Hello
I would like to follow the Anderson-Hsiao framework for a panel data analysis. And I am having issues with the steps and coding involved.
I wish to perform a Granger causality test using the Anderson-HSIAO estimates as instruments. My dependent variable is "GDP", my explanatory variables are "pci" and "ForeigndirectinvestmentnetBo". My control variables are the following: "BroadmoneyofGDPFMLBLB" , "Popula" and " External".
I computed the Anderson-Hsiao 2SLS estimator including all of my variables:
I tested for Granger-causality using GDP and pci
Now, what I would like to do is to perform the Granger-causality test on GDP and pci, including my explanatory and control variables in test, and instrumenting with the Anderson-HSIAO 2SLS.estimator.
Can someone assist me with the code for the above?
My data:
I would like to follow the Anderson-Hsiao framework for a panel data analysis. And I am having issues with the steps and coding involved.
I wish to perform a Granger causality test using the Anderson-HSIAO estimates as instruments. My dependent variable is "GDP", my explanatory variables are "pci" and "ForeigndirectinvestmentnetBo". My control variables are the following: "BroadmoneyofGDPFMLBLB" , "Popula" and " External".
I computed the Anderson-Hsiao 2SLS estimator including all of my variables:
Code:
ivregress 2sls diff_GDP diff_pci diff_Foreigni diff_Broadmoney diff_Pop diff_Externald (L.D.GDP=L2.D.GDP),robust cluster(country)
Code:
pvar pci GDP, lags(5) pvargranger
Code:
**Declare panel data
egen country=group(Entity)
list Entity (country) in 1/10, sepby(Entity)
gen year = real(Year)
xtset country
xtset country year,yearly
gen GDP = real(gdp) //destring gdp varaible
gen Popula =real(PopulationgrowthannualSP)
gen External =real(ExternaldebtstockstotalDOD)
**Index
pca rescoups resmaxintensity resongoing resTerrorismfatalitiesGTD20 resconflict respostconflict
rotate
predict pci
**includin zeros in missing cells
foreach x of varlist pci{
replace `x' = 0 if(`x' == .)
}
** First differencing all columns
gen diff_pci = D.pci
gen diff_GDP = D.GDP
gen diff_Foreigni = D.ForeigndirectinvestmentnetBo
gen diff_Broadmoney= D.BroadmoneyofGDPFMLBLB
gen diff_Pop= D.Popula
gen diff_Externald = D.External
**Second lagged deifference of GDP as instrument
ivregress 2sls diff_GDP diff_pci diff_Foreigni diff_Broadmoney diff_Pop diff_Externald (L.D.GDP=L2.D.GDP),robust cluster(country)
Now, what I would like to do is to perform the Granger-causality test on GDP and pci, including my explanatory and control variables in test, and instrumenting with the Anderson-HSIAO 2SLS.estimator.
Can someone assist me with the code for the above?
My data:
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(GDP pci) double ForeigndirectinvestmentnetBo float(Popula External) double BroadmoneyofGDPFMLBLB
4.400002 -.4595704 -3942928.3 2.675145 2.72485e+10 72.796361
.8000006 -.4595704 4353889.3 2.5664566 28153911296 61.77114
-1.2000005 1.466991 38651266 2.460316 28489965568 49.11131
1.8000023 1.466991 . 2.3503273 27351246848 51.941995
-2.1000009 1.466991 . 2.2216294 26274664448 50.101458
-.8999966 3.393549 . 2.0708578 30241927168 45.318672
3.799995 3.393549 . 1.9098215 33051430912 37.169446
4.0999985 3.393549 . 1.753176 33653880832 33.005836
1.0999999 3.3935504 . 1.6152833 30902562816 36.081434
5.100004 3.3935494 . 1.5008857 30692708352 42.376822
3.2000015 3.393549 . 1.4162657 28209283072 42.208981
3.8 1.466991 . 1.358408 25467371520 37.832606
3 1.466991 . 1.3098426 22752567296 56.850473
5.6 1.466991 . 1.2750655 23045429248 62.726626
7.2 1.466991 . 1.2759147 23778635776 62.816935
4.3 1.466991 . 1.3178462 22426644480 59.265476
5.9 1.466991 -1.101e+09 1.3899006 17092404224 53.827594
1.7 1.466991 -1.762e+09 1.471123 5910806016 57.28216
3.4 1.466991 -1.540e+09 1.5513825 6134513152 64.092886
2.4 1.466991 -2.321e+09 1.6361927 6246398976 62.986986
1.6 1.466991 -2.533e+09 1.7220932 7420896256 73.158861
3.6 1.466991 -2.081e+09 1.8050187 7260318208 69.05566
2.9 1.466991 -2.037e+09 1.8833138 6064672256 68.060812
3.4 1.466991 -1.542e+09 1.9514152 5515632128 67.953132
2.8 1.466991 -1.964e+09 2.0027277 5245580800 71.729813
3.8 1.466991 -1.521e+09 2.0335925 5521129472 79.309932
3.7 1.466991 6.389e+08 2.0453873 4671369728 82.001074
3.2 1.466991 -1.592e+09 2.0513546 5463160832 78.884977
.04162146 3.393549 -2.000e+08 3.434427 7288778240 .
-3.450099 3.393549 3.357e+08 3.378481 8591895552 .
.9913593 1.466991 -6.645e+08 3.324456 9000344576 .
-5.838281 3.393549 -2.880e+08 3.280312 10059207680 .
-23.98342 3.393549 -3.021e+08 3.246642 10571384832 .
