Impact of Energy Production on Growth -...
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1 Impact of Energy Production on Growth One Way Panel Data Analysis of Asian and European Countries Presented By: Muhammad Iqbal Course: Econometrics Methods for Panel Data
Transcript of Impact of Energy Production on Growth -...
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Impact of Energy
Production on GrowthOne Way Panel Data Analysis of Asian and
European Countries
Presented By: Muhammad Iqbal
Course: Econometrics Methods for Panel Data
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Presentation Layout
Introduction
Panel Test Methodology
Estimations Models
Hausman Test
Conclusion
Referrence
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Countries: Region 1: China, India, Pakistan, Sir Lanka, Thailand,
Malaysia, Indonesia, Bangladesh.
Region 2: Austria, Germany, Denmark, Italy, Greece, Sweden, Norway,
Switzerland, France.
Introduction:
Variables: GDP (US $), Capital (US $), Labor, Energy
Production (Kt of Oil Equivalent), Trade Openness (ratio)
Note: Variables are used in logarithm form except Labor and Trade.
Data: Panel Data from 1980 to 2005
Data Source: World Development Indicators 2008
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Notations:
lgdp: Gross Domestic Product
llf: Labor Force
lep: Energy Production
open: Trade Openness
lcap: Capital
Introduction:
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Estimation Models:
Simple Pool Regression:
ititit eXY
ititiit eXY
Fixed Effects Model/Least Square Dummy Variable
(LSDV): (One-Way Panel)
Individual Effect:
Time Effect:
itittit eXY
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Random Effect Model:
Individual Effect:
Time Effect:
ititite
ititiit eXY
itittit eXY
where
ititite where
H0: Random effects are consistent and
efficient
H1: Random effects are inconsistent
Hausman Test:
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Results: Simple Pool Regression
_cons 1.439276 .0935953 15.38 0.000 1.255323 1.623229 lep .038295 .0103611 3.70 0.000 .0179312 .0586588 open -.0014985 .0001222 -12.27 0.000 -.0017386 -.0012584 lcap .976449 .0088913 109.82 0.000 .9589741 .993924 llf -.0838857 .0086883 -9.66 0.000 -.1009617 -.0668097 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 140.863301 441 .319417916 Root MSE = .08269 Adj R-squared = 0.9786 Residual 2.98831064 437 .006838239 R-squared = 0.9788 Model 137.87499 4 34.4687475 Prob > F = 0.0000 F( 4, 437) = 5040.59 Source SS df MS Number of obs = 442
. reg lgdp llf lcap open lep
Overall:
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Region 1:
Results: Simple Pool Regression
_cons 2.754704 .1546815 17.81 0.000 2.449715 3.059692 lep .1346301 .019916 6.76 0.000 .0953613 .1738988 open .0005128 .0002321 2.21 0.028 .0000551 .0009704 lcap .5835063 .0254438 22.93 0.000 .5333383 .6336744 llf .1916584 .0309133 6.20 0.000 .1307061 .2526106 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 61.1732236 207 .295522819 Root MSE = .06924 Adj R-squared = 0.9838 Residual .973356467 203 .004794859 R-squared = 0.9841 Model 60.1998671 4 15.0499668 Prob > F = 0.0000 F( 4, 203) = 3138.77 Source SS df MS Number of obs = 208
. reg lgdp llf lcap open lep if region==1
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Results: Simple Pool Regression
Region 2:
_cons 2.396289 .1240149 19.32 0.000 2.151933 2.640645 lep .0419347 .0061818 6.78 0.000 .0297541 .0541152 open .0016819 .0002265 7.42 0.000 .0012356 .0021283 lcap .5385989 .0333439 16.15 0.000 .4728988 .6042989 llf .4385445 .0343581 12.76 0.000 .3708462 .5062429 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 43.3484653 233 .186044915 Root MSE = .03959 Adj R-squared = 0.9916 Residual .358957291 229 .001567499 R-squared = 0.9917 Model 42.989508 4 10.747377 Prob > F = 0.0000 F( 4, 229) = 6856.38 Source SS df MS Number of obs = 234
. reg lgdp llf lcap open lep if region==2
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Results: Individual Effects
Fixed Effects: Overall
