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Would economic growth affect air pollution in light of the potential transatlantic trade and investment partnership?

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Abstract

This paper examines the impact of income per capita on five air pollutants, respectively. It employs a dataset of the twenty-eight EU members and of the U.S. over a twenty-five-year period. The results provide robust evidence consistent with the Environmental Kuznets Curve argument for CO2, CH4, and HFCs/PFCs/SF6, respectively. The results yield practically a monotonically increasing relationship between per capita income and per capita emissions of GHGs and N2O, respectively, when including the trade variables related to the possible implementation of the Transatlantic Trade and Investment Partnership. Thus, this study suggests that policymakers in both sides of the Atlantic could take into consideration that a future trade deal between the U.S. and the EU may contribute to increasing the depletion of the ozone layer.

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Notes

  1. For a recent and extensive review over the studies that test the empirical validity of the EKC for CO2, see Tables 1-5 of Shahbaz and Sinha (2019).

  2. It could be worth mentioning here that, to the best of our knowledge, the only paper that is inconsistent with the EKC argument for nitrous oxide is Och (2017). Using data for Mongolia during 1981-2012 time period, it finds evidence consistent with a U-shaped relationship between income and emissions of nitrous oxide. However, the current study is different from the latter one, not only because it uses a cross-country dataset over the 1989-2013 time period, but also because it employs a set a trade variables that are absent in Och (2017).

  3. However, the relevant studies have found turning points that are quite different from each other, depending on the type of econometric methods, sample and time period, measurement unit (i.e., total concentrations or emission levels) that each study has used.

  4. For an extensive literature review on the empirical validity of the EKC see Stern (1998), Stern (2004), Stern (2015), Copeland and Taylor (2004), Yandle et al. (2004).See also Table 1 in Pascalau and Qirjo (2017b). This Table provides a brief overview of some of the previous empirical studies that have found some evidence for the existence of the EKC. These studies are listed alphabetically according to the abbreviation of the pollutant (and alphabetically according to author’s last names for the same pollutant). All studies mentioned in Table 1 suggest that, at least partly, the differences in turning points could be due to the different sample sizes used. Further, one can conclude that in the case of CO2, the lowest turning point is indicated in Shafik and Bandyopadhyay (1992) and the highest one is described in Anjum et al. (2014).

  5. See also Pascalau and Qirjo (2017a), that is an earlier working paper version of Qirjo and Pascalau (2019), for even further details on all explanatory variables.

  6. More specifically, following Antweiler et al. (2001), Iit = 0.6 ∗ Iit− 1 + 0.3 ∗ Iit− 2 + 0.1 ∗ Iit− 3. The empirical section demonstrates the better measurement properties of this weighting scheme over an equally weighted one.

  7. Thus, for each EU member i, \(T_{i}=\left (\frac {X_{i}+M_{i}}{GDP_{i}}\right )\), where Xi and Mi denote each EU country’s exports and imports with the U.S., respectively. In the case of the U.S., \(X_{U.S.}={\sum }_{i}M_{i}\) and \(M_{U.S.}={\sum }_{i}X_{i}\), respectively. Thus, the measurement unit is as a percentage of GDP.

  8. \(E\left (Z_{it}\right )\in \left [CO_{2_{it}}, CH_{4_{it}}, GHGs_{it}, \left (HFC/PFC/SF_{6}\right )_{it}, N_{2}O_{it}\right ]\).

  9. In short, the FEH states that a capital-abundant country has a comparative advantage in the production of capital-intensive goods, which tend to pollute more than the labor-intensive goods do. The PHH1 states that one should observe an environmental degradation in the poor countries relative to the rich ones (see Antweiler et al. (2001)). The PHH2 dictates that the countries with more land per capita should act as pollution havens as a consequence of TTIP because they would have lax environmental regulations (see Frankel and Rose (2005)). All these three hypotheses are theoretically valid in accordance with the classical Heckscher-Ohlin theory of international trade.

  10. In all cases, the relative measures divide the respective measure for each EU country to that of the U.S. Thus, RKL, RI, and RLPC will be 1 in the case of the U.S. For more details, see Table 3 in Qirjo and Pascalau (2019).

  11. See Qirjo and Christopherson (2016) for more detailed explanations of the FEH and the PHH1.

  12. This result is available upon request to the authors.

  13. A separate table of cross-section dependence tests, which is available upon request to the authors, confirms that the pollutant measures are cross-dependent. We apply both the Pesaran et al. (2008) bias adjusted LM test as well as the cross-section dependence tests in Pesaran (2015). The latter test shows that the cross-section dependence effects in the residuals diminish in importance and significance when one employs a simple Fixed Effects regression with country and time fixed effects. The additional two regressions should alleviate any remaining concerns about the cross-section dependence in the residuals.

  14. The paper uses all three coefficients α1, α2 and α3 to compute the turning points, irrespective of their statistical significance.

  15. In the case of HFCs/PFCs/SF6, FEH verifies only when using a fixed effects framework with standard errors robust to cross-correlation and serial correlation effects.

  16. Note that according to the data available from the environmental sectors of the EU and the U.S. (see www.eea.europa.eu & www.epa.gov) the annual anthropogenic GHGs emissions during the 1990-2010 period consist of about 77% of CO2, 11% of CH4, 8% of N2O and 4% of F-gases

  17. Note that environmentalists believe that Nitrous Oxide is the dominant anthropogenic ozone-depleting substance emitted in the 21st century. For more details see Ravishankara et al. (2009), Del Grosso and Parton (2012), Portmann et al. (2012), Revell et al. (2012), Thomson et al. (2012), Ming et al. (2016), and Glarborg et al. (2018).

  18. In addition to all the variables in M2, an early version of this paper adds a measure of national inequality (the GINI coefficient) and a global government effectiveness (GE) proxy to capture the political economy effect of growth on pollution. It shows that both national inequality and global government effectiveness are not significant determinants of the shape of the EKCs for all pollutants mentioned in this paper. For more details see Pascalau and Qirjo (2017b).

  19. See Qirjo et al. (2020) for the impact of trade intensity, due to implementation of TTIP, on other air pollutants such SO2, SOx, NH3 etc... See also Qirjo et al. (2019) and Qirjo et al. (2020) for the environmental impact of Comprehensive Economic and Trade Agreement between Canada and the EU (CETA) on various air pollutants.

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  1. Department of Economics & Finance, SUNY Plattsburgh, 329 Au Sable Hall, 101 Broad St., Plattsburgh, NY, 12901, USA

    Dhimitri Qirjo & Razvan Pascalau

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  1. Dhimitri Qirjo
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  2. Razvan Pascalau
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Correspondence to Dhimitri Qirjo.

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Qirjo, D., Pascalau, R. Would economic growth affect air pollution in light of the potential transatlantic trade and investment partnership?. Int Econ Econ Policy 18, 127–156 (2021). https://doi.org/10.1007/s10368-020-00481-3

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