15905413 -2.26493221 13.827700285
diip -0.71549189 0.96819510 -0.7389956 0.45990969 -2.61311941 1.182135634
ldcrisk -0.11288715 0.05931873 -1.9030607 0.05703263 -0.22914973 0.003375433
ddcpi 10.25211791 5.61342418 1.8263572 0.06779647 -0.74999132 21.254227137
const 2.42856066 1.61978755 1.4993081 0.13379371 -0.74616461 5.603285921
$SR[[2]]
Coef(i=2) StdErr z P>|z| Low95%
ec2 0.005437189 0.03615875 0.15036993 0.88047277 -0.06543267
dopeness -0.105145585 1.06568474 -0.09866481 0.92140441 -2.19384929
diip 0.524902326 1.84165895 0.28501603 0.77563186 -3.08468288
ldcrisk -0.015035920 0.08619425 -0.17444227 0.86151790 -0.18397354
ddcpi -10.090130161 5.01905900 -2.01036293 0.04439279 -19.92730503
const -0.507045666 3.26266331 -0.15540852 0.87649927 -6.90174826
High95%
ec2 0.07630704
dopeness 1.98355812
diip 4.13448754
ldcrisk 0.15390170
ddcpi -0.25295529
const 5.88765692
$SR[[3]]
Coef(i=3) StdErr z P>|z| Low95% High95%
ec3 -0.02970157 0.03181960 -0.9334363 0.3505947 -0.09206684 0.0326637
dopeness -3.23702475 2.99810181 -1.0796914 0.2802796 -9.11319633 2.6391468
diip 1.60888770 1.98672142 0.8098205 0.4180434 -2.28501474 5.5027901
ldcrisk 0.04882034 0.08410629 0.5804601 0.5616044 -0.11602495 0.2136656
ddcpi 3.76680966 5.69811066 0.6610629 0.5085720 -7.40128202 14.9349013
const 2.63390942 2.84243903 0.9266371 0.3541150 -2.93716871 8.2049876
$SR[[4]]
Coef(i=4) StdErr z P>|z| Low95%
ec4 -0.01226319 0.00770199 -1.59221106 0.11133729 -0.02735882
dopeness -0.77268118 3.38763202 -0.22808888 0.81957715 -7.41231793
diip -0.01801168 0.47559911 -0.03787156 0.96979009 -0.95016881
ldcrisk 0.24045770 0.13079955 1.83836798 0.06600820 -0.01590470
ddcpi 11.39009110 10.45633677 1.08930033 0.27602147 -9.10395237
const 2.20722689 1.33580220 1.65236058 0.09846107 -0.41089731
High95%
ec4 0.002832429
dopeness 5.866955572
diip 0.914145448
ldcrisk 0.496820109
ddcpi 31.884134570
const 4.825351086
$SR[[5]]
Coef(i=5) StdErr z P>|z| Low95%
ec5 -0.108259365 0.02843894 -3.80672995 1.408164e-04 -0.1639987
dopeness 1.062657752 4.92344117 0.21583639 8.291153e-01 -8.5871096
diip 0.094633442 1.46369062 0.06465399 9.484495e-01 -2.7741475
ldcrisk 0.002816518 0.07754721 0.03632005 9.710272e-01 -0.1491732
ddcpi -5.590853908 8.67143722 -0.64474363 5.190933e-01 -22.5865585
const 10.766576320 2.63696920 4.08293593 4.447029e-05 5.5982117
High95%
ec5 -0.05252007
dopeness 10.71242513
diip 2.96341434
ldcrisk 0.15480625
ddcpi 11.40485073
const 15.93494099
$SR[[6]]
Coef(i=6) StdErr z P>|z| Low95% High95%
ec6 -0.6613952 0.1085914 -6.0906800 1.124321e-09 -0.87423041 -0.4485601
dopeness 3.5861939 2.8373974 1.2639026 2.062650e-01 -1.97500289 9.1473906
diip 9.5282520 4.2552124 2.2391954 2.514321e-02 1.18818890 17.8683151
ldcrisk 0.3823820 0.1656203 2.3087875 2.095538e-02 0.05777225 0.7069918
ddcpi -7.9951316 11.4489855 -0.6983266 4.849729e-01 -30.43473082 14.4444676
const 53.7561478 9.3244703 5.7650618 8.162792e-09 35.48052175 72.0317738
$SR[[7]]
Coef(i=7) StdErr z P>|z| Low95% High95%
ec7 -0.1194340 0.03979717 -3.0010686 0.002690339 -0.1974351 -0.04143302
dopeness 5.3567722 3.61597827 1.4814171 0.138495448 -1.7304150 12.44395939
diip 2.3326909 2.37340456 0.9828459 0.325683291 -2.3190965 6.98447837
ldcrisk -0.2740191 0.11969589 -2.2892944 0.022062252 -0.5086188 -0.03941950
ddcpi -9.1485306 7.02294579 -1.3026629 0.192689890 -22.9132514 4.61619023
const 7.4784115 2.74365737 2.7257090 0.006416355 2.1009419 12.85588112
$SR[[8]]
Coef(i=8) StdErr z P>|z| Low95% High95%
ec8 -0.02511281 0.02059799 -1.21918716 0.2227732 -0.06548413 0.01525852
dopeness -1.29529955 1.46579894 -0.88368160 0.3768681 -4.16821269 1.57761358
diip 0.01370873 1.18972883 0.01152257 0.9908065 -2.31811692 2.34553439
ldcrisk -0.04158099 0.09265288 -0.44878250 0.6535886 -0.22317729 0.14001531
ddcpi 3.57092373 9.91379967 0.36019729 0.7186996 -15.85976658 23.00161404
const 2.63783938 2.14298476 1.23091840 0.2183534 -1.56233357 6.83801234
$SR[[9]]
Coef(i=9) StdErr z P>|z| Low95% High95%
ec9 0.004225582 0.04286380 0.09858160 0.92147048 -0.07978592 0.08823708
dopeness -1.467376672 2.90674128 -0.50481847 0.61368634 -7.16448488 4.22973154
diip -1.286021984 2.04436897 -0.62905571 0.52931258 -5.29291154 2.72086757
ldcrisk 0.128452004 0.07472079 1.71909329 0.08559739 -0.01799805 0.27490206
ddcpi 10.996486203 5.83318488 1.88515990 0.05940825 -0.43634607 22.42931848
const -0.261810126 3.88473417 -0.06739461 0.94626756 -7.87574919 7.35212894
$LR
Coef StdErr z P>|z| Low95% High95%
openess -14.2276868 1.8946444 -7.509423 5.928591e-14 -17.941122 -10.5142521
iip -23.8442569 3.7437265 -6.369124 1.901113e-10 -31.181826 -16.5066877