F test that all u_i=0: F(16, 421) = 102.36 Prob > F = 0.0000 rho .99628513 (fraction of variance due to u_i) sigma_e .03809825 sigma_u .62391404 _cons -.6102154 .3170724 -1.92 0.055 -1.233458 .0130268 lep .0589888 .0161484 3.65 0.000 .0272473 .0907303 open .0005033 .0001492 3.37 0.001 .00021 .0007967 llf .8372439 .0594433 14.08 0.000 .7204014 .9540865 lcap .5166039 .0198838 25.98 0.000 .4775201 .5556878 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = -0.6883 Prob > F = 0.0000 F(4,421) = 1463.98
overall = 0.3907 max = 26 between = 0.3728 avg = 26.0R-sq: within = 0.9329 Obs per group: min = 26
Group variable: code Number of groups = 17Fixed-effects (within) regression Number of obs = 442
. xtreg lgdp lcap llf open lep, fe
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Results: Individual Effects
Fixed Effects: Region 1
F test that all u_i=0: F(7, 196) = 38.53 Prob > F = 0.0000 rho .98314376 (fraction of variance due to u_i) sigma_e .04571802 sigma_u .34915284 _cons -.0391871 .5792467 -0.07 0.946 -1.181543 1.103169 lep .301507 .063916 4.72 0.000 .1754557 .4275584 open -.0000894 .000223 -0.40 0.689 -.0005291 .0003503 llf .5440987 .1109383 4.90 0.000 .3253128 .7628846 lcap .5171968 .0259565 19.93 0.000 .4660069 .5683868 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = -0.9414 Prob > F = 0.0000 F(4,196) = 895.24
overall = 0.9521 max = 26 between = 0.9727 avg = 26.0R-sq: within = 0.9481 Obs per group: min = 26
Group variable: code Number of groups = 8Fixed-effects (within) regression Number of obs = 208
. xtreg lgdp lcap llf open lep if region==1, fe
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Results: Individual Effects
Fixed Effects: Region
F test that all u_i=0: F(8, 221) = 58.85 Prob > F = 0.0000 rho .80524103 (fraction of variance due to u_i) sigma_e .02277904 sigma_u .04631799 _cons 3.696183 .5346077 6.91 0.000 2.642601 4.749764 lep .0473545 .0111758 4.24 0.000 .0253298 .0693792 open .0023977 .0002174 11.03 0.000 .0019694 .0028261 llf .6750935 .0879497 7.68 0.000 .5017661 .8484209 lcap .261815 .0359529 7.28 0.000 .1909605 .3326694 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = 0.4406 Prob > F = 0.0000 F(4,221) = 530.85
overall = 0.9891 max = 26 between = 0.9915 avg = 26.0R-sq: within = 0.9057 Obs per group: min = 26
Group variable: code Number of groups = 9Fixed-effects (within) regression Number of obs = 234
. xtreg lgdp lcap llf open lep if region==2, fe
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Results: Individual Effects
Random Effects: Overall
rho .74513198 (fraction of variance due to u_i) sigma_e .03809825 sigma_u .06514242 _cons 2.475172 .2061735 12.01 0.000 2.07108 2.879265 lep .0654829 .0192378 3.40 0.001 .0277775 .1031884 open .0005532 .0001692 3.27 0.001 .0002216 .0008848 llf .0875032 .0301673 2.90 0.004 .0283764 .1466299 lcap .736694 .0186704 39.46 0.000 .7001008 .7732872 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 4145.87
overall = 0.9193 max = 26 between = 0.9225 avg = 26.0R-sq: within = 0.9055 Obs per group: min = 26
Group variable: code Number of groups = 17Random-effects GLS regression Number of obs = 442
. xtreg lgdp lcap llf open lep
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Results: Individual Effects
Random Effects: Region 1
rho .65838757 (fraction of variance due to u_i) sigma_e .04571802 sigma_u .06346896 _cons 2.225757 .3194036 6.97 0.000 1.599738 2.851777 lep .2631458 .0520965 5.05 0.000 .1610385 .365253 open .0004869 .000224 2.17 0.030 .0000478 .000926 llf .1709329 .063459 2.69 0.007 .0465556 .2953102 lcap .5911597 .025625 23.07 0.000 .5409355 .6413839 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 3303.58
overall = 0.9821 max = 26 between = 0.9922 avg = 26.0R-sq: within = 0.9405 Obs per group: min = 26
Group variable: code Number of groups = 8Random-effects GLS regression Number of obs = 208
. xtreg lgdp lcap llf open lep if region==1
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Results: Individual Effects
Random Effects: Region 2
rho .76765289 (fraction of variance due to u_i) sigma_e .02277904 sigma_u .04140467 _cons 3.456373 .2288301 15.10 0.000 3.007874 3.904872 lep .0477709 .0106086 4.50 0.000 .0269785 .0685633 open .0023209 .000189 12.28 0.000 .0019505 .0026914 llf .695094 .0451951 15.38 0.000 .6065132 .7836749 lcap .2715978 .0353141 7.69 0.000 .2023834 .3408122 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 3040.52