1.3393635 3.393549 -1.703e+08 3.2261446 11292755968 .
15 1.466991 -4.724e+08 3.216859 11502043136 36.48713
13.54437 1.466991 -1.806e+08 3.214234 10545818624 27.577574
7.274277 1.466991 -4.117e+08 3.21732 9948273664 22.615484
4.6911464 3.393549 -1.114e+09 3.2289414 10784075776 24.437043
2.1814897 3.393549 -2.471e+09 3.249247 10673242112 22.849355
3.054624 3.393549 -8.786e+08 3.2772036 9763465216 17.280556
4.2059984 3.393549 -2.145e+09 3.301198 8776916992 21.135714
13.665687 1.466991 -1.643e+09 3.329257 9109536768 16.049883
2.98985 -.4595705 -3.481e+09 3.378811 9099850752 13.508367
10.952862 1.466991 -1.414e+09 3.453014 9786029056 13.553646
15.028915 -.4595705 1.523e+09 3.537557 12223970304 13.299819
11.547683 -.4595705 2.283e+08 3.6195745 9890493440 16.273326
14.010018 1.466991 1.805e+09 3.6806355 11931686912 20.446871
11.16614 -.4595705 8.907e+08 3.710531 15501571072 31.520504
.8587126 1.466991 -2.199e+09 3.703878 20172423168 45.60817
4.85922 -.4595705 4.568e+09 3.671462 26599589888 34.774751
3.471981 -.4595705 5.116e+09 3.6341586 33964863488 34.978872
8.542148 -.4595705 2.351e+09 3.597774 4.42591e+10 31.517732
4.95459 -.4595705 8.042e+09 3.5519505 5.49465e+10 33.331549
4.822626 -.4595705 -2.771e+09 3.497493 5.69355e+10 35.675553
.9435756 -.4595705 -1.081e+10 3.4388506 56272310272 40.94466
-2.580097 -.4595705 4.525e+08 3.378273 57167384576 39.162307
-2.8541605 -.4595704 -62096190 3.1007655 1070152448 21.740975
8.976134 -.4595704 -62376777 3.235059 1119735936 25.115607
4.2257996 -.4595704 -1.208e+08 3.377159 1149708032 26.467866
2.957711 -.45957035 -77571727 3.479003 1198996352 29.622098
5.836172 -.4595704 -1403787.2 3.500774 1270610560 26.490936
2.0204005 -.4595704 -13648840 3.426061 1382104448 28.441371
6.045198 -.45957035 -13329502 3.293614 1396512512 22.873627
4.324284 -.4595704 -13595869 3.145324 1377641344 23.18018
5.734688 -.4595704 -13876006 3.0283754 1411356800 22.128608
3.961012 -.4595704 -32748440 2.958613 1433932288 19.507034
5.341449 -.4595704 -37820420 2.9517546 1488489216 22.995933
5.859992 -.4595704 -56153557 2.983995 1399684864 26.22559
5.330411 -.4595704 -41553069 3.02378 1470316544 24.597384
4.64447 -.4595704 -12158025 3.043083 1608563072 20.009685
3.444045 -.4595704 -44416700 3.039675 1485978752 22.943317
4.429629 -.4595704 -65154249 3.005342 1612808832 19.179256
1.7115777 -.4595704 -53428819 2.9523835 1551746432 21.128573
3.947014 -.4595704 -54929324 2.897545 648364672 25.330737
5.986516 -.4595704 -2.613e+08 2.8540854 883287872 28.304637
4.889899 -.4595704 -1.738e+08 2.8235555 973593408 31.798127
2.329301 -.4595704 -1.031e+08 2.809302 1309266304 32.73525
2.1101992 -.4595704 -1.947e+08 2.8060865 1581966848 34.882235
2.9627504 -.4595704 -1.014e+08 2.803718 1851264384 35.722533
4.816478 -.4595704 -2.412e+08 2.797649 1675225728 34.007497
7.189716 -.45957035 -3.017e+08 2.790718 2003816448 36.709118
6.351832 -.4595704 -3.879e+08 2.7821815 2041492864 40.952857
2.0958083 -.4595704 -1.170e+08 2.771714 2178021376 42.541423
3.96486 -.4595704 -1.143e+08 2.7614095 2316211200 41.105935
13.059406 -.4595704 -42186013 3.63436 549840384 28.924689
6.772822 -.4595704 -88526216 3.340334 552920448 21.920211
7.458709 -.4595704 16719789 3.0285375 612559232 27.456387
2.9170704 -.4595704 11423290 2.768483 606348608 28.332171
1.916107 -.4595704 2.964e+08 2.5741794 663983872 21.037856
3.627916 -.4595704 23615781 2.4672565 700397760 20.921851
7.03041 -.4595704 -29507180 2.419145 717153216 20.47826
5.8298 -.4595704 -72235497 2.391314 626530368 19.794538
8.325891 -.4595704 -96006497 2.3444872 574727360 22.389681
.4436635 -.4595704 -91820639 2.2719958 532169056 28.263056
9.667241 -.4595704 -35161354 2.161983 510191232 28.50095
1.9876958 -.4595704 -54918579 2.0328965 452434624 24.816209
.25057387 -.4595704 3.490e+08 1.8893803 400352896 39.399228
6.069531 -.4595704 -3.651e+08 1.773421 491350080 45.248542
4.625895 -.4595704 -2.120e+08 1.730526 514126464 47.878314
2.705822 -.4595704 -4.296e+08 1.778885 515796288 46.884142
end
