PUBLIC BUDGET IN ENERGY RD&D, AND THEIR EFFECTS ON ENERGY INTENSITY AND GHGPC EMISSION

Transcription

1 PUBLIC BUDGET IN ENERGY RD&D, AND THEIR EFFECTS ON ENERGY INTENSITY AND GHGPC EMISSION BALSALOBRE LORENTE, DANIEL ÁLVAREZ-HERRANZ, AGUSTÍN CANTOS, CANTOS, JOSÉ MARÍA

2 MAIN HYPOTHESIS INCOME LEVEL-ENVIRONMENTAL QUALITY ADOPTS THE EKC SCHEME (N-SHAPED). The EKC is an empirical model that studies the relationship between economic growth and environmental quality. ENERGY INTENSITY IS INFLUENCED BY THE INCOME LEVEL. TECHNICAL INNOVATION (PUBLIC BUDGET IN ENERGY RD&D) IS THE KEY TO REDUCE THE GHGpc EMISSIONS AND THE NEGATIVE IMPACT OF ENERGY INTENSITY.

3 EVOLUTION OF GHG EMISSIONS AND GDP IN OECD COUNTRIES GHG OECD - Total GDP OECD - US$millions Notes: principal axis Greenhouse gas excluding LULUCF (TeCO2) (OECD,2012). Secondary axis: Gross domestic product (expenditure approach) US $, current prices, current PPPs, millions(oecd,2012)

4 EKC SCHEME: POSSIBLE BEHAVIORS BETWEEN ENVIRONMENTAL QUALITY AND GDP PER CAPITA CONFIRM AN N-SHAPED PATTERN BETWEEN INCOME PER CAPITA INCOME AND THE LEVEL OF ENVIRONMENTAL POLLUTION (EKC MODEL): GHGpc it = α it + β 1 GDPpc it + β 2 GDPpc 2 it+ β 3 GDPpc 3 it + β 4 Z it+ e it (5) If β1>0, β2<0, β3>0, CUBIC POLYNOMIAL, REPRESENTING THE N-SHAPE, WHERE THE INVERTED U HYPOTHESIS OCCURS UP TO A CERTAIN POINT, FROM WHICH POLLUTION INCREASES AGAIN.

5 METHODOLOGY MODEL HAS BEEN ESTIMATED BY GENERALIZED LEAST SQUARES (GLS), PANEL DATA, FOR 28 OECD COUNTRIES. GHGPC it = α i + β 1 GDP PCit + β 2 GDP PC 2 it + β 3 GDP PC 3 it + β 4 ZP2C it +β 5 ESUPGDP it +β 6 GDPPC*ESUPGDP it + β 7 DRANKING*ESUPGDP it +ξ it IN ADDITION TO ECONOMIC GROWTH, THERE ARE AUXILIARY VARIABLES THAT HELP TO UNDERSTAND THE EVOLUTION OF GHGPC. -Public budget in energy RD&D is transformed into a dynamic variable from a structure of finite delays with restriction in the parameters is in the form of cumulative delays in order 2 (ZP2Cit). -Dumpening effect which analyze how GDPpc influences energy intensity. (GDPPC*ESUPGDP). -(DRANKING*ESUPGDPit): variable that captures the interaction between the dummy variable (DRANKING) and the variable of energy intensity (ESUPGDP). Allows to differentiate countries according to the effort in RD&D and its effects on the energy intensity

6 RESULTS OF THE ECONOMETRIC ANALYSIS COMPARING MODEL 1 AND MODEL 2 GHGPCit = αi + β1gdppcit + β2gdppc 2 it + β3gdppc 3 it + β4zp2cit + β5esupgdpit+β6gdppc*esupgdpit + β7 DRANKING*ESUPGDPit +ξ it Dependent Variable: GHGPC.Method: Panel EGLS (Cross-section weights) Sample: Periods included: 17. Cross-sections included: 28.Total panel (balanced) observations: 476.Iterate coefficients after one-step weighting matrix.white cross-section standard errors & covariance (d.f. corrected).convergence achieved after 21 total coef iterations Variable MODEL 1 MODEL 2 EKC Coefficient Coefficient N-SHAPE C 6802, ,55*** (8,766499)*** (8,312838)*** GDPpc 0, , β1>0 (3,782104)*** (3,856521)*** GDPpc^2-7,84E-06-8,61E-06 Β2<0 (-9,635634)*** (-8,9562)*** GDPpc^3 5,90E-11 6,58E-11 Β3>0 (7,226136)*** (7,091054)*** ZF2C ,03 - Β4<0 (-5,863531)*** - ESUPGDP 15101, ,26 Β5>0 (5,382436)*** (5,335366)*** GDPpc*ESUPGDP 1, , Β6>0 (4,08163)*** (3,599868)*** DRANKING*ESUPGDP -7642,626 - Β7<0 (-2,515247)*** - AR(2) 0, , EKC (10,31021)*** (8,399439)*** Adjusted R-squared 0, , F-statistic 1994, ,607 Prob(F-statistic) , Notes: t-student in parentheses; significance levels: * <0.10; **<0,05; ***<0,01

