summary.panelAR: Summary method for fitted objects of class '"panelAR"'
In panelAR: Estimation of Linear AR(1) Panel Data Models with Cross-Sectional Heteroskedasticity and/or Correlation
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
View source: R/summary.panelAR.R
Description
summary method for class "panelAR".
Usage
1
2
3
4
5
6
Arguments
object
an object of class "panelAR".
x
an object of class "summary.panelAR".
digits
integer. the number of significant digits to use when printing.
signif.stars
logical. If TRUE, ‘significance stars’ are printed for each coefficient.
...
further arguments passed to or from other methods.
Value
The function summary.panelAR returns a list of summary statistics from the fitted model in object. The list contains the following components:
call
the matched call.
terms
the terms object used.
coefficients
the named vector of coefficients.
residuals
the residuals.
aliased
named logical vector designating if original coefficients are aliased.
df
vector of the form (k,N-k,k^*), where k is the rank of the model matrix, N-k gives the residual degrees of freedom, and k^* is the number of total coefficients.
rho
autocorrelation parameters. Scalar if "ar1" option was used, vector of length N_p (number of panels) if "psar1" option was used, and NULL if "none" option was used.
Sigma
N_p \times N_p matrix of estimated panel covariances.
r2
R^2 based on quasi-differenced data from the Prais-Winsten regression. Set to NULL if PWLS or Parks-Kmenta procedures are used.
wald
results of Wald test.
vcov
estimated variance-covariance matrix of coefficients.
na.action
information passed on from obj about the handling of NAs.
panelStructure
a list of several objects which contain information on the panel structure of the data. See details below.
Contents of panelStructure:
N
number of observations.
N.panel
number of panels.
N.time
number of times.
balanced
logical indicating whether panels are balanced.
N.min
minimum number of observations per panel.
N.max
maximum number of observations per panel.
N.avg
average number of observations per panel.
N.per.panel
named vector giving number of observations per panel.
Author(s)
Konstantin Kashin kkashin@fas.harvard.edu
See Also
The function panelAR. Function coef will extract the table of coefficients, standard errors, t-statistics, and p-values.
Examples
1
2
3
4
5
6
7
8
9
10
11
data(WhittenWilliams)
# expect warning urging to use 'complete.case=FALSE'
out <- panelAR(milex_gdp~lag_milex_gdp+GOV_rl+gthreat+GOV_min+GOV_npty+election_yr+
lag_real_GDP_gr+cinclag+lag_alliance+lag_cinc_ratio+lag_us_change_milex_gdp,
data=WhittenWilliams, panelVar="ccode", timeVar="year", autoCorr="psar1",
panelCorrMethod="pcse", complete.case=TRUE)
summary(out)
summary(out)$rho # psar1 coefficients
summary(out)$Sigma # panel covariances
summary(out)$wald # results of Wald test
Example output
The following units have non-consecutive observations. Use runs.analysis() on output for additional details: 235.
Warning message:
The number of time periods used for the calculation of correlated SEs / PCSEs (18) is less than half the average number of time periods per panel (40.84). Consider setting complete.case=FALSE.
Panel Regression with AR(1) Prais-Winsten correction and panel-corrected standard errors
Unbalanced Panel Design:
Total obs.: 776 Avg obs. per panel 40.8421
Number of panels: 19 Max obs. per panel 46
Number of times: 46 Min obs. per panel 19
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.1215313 0.0885570 1.372 0.1704
lag_milex_gdp 0.9317542 0.0183304 50.831 <2e-16 ***
GOV_rl -0.0016167 0.0008436 -1.916 0.0557 .
gthreat 0.0053543 0.0028483 1.880 0.0605 .
