Hello,
My sample is 27 countries over the period 1970-2020.
I would like to explain the growth in per capita CO2 emissions (ln_co2pc_gr) by one-year lagged level of per capita CO2 emissions (l.ln_co2pc_gr), the growth in per capita GDP (ln_gdppc_gr), changes in Energy Intensity (ei_ch.), and the change of the renewable share into the primary energy supply (res_share_ch).
I have to compare results when:
Case 1. country and year fixed effects are omitted
Case 2. year fixed effects are omitted and country effects are added.
Case 3. year fixed effects and country effects are added
Should I change to xtdpdgmm?
Or I should use PVAR o Panel ARDL because is long panel?
Thanks in advance,
Sebastian.
My sample is 27 countries over the period 1970-2020.
Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input float(ln_co2pc_gr res_share_ch ei_ch) long pais float year
. . . 1 1970
.04318523 -.6838717 8.359551e-06 1 1971
-.003316879 -.5843963 .0009368509 1 1972
.035467148 -.19065896 .0010287017 1 1973
-.01744461 1.1816183 -.0017663687 1 1974
-.04150105 -1.1635613 -.0006288141 1 1975
.02756405 -.4502255 .004128687 1 1976
.027318 .4519265 -.003269479 1 1977
-.01889515 .7232267 .005923823 1 1978
.03856087 -.03159031 -.003776513 1 1979
-.033974648 1.6892276 .000064082444 1 1980
-.03340912 .3562208 .003573708 1 1981
-.029852867 .22335 .0005264431 1 1982
.010718346 .55891395 -.0008517876 1 1983
-.025982857 .3025955 .0005473718 1 1984
-.09177828 .2845615 .001306817 1 1985
.06215334 -.57471985 -.0015678406 1 1986
.035816193 -.04727695 .0022074506 1 1987
.01995754 -2.0891473 .0035996065 1 1988
-.051548 -.8556552 .003797956 1 1989
-.08002138 2.5997005 -.00005368143 1 1990
.04825544 -.7621235 -.0037634596 1 1991
.014944077 .8977495 -.004395187 1 1992
.020612717 .9866562 -.005773418 1 1993
.02478409 .05130513 .00046010315 1 1994
-.012306213 .1040608 .00382334 1 1995
.04091835 -.889446 -.0021086782 1 1996
.0079956055 .5504242 -.0032310635 1 1997
.014033318 .14474016 -.0015993714 1 1998
.029364586 -1.4123623 .004682116 1 1999
-.013619423 -.7077209 .00665576 1 2000
-.04242325 1.7975198 -.0001920089 1 2001
-.064777374 .4461319 .007865772 1 2002
.05957603 -.9268353 -.001951866 1 2003
.07559109 -1.3884256 .00006687641 1 2004
.02943516 .53251714 -.005813979 1 2005
.04256248 .10701164 -.003355786 1 2006
.08056164 -1.0392638 -.0004028007 1 2007
.02333355 .4650531 -.0015919358 1 2008
-.07792091 1.7649453 -.000819169 1 2009
.07104397 .3953756 -.003054425 1 2010
.036629677 .19075124 -.0014053434 1 2011
.005539894 -.5361876 .00164406 1 2012
.017653465 .006848871 .00021656603 1 2013
-.02623844 .9186995 .0021337345 1 2014
.01380539 -1.0696038 -.0012462884 1 2015
-.014710426 .5231693 .0019309297 1 2016
-.024267197 1.1013072 -.0033791065 1 2017
-.04940796 -.1671047 .0008261427 1 2018
-.03939629 -.0826373 .0004553869 1 2019
-.12809563 . . 1 2020
. . . 2 1970
.03735685 -3.583941 . 2 1971
.006715775 -3.595976 . 2 1972
.0723815 1.0047908 . 2 1973
-.013946533 -2.443425 . 2 1974
.06486988 -5.076143 .0021264479 2 1975
.06060696 1.480327 -.0028430596 2 1976
.15053034 -.9558575 .017706402 2 1977
.05724525 -5.38981 -.004387319 2 1978
.2042713 1.2600955 .011719197 2 1979
.064723015 2.294343 -.007564358 2 1980
.0004091263 -4.1512866 .00523252 2 1981
-.010876656 -1.286386 .0008103475 2 1982
-.08180618 -.2205604 -.015049823 2 1983
.02359295 .52316314 .00834471 2 1984
-.05776501 -.6478212 -.005634196 2 1985
.281785 -.4750064 .02013827 2 1986
.062625885 -5.436717 -.005898573 2 1987
.008115768 .7065676 -.003384814 2 1988
.05866051 -1.0042635 .006946467 2 1989