crisk -0.7571657 0.1489207 -5.084354 3.688789e-07 -1.049045 -0.4652864
cpi 27.5775415 3.6967195 7.460004 8.659740e-14 20.332104 34.8229786
$varianceLR
varianceLR
sigma2_1 0.1004212
sigma2_2 0.3128378
sigma2_3 0.1938468
sigma2_4 0.7153513
sigma2_5 0.4984649
sigma2_6 0.6005677
sigma2_7 0.2654734
sigma2_8 0.2048989
sigma2_9 0.3469451
$DiagTests
R^2 Rbar^2 statJB probJB statGQ probGQ
i=1 0.30080873 0.17132887 0.71304687 7.001061e-01 1.171859 0.405067885
i=2 0.11834715 -0.04492189 173.18230048 0.000000e+00 3.298567 0.031333751
i=3 0.09058000 -0.07783111 1.24067668 5.377625e-01 2.437156 0.085821599
i=4 0.20357786 0.05609228 51.82312262 5.581535e-12 3.450052 0.026927735
i=5 0.55013675 0.46682874 0.03905221 9.806633e-01 1.583563 0.238588798
i=6 0.78296300 0.74277096 0.82874269 6.607555e-01 1.210711 0.385312261
i=7 0.45998100 0.35997748 1.59648200 4.501200e-01 1.424954 0.292270389
i=8 0.08191096 -0.08810553 2.81556454 2.446853e-01 2.072518 0.130634368
i=9 0.21505444 0.06969415 2.14641478 3.419101e-01 9.256365 0.000729432
statCON probCON statBG(F) probBG(F) statBG(Chi^2) probBG(Chi^2)
i=1 0.1003408 0.951067335 0.04856333 0.99503572 0.1942533 0.995577781
i=2 3.1754160 0.204393548 0.10580401 0.97857084 0.4232160 0.980532389
i=3 7.7181030 0.021087992 0.50897063 0.73014723 2.0358825 0.729159016
i=4 7.1914359 0.027440974 0.31071881 0.86604347 1.2428752 0.870990298
i=5 4.4001322 0.110795835 0.35108588 0.83897625 1.4043435 0.843439744
i=6 5.8912389 0.052569485 1.67433801 0.21153807 6.6973520 0.152772624
i=7 3.9016396 0.142157481 0.17147570 0.94938200 0.6859028 0.953055945
i=8 1.3961242 0.497548578 0.37641830 0.82167870 1.5056732 0.825636060
i=9 11.9132322 0.002588657 3.48987941 0.03547412 13.9595176 0.007425386
$residuals
$residuals[[1]]
[,1]
i=1,t=3,2005q4 0.34318799
i=1,t=4,2006q1 -0.39040385
i=1,t=5,2006q2 0.58024560
i=1,t=6,2006q3 -0.15044804
i=1,t=7,2006q4 -0.17693140
i=1,t=8,2007q1 -0.11127398
i=1,t=9,2007q2 0.30474011
i=1,t=10,2007q3 0.30858057
i=1,t=11,2007q4 0.01052413
i=1,t=12,2008q1 0.14234326
i=1,t=13,2008q2 0.54540510
i=1,t=14,2008q3 -0.20241243
i=1,t=15,2008q4 -0.32335051
i=1,t=16,2009q1 0.14299006
i=1,t=17,2009q2 -0.36639809
i=1,t=18,2009q3 0.02550577
i=1,t=19,2009q4 0.21071934
i=1,t=20,2010q1 -0.31833941
i=1,t=21,2010q2 0.03916352
i=1,t=22,2010q3 -0.26555045
i=1,t=23,2010q4 0.57088633
i=1,t=24,2011q1 0.34986766
i=1,t=25,2011q2 -0.29012180
i=1,t=26,2011q3 -0.16939729
i=1,t=27,2011q4 -0.32368532
i=1,t=28,2012q1 -0.43015726
i=1,t=29,2012q2 -0.03391340
i=1,t=30,2012q3 0.11646633
i=1,t=31,2012q4 -0.69875743
i=1,t=32,2013q1 0.16561437
i=1,t=33,2013q2 -0.11225242
i=1,t=34,2013q3 0.46980465
i=1,t=35,2013q4 0.03734827
$residuals[[2]]
[,1]
i=2,t=3,2005q4 0.26138865
i=2,t=4,2006q1 0.53256070
i=2,t=5,2006q2 0.13915663
i=2,t=6,2006q3 -0.27397762
i=2,t=7,2006q4 0.19196392
i=2,t=8,2007q1 0.10095362
i=2,t=9,2007q2 0.05159307
i=2,t=10,2007q3 0.23508923
i=2,t=11,2007q4 0.53021755
i=2,t=12,2008q1 -0.22562190
i=2,t=13,2008q2 0.01823014
i=2,t=14,2008q3 -0.04268973
i=2,t=15,2008q4 2.51773446
i=2,t=16,2009q1 -0.10327599
i=2,t=17,2009q2 -0.48045625
i=2,t=18,2009q3 -0.04024964
i=2,t=19,2009q4 -0.65808288
i=2,t=20,2010q1 -0.61946228
i=2,t=21,2010q2 0.34593949
i=2,t=22,2010q3 -0.36476064
i=2,t=23,2010q4 0.11771760
i=2,t=24,2011q1 -0.26445693
i=2,t=25,2011q2 -0.15142630
i=2,t=26,2011q3 -0.27630002
i=2,t=27,2011q4 0.21920098
i=2,t=28,2012q1 -0.14452805
i=2,t=29,2012q2 -0.11795164
i=2,t=30,2012q3 -1.09601074
i=2,t=31,2012q4 -0.36964876
i=2,t=32,2013q1 0.03445875
i=2,t=33,2013q2 -0.36273376
i=2,t=34,2013q3 0.20371566
i=2,t=35,2013q4 0.09171267
$residuals[[3]]
[,1]
i=3,t=3,2005q4 0.276955545
i=3,t=4,2006q1 0.003448038
i=3,t=5,2006q2 0.458122322
i=3,t=6,2006q3 -0.066495935
i=3,t=7,2006q4 -0.030285866
i=3,t=8,2007q1 0.064869727
i=3,t=9,2007q2 0.586401081
i=3,t=10,2007q3 0.117059983
i=3,t=11,2007q4 0.127007830
i=3,t=12,2008q1 -0.108117520
i=3,t=13,2008q2 0.433678987
i=3,t=14,2008q3 -0.749972764
i=3,t=15,2008q4 -0.112923799
i=3,t=16,2009q1 0.344958286
i=3,t=17,2009q2 0.157437738
i=3,t=18,2009q3 -0.473204490
i=3,t=19,2009q4 -1.109710253
i=3,t=20,2010q1 0.016619395
i=3,t=21,2010q2 0.461717253
i=3,t=22,2010q3 -0.733644621
i=3,t=23,2010q4 0.731807083
i=3,t=24,2011q1 0.397476286
i=3,t=25,2011q2 -0.231406166
i=3,t=26,2011q3 -0.555446057
i=3,t=27,2011q4 0.761239923
i=3,t=28,2012q1 -0.016923204
i=3,t=29,2012q2 -0.264596303
i=3,t=30,2012q3 -0.631509256
i=3,t=31,2012q4 -0.458512121
i=3,t=32,2013q1 0.002687766
i=3,t=33,2013q2 0.301876523
i=3,t=34,2013q3 0.424372472
i=3,t=35,2013q4 -0.124987883
$residuals[[4]]
[,1]
i=4,t=3,2005q4 0.43935264
i=4,t=4,2006q1 -0.12766495
i=4,t=5,2006q2 -0.34599199
