Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund

References

  • Agrawala, S., D. Dussaux and N. Monti, 2020. “What policies for greening the crisis response and economic recovery? Lessons learned from past green stimulus measures and implications for the COVID-19 crisis”, OECD Environment Working Papers, No. 164, OECD Publishing, Paris.

    • Search Google Scholar
    • Export Citation
  • Amendola, A., M. Di Serio, M. Fragetta, and G. Melina, 2020. “The Euro-Area Government Spending Multiplier at the Effective Lower Bound.” European Economic Review 127, 103480.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Andersen, K. G., Rambaut, A., Lipkin, W.I. et al., 2020. “The proximal origin of SARS-CoV-2,” Nature Medicine, 26: 450452.

  • Attenborough, D., 2020. “A Life on Our Planet: My Witness statement and a vision for the Future.” Grand Central Publishing.

  • Bai, J. and S. Ng, 2007. “Determining the Number of Primitive Shocks in Factor Models.” Journal of Business and Economic Statistics 25 (1), 5260.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Batini, N., 2019. “Reaping What We Sow.” International Monetary Fund, Finance and Development, December 2019.

  • Batini, N. (ed.), 2021. The Economics of Sustainable Food: Smart Policies for Health and The Planet. Washington D.C.: Island Press and International Monetary Fund.

    • Search Google Scholar
    • Export Citation
  • Batini, N. and B. Smith, 2021. “Regenerative ocean farming”. In Batini, N. (ed.), 2021. The Economics of Sustainable Food: Smart Policies for Health and The Planet. Washington D.C.: Island Press and International Monetary Fund.

    • Search Google Scholar
    • Export Citation
  • Bernanke, B. S., J. Boivin, and P. S. Eliasz, 2005. “Measuring the Effects of Monetary Policy: a Factor Augmented Vector Autoregressive (FAVAR) approach.” The Quarterly Journal of Economics 120, 387422.

    • Search Google Scholar
    • Export Citation
  • Berthélemy, M. and L. Escobar Rangel, 2015. “Nuclear reactors’ construction costs: The role of lead-time, standardization and technological progress,” Energy Policy, 82:118130.

    • Search Google Scholar
    • Export Citation
  • Bloomberg, 2019. BNEF’s New Energy Outlook 2019.

  • Bloomberg, 2020. Bloomberg Terminal (accessed multiple times during September 2020).

  • Bozuwa, J., Cha, J. M., Cohen, D. A., Fleming, B., Goodman, J., Johnson, A. E., Kammen, D. M., NoiseCat, J. B., Paul, M., Patel, R. et al., 2020. “A green stimulus to rebuild our economy: an open letter and call to action to members of congress.” Medium, 23 March 2020.

    • Search Google Scholar
    • Export Citation
  • Burke, M., S. M. Hsiang, and E. Miguel. 2015. “Global Non-Linear Effect of Temperature on Economic Production.” Nature 527(7577): 23539.

    • Search Google Scholar
    • Export Citation
  • Caggiano, G., E. Castelnuovo, V. Colombo, and G. Nodari, 2015. “Estimating Fiscal Multipliers: News From A Non-linear World.” Economic Journal 125 (584), 746776.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caggiano, G, E. Castelnuovo, and G. Pellegrino, 2017. “Estimating the Real Effects of Uncertainty Shocks at the Zero Lower Bound.” European Economic Review 100, 257272.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Canova, F. and M. Hamidi Sahneh, 2018. “Are Small-Scale SVARs Useful for Business Cycle Analysis? Revisiting Nonfundamentalness,” Journal of the European Economic Association, 16(4):10691093.

    • Search Google Scholar
    • Export Citation
  • Carney, Mark, 2021. Value(s): Building a Better World for All. New York: Public Affairs (Hatchet Group Books).

  • Christian, W., 2021. Opinion: An assault from all fronts on energy independence. Speech posted on Jan 5, 2021, Texas Railroad Commission. https://www.worldoil.com/news/2021/1/5/opinion-an-assault-from-all-fronts-on-energy-independence

    • Search Google Scholar
    • Export Citation
  • Clark, M. A., N. G. G. Domingo, K. Colgan, S. K. Thakrar, D. Tilman, J. Lynch, I. L. Azevedo, J. D. Hill, 2020. “Global food system emissions could preclude achieving the 1.5° and 2°C climate change targets.” Science, 370 (6157): 705708.

    • Search Google Scholar
    • Export Citation
  • Dasgupta, P. et al., 2021. Report of the independent Review on the Economics of Biodiversity led by Professor Sir Partha Dasgupta. London, UK: HM Treasury.

    • Search Google Scholar
    • Export Citation
  • E2-ACORE-CELI, 2020. Clean Jobs, Better Jobs: An examination of clean energy job wages and benefits. https://e2.org/reports/clean-jobs-better-jobs/

    • Search Google Scholar
    • Export Citation
  • Environment Protection Agency (EPA), 2020. Quantifying the Multiple Benefits of Energy Efficiency and Renewable Energy: A Guide for State and Local Governments.