-.02052593 .9601043 .0005567968 2 1990
-.0022001266 -.832518 .016187295 2 1991
-.12391949 -1.431724 -.02331887 2 1992
-.013767242 -1.408625 .002412543 2 1993
.1101904 1.988639 .008190632 2 1994
.034041405 -1.8642867 .006239846 2 1995
.0448246 .2397784 .0004650354 2 1996
.12469387 -.6353271 .007994488 2 1997
-.02123642 .59386986 -.0091282725 2 1998
.05735397 -2.49613 .0045640916 2 1999
.04701233 2.706013 .00487949 2 2000
-.04536247 -1.0512298 -.005044684 2 2001
-.015072823 .05328191 -.0028871745 2 2002
.0005598068 -.10914221 -.0025393665 2 2003
.012296677 -.2341628 -.00010548532 2 2004
.017718315 .7751106 -.003184572 2 2005
.008773804 -1.2377497 -.007161543 2 2006
.010412216 .3962357 -.00034835935 2 2007
.15820885 -.927561 .01863219 2 2008
-.035902023 .4229553 .0033046156 2 2009
-.07738018 -.8142483 -.008181274 2 2010
.0507679 -.3567042 .007837012 2 2011
-.06547451 -.08397305 -.008323476 2 2012
.010436058 -1.083137 .0025542825 2 2013
-.09462738 .20679207 -.014072418 2 2014
-.010979652 -1.1899234 -.004809044 2 2015
-.06432438 .5234437 -.009212226 2 2016
.026329994 .5948993 .004054792 2 2017
.01234913 .7516962 .0006327629 2 2018
end
label values pais pais
label def pais 1 "Argentina", modify
label def pais 2 "Barbados", modify
I have to compare results when:
- country and year fixed effects are omitted
- year fixed effects are omitted and country effects are added
- year fixed effects and country effects are added
Case 1. country and year fixed effects are omitted
Code:
. reg ln_co2pc_gr l.ln_co2pc res_share_ch ei_ch
Source | SS df MS Number of obs = 1,173
-------------+---------------------------------- F(3, 1169) = 204.16
Model | 4.37886025 3 1.45962008 Prob > F = 0.0000
Residual | 8.35748358 1,169 .007149259 R-squared = 0.3438
-------------+---------------------------------- Adj R-squared = 0.3421
Total | 12.7363438 1,172 .010867188 Root MSE = .08455
------------------------------------------------------------------------------
ln_co2pc_gr | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
ln_co2pc |
L1. | -.0050447 .0027289 -1.85 0.065 -.0103987 .0003094
|
res_share_ch | -.0207655 .0009512 -21.83 0.000 -.0226317 -.0188993
ei_ch | 2.793124 .2764864 10.10 0.000 2.250659 3.335589
_cons | .048808 .0200982 2.43 0.015 .0093755 .0882406
------------------------------------------------------------------------------
Code:
. xtabond ln_co2pc_gr ln_gdppc_gr ei_ch res_share_ch, noconst
Arellano–Bond dynamic panel-data estimation Number of obs = 1,126
Group variable: pais Number of groups = 25
Time variable: year
Obs per group:
min = 17
avg = 45.04
max = 47
Number of instruments = 862 Wald chi2(4) = 968.45
Prob > chi2 = 0.0000
One-step results
------------------------------------------------------------------------------
ln_co2pc_gr | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
ln_co2pc_gr |
L1. | -.1543293 .0217159 -7.11 0.000 -.1968917 -.1117669
|
ln_gdppc_gr | 1.141223 .0654731 17.43 0.000 1.012898 1.269548
ei_ch | 3.959746 .279658 14.16 0.000 3.411626 4.507865
res_share_ch | -.0172658 .0009338 -18.49 0.000 -.019096 -.0154355
------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(2/.).ln_co2pc_gr
Standard: D.ln_gdppc_gr D.ei_ch D.res_share_ch
Code:
. xtabond ln_co2pc_gr ln_gdppc_gr ei_ch res_share_ch yr*, noconst
note: yr1 omitted from div() because of collinearity.
note: yr2 omitted from div() because of collinearity.
note: yr51 omitted from div() because of collinearity.
note: yr1 omitted because of collinearity.
note: yr2 omitted because of collinearity.
note: yr51 omitted because of collinearity.