i=4,t=6,2006q3 -0.25197505
i=4,t=7,2006q4 -1.10731699
i=4,t=8,2007q1 -0.08081344
i=4,t=9,2007q2 -0.21543978
i=4,t=10,2007q3 0.20625856
i=4,t=11,2007q4 -0.08834087
i=4,t=12,2008q1 1.21362874
i=4,t=13,2008q2 -0.11845457
i=4,t=14,2008q3 -0.15021415
i=4,t=15,2008q4 0.45466207
i=4,t=16,2009q1 3.34018215
i=4,t=17,2009q2 -1.21198077
i=4,t=18,2009q3 -1.40543744
i=4,t=19,2009q4 0.07392225
i=4,t=20,2010q1 -0.68005390
i=4,t=21,2010q2 0.98032989
i=4,t=22,2010q3 -0.63419611
i=4,t=23,2010q4 0.77739716
i=4,t=24,2011q1 -0.84405256
i=4,t=25,2011q2 -0.14103940
i=4,t=26,2011q3 0.81084432
i=4,t=27,2011q4 0.38926662
i=4,t=28,2012q1 0.18548943
i=4,t=29,2012q2 0.50767513
i=4,t=30,2012q3 -0.31297389
i=4,t=31,2012q4 -0.79634884
i=4,t=32,2013q1 -0.22473153
i=4,t=33,2013q2 -0.09128784
i=4,t=34,2013q3 0.14646990
i=4,t=35,2013q4 -0.69716481
$residuals[[5]]
[,1]
i=5,t=3,2005q4 -0.64994135
i=5,t=4,2006q1 -0.44099117
i=5,t=5,2006q2 0.19730730
i=5,t=6,2006q3 0.17460610
i=5,t=7,2006q4 0.55312482
i=5,t=8,2007q1 0.04272689
i=5,t=9,2007q2 -0.01656275
i=5,t=10,2007q3 -0.82797701
i=5,t=11,2007q4 -0.54883445
i=5,t=12,2008q1 -0.63591564
i=5,t=13,2008q2 0.03651006
i=5,t=14,2008q3 -0.50075411
i=5,t=15,2008q4 1.46557325
i=5,t=16,2009q1 1.01796971
i=5,t=17,2009q2 0.12552291
i=5,t=18,2009q3 0.54728173
i=5,t=19,2009q4 1.30248503
i=5,t=20,2010q1 -1.71752717
i=5,t=21,2010q2 0.82109882
i=5,t=22,2010q3 0.91352391
i=5,t=23,2010q4 -0.66249426
i=5,t=24,2011q1 0.21056548
i=5,t=25,2011q2 0.30030223
i=5,t=26,2011q3 0.39885162
i=5,t=27,2011q4 0.88444112
i=5,t=28,2012q1 -0.31322945
i=5,t=29,2012q2 0.11167875
i=5,t=30,2012q3 -1.32508096
i=5,t=31,2012q4 -0.80688351
i=5,t=32,2013q1 -0.22970922
i=5,t=33,2013q2 -0.18465771
i=5,t=34,2013q3 -0.05597284
i=5,t=35,2013q4 -0.18703813
$residuals[[6]]
[,1]
i=6,t=3,2005q4 -0.55088917
i=6,t=4,2006q1 -0.35655758
i=6,t=5,2006q2 -0.05284711
i=6,t=6,2006q3 -0.72217947
i=6,t=7,2006q4 0.33862052
i=6,t=8,2007q1 -0.05693838
i=6,t=9,2007q2 0.70685034
i=6,t=10,2007q3 0.45337900
i=6,t=11,2007q4 0.14107193
i=6,t=12,2008q1 -0.72138380
i=6,t=13,2008q2 0.24619768
i=6,t=14,2008q3 -1.71421889
i=6,t=15,2008q4 0.80542653
i=6,t=16,2009q1 0.83113196
i=6,t=17,2009q2 -0.17449362
i=6,t=18,2009q3 1.40851813
i=6,t=19,2009q4 -0.78530805
i=6,t=20,2010q1 -1.62770671
i=6,t=21,2010q2 0.24957011
i=6,t=22,2010q3 0.79799246
i=6,t=23,2010q4 1.19529811
i=6,t=24,2011q1 0.68736316
i=6,t=25,2011q2 -0.02226580
i=6,t=26,2011q3 -0.01515000
i=6,t=27,2011q4 -0.07359208
i=6,t=28,2012q1 -1.14961842
i=6,t=29,2012q2 -1.41740665
i=6,t=30,2012q3 0.34972343
i=6,t=31,2012q4 0.03926224
i=6,t=32,2013q1 1.33751501
i=6,t=33,2013q2 -0.05408450
i=6,t=34,2013q3 0.06307727
i=6,t=35,2013q4 -0.15635768
$residuals[[7]]
[,1]
i=7,t=3,2005q4 0.289479122
i=7,t=4,2006q1 -0.070631391
i=7,t=5,2006q2 0.218489225
i=7,t=6,2006q3 0.708758769
i=7,t=7,2006q4 0.499107343
i=7,t=8,2007q1 0.435613887
i=7,t=9,2007q2 -0.109365749
i=7,t=10,2007q3 -0.090849112
i=7,t=11,2007q4 0.061391892
i=7,t=12,2008q1 -0.382107671
i=7,t=13,2008q2 -0.904481694
i=7,t=14,2008q3 0.423753216
i=7,t=15,2008q4 -0.225348730
i=7,t=16,2009q1 -0.049477237
i=7,t=17,2009q2 1.107869816
i=7,t=18,2009q3 0.135919662
i=7,t=19,2009q4 -1.435359896
i=7,t=20,2010q1 -0.794224277
i=7,t=21,2010q2 0.023576791
i=7,t=22,2010q3 0.570590416
i=7,t=23,2010q4 -0.724639217
i=7,t=24,2011q1 0.490994720
i=7,t=25,2011q2 0.644891716
i=7,t=26,2011q3 -0.059141595
i=7,t=27,2011q4 0.526304188
i=7,t=28,2012q1 -0.481274030
i=7,t=29,2012q2 0.230084295
i=7,t=30,2012q3 -0.101528295
i=7,t=31,2012q4 0.111774165
i=7,t=32,2013q1 -0.339677651
i=7,t=33,2013q2 -0.183466890
i=7,t=34,2013q3 -0.529171193
i=7,t=35,2013q4 0.002145407
$residuals[[8]]
[,1]
i=8,t=3,2005q4 0.30641464
i=8,t=4,2006q1 0.10477171
i=8,t=5,2006q2 0.52184981
i=8,t=6,2006q3 0.18014686
i=8,t=7,2006q4 -0.70181809
i=8,t=8,2007q1 0.07450210
i=8,t=9,2007q2 0.49279882
i=8,t=10,2007q3 0.07315404
i=8,t=11,2007q4 0.14591303
i=8,t=12,2008q1 -0.09541712
i=8,t=13,2008q2 0.71888473
i=8,t=14,2008q3 0.09620162
i=8,t=15,2008q4 -0.43180102
i=8,t=16,2009q1 -0.31424598
i=8,t=17,2009q2 0.09003529
i=8,t=18,2009q3 -0.35520960
i=8,t=19,2009q4 -0.51105582
i=8,t=20,2010q1 -0.23428657
i=8,t=21,2010q2 -0.22197321
i=8,t=22,2010q3 -0.07536084
i=8,t=23,2010q4 0.53919534
i=8,t=24,2011q1 0.40750974
i=8,t=25,2011q2 0.30621069
i=8,t=26,2011q3 -0.04912912
i=8,t=27,2011q4 0.89660874
i=8,t=28,2012q1 -0.21186319
i=8,t=29,2012q2 -0.05253705
i=8,t=30,2012q3 -0.48319942
i=8,t=31,2012q4 -0.29007343
i=8,t=32,2013q1 0.10533669
i=8,t=33,2013q2 -1.38755332
i=8,t=34,2013q3 0.69609338
i=8,t=35,2013q4 -0.34010344
$residuals[[9]]
[,1]
i=9,t=3,2005q4 -0.03163471
i=9,t=4,2006q1 0.13217613