7 COMPARISON OF TURNING POINTS BETWEEN MODEL 1 & MODEL 2 MODEL 1: X1=US$ ,48; X2=US$ ,08; MODEL 2: X3=US$ ,77; X4=US$ ,26 Comparing model 1 and model 2; it is possible to isolate the technical effect by omitting variables related to RD&D in energy, to prove that technical efforts help to reduce a part of the scale effect (Torras and Boyce, 1998). IN A N-SHAPED SCHEME, THE PUBLIC BUDGET IN RD&D (RDETPCit) EXERTS A TECHNICAL COMPENSATION TO THE SCALE EFFECT, IN THE SENSE THAT, WHEN THERE ARE NO TECHNICAL ADVANCES AIMED AT CORRECTING ENVIRONMENTAL DEGRADATION, DECREASING TECHNICAL RETURNS WOULD LEAD TO A SITUATION THAT WOULD RETURN TO A RISE IN THE LEVEL OF GHGPC EMISSIONS.

8 . SCALE TECHNOLOGIAL AND COMPOSITION EFFECT ECONOMIC GROWTH AFFECTS THE ENVIRONMENTAL QUALITY IN THREE DIFFERENT CHANNELS: SCALE, TECHNOLOGICAL AND COMPOSITION EFFECTS (GROSSMAN AND KRUEGER, 1991) GHGpc EMISSIONS DECREASE WITH INCREASING THE LEVEL OF INCOME OF THE COUNTRIES, BUT ONCE THE SCALE EFFECT EXCEEDS THE TECHNOLOGICAL EFFECT, AS A RESULT OF A TECHNICAL OBSOLESCENCE, ALTHOUGH THE SAVINGS PRESENTED POSITIVE GROWTH RATES, WILL BE PLACED IN A GROWING LEVEL OF POLLUTION.

9 COMPARISON OF TURNING POINTS BETWEEN MODEL 1 & MODEL 2 ENERGY INNOVATION DELAYS SCALE EFFECT MODEL 1: X1=US$ ,48; X2=US$ ,08; MODEL 2: X3=US$ ,77; X4=US$ ,26 Comparing model 1 and model 2; it is possible to isolate the technical effect by omitting variables related to RD&D in energy, to prove that technical efforts help to reduce a part of the scale effect (Torras and Boyce, 1998). IN A N-SHAPED SCHEME, THE PUBLIC BUDGET IN RD&D (RDETPCit) EXERTS A TECHNICAL COMPENSATION TO THE SCALE EFFECT, IN THE SENSE THAT, WHEN THERE ARE NO TECHNICAL ADVANCES AIMED AT CORRECTING ENVIRONMENTAL DEGRADATION, DECREASING TECHNICAL RETURNS WOULD LEAD TO A SITUATION THAT WOULD RETURN TO A RISE IN THE LEVEL OF GHGPC EMISSIONS.

10 CONCLUSIONS & POLICY IMPLICATIONS OUR STUDY CONFIRMES AN N-SHAPED PATTERN BETWEEN INCOME PER CAPITA INCOME AND ENVIRONMENTAL POLLUTION LEVEL. TECHNICAL OBSOLESCENCE IS USED AS A BUILT-IN HYPOTHESIS IN THE STUDY OF THE EKC. TECHNICAL INNOVATION HAS A POSITIVE EFFECT THAT ENABLES COUNTRIES TO ENHANCE THEIR ENVIRONMENTAL QUALITY. ENERGY RD&D DELAYS THE SCALE EFFECT AND THE RETURN TO A TIER OF ASCENDING GHGPC EMISSIONS. ENERGY RD&D REDUCES THE NEGATIVE IMPACT THAT THE ENERGY INTENSITY EXERTS ON GHGPC EMISSIONS.