overall = 0.9888 max = 26 between = 0.9912 avg = 26.0R-sq: within = 0.9057 Obs per group: min = 26
Group variable: code Number of groups = 9Random-effects GLS regression Number of obs = 234
. xtreg lgdp lcap llf open lep if region==2
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Results: Time Effects
Fixed Effects: Overall
F test that all u_i=0: F(25, 412) = 0.76 Prob > F = 0.7879 rho .05023315 (fraction of variance due to u_i) sigma_e .08325718 sigma_u .01914734 _cons 1.555165 .0995779 15.62 0.000 1.35942 1.750909 open -.0016938 .0001337 -12.66 0.000 -.0019567 -.0014309 lcap .9685061 .0092319 104.91 0.000 .9503585 .9866536 lep .0412477 .0104947 3.93 0.000 .0206179 .0618775 llf -.0885404 .0088422 -10.01 0.000 -.1059219 -.0711589 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = 0.1529 Prob > F = 0.0000 F(4,412) = 4728.98
overall = 0.9786 max = 17 between = 0.9909 avg = 17.0R-sq: within = 0.9787 Obs per group: min = 17
Group variable: year Number of groups = 26Fixed-effects (within) regression Number of obs = 442
. xtreg lgdp llf lep lcap open, fe
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Results: Time Effects
Fixed Effects: Region 1
F test that all u_i=0: F(25, 178) = 3.99 Prob > F = 0.0000 rho .40304956 (fraction of variance due to u_i) sigma_e .0591908 sigma_u .04863672 _cons 3.437845 .1538295 22.35 0.000 3.13428 3.741409 open 8.32e-06 .0002082 0.04 0.968 -.0004025 .0004191 lcap .5245047 .023353 22.46 0.000 .4784204 .570589 lep .1946448 .0184184 10.57 0.000 .1582984 .2309912 llf .1490465 .0271952 5.48 0.000 .09538 .202713 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = 0.2503 Prob > F = 0.0000 F(4,178) = 3802.79
overall = 0.9826 max = 8 between = 0.9910 avg = 8.0R-sq: within = 0.9884 Obs per group: min = 8
Group variable: year Number of groups = 26Fixed-effects (within) regression Number of obs = 208
. xtreg lgdp llf lep lcap open if region==1,fe
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Results: Time Effects
Fixed Effects: Region 2
F test that all u_i=0: F(25, 204) = 0.52 Prob > F = 0.9739 rho .07398117 (fraction of variance due to u_i) sigma_e .04068082 sigma_u .01149848 _cons 2.292892 .13174 17.40 0.000 2.033146 2.552639 open .0020215 .000307 6.59 0.000 .0014163 .0026268 lcap .5467505 .0348807 15.67 0.000 .4779776 .6155235 lep .0402716 .0064144 6.28 0.000 .0276246 .0529185 llf .4390485 .0364548 12.04 0.000 .367172 .510925 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
corr(u_i, Xb) = -0.1301 Prob > F = 0.0000 F(4,204) = 6323.61
overall = 0.9915 max = 9 between = 0.9875 avg = 9.0R-sq: within = 0.9920 Obs per group: min = 9
Group variable: year Number of groups = 26Fixed-effects (within) regression Number of obs = 234
. xtreg lgdp llf lep lcap open if region==2,fe
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Results: Time Effects
Random Effects: Overall
rho 0 (fraction of variance due to u_i) sigma_e .08325718 sigma_u 0 _cons 1.439276 .0935953 15.38 0.000 1.255832 1.622719 open -.0014985 .0001222 -12.27 0.000 -.0017379 -.001259 lcap .976449 .0088913 109.82 0.000 .9590225 .9938756 lep .038295 .0103611 3.70 0.000 .0179876 .0586024 llf -.0838857 .0086883 -9.66 0.000 -.1009144 -.066857 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 20162.35
overall = 0.9788 max = 17 between = 0.9919 avg = 17.0R-sq: within = 0.9786 Obs per group: min = 17
Group variable: year Number of groups = 26Random-effects GLS regression Number of obs = 442
. xtreg lgdp llf lep lcap open
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Results: Time Effects
Random Effects: Region 1
rho 0 (fraction of variance due to u_i) sigma_e .0591908 sigma_u 0 _cons 2.754704 .1546815 17.81 0.000 2.451533 3.057874 open .0005128 .0002321 2.21 0.027 .0000578 .0009677 lcap .5835063 .0254438 22.93 0.000 .5336373 .6333753 lep .1346301 .019916 6.76 0.000 .0955955 .1736647 llf .1916584 .0309133 6.20 0.000 .1310695 .2522472 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 12555.08
overall = 0.9841 max = 8 between = 0.9911 avg = 8.0R-sq: within = 0.9872 Obs per group: min = 8