i=9,t=5,2006q2 -0.27896256
i=9,t=6,2006q3 -0.05130030
i=9,t=7,2006q4 -0.04915137
i=9,t=8,2007q1 0.43231710
i=9,t=9,2007q2 0.04626244
i=9,t=10,2007q3 -0.03751946
i=9,t=11,2007q4 -0.33001572
i=9,t=12,2008q1 -0.13550657
i=9,t=13,2008q2 0.56160695
i=9,t=14,2008q3 -0.22490184
i=9,t=15,2008q4 -0.21373151
i=9,t=16,2009q1 -0.17147760
i=9,t=17,2009q2 -0.12929558
i=9,t=18,2009q3 -0.47632242
i=9,t=19,2009q4 -0.34548272
i=9,t=20,2010q1 0.66412144
i=9,t=21,2010q2 -0.35914367
i=9,t=22,2010q3 0.19937282
i=9,t=23,2010q4 0.31753331
i=9,t=24,2011q1 0.03606496
i=9,t=25,2011q2 -0.49196431
i=9,t=26,2011q3 0.59580936
i=9,t=27,2011q4 1.66144105
i=9,t=28,2012q1 -0.94941794
i=9,t=29,2012q2 0.09683314
i=9,t=30,2012q3 0.80518546
i=9,t=31,2012q4 -1.19511184
i=9,t=32,2013q1 -0.19562919
i=9,t=33,2013q2 1.12549410
i=9,t=34,2013q3 0.31979752
i=9,t=35,2013q4 -1.32744644
PooledMeanGroup documentation built on May 2, 2019, 12:40 p.m.
R Package Documentation
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Description Usage Arguments Details Value Author(s) References Examples
Description
Having particular long-run parameters (exp. start values) estimates parameters of short-run relationships as well as standard errors of estimations, Student's t-distribution type statistics, probs, confidence intervals. Also performs diagnostic tests of error terms, such as autocorrelation, heteroscedasticity and normality
Usage
1 | PMG(paramTeta, vecSR, vecLR, dataset, quantity, const)
|
Arguments
paramTeta |
the vector of parameters of long-run relationships, as outlined in Equation 7 (Pesaran, Shin and Smith, 1999) |
vecSR |
a list of vectors containing the column numbers of variables in short-run relationships for each group (alternatively a list of vectors containing the variables names instead of column numbers). In each vector of the list the first number must indicate dy (i.e., the dependant variable) |
vecLR |
a vector containing the column numbers of variables in long-run relationships (alternatively a vector containing the variables names instead of column numbers). The first number must indicate ly (i.e., the lagged dependant variable) |
dataset |
a panel data set in the form of stacked time series, containing variables of long-run and short-run relationships (i.e., including differentiated and lagged variables) |
quantity |
a vector of the number of time series observations in each group; in practice, it takes the form c(T1,...,Tn) since the PMG allows the numbers of time series observations to differ freely across groups (if the number of time series observations in each group is the same, then c(T,...,T) and T=T1=T2=...=Tn |
const |
logical. If TRUE (the default value), the intercept term is added to the model (i.e., to the short-run relationship) |
Details
Having particular long-run parameters estimates parameters of short-run relationships. Also estimates the information matrix as well as standard errors of estimations, as indicated in Equation 13 (Pesaran, Shin and Smith, 1999). Calculates Student's t-distribution type statistics, probs and confidence intervals. Also performs diagnostic tests of error terms, such as the Breusch-Godfrey autocorrelation test, the Goldfeld-Quandt heteroscedasticity test and the Conover nonparametric test of homogeneity of variance and the Jarque-Bera normality test
Value
$LogL |
the concentrated log-likelihood function |
$LR |
parameters of long-run relationships |
$SR |
the estimated parameters of short-run relationships |
$DiagTests |
results of diagnostic tests |
$residuals |
residuals |
Author(s)
Lech Kujawski, Piotr Zientara
References
Pesaran, Shin and Smith (1999) <doi:10.1080/01621459.1999.10474156>
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | # first import DataExp, i=1...9, T1=T2=...T9=35
data(DataExp)
DataExp[1:5,]
# then prepare lags and diffs using LagPanel and DiffPanel
y10=data.frame(y10=DataExp[,1], row.names=row.names(DataExp))
cpi=data.frame(cpi=DataExp[,7], row.names=row.names(DataExp))
dy10=DiffPanel(variable=y10, quantity=rep(35,9))
dopeness=DiffPanel(variable=DataExp[,6], quantity=rep(35,9))
ly10=LagPanel(variable=y10, quantity=rep(35,9))
diip=DiffPanel(variable=DataExp[,11], quantity=rep(35,9))
dcrisk=DiffPanel(variable=DataExp[,9], quantity=rep(35,9))
ldcrisk=LagPanel(variable=dcrisk, quantity=rep(35,9))
dcpi=DiffPanel(variable=DataExp[,7], quantity=rep(35,9))
ddcpi=DiffPanel(variable=dcpi, quantity=rep(35,9))
ldebt=LagPanel(variable=DataExp[,4], quantity=rep(35,9))
# create homogenous preliminary dataset (containing "NA" as a result of DiffPanel, LagPanel)
dataPanel=cbind(y10, dy10, ly10, DataExp[,6], dopeness, diip,
