3. 在country列上计算标准误
## Warning: package 'plm' was built under R version 4.0.2
##
## Attaching package: 'plm'
## The following objects are masked from 'package:dplyr':
##
## between, lag, lead
计算的时候删除了income这个数据集中的na值，最终length：679
fix_md <- plm(formula = dem_ind ~ log_gdppc, data = income_dat_no_na, model = 'pooling', index = c('country','year'))
coeftest(fix_md, vcov=vcovHC(fix_md, type='sss', cluster='group'))
##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.367791 0.113850 -12.014 < 2.2e-16 ***
## log_gdppc 0.238269 0.012987 18.347 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
coeftest(fix_md, vcov=vcovHC(fix_md, type='sss', cluster='time'))
##
## t test of coefficients:
##
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.367791 0.130990 -10.442 < 2.2e-16 ***
## log_gdppc 0.238269 0.014471 16.466 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
res <- predict(fix_md, log_gdppc=0.2, interval='confidence')
res
## [1] 0.563185127 0.572021251 0.587574337 0.650140481 0.684205435 0.659928478
## [7] 0.642616847 0.754087297 0.780484325 0.808559684 0.824964433 0.841238752
## [13] 0.792196744 0.749096839 0.833010700 0.842843234 0.876884328 0.920491187
## [19] 0.933292499 0.954865629 0.972052283 0.992661497 1.017753079 0.752968182
## [25] 0.795801317 0.853233848 0.894398649 0.935467786 0.949854721 0.989667040
## [31] 1.003824244 0.269237796 0.271667468 0.314418459 0.336586141 0.369437110
## [37] 0.706608642 0.781134661 0.831649129 0.835523653 0.897949141 0.901629837
## [43] 0.766883838 0.821459842 0.873017757 0.907868250 0.943552683 0.952365401
## [49] 0.990435992 1.002568562 0.299590242 0.273408516 0.278121184 0.315874104
## [55] 0.278116980 0.293307064 0.482086778 0.514285593 0.496238869 0.533642421
## [61] 0.544075868 0.500454808 0.491235459 0.507099170 0.320090498 0.468017059
## [67] 0.572055108 0.615247496 0.680857406 0.700595869 0.483861229 0.527046800
## [73] 0.584638052 0.669362675 0.719661500 0.710953535 0.713530795 0.733632146
## [79] 0.233213425 0.401731590 0.404156718 0.387129240 0.431162725 0.457848904
## [85] 0.522994581 0.473058076 0.425292881 0.835718845 0.878851926 0.908651517
## [91] 0.948033233 0.979490706 1.000104919 1.018375012 1.024655690 0.463530828
## [97] 0.457721655 0.470283239 0.429946355 0.417755499 0.383500239 0.355220713
## [103] 0.299417546 0.599501263 0.614292442 0.651573858 0.618447143 0.680458842
## [109] 0.660942385 0.710834920 0.787691198 0.254998108 0.293956605 0.370605989
## [115] 0.416379954 0.524979561 0.499283430 0.518771256 0.552214391 0.590805569
## [121] 0.626306171 0.628196055 0.658453064 0.683431939 0.273276040 0.265457232
## [127] 0.291009753 0.268645971 0.200967914 0.172927435 0.145178494 0.007958626
## [133] 0.321305618 0.384587428 0.462305709 0.454054139 0.412865251 0.574956627
## [139] 0.591473857 0.618973411 0.653561224 0.680754925 0.643942288 0.658300591
## [145] 0.676999470 0.537736337 0.607627288 0.674335636 0.637308720 0.766523222
## [151] 0.816241471 0.887583296 0.939669751 0.849202534 0.903459505 0.939298682
## [157] 0.947601039 0.970707073 0.994327558 1.012497897 1.031972998 0.403794851
## [163] 0.406634791 0.445382417 0.503788180 0.533187958 0.546958072 0.552243477
## [169] 0.591127101 0.443704426 0.455679866 0.475713162 0.576647684 0.622398926
## [175] 0.604218362 0.594568977 0.601332067 0.403260857 0.489076646 0.520724311
## [181] 0.558528018 0.583644596 0.563291699 0.602336430 0.616659058 0.634390158
## [187] 0.617698870 