GOV_min 0.0363388 0.0317194 1.146 0.2523
GOV_npty 0.0087735 0.0110240 0.796 0.4264
election_yr 0.0085757 0.0264547 0.324 0.7459
lag_real_GDP_gr 0.6103200 0.5452297 1.119 0.2633
cinclag 1.3712229 2.2334560 0.614 0.5394
lag_alliance 0.0194962 0.0357330 0.546 0.5855
lag_cinc_ratio -0.0313205 0.0658145 -0.476 0.6343
lag_us_change_milex_gdp 0.0580540 0.0270741 2.144 0.0323 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
R-squared: 0.9238
Wald statistic: 5671.9587, Pr(>Chisq(11)): 0
20 200 205 210 211 220
0.15750269 0.15528457 -0.05497798 0.14284367 0.29303502 0.12308926
225 230 235 305 325 350
0.05500530 0.05912737 0.16965981 0.17480153 0.20243282 0.26654458
375 380 385 390 640 900
0.11134871 0.08130810 -0.14279187 -0.44085962 0.11414091 -0.11631097
920
0.17101495
20 200 205 210 211
20 0.0146408346 -0.003510656 0.003224284 0.005131330 -0.001851672
200 -0.0035106563 0.277740081 0.075533004 0.071767585 0.055120723
205 0.0032242841 0.075533004 0.051243228 0.046114179 0.058663010
210 0.0051313303 0.071767585 0.046114179 0.122585531 0.102079318
211 -0.0018516721 0.055120723 0.058663010 0.102079318 0.203611859
220 -0.0015894912 0.124206077 0.069406726 0.129817086 0.172117422
225 -0.0040660636 0.027730695 0.023223833 0.072559767 0.071270233
230 0.0090318930 0.016661465 0.018557557 0.026435517 0.048186963
235 -0.0026105807 0.010266131 0.017407309 0.012421870 0.047316105
305 -0.0017560340 0.019344190 0.026457867 0.043963479 0.060241589
325 0.0040114422 0.029071661 0.023729351 0.041870880 0.056729417
350 0.0022202145 -0.008678822 -0.012935961 0.006562278 0.013575749
375 0.0035243020 0.055348922 0.026490230 0.035673265 0.030219449
380 0.0012703618 0.153440225 0.064775757 0.125953058 0.082502648
385 0.0142983079 0.101427964 0.045104862 0.090721453 0.082405014
390 -0.0133052044 0.040984766 0.034836766 0.043834525 0.099386969
640 0.0089927779 -0.105471215 -0.021312412 -0.011204056 0.052329986
900 0.0031631302 0.035029211 0.001464241 0.017533744 -0.003095081
920 -0.0003015568 0.018224250 0.013144776 0.040838557 0.036682812
220 225 230 235 305
20 -0.001589491 -0.0040660636 9.031893e-03 -0.002610581 -0.001756034
200 0.124206077 0.0277306953 1.666146e-02 0.010266131 0.019344190
205 0.069406726 0.0232238332 1.855756e-02 0.017407309 0.026457867
210 0.129817086 0.0725597673 2.643552e-02 0.012421870 0.043963479
211 0.172117422 0.0712702326 4.818696e-02 0.047316105 0.060241589
220 0.234533513 0.1058714158 4.574369e-02 0.047322177 0.056841968
225 0.105871416 0.1176971283 1.917363e-02 0.046853031 0.041811980
230 0.045743687 0.0191736329 3.135784e-02 0.019674801 0.011733857
235 0.047322177 0.0468530307 1.967480e-02 0.056193515 0.022525765
305 0.056841968 0.0418119800 1.173386e-02 0.022525765 0.036585382
325 0.045266864 0.0411564211 2.395379e-02 0.036843261 0.032263103
350 -0.014160891 0.0418038794 2.367902e-06 0.031690398 0.020387748
375 0.044878006 0.0372102044 7.496605e-03 0.021551232 0.023060203
380 0.125197654 0.0832326952 1.344036e-02 0.025541471 0.064718438
385 0.100191517 0.0685253858 3.779440e-02 0.024628291 0.033597336
390 0.087481012 0.0791289657 3.259515e-02 0.066389057 0.028013857
640 -0.019154756 0.0003732709 1.431447e-02 0.018355756 0.013883786
900 0.013770692 0.0239867431 -1.908608e-03 0.004621613 0.009651126
920 0.056034974 0.0509860491 1.115415e-02 0.027187152 0.029700739
325 350 375 380 385 390
20 0.004011442 2.220214e-03 0.003524302 0.001270362 0.01429831 -0.013305204
200 0.029071661 -8.678822e-03 0.055348922 0.153440225 0.10142796 0.040984766
205 0.023729351 -1.293596e-02 0.026490230 0.064775757 0.04510486 0.034836766
210 0.041870880 6.562278e-03 0.035673265 0.125953058 0.09072145 0.043834525
211 0.056729417 1.357575e-02 0.030219449 0.082502648 0.08240501 0.099386969
220 0.045266864 -1.416089e-02 0.044878006 0.125197654 0.10019152 0.087481012
225 0.041156421 4.180388e-02 0.037210204 0.083232695 0.06852539 0.079128966