Group variable: year Number of groups = 26Random-effects GLS regression Number of obs = 208
. xtreg lgdp llf lep lcap open if region==1
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Results: Time Effects
Random Effects: Region 2
rho 0 (fraction of variance due to u_i) sigma_e .04068082 sigma_u 0 _cons 2.396289 .1240149 19.32 0.000 2.153224 2.639354 open .0016819 .0002265 7.42 0.000 .0012379 .0021259 lcap .5385989 .0333439 16.15 0.000 .4732461 .6039517 lep .0419347 .0061818 6.78 0.000 .0298185 .0540508 llf .4385445 .0343581 12.76 0.000 .3712039 .5058851 lgdp Coef. Std. Err. z P>|z| [95% Conf. Interval]
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000Random effects u_i ~ Gaussian Wald chi2(4) = 27425.54
overall = 0.9917 max = 9 between = 0.9877 avg = 9.0R-sq: within = 0.9919 Obs per group: min = 9
Group variable: year Number of groups = 26Random-effects GLS regression Number of obs = 234
. xtreg lgdp llf lep lcap open if region==2
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Results: Hausman Test
Individual Effects: Overall
(V_b-V_B is not positive definite) Prob>chi2 = 0.0000 = 120.29 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg lep .0589888 .0654829 -.0064941 . open .0005033 .0005532 -.0000498 . llf .8372439 .0875032 .7497407 .0512195 lcap .5166039 .736694 -.2200901 .0068398 rfe rre Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe rre
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Results: Hausman Test
Individual Effects: Region 1
(V_b-V_B is not positive definite) Prob>chi2 = 0.0000 = 55.80 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg lep .301507 .2631458 .0383613 .0370299 open -.0000894 .0004869 -.0005763 . llf .5440987 .1709329 .3731658 .0909959 lcap .5171968 .5911597 -.0739629 .0041351 rfe1 rre1 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe1 rre1
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Results: Hausman Test
Individual Effects: Region 2
Prob>chi2 = 0.2565 = 5.32 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg lep .0473545 .0477709 -.0004164 .0035151 open .0023977 .0023209 .0000768 .0001073 llf .6750935 .695094 -.0200005 .075449 lcap .261815 .2715978 -.0097828 .0067475 rfe2 rre2 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe2 rre2
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Results: Hausman Test
Time Effects: Overall
Prob>chi2 = 0.0117 = 12.91 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg lep .0412477 .038295 .0029527 .001669 open -.0016938 -.0014985 -.0001953 .0000544 lcap .9685061 .976449 -.007943 .0024847 llf -.0885404 -.0838857 -.0046547 .0016427 rfe rre Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe rre
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Results: Hausman Test
Time Effects: Region 1
(V_b-V_B is not positive definite) Prob>chi2 = 0.0000 = 410.50 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg open 8.32e-06 .0005128 -.0005044 . lcap .5245047 .5835063 -.0590016 . lep .1946448 .1346301 .0600147 . llf .1490465 .1916584 -.0426119 . rfe1 rre1 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe1 rre1
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Results: Hausman Test
Time Effects: Region 2
Prob>chi2 = 0.1843 = 6.21 chi2(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg open .0020215 .0016819 .0003396 .0002072 lcap .5467505 .5385989 .0081516 .0102396 lep .0402716 .0419347 -.0016631 .0017115 llf .4390485 .4385445 .000504 .0121851 rfe2 rre2 Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman rfe2 rre2
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References:
• Econometric Analysis of Panel Data by Badi H. Baltagi, 3rd
Edition.
• Lecture Notes “Econometrics Methods for Panel Data” by
Robert Kunst.
• Internet Resources:
http://en.wikipedia.org/wiki/Hausman_test
http://en.wikipedia.org/wiki/Fixed_effects_model
http://en.wikipedia.org/wiki/Random_effects_model
http://en.wikipedia.org/wiki/Exogenous_growth_model
http://en.wikipedia.org/wiki/Economic_growth
http://en.wikipedia.org/wiki/Harod_domar_model
http://en.wikipedia.org/wiki/Logarithm
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