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The environmental Kuznets curve and CO2 emissions in the USA

Is the relationship between GDP and CO2 emissions time varying? Evidence across economic sectors

Environmental Science and Pollution Research volume 23, pages 18407–18420 (2016)Cite this article

Abstract

In this paper, we analyze the existence of the environmental Kuznets curve as reported by Kuznets (Am Econ Rev 5:1–28, 1955) by using the methodology proposed by Kejriwal and Perron (J Econ 146:59–73, 2008, J Bus Econ Stat 28:503–522, 2010) and applying Jaunky’s (Energy Policy 39(3):1228–1240, 2011) specification using quarterly data from 1973:1 to 2015:2. We also allow different behaviors across time and identify it by economic sectors. Our results show the existence of the environmental Kuznets curve (EKC) in the USA only when we allow for structural breaks. Interestingly, the industrial sector shows a different pattern than do other economic sectors; with the beginning of the economic crisis, it appears to have abandoned the objective of the environmental stabilization found until then.

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Fig. 1

Notes

  1. In this action, the Environmental Protection Agency (EPA) established final emission guidelines for states to follow when developing plans to reduce greenhouse gas (GHG) emissions from existing fossil fuel-fired electric generating units (EGUs). Specifically, the EPA established subcategories of existing fossil fuel-fired EGUs, fossil fuel-fired electric utility steam generating units and stationary combustion turbines; and state- implementation of state plans that establish emission standards emission performance rates, which may be accomplished by meeting the state goals.

  2. The Jaunky (2011) specification is based on Narayan and Narayan (2010). We make references to the Jaunky specification because we also apply the DOLS analysis.

  3. The works of Beckerman (1992) and Panayotou (1993) were the first to use the term EKC as an extension of the relationship between the level of inequality and income per capita as Kuznets (1955) proposed.

  4. The argument over technological change, as detailed in the work of Roca and Padilla (2003), is ruled by the so-called “rebound effect”, by which the increase in environmental efficiency derived from technology leads to greater technological demands that nullify this effect. In addition, it would be unconvincing if environmental improvement resulted from the replacement of the service sector by industry, if we suppose that the environmentally most problematic sectors produce inferior goods, which is not likely (Torras and Boyce 1998).

  5. Jaunky (2009) previously surveyed the link between CO2 emissions and productivity growth for 27 rich countries over the period 1974–2000. Unidirectional causality running from productivity growth to CO2 emissions is found in the short run, whereas bidirectional causality is revealed in the long run. Productivity growth is found to exert a positive impact on CO2 emissions in the long run.

  6. The exercise was also conducted using variables in per capita terms. The results are very similar to those presented in this work and are available to the reader upon request. We consider it more appropriate to show the results in aggregate terms that establish no comparison between countries.

  7. In general, the majority of conventional unit root tests, such as the Dickey-Fuller tests and the Phillips-Perron tests, suffer from three problems. First, many tests have low power when the root of the autoregressive polynomial is close to but less than one (de Jong et al., 1992). Second, most tests suffer from severe size distortions when the moving-average polynomial of the first-differenced series has a large negative autoregressive root (Schwert 1989 and Perron and Ng 1996). Third, the implementation of unit root tests often requires the selection of an autoregressive truncation lag k; however, as discussed by Ng and Perron (1995), there is a strong association between k and the severity of size distortions and/or the extent of power loss. Ng and Perron (2001) solved these problems, and we refer to their article for further details.

  8. We use 15 % trimming so that the maximum number of breaks allowed under the alternative hypothesis is 3. However, a lower trimming than 15 % would mean that the required years of each regime is at least 2.25 or 4.25 years, perhaps some significant periods, so we opted for the broader trimming permitted by this technique, as 15 % involved at least 6.5 years. However, if a higher number of breaks states that three breaks (four regimes), in the case of the existence of more breaks, occurs, than the number of years of each regimen should be 8.4 years maximum, so again it seems more representative to opt for the largest possible amplitude by this technique, i.e., 10.5 years corresponding to 42 quarters.

  9. DOLS approach allows a robust correction to the possible presence of endogeneity in the independent variables and the serial correlation in error terms of OLS estimation.

  10. To overcome the problem of the low power of classical tests under the presence of persistent roots in the residuals of the regression, Shin (1994) suggested a test in which the null hypothesis is cointegration.

  11. These tests are called the Kwiatkowski et al. (1992) tests and assume the null hypothesis of stationarity.

  12. Cμ is the test statistic for deterministic cointegration, i.e., when no trend is present in the regression.

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  1. Departamento de Economía, Universidad de Huelva, Huelva, Spain

    Emilio Congregado, Julia Feria-Gallardo, Antonio A. Golpe & Jesús Iglesias

Authors
  1. Emilio Congregado
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  2. Julia Feria-Gallardo
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  3. Antonio A. Golpe
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  4. Jesús Iglesias
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Corresponding author

Correspondence to Antonio A. Golpe.

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Responsible editor: Philippe Garrigues

Appendix 1

Appendix 1

Fig. 2
figure 2

GDP (in logs)

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Fig. 3
figure 3

CO2 emissions by economic sector (in logs)

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Congregado, E., Feria-Gallardo, J., Golpe, A.A. et al. The environmental Kuznets curve and CO2 emissions in the USA. Environ Sci Pollut Res 23, 18407–18420 (2016). https://doi.org/10.1007/s11356-016-6982-9

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Keywords

  • CO2 emissions
  • Growth
  • Cointegration
  • Time varying
  • Structural breaks
  • USA