230 0.023953792 2.367902e-06 0.007496605 0.013440361 0.03779440 0.032595150
235 0.036843261 3.169040e-02 0.021551232 0.025541471 0.02462829 0.066389057
305 0.032263103 2.038775e-02 0.023060203 0.064718438 0.03359734 0.028013857
325 0.053817597 5.226807e-02 0.030882439 0.060068304 0.06071072 0.053986404
350 0.052268066 2.507889e-01 0.043997391 0.041750332 0.06679550 0.079074104
375 0.030882439 4.399739e-02 0.050950550 0.070255536 0.05674053 0.021742808
380 0.060068304 4.175033e-02 0.070255536 0.248709024 0.09253996 0.003523275
385 0.060710719 6.679550e-02 0.056740526 0.092539964 0.16656716 0.081000058
390 0.053986404 7.907410e-02 0.021742808 0.003523275 0.08100006 0.217980620
640 0.026210673 8.569859e-02 0.009199285 -0.037859800 -0.02735984 0.032337400
900 0.014487379 2.174867e-02 0.015240850 0.034399859 0.02463698 0.015089194
920 0.033373038 3.029833e-02 0.018143112 0.062780160 0.02455000 0.014704447
640 900 920
20 0.0089927779 0.003163130 -0.0003015568
200 -0.1054712151 0.035029211 0.0182242495
205 -0.0213124125 0.001464241 0.0131447761
210 -0.0112040556 0.017533744 0.0408385569
211 0.0523299856 -0.003095081 0.0366828118
220 -0.0191547563 0.013770692 0.0560349743
225 0.0003732709 0.023986743 0.0509860491
230 0.0143144721 -0.001908608 0.0111541484
235 0.0183557562 0.004621613 0.0271871517
305 0.0138837858 0.009651126 0.0297007388
325 0.0262106734 0.014487379 0.0333730377
350 0.0856985921 0.021748665 0.0302983327
375 0.0091992853 0.015240850 0.0181431124
380 -0.0378597997 0.034399859 0.0627801596
385 -0.0273598361 0.024636977 0.0245500046
390 0.0323374000 0.015089194 0.0147044472
640 0.1679038586 0.006169823 0.0038244428
900 0.0061698231 0.060051726 0.0079325725
920 0.0038244428 0.007932572 0.0480651336
value df Pr(>Chisq)
5671.959 11.000 0.000
panelAR documentation built on May 1, 2019, 8:19 p.m.
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Description Usage Arguments Value Author(s) See Also Examples
View source: R/summary.panelAR.R
Description
summary method for class "panelAR".
Usage
1 2 3 4 5 6 |
Arguments
object |
an object of class |
x |
an object of class |
digits |
integer. the number of significant digits to use when printing. |
signif.stars |
logical. If |
... |
further arguments passed to or from other methods. |
Value
The function summary.panelAR returns a list of summary statistics from the fitted model in object. The list contains the following components:
call |
the matched call. |
terms |
the terms object used. |
coefficients |
the named vector of coefficients. |
residuals |
the residuals. |
aliased |
named logical vector designating if original coefficients are aliased. |
df |
vector of the form (k,N-k,k^*), where k is the rank of the model matrix, N-k gives the residual degrees of freedom, and k^* is the number of total coefficients. |
rho |
autocorrelation parameters. Scalar if |
Sigma |
N_p \times N_p matrix of estimated panel covariances. |
r2 |
R^2 based on quasi-differenced data from the Prais-Winsten regression. Set to |
wald |
results of Wald test. |
vcov |
estimated variance-covariance matrix of coefficients. |
na.action |
information passed on from |
panelStructure |
a list of several objects which contain information on the panel structure of the data. See details below. |
Contents of panelStructure:
N |
number of observations. |
N.panel |
number of panels. |
N.time |
number of times. |
balanced |
logical indicating whether panels are balanced. |
N.min |
minimum number of observations per panel. |
N.max |
maximum number of observations per panel. |
N.avg |
average number of observations per panel. |
N.per.panel |
named vector giving number of observations per panel. |
Author(s)
Konstantin Kashin kkashin@fas.harvard.edu
See Also
The function panelAR. Function coef will extract the table of coefficients, standard errors, t-statistics, and p-values.