DataExp[,11], ldcrisk, DataExp[,9], ddcpi, DataExp[,7])
dataPanel=data.frame(dataPanel)
names(dataPanel)=c("y10", "dy10", "ly10", "openess", "dopeness", "diip",
"iip", "ldcrisk", "crisk", "ddcpi", "cpi")
dataPanel[1:5,]
# prepare dataset and quantity for PMG or optimPMG functions using PanelNaOmit
dataPanel=PanelNaOmit(dataset=dataPanel, quantity=rep(35,9))
dataPanel$dataset[1:5,]
dataPanel$quantity
# PMG
PmgExp=PMG(
paramTeta=c(-14.22768, -23.84427, -0.75717, 27.57753),
vecSR=list(SR1=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR2=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR3=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR4=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR5=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR6=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR7=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR8=c("dy10","dopeness","diip","ldcrisk","ddcpi"),
SR9=c("dy10","dopeness","diip","ldcrisk","ddcpi")),
vecLR=c("ly10","openess","iip","crisk","cpi"),
dataset=dataPanel$dataset,
quantity=dataPanel$quantity,
const=TRUE)
PmgExp
|
Example output
y10 y10spread riskavers debt deficit openess cpi growth
i=1,t=1,2005q2 4.91 1.78 0.4907953 0.478 -0.0446 0.749 1.001360 0.006
i=1,t=2,2005q3 4.57 1.50 0.5888259 0.468 -0.0436 0.754 0.999384 0.016
i=1,t=3,2005q4 5.16 1.82 0.4938176 0.471 -0.0487 0.776 1.003080 0.012
i=1,t=4,2006q1 4.79 1.15 0.7014965 0.490 -0.0215 0.804 1.002830 0.016
i=1,t=5,2006q2 5.55 1.59 0.6218348 0.494 -0.0430 0.819 1.011460 0.017
crisk urate iip iipnetto cagdp caresvs cds
i=1,t=1,2005q2 74.76667 0.1830 1.079462 0.4271757 -0.018 -0.04051902 16.21965
i=1,t=2,2005q3 74.80000 0.1773 1.093086 0.4364869 -0.028 -0.04921230 15.82511
i=1,t=3,2005q4 76.00000 0.1740 1.117122 0.4430011 -0.027 -0.03684523 16.41765
i=1,t=4,2006q1 76.86667 0.1793 1.113280 0.4436238 -0.036 -0.07054284 17.54188
i=1,t=5,2006q2 76.33333 0.1653 1.085001 0.4320550 -0.035 -0.06876323 23.02218
bidask
i=1,t=1,2005q2 0.000245231
i=1,t=2,2005q3 0.000252121
i=1,t=3,2005q4 0.000385385
i=1,t=4,2006q1 0.000323231
i=1,t=5,2006q2 0.000337833
y10 dy10 ly10 openess dopeness diip iip
i=1,t=1,2005q2 4.91 NA NA 0.749 NA NA 1.079462
i=1,t=2,2005q3 4.57 -0.34 4.91 0.754 0.005 0.013623126 1.093086
i=1,t=3,2005q4 5.16 0.59 4.57 0.776 0.022 0.024036799 1.117122
i=1,t=4,2006q1 4.79 -0.37 5.16 0.804 0.028 -0.003842008 1.113280
i=1,t=5,2006q2 5.55 0.76 4.79 0.819 0.015 -0.028278985 1.085001
ldcrisk crisk ddcpi cpi
i=1,t=1,2005q2 NA 74.76667 NA 1.001360
i=1,t=2,2005q3 NA 74.80000 NA 0.999384
i=1,t=3,2005q4 0.03333333 76.00000 0.005672 1.003080
i=1,t=4,2006q1 1.20000000 76.86667 -0.003946 1.002830
i=1,t=5,2006q2 0.86666667 76.33333 0.008880 1.011460
y10 dy10 ly10 openess dopeness diip iip
i=1,t=3,2005q4 5.16 0.59 4.57 0.776 0.022 0.024036799 1.117122
i=1,t=4,2006q1 4.79 -0.37 5.16 0.804 0.028 -0.003842008 1.113280
i=1,t=5,2006q2 5.55 0.76 4.79 0.819 0.015 -0.028278985 1.085001
i=1,t=6,2006q3 5.48 -0.07 5.55 0.836 0.017 0.020901595 1.105903
i=1,t=7,2006q4 5.14 -0.34 5.48 0.845 0.009 0.057480412 1.163383
ldcrisk crisk ddcpi cpi
i=1,t=3,2005q4 0.03333333 76.00000 0.005672 1.00308
i=1,t=4,2006q1 1.20000000 76.86667 -0.003946 1.00283
i=1,t=5,2006q2 0.86666667 76.33333 0.008880 1.01146
i=1,t=6,2006q3 -0.53333334 77.66667 -0.006170 1.01392
i=1,t=7,2006q4 1.33333334 76.83333 0.000010 1.01639
[1] 33 33 33 33 33 33 33 33 33
$TetaHat
[,1]
openess -14.2276868
iip -23.8442569
crisk -0.7571657
cpi 27.5775415
$LogL
[,1]
[1,] -246.3219
$SR
$SR[[1]]
Coef(i=1) StdErr z P>|z| Low95% High95%
ec1 -0.03252634 0.02202630 -1.4767049 0.13975475 -0.07569708 0.010644406
dopeness 5.78138404 4.10533883 1.4082599 0.15905413 -2.26493221 13.827700285
diip -0.71549189 0.96819510 -0.7389956 0.45990969 -2.61311941 1.182135634
ldcrisk -0.11288715 0.05931873 -1.9030607 0.05703263 -0.22914973 0.003375433
ddcpi 10.25211791 5.61342418 1.8263572 0.06779647 -0.74999132 21.254227137
const 2.42856066 1.61978755 1.4993081 0.13379371 -0.74616461 5.603285921
$SR[[2]]
Coef(i=2) StdErr z P>|z| Low95%
ec2 0.005437189 0.03615875 0.15036993 0.88047277 -0.06543267
dopeness -0.105145585 1.06568474 -0.09866481 0.92140441 -2.19384929
diip 0.524902326 1.84165895 0.28501603 0.77563186 -3.08468288
ldcrisk -0.015035920 0.08619425 -0.17444227 0.86151790 -0.18397354
ddcpi -10.090130161 5.01905900 -2.01036293 0.04439279 -19.92730503
const -0.507045666 3.26266331 -0.15540852 0.87649927 -6.90174826
High95%
ec2 0.07630704
dopeness 1.98355812
diip 4.13448754
ldcrisk 0.15390170
ddcpi -0.25295529
const 5.88765692
$SR[[3]]
Coef(i=3) StdErr z P>|z| Low95% High95%