0.584490124 0.578276479 0.618912058 0.571988757 0.612231226
## [193] 0.641735189 0.627367796 0.651053952 0.672325546 0.757922283 0.807303775
## [199] 0.858217262 0.905641836 0.931932292 0.958548143 0.995107871 0.977025698
## [205] 0.768298809 0.822426485 0.876775257 0.906711415 0.941954564 0.956538735
## [211] 0.992184993 0.993281839 0.328862883 0.334442211 0.356080102 0.331361634
## [217] 0.292979055 0.243904553 0.231531458 0.337307600 0.318861289 0.322358836
## [223] 0.306883463 0.317804095 0.335646652 0.618140835 0.710008934 0.786365984
## [229] 0.836184442 0.867291978 0.859950584 0.869589289 0.879390919 0.481094458
## [235] 0.501530749 0.539185847 0.572376186 0.611819028 0.581809020 0.583177635
## [241] 0.594428320 0.489847301 0.506482464 0.525383693 0.469212637 0.453671708
## [247] 0.509337968 0.260755017 0.258763788 0.303257985 0.270310783 0.243811161
## [253] 0.368932656 0.404584708 0.416445055 0.426089669 0.441390642 0.474470320
## [259] 0.472972523 0.468607634 0.449405551 0.678681892 0.739887602 0.779355439
## [265] 0.805723380 0.817090181 0.791891345 0.780043950 0.842161767 0.847837100
## [271] 0.911186512 0.969262562 0.980916129 1.004115327 0.997661271 0.238595176
## [277] 0.260035148 0.294940972 0.299514005 0.313219245 0.352987936 0.401013197
## [283] 0.440754166 0.262376200 0.251893444 0.298079379 0.361254618 0.430504549
## [289] 0.474245815 0.527730199 0.586250941 0.511964196 0.572088739 0.672085362
## [295] 0.662758419 0.610127516 0.633050629 0.601277077 0.662218062 0.667994514
## [301] 0.705022793 0.750447958 0.787469193 0.825854954 0.847083373 0.909591574
## [307] 0.956886626 0.686102136 0.752504176 0.797304454 0.849444763 0.858510390
## [313] 0.870153504 0.900485727 0.941016098 0.737970450 0.788320857 0.855739757
## [319] 0.880361424 0.927081127 0.944455246 0.983514521 0.995368506 0.558070374
## [325] 0.600342474 0.606168917 0.573313289 0.562248025 0.614335389 0.596597245
## [331] 0.638837987 0.736230766 0.859504301 0.892248812 0.932991872 0.963376812
## [337] 1.016990718 1.027972361 0.475037376 0.519267530 0.469022558 0.482457052
## [343] 0.611479089 0.633875933 0.573820697 0.593381238 0.238537800 0.231161411
## [349] 0.308900143 0.329082843 0.311469904 0.347149337 0.331885744 0.373968674
## [355] 0.418518202 0.516148437 0.587036935 0.651363669 0.726620919 0.825614543
## [361] 0.899165739 0.248446910 0.290553473 0.351056242 0.342828076 0.353004524
## [367] 0.349475051 0.103462997 0.090579085 0.154576788 0.176851495 0.175451181
## [373] 0.164447838 0.183650261 0.457046323 0.496219554 0.530445274 0.582686588
## [379] 0.655634030 0.682061961 0.725010075 0.793701471 0.273937965 0.218559607
## [385] 0.220110235 0.238314545 0.264489339 0.241907643 0.211056992 0.228406797
## [391] 0.879524076 0.339861342 0.608735042 0.645888299 0.695308420 0.736826794
## [397] 0.801796593 0.856491439 0.607253720 0.650151389 0.685255699 0.722838878
## [403] 0.763072258 0.763648971 0.752866155 0.747649375 0.409803193 0.307016394
## [409] 0.217796450 0.259753040 0.225820335 0.218502913 0.217139751 0.229584538
## [415] 0.248864789 0.242049889 0.278250137 0.297969513 0.329848386 0.808071136
## [421] 0.848321558 0.895053076 0.919905157 0.942010463 0.950583452 0.985635727
## [427] 1.002184541 0.860866326 0.898530854 0.901158332 0.926294451 0.910932921
## [433] 0.941146983 0.941237194 0.958998289 0.529897760 0.597388919 0.607231451
## [439] 0.627158062 0.542936757 0.539076321 0.471364179 0.420728823 0.393701683
