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Public budgets for energy RD&D and the effects on energy intensity and pollution levels

  • Atmospheric Pollutants in a Changing Environment
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Abstract

This study, based on the N-shaped cubic model of the environmental Kuznets curve, analyzes the evolution of per capita greenhouse gas emissions (GHGpc) using not just economic growth but also public budgets dedicated to energy-oriented research development and demonstration (RD&D) and energy intensity. The empirical evidence, obtained from an econometric model of fixed effects for 28 OECD countries during 1994–2010, suggests that energy innovations help reduce GHGpc levels and mitigate the negative impact of energy intensity on environmental quality. When countries develop active energy RD&D policies, they can reduce both the rates of energy intensity and the level of GHGpc emissions. This paper incorporates a moderating variable to the econometric model that emphasizes the effect that GDP has on energy intensity. It also adds a variable that reflects the difference between countries that have made a greater economic effort in energy RD&D, which in turn corrects the GHG emissions resulting from the energy intensity of each country.

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Notes

  1. Empirical evidence suggests complementarity between measures for pollution reduction and economic growth, which would have a bearing on the potential for lower income requirements to achieve environmental decontamination (Cantos and Balsalobre 2011).

  2. Initially, economic development is characterized by the application of distorting policies, such as subsidies for energy consumption, and by market failures, such as incorrect definitions of property rights or a lack of payment for environmental externalities (De Bruyn and Heintz 1999; Panayotou 1993). The second phase leads to the disappearance of distortions and a correction of market failures. Subsequent stages then involve the implementation of strict environmental policies and greater environmental awareness. Thus, institutional changes, in parallel with economic development, also can reveal the pattern described by the EKC (Jones and Manuelli 1995). Selden and Song (1994) acknowledge that well-administered corrective measures allow for lower income levels before correction occurs.

  3. Panayotou (1993) derived the EKC terminology, noting the similarities with conclusions drawn by Kuznets (1955) in a study of the relationship between economic growth and inequality.

  4. When the EKC takes an N-shaped form, environmental pollution increases at a low level of income, then reaches a turning point and begins to decline, after which it increases again. The authors cite evidence of the N shape but also interpret the last stretch of the ascending income curve as too high for most regions. Thus they largely ignore the cubic shape of the function and focus instead on the inverted U (quadratic form).

  5. Grossman and Krueger (1995) allude to the possibility of an N pattern, as a statistical result of stabilization in the level of GHG emissions or as a recovery effect, after the initial impact of the shock. Moomaw and Unruh (1997) suggest that developed countries would have experienced a structural transition toward lower CHG emissions in the wake of the 1973 oil crisis, such that the cubic shape would result more from adjusting the polynomial curve, reflecting an underlying structural relationship. Panayotou (1997) argues that no special significance should be accorded to the possibility of returning to a new tier of increasing pollution, because such a rise often occurs outside the range of data or at the end, where there are relatively few observations.

  6. Technological improvements lead to cleaner and more efficient energy processes (Stokey 1998; Bovenberg and Smulders 1995; Verdier 1993; Focacci 2003; Turner and Hanley 2011).

  7. Opschoor and Vos (1989) propose that with depletions of improvements in technological efficiency or costly applications, further growth in income levels results in greater environmental degradation.

  8. The 28 OECD countries are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Korea, Luxembourg, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, the UK, and the USA.

  9. In Fisher’s empirical methodology of distributed lags, any cause can produce an effect only after some time lag, and this effect is not felt all at once but rather is distributed over multiple points in time.

  10. The dummy variable (DRANKING it ) indicates 15 countries that spent more of their public budgets during 2008–2010 on energy RD&D as follows: Australia, Austria, Canada, Denmark, Finland, France, Hungary, Ireland, Japan, Korea, the Netherlands, Norway, Sweden, Switzerland, and the USA.

  11. The estimation of the turning points for the cubic model used the following formulation (Diao et al. 2009):

    $$ Xj=\frac{-{\beta}_2\pm \sqrt{\beta_2^2-3{\beta}_1{\beta}_3}}{3{\beta}_3},\forall j=1,2 $$

    where X 1 represents the first breaking point and X 2 is the second. After this point, economic growth again produces an increase in the rate of environmental destruction.

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Authors and Affiliations

  1. Departament of Economía Política y Hacienda Pública, Estadística Económica y Empresarial, y Política Económica, Albacete, Spain

    Daniel Balsalobre & José María Cantos

  2. Departament of Economía Española e Internacional, Econometría e Historia e Instituciones Económicas, Universidad de Castilla La Mancha, Albacete, Spain

    Agustín Álvarez

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  1. Daniel Balsalobre
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  2. Agustín Álvarez
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  3. José María Cantos
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Correspondence to Daniel Balsalobre.

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Responsible editor: Philippe Garrigues

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Balsalobre, D., Álvarez, A. & Cantos, J.M. Public budgets for energy RD&D and the effects on energy intensity and pollution levels. Environ Sci Pollut Res 22, 4881–4892 (2015). https://doi.org/10.1007/s11356-014-3121-3

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