Examples
1 2 3 4 5 6 7 8 9 10 11 | data(WhittenWilliams)
# expect warning urging to use 'complete.case=FALSE'
out <- panelAR(milex_gdp~lag_milex_gdp+GOV_rl+gthreat+GOV_min+GOV_npty+election_yr+
lag_real_GDP_gr+cinclag+lag_alliance+lag_cinc_ratio+lag_us_change_milex_gdp,
data=WhittenWilliams, panelVar="ccode", timeVar="year", autoCorr="psar1",
panelCorrMethod="pcse", complete.case=TRUE)
summary(out)
summary(out)$rho # psar1 coefficients
summary(out)$Sigma # panel covariances
summary(out)$wald # results of Wald test
|
Example output
The following units have non-consecutive observations. Use runs.analysis() on output for additional details: 235.
Warning message:
The number of time periods used for the calculation of correlated SEs / PCSEs (18) is less than half the average number of time periods per panel (40.84). Consider setting complete.case=FALSE.
Panel Regression with AR(1) Prais-Winsten correction and panel-corrected standard errors
Unbalanced Panel Design:
Total obs.: 776 Avg obs. per panel 40.8421
Number of panels: 19 Max obs. per panel 46
Number of times: 46 Min obs. per panel 19
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.1215313 0.0885570 1.372 0.1704
lag_milex_gdp 0.9317542 0.0183304 50.831 <2e-16 ***
GOV_rl -0.0016167 0.0008436 -1.916 0.0557 .
gthreat 0.0053543 0.0028483 1.880 0.0605 .
GOV_min 0.0363388 0.0317194 1.146 0.2523
GOV_npty 0.0087735 0.0110240 0.796 0.4264
election_yr 0.0085757 0.0264547 0.324 0.7459
lag_real_GDP_gr 0.6103200 0.5452297 1.119 0.2633
cinclag 1.3712229 2.2334560 0.614 0.5394
lag_alliance 0.0194962 0.0357330 0.546 0.5855
lag_cinc_ratio -0.0313205 0.0658145 -0.476 0.6343
lag_us_change_milex_gdp 0.0580540 0.0270741 2.144 0.0323 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
R-squared: 0.9238
Wald statistic: 5671.9587, Pr(>Chisq(11)): 0
20 200 205 210 211 220
0.15750269 0.15528457 -0.05497798 0.14284367 0.29303502 0.12308926
225 230 235 305 325 350
0.05500530 0.05912737 0.16965981 0.17480153 0.20243282 0.26654458
375 380 385 390 640 900
0.11134871 0.08130810 -0.14279187 -0.44085962 0.11414091 -0.11631097
920
0.17101495
20 200 205 210 211
20 0.0146408346 -0.003510656 0.003224284 0.005131330 -0.001851672
200 -0.0035106563 0.277740081 0.075533004 0.071767585 0.055120723
205 0.0032242841 0.075533004 0.051243228 0.046114179 0.058663010
210 0.0051313303 0.071767585 0.046114179 0.122585531 0.102079318
211 -0.0018516721 0.055120723 0.058663010 0.102079318 0.203611859
220 -0.0015894912 0.124206077 0.069406726 0.129817086 0.172117422
225 -0.0040660636 0.027730695 0.023223833 0.072559767 0.071270233
230 0.0090318930 0.016661465 0.018557557 0.026435517 0.048186963
235 -0.0026105807 0.010266131 0.017407309 0.012421870 0.047316105
305 -0.0017560340 0.019344190 0.026457867 0.043963479 0.060241589
325 0.0040114422 0.029071661 0.023729351 0.041870880 0.056729417
350 0.0022202145 -0.008678822 -0.012935961 0.006562278 0.013575749
375 0.0035243020 0.055348922 0.026490230 0.035673265 0.030219449
380 0.0012703618 0.153440225 0.064775757 0.125953058 0.082502648
385 0.0142983079 0.101427964 0.045104862 0.090721453 0.082405014
390 -0.0133052044 0.040984766 0.034836766 0.043834525 0.099386969
640 0.0089927779 -0.105471215 -0.021312412 -0.011204056 0.052329986
900 0.0031631302 0.035029211 0.001464241 0.017533744 -0.003095081
920 -0.0003015568 0.018224250 0.013144776 0.040838557 0.036682812
220 225 230 235 305
20 -0.001589491 -0.0040660636 9.031893e-03 -0.002610581 -0.001756034
200 0.124206077 0.0277306953 1.666146e-02 0.010266131 0.019344190