## [445] 0.411253384 0.377676183 0.313599290 0.307799888 0.251821525 0.265407696
## [451] 0.232604672 0.780634979 0.821992018 0.853496300 0.905461414 0.950624808
## [457] 0.983419538 0.997160908 1.034274626 0.282679334 0.311843472 0.365751983
## [463] 0.411076598 0.431465057 0.479103229 0.540482884 0.597697045 0.620875566
## [469] 0.677491426 0.698724164 0.661060999 0.689634677 0.582267573 0.549235614
## [475] 0.544962298 0.530269397 0.580617872 0.489222074 0.502926291 0.529670187
## [481] 0.562637954 0.635810128 0.628179695 0.659788503 0.678265831 0.557349823
## [487] 0.611402058 0.646148933 0.677261923 0.656845855 0.629537175 0.582308020
## [493] 0.632644112 0.445001804 0.467093931 0.486326122 0.523018895 0.561789926
## [499] 0.520020234 0.540620813 0.542200527 0.742869561 0.722233760 0.727782526
## [505] 0.751165100 0.571724714 0.639239051 0.716524342 0.756249405 0.802798229
## [511] 0.807192204 0.876208087 0.889747448 0.249443320 0.241130852 0.300185474
## [517] 0.295060495 0.293442153 0.206608935 0.405476478 0.394089113 0.386432775
## [523] 0.368626234 0.373231081 0.375522028 0.367768436 0.330690392 0.374148073
## [529] 0.360998528 0.328657239 0.323507946 0.337719117 0.250032872 0.546653128
## [535] 0.674515830 0.770003500 0.859301383 0.898741952 0.965912715 1.021472404
## [541] 0.659773279 0.701054195 0.737572113 0.759989635 0.772091757 0.768582621
## [547] 0.767124704 0.749219090 0.643618711 0.741036030 0.803644212 0.853711716
## [553] 0.860077606 0.865623418 0.914908791 0.943316362 0.346613412 0.355756070
## [559] 0.383679866 0.398705093 0.416778063 0.472552259 0.497871186 0.545039102
## [565] 0.830743839 0.883289302 0.920613210 0.945414163 0.955483699 0.976040195
## [571] 1.001101102 1.000064017 0.923015728 0.962916214 0.999076015 0.996662362
## [577] 1.018079611 1.027710363 1.055616434 1.040612567 0.358723259 0.444701404
## [583] 0.396782829 0.501530067 0.539079957 0.545297919 0.548796148 0.603895920
## [589] 0.298893777 0.349293266 0.421124661 0.452160164 0.517451496 0.560387226
## [595] 0.653502144 0.733641463 0.251984450 0.304290638 0.357847168 0.313037460
## [601] 0.354490164 0.340332392 0.320283986 0.247977791 0.688152446 0.727082653
## [607] 0.752992269 0.816852497 0.825143037 0.795347763 0.806839768 0.463071025
## [613] 0.502877209 0.584794614 0.629168833 0.651746781 0.658573951 0.684872587
## [619] 0.513703540 0.541627676 0.584545796 0.627893610 0.624095436 0.656161661
## [625] 0.694481525 0.709417450 0.148934403 0.159381030 0.163154550 0.084148662
## [631] 0.174821409 0.188403717 0.226887869 0.818857814 0.846916813 0.871869102
## [637] 0.892270399 0.912230186 0.935587537 0.971038830 0.987232028 0.875548207
## [643] 0.918314991 0.943915799 0.967349046 1.007309747 1.031584660 1.058580442
## [649] 1.075533501 0.699991434 0.686613862 0.710183902 0.724136597 0.774391112
## [655] 0.712772750 0.750547258 0.796096945 0.768790992 0.825157126 0.839000522
## [661] 0.780820173 0.772599619 0.735049843 0.740123923 0.744934640 0.368742009
## [667] 0.346984935 0.350139817 0.329179530 0.298956947 0.283015522 0.229192337
## [673] 0.365019048 0.461030941 0.498333716 0.508900207 0.517811090 0.532954023
## [679] 0.510313928
quantile(res, .95)
## 95%
## 0.9906109
4. 固定效应回归
fix_md4 <- plm(formula = dem_ind ~ log_gdppc, data = income_dat_no_na, model = 'within', index = c('country','year'))
modelsummary(fix_md4)
|
|
Model 1
|
|
log_gdppc
|
0.095
|
|
|
(0.027)
|
|
R2
|
0.020
|
|
R2 Adj.
|
-0.139
|