ec3 -0.02970157 0.03181960 -0.9334363 0.3505947 -0.09206684 0.0326637
dopeness -3.23702475 2.99810181 -1.0796914 0.2802796 -9.11319633 2.6391468
diip 1.60888770 1.98672142 0.8098205 0.4180434 -2.28501474 5.5027901
ldcrisk 0.04882034 0.08410629 0.5804601 0.5616044 -0.11602495 0.2136656
ddcpi 3.76680966 5.69811066 0.6610629 0.5085720 -7.40128202 14.9349013
const 2.63390942 2.84243903 0.9266371 0.3541150 -2.93716871 8.2049876
$SR[[4]]
Coef(i=4) StdErr z P>|z| Low95%
ec4 -0.01226319 0.00770199 -1.59221106 0.11133729 -0.02735882
dopeness -0.77268118 3.38763202 -0.22808888 0.81957715 -7.41231793
diip -0.01801168 0.47559911 -0.03787156 0.96979009 -0.95016881
ldcrisk 0.24045770 0.13079955 1.83836798 0.06600820 -0.01590470
ddcpi 11.39009110 10.45633677 1.08930033 0.27602147 -9.10395237
const 2.20722689 1.33580220 1.65236058 0.09846107 -0.41089731
High95%
ec4 0.002832429
dopeness 5.866955572
diip 0.914145448
ldcrisk 0.496820109
ddcpi 31.884134570
const 4.825351086
$SR[[5]]
Coef(i=5) StdErr z P>|z| Low95%
ec5 -0.108259365 0.02843894 -3.80672995 1.408164e-04 -0.1639987
dopeness 1.062657752 4.92344117 0.21583639 8.291153e-01 -8.5871096
diip 0.094633442 1.46369062 0.06465399 9.484495e-01 -2.7741475
ldcrisk 0.002816518 0.07754721 0.03632005 9.710272e-01 -0.1491732
ddcpi -5.590853908 8.67143722 -0.64474363 5.190933e-01 -22.5865585
const 10.766576320 2.63696920 4.08293593 4.447029e-05 5.5982117
High95%
ec5 -0.05252007
dopeness 10.71242513
diip 2.96341434
ldcrisk 0.15480625
ddcpi 11.40485073
const 15.93494099
$SR[[6]]
Coef(i=6) StdErr z P>|z| Low95% High95%
ec6 -0.6613952 0.1085914 -6.0906800 1.124321e-09 -0.87423041 -0.4485601
dopeness 3.5861939 2.8373974 1.2639026 2.062650e-01 -1.97500289 9.1473906
diip 9.5282520 4.2552124 2.2391954 2.514321e-02 1.18818890 17.8683151
ldcrisk 0.3823820 0.1656203 2.3087875 2.095538e-02 0.05777225 0.7069918
ddcpi -7.9951316 11.4489855 -0.6983266 4.849729e-01 -30.43473082 14.4444676
const 53.7561478 9.3244703 5.7650618 8.162792e-09 35.48052175 72.0317738
$SR[[7]]
Coef(i=7) StdErr z P>|z| Low95% High95%
ec7 -0.1194340 0.03979717 -3.0010686 0.002690339 -0.1974351 -0.04143302
dopeness 5.3567722 3.61597827 1.4814171 0.138495448 -1.7304150 12.44395939
diip 2.3326909 2.37340456 0.9828459 0.325683291 -2.3190965 6.98447837
ldcrisk -0.2740191 0.11969589 -2.2892944 0.022062252 -0.5086188 -0.03941950
ddcpi -9.1485306 7.02294579 -1.3026629 0.192689890 -22.9132514 4.61619023
const 7.4784115 2.74365737 2.7257090 0.006416355 2.1009419 12.85588112
$SR[[8]]
Coef(i=8) StdErr z P>|z| Low95% High95%
ec8 -0.02511281 0.02059799 -1.21918716 0.2227732 -0.06548413 0.01525852
dopeness -1.29529955 1.46579894 -0.88368160 0.3768681 -4.16821269 1.57761358
diip 0.01370873 1.18972883 0.01152257 0.9908065 -2.31811692 2.34553439
ldcrisk -0.04158099 0.09265288 -0.44878250 0.6535886 -0.22317729 0.14001531
ddcpi 3.57092373 9.91379967 0.36019729 0.7186996 -15.85976658 23.00161404
const 2.63783938 2.14298476 1.23091840 0.2183534 -1.56233357 6.83801234
$SR[[9]]
Coef(i=9) StdErr z P>|z| Low95% High95%
ec9 0.004225582 0.04286380 0.09858160 0.92147048 -0.07978592 0.08823708
dopeness -1.467376672 2.90674128 -0.50481847 0.61368634 -7.16448488 4.22973154
diip -1.286021984 2.04436897 -0.62905571 0.52931258 -5.29291154 2.72086757
ldcrisk 0.128452004 0.07472079 1.71909329 0.08559739 -0.01799805 0.27490206
ddcpi 10.996486203 5.83318488 1.88515990 0.05940825 -0.43634607 22.42931848
const -0.261810126 3.88473417 -0.06739461 0.94626756 -7.87574919 7.35212894
$LR
Coef StdErr z P>|z| Low95% High95%
openess -14.2276868 1.8946444 -7.509423 5.928591e-14 -17.941122 -10.5142521
iip -23.8442569 3.7437265 -6.369124 1.901113e-10 -31.181826 -16.5066877
crisk -0.7571657 0.1489207 -5.084354 3.688789e-07 -1.049045 -0.4652864
cpi 27.5775415 3.6967195 7.460004 8.659740e-14 20.332104 34.8229786
$varianceLR
varianceLR
sigma2_1 0.1004212
sigma2_2 0.3128378
sigma2_3 0.1938468
sigma2_4 0.7153513
sigma2_5 0.4984649
sigma2_6 0.6005677
sigma2_7 0.2654734
sigma2_8 0.2048989
sigma2_9 0.3469451
$DiagTests
R^2 Rbar^2 statJB probJB statGQ probGQ
i=1 0.30080873 0.17132887 0.71304687 7.001061e-01 1.171859 0.405067885
i=2 0.11834715 -0.04492189 173.18230048 0.000000e+00 3.298567 0.031333751
i=3 0.09058000 -0.07783111 1.24067668 5.377625e-01 2.437156 0.085821599
i=4 0.20357786 0.05609228 51.82312262 5.581535e-12 3.450052 0.026927735
i=5 0.55013675 0.46682874 0.03905221 9.806633e-01 1.583563 0.238588798
i=6 0.78296300 0.74277096 0.82874269 6.607555e-01 1.210711 0.385312261
i=7 0.45998100 0.35997748 1.59648200 4.501200e-01 1.424954 0.292270389
i=8 0.08191096 -0.08810553 2.81556454 2.446853e-01 2.072518 0.130634368
