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The impact of financial crises on the environment in developing countries

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Abstract

This paper evaluates empirically the effect of financial crises on several types of pollutant emissions. We focus on a sample of 55 developing countries from 1980 until 2012 and rely on the local projection method to plot impulse response functions. Our results show that financial crises lead to a fall in CO2 emissions. Moreover, systemic crises increase consumption-based emissions, which suggests that this type of crises encourages the consumption of goods with an inferior environmental quality. A country hit by a sovereign debt crisis, experiences an increase in emissions stemming from energy related activities or industrial processes. During bad times, financial crises positively affect both methane and nitrous oxide emissions. Finally, in countries under fiscal retrenchment, a financial crisis leads to a negative response of CO2 emissions.

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Notes

  1. The assessment of the output-emissions decoupling hypothesis has been done by several authors [e.g. Kriström and Lundgren (2005) for Sweden; Ajmi et al. (2015) for G7 countries; Doda (2014) for 81 countries; Cohen et al. (2018) for the top 20 emitters]. Others have focused on the validity testing of the so-called Environmental Kuznets Curve—see, e.g., Stern (2004) and Kaika and Zervas (2013a, b).

  2. The authors compare this effect to the effect on emissions after the oil crises in 1973 and 1979 which led to a permanent shift from oil to natural gases and meant a decrease in emissions. In contrast, the Asian financial crisis also led to a drop in global CO2 emissions that lasted post-crisis as a result of economic and political changes.

  3. This relatively uncharacteristic bounce back in emissions can be attributed to: (1) the globally coordinated action of central banks and initial fiscal stimulus; (2) the immediate easing of energy prices reducing pressure for structural changes in energy consumption; (3) the continuing and accelerated increase in coal-fired power (IEA 2013).

  4. For instance, a rise in German emissions in 2016 led to alarm in some circles that the country had “further dented” its chances of reaching its 2020 climate targets (Wettengel 2016).

  5. Leichenko et al. (2010) used the GFC as an example of the close linkage between globalization and climate change. Amann et al. (2009) provide estimates of greenhouse gas mitigation potentials and costs in different countries. They employ the IIASA’s Greenhouse gas-Air pollution Interactions and Synergies (GAINS) model. These types pf models have been applied before to identify cost-effective air pollution control strategies, and to study the co-benefits between greenhouse gas mitigation and air pollution control in Europe and Asia (Hordijk and Amann 2007; Tuinstra 2007).

  6. According to Giedraitis et al. (2010), the regional differences in the relationship between economic activity and CO2 emissions can partly be explained by the different marginal costs of reducing pollution. For industrial intensive economies the marginal costs of pollution reduction are much higher than for service-oriented economies. Combining this with the displacement effect (Stern 2004; Jaunky 2010) advanced countries can more easily lower emissions by displacing polluting intensive production to emerging and low income economies.

  7. Carbon lock-in refers to the difficulty to shift the economy and technological systems into a low-carbon path. Whereas traditional economic approaches emphasize the role of existing physical infrastructures and the long age of the capital stock in key sectors (energy production and transport), more recent “evolutionary” approaches consider a wide array of sources of carbon lock-in, including economic and non-economic barriers to changes in complex technological systems (Unruh 2000; Marechal 2007).

  8. Acemoglu and Robinson (2012) provide a sweeping account of the development of nations over millennia and how different crises or historical contingencies were often turning points that could substantially alter the trajectory of a country, locking them into a virtuous cycle of prosperity or sometimes having the opposite effect.

  9. Geels (2013) frames the relationship between the financial crises and sustainability transitions within a multi-level perspective (see also Geels 2002; Van Bree et al. 2010).

  10. Our results are robust even with the inclusion of LULUCF—see the Appendix Fig. 7. That said, Nitrous oxide and, to a large degree, methane are emitted by activities related to agriculture (we thank an anonymous referee for this comment). We estimated the baseline regression for financial crises adding up to two lags of the value-added in agriculture in percent of GDP (from the World Bank’s WDI) and while the IRF for nitrous oxide lost a bit of statistical significance at the end of the horizon, results remain qualitatively unchanged for methane.

  11. This procedure also overcomes the problem of fiscal foresight (Forni and Gambetti 2010; Leeper et al. 2013; Ben Zeev and Pappa 2014), because it aligns the economic agents’ and the econometrician’s information sets.

  12. The results do not qualitatively change for different values of δ > 0.

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Acknowledgements

The author is grateful to the editor and one anonymous referee for useful comments and suggestions on an earlier version of the paper. Thanks also go to Prakash Loungani for useful discussions. The usual disclaimer applies and any remaining errors are the author’s sole responsibility.

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Correspondence to João Tovar Jalles.

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Appendix

Appendix

1.1 List of countries

Turkey, South Africa, Argentina, Bolivia, Brazil, Chile, Colombia, Haiti, Honduras Mexico, Nicaragua, Peru, Jordan, Egypt, Yemen, Bangladesh, Cambodia, India, Indonesia, Lao P.D.R., Nepal, Pakistan, Philippines, Thailand, Vietnam, Cameroon, Chad, Congo, Rep., Congo, Dem. Rep., Ethiopia, Ghana, Côte d’Ivoire, Kenya, Madagascar, Mali, Morocco, Mozambique, Nigeria, Sudan, Tanzania, Uganda, Burkina Faso, Zambia, Kazakhstan, Bulgaria, Moldova, Russia, Tajikistan, China, Ukraine, Uzbekistan, Hungary, Lithuania, Poland, Romania.

See Tables 1 and 2.

See Figs. 7, 8, 9 and 10

Fig. 7
figure 7

Impulse responses of greenhouse gas emissions including land-use change and forestry

Fig. 8
figure 8

Impulse responses of emissions to different financial crises, emissions by economic sector, developing countries

Fig. 9
figure 9

Impulse responses of emissions to different financial crises, CO2 emissions by type of activity, developing countries

Fig. 10
figure 10

Impulse responses of emissions to different financial crises, state contingent using alternative measure of slack (Hamilton 2018 filter), developing countries

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Jalles, J.T. The impact of financial crises on the environment in developing countries. Ann Finance 16, 281–306 (2020). https://doi.org/10.1007/s10436-019-00356-x

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