Arellano–Bond dynamic panel-data estimation Number of obs = 1,126
Group variable: pais Number of groups = 25
Time variable: year
Obs per group:
min = 17
avg = 45.04
max = 47
Number of instruments = 885 Wald chi2(51) = 1077.88
Prob > chi2 = 0.0000
One-step results
------------------------------------------------------------------------------
ln_co2pc_gr | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
ln_co2pc_gr |
L1. | -.1699338 .0221739 -7.66 0.000 -.2133939 -.1264737
|
ln_gdppc_gr | 1.189569 .0714606 16.65 0.000 1.049509 1.329629
ei_ch | 3.926077 .2800375 14.02 0.000 3.377213 4.47494
res_share_ch | -.0164984 .0009514 -17.34 0.000 -.0183632 -.0146337
yr3 | .0086196 .0232371 0.37 0.711 -.0369241 .0541634
yr4 | 0 (omitted)
yr5 | -.0095069 .023281 -0.41 0.683 -.0551368 .0361231
yr6 | .0047888 .0233236 0.21 0.837 -.0409246 .0505023
yr7 | .0116231 .0232843 0.50 0.618 -.0340132 .0572594
yr8 | .0150959 .0232158 0.65 0.516 -.0304061 .060598
yr9 | .0164546 .0232008 0.71 0.478 -.0290182 .0619273
yr10 | -.0110719 .0232537 -0.48 0.634 -.0566484 .0345045
yr11 | -.0092358 .023345 -0.40 0.692 -.0549912 .0365195
yr12 | -.0186959 .0233934 -0.80 0.424 -.0645461 .0271544
yr13 | .0080493 .0237823 0.34 0.735 -.0385631 .0546618
yr14 | .0179798 .0237258 0.76 0.449 -.0285219 .0644814
yr15 | -.0115345 .0234152 -0.49 0.622 -.0574275 .0343585
yr16 | -.0263228 .0233368 -1.13 0.259 -.072062 .0194165
yr17 | .0019019 .023264 0.08 0.935 -.0436948 .0474985
yr18 | -.0038237 .0231897 -0.16 0.869 -.0492747 .0416273
yr19 | .0215469 .0233356 0.92 0.356 -.0241901 .0672838
yr20 | .0036934 .0232789 0.16 0.874 -.0419324 .0493193
yr21 | .0050649 .0233687 0.22 0.828 -.0407368 .0508667
yr22 | -.0160545 .0232246 -0.69 0.489 -.0615739 .0294649
yr23 | .0200222 .0231971 0.86 0.388 -.0254433 .0654878
yr24 | .0051773 .0232444 0.22 0.824 -.0403809 .0507356
yr25 | -.0364671 .023216 -1.57 0.116 -.0819697 .0090355
yr26 | .0629364 .0231853 2.71 0.007 .017494 .1083787
yr27 | .0028832 .0232247 0.12 0.901 -.0426364 .0484029
yr28 | .0017144 .0231843 0.07 0.941 -.043726 .0471548
yr29 | .0132832 .0231714 0.57 0.566 -.0321318 .0586983
yr30 | .004425 .0232676 0.19 0.849 -.0411787 .0500287
yr31 | -.0367104 .0232841 -1.58 0.115 -.0823463 .0089256
yr32 | -.011032 .0233507 -0.47 0.637 -.0567986 .0347345
yr33 | .0140877 .0230807 0.61 0.542 -.0311496 .0593251
yr34 | -.0057824 .023058 -0.25 0.802 -.0509753 .0394105
yr35 | .0041397 .023038 0.18 0.857 -.0410139 .0492933
yr36 | -.0405128 .0230048 -1.76 0.078 -.0856013 .0045758
yr37 | -.0030994 .0230534 -0.13 0.893 -.0482832 .0420844
yr38 | .0040511 .0230197 0.18 0.860 -.0410668 .0491689
yr39 | .0035858 .0230256 0.16 0.876 -.0415436 .0487152
yr40 | .0079728 .0231945 0.34 0.731 -.0374876 .0534333
yr41 | -.0181299 .0233019 -0.78 0.437 -.0638007 .0275409
yr42 | -.0152946 .0232321 -0.66 0.510 -.0608287 .0302395
yr43 | .0048455 .0232524 0.21 0.835 -.0407284 .0504195
yr44 | -.025654 .0232216 -1.10 0.269 -.0711674 .0198595
yr45 | -.0201522 .0232677 -0.87 0.386 -.0657562 .0254517
yr46 | .0215768 .023257 0.93 0.354 -.0240061 .0671597
yr47 | -.0027177 .023233 -0.12 0.907 -.0482534 .0428181
yr48 | -.0274366 .0232932 -1.18 0.239 -.0730905 .0182172
yr49 | -.0159166 .0232996 -0.68 0.495 -.0615831 .0297498
yr50 | .012279 .0232845 0.53 0.598 -.0333577 .0579157
------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(2/.).ln_co2pc_gr
Standard: D.ln_gdppc_gr D.ei_ch D.res_share_ch D.yr3 D.yr4 D.yr5
D.yr6 D.yr7 D.yr8 D.yr9 D.yr10 D.yr11 D.yr12 D.yr13 D.yr14
D.yr15 D.yr16 D.yr17 D.yr18 D.yr19 D.yr20 D.yr21 D.yr22
D.yr23 D.yr24 D.yr25 D.yr26 D.yr27 D.yr28 D.yr29 D.yr30
D.yr31 D.yr32 D.yr33 D.yr34 D.yr35 D.yr36 D.yr37 D.yr38
D.yr39 D.yr40 D.yr41 D.yr42 D.yr43 D.yr44 D.yr45 D.yr46
D.yr47 D.yr48 D.yr49 D.yr50
Or I should use PVAR o Panel ARDL because is long panel?
Thanks in advance,
Sebastian.
Comment