i=9 0.21505444 0.06969415 2.14641478 3.419101e-01 9.256365 0.000729432
statCON probCON statBG(F) probBG(F) statBG(Chi^2) probBG(Chi^2)
i=1 0.1003408 0.951067335 0.04856333 0.99503572 0.1942533 0.995577781
i=2 3.1754160 0.204393548 0.10580401 0.97857084 0.4232160 0.980532389
i=3 7.7181030 0.021087992 0.50897063 0.73014723 2.0358825 0.729159016
i=4 7.1914359 0.027440974 0.31071881 0.86604347 1.2428752 0.870990298
i=5 4.4001322 0.110795835 0.35108588 0.83897625 1.4043435 0.843439744
i=6 5.8912389 0.052569485 1.67433801 0.21153807 6.6973520 0.152772624
i=7 3.9016396 0.142157481 0.17147570 0.94938200 0.6859028 0.953055945
i=8 1.3961242 0.497548578 0.37641830 0.82167870 1.5056732 0.825636060
i=9 11.9132322 0.002588657 3.48987941 0.03547412 13.9595176 0.007425386
$residuals
$residuals[[1]]
[,1]
i=1,t=3,2005q4 0.34318799
i=1,t=4,2006q1 -0.39040385
i=1,t=5,2006q2 0.58024560
i=1,t=6,2006q3 -0.15044804
i=1,t=7,2006q4 -0.17693140
i=1,t=8,2007q1 -0.11127398
i=1,t=9,2007q2 0.30474011
i=1,t=10,2007q3 0.30858057
i=1,t=11,2007q4 0.01052413
i=1,t=12,2008q1 0.14234326
i=1,t=13,2008q2 0.54540510
i=1,t=14,2008q3 -0.20241243
i=1,t=15,2008q4 -0.32335051
i=1,t=16,2009q1 0.14299006
i=1,t=17,2009q2 -0.36639809
i=1,t=18,2009q3 0.02550577
i=1,t=19,2009q4 0.21071934
i=1,t=20,2010q1 -0.31833941
i=1,t=21,2010q2 0.03916352
i=1,t=22,2010q3 -0.26555045
i=1,t=23,2010q4 0.57088633
i=1,t=24,2011q1 0.34986766
i=1,t=25,2011q2 -0.29012180
i=1,t=26,2011q3 -0.16939729
i=1,t=27,2011q4 -0.32368532
i=1,t=28,2012q1 -0.43015726
i=1,t=29,2012q2 -0.03391340
i=1,t=30,2012q3 0.11646633
i=1,t=31,2012q4 -0.69875743
i=1,t=32,2013q1 0.16561437
i=1,t=33,2013q2 -0.11225242
i=1,t=34,2013q3 0.46980465
i=1,t=35,2013q4 0.03734827
$residuals[[2]]
[,1]
i=2,t=3,2005q4 0.26138865
i=2,t=4,2006q1 0.53256070
i=2,t=5,2006q2 0.13915663
i=2,t=6,2006q3 -0.27397762
i=2,t=7,2006q4 0.19196392
i=2,t=8,2007q1 0.10095362
i=2,t=9,2007q2 0.05159307
i=2,t=10,2007q3 0.23508923
i=2,t=11,2007q4 0.53021755
i=2,t=12,2008q1 -0.22562190
i=2,t=13,2008q2 0.01823014
i=2,t=14,2008q3 -0.04268973
i=2,t=15,2008q4 2.51773446
i=2,t=16,2009q1 -0.10327599
i=2,t=17,2009q2 -0.48045625
i=2,t=18,2009q3 -0.04024964
i=2,t=19,2009q4 -0.65808288
i=2,t=20,2010q1 -0.61946228
i=2,t=21,2010q2 0.34593949
i=2,t=22,2010q3 -0.36476064
i=2,t=23,2010q4 0.11771760
i=2,t=24,2011q1 -0.26445693
i=2,t=25,2011q2 -0.15142630
i=2,t=26,2011q3 -0.27630002
i=2,t=27,2011q4 0.21920098
i=2,t=28,2012q1 -0.14452805
i=2,t=29,2012q2 -0.11795164
i=2,t=30,2012q3 -1.09601074
i=2,t=31,2012q4 -0.36964876
i=2,t=32,2013q1 0.03445875
i=2,t=33,2013q2 -0.36273376
i=2,t=34,2013q3 0.20371566
i=2,t=35,2013q4 0.09171267
$residuals[[3]]
[,1]
i=3,t=3,2005q4 0.276955545
i=3,t=4,2006q1 0.003448038
i=3,t=5,2006q2 0.458122322
i=3,t=6,2006q3 -0.066495935
i=3,t=7,2006q4 -0.030285866
i=3,t=8,2007q1 0.064869727
i=3,t=9,2007q2 0.586401081
i=3,t=10,2007q3 0.117059983
i=3,t=11,2007q4 0.127007830
i=3,t=12,2008q1 -0.108117520
i=3,t=13,2008q2 0.433678987
i=3,t=14,2008q3 -0.749972764
i=3,t=15,2008q4 -0.112923799
i=3,t=16,2009q1 0.344958286
i=3,t=17,2009q2 0.157437738
i=3,t=18,2009q3 -0.473204490
i=3,t=19,2009q4 -1.109710253
i=3,t=20,2010q1 0.016619395
i=3,t=21,2010q2 0.461717253
i=3,t=22,2010q3 -0.733644621
i=3,t=23,2010q4 0.731807083
i=3,t=24,2011q1 0.397476286
i=3,t=25,2011q2 -0.231406166
i=3,t=26,2011q3 -0.555446057
i=3,t=27,2011q4 0.761239923
i=3,t=28,2012q1 -0.016923204
i=3,t=29,2012q2 -0.264596303
i=3,t=30,2012q3 -0.631509256
i=3,t=31,2012q4 -0.458512121
i=3,t=32,2013q1 0.002687766
i=3,t=33,2013q2 0.301876523
i=3,t=34,2013q3 0.424372472
i=3,t=35,2013q4 -0.124987883
$residuals[[4]]
[,1]
i=4,t=3,2005q4 0.43935264
i=4,t=4,2006q1 -0.12766495
i=4,t=5,2006q2 -0.34599199
i=4,t=6,2006q3 -0.25197505
i=4,t=7,2006q4 -1.10731699
i=4,t=8,2007q1 -0.08081344
i=4,t=9,2007q2 -0.21543978
i=4,t=10,2007q3 0.20625856
i=4,t=11,2007q4 -0.08834087
i=4,t=12,2008q1 1.21362874
i=4,t=13,2008q2 -0.11845457
i=4,t=14,2008q3 -0.15021415
i=4,t=15,2008q4 0.45466207
i=4,t=16,2009q1 3.34018215
i=4,t=17,2009q2 -1.21198077
i=4,t=18,2009q3 -1.40543744
i=4,t=19,2009q4 0.07392225
i=4,t=20,2010q1 -0.68005390
i=4,t=21,2010q2 0.98032989
i=4,t=22,2010q3 -0.63419611
i=4,t=23,2010q4 0.77739716
i=4,t=24,2011q1 -0.84405256
i=4,t=25,2011q2 -0.14103940
i=4,t=26,2011q3 0.81084432
i=4,t=27,2011q4 0.38926662
i=4,t=28,2012q1 0.18548943
i=4,t=29,2012q2 0.50767513
i=4,t=30,2012q3 -0.31297389
i=4,t=31,2012q4 -0.79634884
i=4,t=32,2013q1 -0.22473153
i=4,t=33,2013q2 -0.09128784
i=4,t=34,2013q3 0.14646990
i=4,t=35,2013q4 -0.69716481
$residuals[[5]]
[,1]
i=5,t=3,2005q4 -0.64994135
i=5,t=4,2006q1 -0.44099117