205 0.069406726 0.0232238332 1.855756e-02 0.017407309 0.026457867
210 0.129817086 0.0725597673 2.643552e-02 0.012421870 0.043963479
211 0.172117422 0.0712702326 4.818696e-02 0.047316105 0.060241589
220 0.234533513 0.1058714158 4.574369e-02 0.047322177 0.056841968
225 0.105871416 0.1176971283 1.917363e-02 0.046853031 0.041811980
230 0.045743687 0.0191736329 3.135784e-02 0.019674801 0.011733857
235 0.047322177 0.0468530307 1.967480e-02 0.056193515 0.022525765
305 0.056841968 0.0418119800 1.173386e-02 0.022525765 0.036585382
325 0.045266864 0.0411564211 2.395379e-02 0.036843261 0.032263103
350 -0.014160891 0.0418038794 2.367902e-06 0.031690398 0.020387748
375 0.044878006 0.0372102044 7.496605e-03 0.021551232 0.023060203
380 0.125197654 0.0832326952 1.344036e-02 0.025541471 0.064718438
385 0.100191517 0.0685253858 3.779440e-02 0.024628291 0.033597336
390 0.087481012 0.0791289657 3.259515e-02 0.066389057 0.028013857
640 -0.019154756 0.0003732709 1.431447e-02 0.018355756 0.013883786
900 0.013770692 0.0239867431 -1.908608e-03 0.004621613 0.009651126
920 0.056034974 0.0509860491 1.115415e-02 0.027187152 0.029700739
325 350 375 380 385 390
20 0.004011442 2.220214e-03 0.003524302 0.001270362 0.01429831 -0.013305204
200 0.029071661 -8.678822e-03 0.055348922 0.153440225 0.10142796 0.040984766
205 0.023729351 -1.293596e-02 0.026490230 0.064775757 0.04510486 0.034836766
210 0.041870880 6.562278e-03 0.035673265 0.125953058 0.09072145 0.043834525
211 0.056729417 1.357575e-02 0.030219449 0.082502648 0.08240501 0.099386969
220 0.045266864 -1.416089e-02 0.044878006 0.125197654 0.10019152 0.087481012
225 0.041156421 4.180388e-02 0.037210204 0.083232695 0.06852539 0.079128966
230 0.023953792 2.367902e-06 0.007496605 0.013440361 0.03779440 0.032595150
235 0.036843261 3.169040e-02 0.021551232 0.025541471 0.02462829 0.066389057
305 0.032263103 2.038775e-02 0.023060203 0.064718438 0.03359734 0.028013857
325 0.053817597 5.226807e-02 0.030882439 0.060068304 0.06071072 0.053986404
350 0.052268066 2.507889e-01 0.043997391 0.041750332 0.06679550 0.079074104
375 0.030882439 4.399739e-02 0.050950550 0.070255536 0.05674053 0.021742808
380 0.060068304 4.175033e-02 0.070255536 0.248709024 0.09253996 0.003523275
385 0.060710719 6.679550e-02 0.056740526 0.092539964 0.16656716 0.081000058
390 0.053986404 7.907410e-02 0.021742808 0.003523275 0.08100006 0.217980620
640 0.026210673 8.569859e-02 0.009199285 -0.037859800 -0.02735984 0.032337400
900 0.014487379 2.174867e-02 0.015240850 0.034399859 0.02463698 0.015089194
920 0.033373038 3.029833e-02 0.018143112 0.062780160 0.02455000 0.014704447
640 900 920
20 0.0089927779 0.003163130 -0.0003015568
200 -0.1054712151 0.035029211 0.0182242495
205 -0.0213124125 0.001464241 0.0131447761
210 -0.0112040556 0.017533744 0.0408385569
211 0.0523299856 -0.003095081 0.0366828118
220 -0.0191547563 0.013770692 0.0560349743
225 0.0003732709 0.023986743 0.0509860491
230 0.0143144721 -0.001908608 0.0111541484
235 0.0183557562 0.004621613 0.0271871517
305 0.0138837858 0.009651126 0.0297007388
325 0.0262106734 0.014487379 0.0333730377
350 0.0856985921 0.021748665 0.0302983327
375 0.0091992853 0.015240850 0.0181431124
380 -0.0378597997 0.034399859 0.0627801596
385 -0.0273598361 0.024636977 0.0245500046
390 0.0323374000 0.015089194 0.0147044472
640 0.1679038586 0.006169823 0.0038244428
900 0.0061698231 0.060051726 0.0079325725
920 0.0038244428 0.007932572 0.0480651336
value df Pr(>Chisq)
5671.959 11.000 0.000
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