i=5,t=5,2006q2 0.19730730
i=5,t=6,2006q3 0.17460610
i=5,t=7,2006q4 0.55312482
i=5,t=8,2007q1 0.04272689
i=5,t=9,2007q2 -0.01656275
i=5,t=10,2007q3 -0.82797701
i=5,t=11,2007q4 -0.54883445
i=5,t=12,2008q1 -0.63591564
i=5,t=13,2008q2 0.03651006
i=5,t=14,2008q3 -0.50075411
i=5,t=15,2008q4 1.46557325
i=5,t=16,2009q1 1.01796971
i=5,t=17,2009q2 0.12552291
i=5,t=18,2009q3 0.54728173
i=5,t=19,2009q4 1.30248503
i=5,t=20,2010q1 -1.71752717
i=5,t=21,2010q2 0.82109882
i=5,t=22,2010q3 0.91352391
i=5,t=23,2010q4 -0.66249426
i=5,t=24,2011q1 0.21056548
i=5,t=25,2011q2 0.30030223
i=5,t=26,2011q3 0.39885162
i=5,t=27,2011q4 0.88444112
i=5,t=28,2012q1 -0.31322945
i=5,t=29,2012q2 0.11167875
i=5,t=30,2012q3 -1.32508096
i=5,t=31,2012q4 -0.80688351
i=5,t=32,2013q1 -0.22970922
i=5,t=33,2013q2 -0.18465771
i=5,t=34,2013q3 -0.05597284
i=5,t=35,2013q4 -0.18703813
$residuals[[6]]
[,1]
i=6,t=3,2005q4 -0.55088917
i=6,t=4,2006q1 -0.35655758
i=6,t=5,2006q2 -0.05284711
i=6,t=6,2006q3 -0.72217947
i=6,t=7,2006q4 0.33862052
i=6,t=8,2007q1 -0.05693838
i=6,t=9,2007q2 0.70685034
i=6,t=10,2007q3 0.45337900
i=6,t=11,2007q4 0.14107193
i=6,t=12,2008q1 -0.72138380
i=6,t=13,2008q2 0.24619768
i=6,t=14,2008q3 -1.71421889
i=6,t=15,2008q4 0.80542653
i=6,t=16,2009q1 0.83113196
i=6,t=17,2009q2 -0.17449362
i=6,t=18,2009q3 1.40851813
i=6,t=19,2009q4 -0.78530805
i=6,t=20,2010q1 -1.62770671
i=6,t=21,2010q2 0.24957011
i=6,t=22,2010q3 0.79799246
i=6,t=23,2010q4 1.19529811
i=6,t=24,2011q1 0.68736316
i=6,t=25,2011q2 -0.02226580
i=6,t=26,2011q3 -0.01515000
i=6,t=27,2011q4 -0.07359208
i=6,t=28,2012q1 -1.14961842
i=6,t=29,2012q2 -1.41740665
i=6,t=30,2012q3 0.34972343
i=6,t=31,2012q4 0.03926224
i=6,t=32,2013q1 1.33751501
i=6,t=33,2013q2 -0.05408450
i=6,t=34,2013q3 0.06307727
i=6,t=35,2013q4 -0.15635768
$residuals[[7]]
[,1]
i=7,t=3,2005q4 0.289479122
i=7,t=4,2006q1 -0.070631391
i=7,t=5,2006q2 0.218489225
i=7,t=6,2006q3 0.708758769
i=7,t=7,2006q4 0.499107343
i=7,t=8,2007q1 0.435613887
i=7,t=9,2007q2 -0.109365749
i=7,t=10,2007q3 -0.090849112
i=7,t=11,2007q4 0.061391892
i=7,t=12,2008q1 -0.382107671
i=7,t=13,2008q2 -0.904481694
i=7,t=14,2008q3 0.423753216
i=7,t=15,2008q4 -0.225348730
i=7,t=16,2009q1 -0.049477237
i=7,t=17,2009q2 1.107869816
i=7,t=18,2009q3 0.135919662
i=7,t=19,2009q4 -1.435359896
i=7,t=20,2010q1 -0.794224277
i=7,t=21,2010q2 0.023576791
i=7,t=22,2010q3 0.570590416
i=7,t=23,2010q4 -0.724639217
i=7,t=24,2011q1 0.490994720
i=7,t=25,2011q2 0.644891716
i=7,t=26,2011q3 -0.059141595
i=7,t=27,2011q4 0.526304188
i=7,t=28,2012q1 -0.481274030
i=7,t=29,2012q2 0.230084295
i=7,t=30,2012q3 -0.101528295
i=7,t=31,2012q4 0.111774165
i=7,t=32,2013q1 -0.339677651
i=7,t=33,2013q2 -0.183466890
i=7,t=34,2013q3 -0.529171193
i=7,t=35,2013q4 0.002145407
$residuals[[8]]
[,1]
i=8,t=3,2005q4 0.30641464
i=8,t=4,2006q1 0.10477171
i=8,t=5,2006q2 0.52184981
i=8,t=6,2006q3 0.18014686
i=8,t=7,2006q4 -0.70181809
i=8,t=8,2007q1 0.07450210
i=8,t=9,2007q2 0.49279882
i=8,t=10,2007q3 0.07315404
i=8,t=11,2007q4 0.14591303
i=8,t=12,2008q1 -0.09541712
i=8,t=13,2008q2 0.71888473
i=8,t=14,2008q3 0.09620162
i=8,t=15,2008q4 -0.43180102
i=8,t=16,2009q1 -0.31424598
i=8,t=17,2009q2 0.09003529
i=8,t=18,2009q3 -0.35520960
i=8,t=19,2009q4 -0.51105582
i=8,t=20,2010q1 -0.23428657
i=8,t=21,2010q2 -0.22197321
i=8,t=22,2010q3 -0.07536084
i=8,t=23,2010q4 0.53919534
i=8,t=24,2011q1 0.40750974
i=8,t=25,2011q2 0.30621069
i=8,t=26,2011q3 -0.04912912
i=8,t=27,2011q4 0.89660874
i=8,t=28,2012q1 -0.21186319
i=8,t=29,2012q2 -0.05253705
i=8,t=30,2012q3 -0.48319942
i=8,t=31,2012q4 -0.29007343
i=8,t=32,2013q1 0.10533669
i=8,t=33,2013q2 -1.38755332
i=8,t=34,2013q3 0.69609338
i=8,t=35,2013q4 -0.34010344
$residuals[[9]]
[,1]
i=9,t=3,2005q4 -0.03163471
i=9,t=4,2006q1 0.13217613
i=9,t=5,2006q2 -0.27896256
i=9,t=6,2006q3 -0.05130030
i=9,t=7,2006q4 -0.04915137
i=9,t=8,2007q1 0.43231710
i=9,t=9,2007q2 0.04626244
i=9,t=10,2007q3 -0.03751946
i=9,t=11,2007q4 -0.33001572
i=9,t=12,2008q1 -0.13550657
i=9,t=13,2008q2 0.56160695
i=9,t=14,2008q3 -0.22490184
i=9,t=15,2008q4 -0.21373151
i=9,t=16,2009q1 -0.17147760
i=9,t=17,2009q2 -0.12929558
i=9,t=18,2009q3 -0.47632242
i=9,t=19,2009q4 -0.34548272
i=9,t=20,2010q1 0.66412144
i=9,t=21,2010q2 -0.35914367
i=9,t=22,2010q3 0.19937282
i=9,t=23,2010q4 0.31753331
i=9,t=24,2011q1 0.03606496
i=9,t=25,2011q2 -0.49196431
i=9,t=26,2011q3 0.59580936
i=9,t=27,2011q4 1.66144105
i=9,t=28,2012q1 -0.94941794
i=9,t=29,2012q2 0.09683314
i=9,t=30,2012q3 0.80518546
i=9,t=31,2012q4 -1.19511184
i=9,t=32,2013q1 -0.19562919
i=9,t=33,2013q2 1.12549410
i=9,t=34,2013q3 0.31979752
i=9,t=35,2013q4 -1.32744644
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