    • Search Google Scholar
    • Export Citation
  • Eyraud, L., A. Wane, C. Zhang, and B. Clements, 2011. “Who’s Going Green and Why? Trends and Determinants of Green Investment,” IMF Working Paper 11/296 (Washington: International Monetary Fund).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Foley, J., K. Wilkinson, C. Frischmann, R. Allard, J. Gouveia, K. Bayuk, M. Mehra, E. Toensmeier, C. Forest, T. Daya, et al., 2020. The Drawdown Review (2020)-Climate Solutions for a New Decade. Project Drawdown.

    • Search Google Scholar
    • Export Citation
  • FOLU, 2019. Growing Better: Ten Critical Transitions toTransform Food and Land Use. https://www.foodandlandusecoalition.org/wp-content/uploads/2019/09/FOLU-GrowingBetter-GlobalReport.pdf

    • Search Google Scholar
    • Export Citation
  • FOLU, 2017. The Future of Food and Agriculture. Rome: FAO.

  • FOLU, 2020. The State of World Fisheries and Aquaculture. Rome: FAO.

  • Forni, M. and L. Gambetti, 2010. “Fiscal Foresight and the Effects of Government Spending.” CEPR Discussion Papers 7840, C.E.P.R. Discussion Papers.

    • Search Google Scholar
    • Export Citation
  • Forni, M., D. Giannone, M. Lippi, L. Reichlin, 2009. “Opening the black box: structural factor models with large cross sections,” Econometric Theory, 25 (2009), pp. 13191347.

    • Search Google Scholar
    • Export Citation
  • Fragetta, M. and E. Gasteiger, 2014. “Fiscal foresight, limited information and the effects of government spending shocks,” Oxford Bulletin of Economics and Statistics, 76 (5), pp.667692

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett-Peltier, H., 2017. “Green versus brown: Comparing the employment impacts of energy efficiency, renewable energy, and fossil fuels using an input-output model.” Economic Modelling, 61: 439447.

    • Search Google Scholar
    • Export Citation
  • Gates, B., 2021. How to Avoid a Climate Disaster: The Solutions We Have and the Breakthroughs We Need. Random House Large Print (Penguin Books).

    • Search Google Scholar
    • Export Citation
  • Georgieva, K., 2020. “The Long Ascent: Overcoming the Crisis and Building a More Resilient Economy.” Speech delivered for the 125th Anniversary of the London School of Economics on October 6, 2020. Washington D.C.: International Monetary Fund.

    • Search Google Scholar
    • Export Citation
  • Goldstein, J. S. and S. A. Qvist, 2019. A Bright Future: How Some Countries Have Solved Climate Change and the Rest Can Follow, New York, NY: Public Affairs.

    • Search Google Scholar
    • Export Citation
  • Gordon, R.J. and R. Krenn, 2010. “The End of the Great Depression 1939–41: Policy Contributions and Fiscal Multipliers,” NBER Working Paper, National Bureau of Economic Research.

    • Search Google Scholar
    • Export Citation
  • Grubler, A., 2010. “The costs of the French nuclear scale-up: A case of negative learning by doing.” Energy Policy, 38(9): 51745188.

    • Search Google Scholar
    • Export Citation
  • Helm, D., 2020. “The environmental impacts of the Coronoavirus.” Environment and Resource Economics, 76:2138.

  • Hepburn, C., O’Callaghan, B., Stern, N., Stiglitz, J., and Zenghelis, D., 2020. “Will COVID-19 fiscal recovery packages accelerate or retard progress on climate change?Smith School Working Paper 20–02.

    • Search Google Scholar
    • Export Citation
  • Intergovernmental Panel on Climate Change (IPCC), 2018. “Global warming of 1.5°C, Summary for Policymakers,” Intergovernmental Panel on Climate Change Working Group I, Geneva: IPCC: chapter 2:130 and chapter 5: 464–466 and 485.

    • Search Google Scholar
    • Export Citation
  • Intergovernmental Panel on Climate Change (IPCC), 2019. “Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems.” Geneva: IPCC.

    • Search Google Scholar
    • Export Citation
  • Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), 2019. “Global Assessment Report on Biodiversity and Ecosystem Services.” Bonn, Germany: IPBES.

    • Search Google Scholar
    • Export Citation
  • International Energy Agency, 2019. “The Future of Hydrogen. Seizing Today’s Opportunities.” IEA Technology Report. https://www.iea.org/reports/the-future-of-hydrogen

    • Search Google Scholar
    • Export Citation
  • International Energy Agency, 2019a. World Energy Investment 2019, Paris, www.iea.org/reports/world-energyinvestment-2019

  • International Energy Agency, 2019b. Nuclear Power in a Clean Energy System, Paris: IEA.

  • International Energy Agency 2020. World Energy Outlook 2020, Paris: IEA. https://www.iea.org/reports/world-energy-outlook-2020

  • International Energy Agency, 2020a. Nuclear Power-Tracking Report 2020, Paris: IEA.

  • International Energy Agency, 2020b. World Energy Investment 2020. https://webstore.iea.org/download/direct/3003?fileName=WEI2020.pdf

  • International Energy Agency, 2020c. Renewable Energy Market Update: Outlook for 2020 and 2021.

  • International Energy Agency, 2021. RTE and IEA publish study on the technical conditions necessary for a power system with a High Share of Renewables in France Towards 2050. https://www.iea.org/news/rte-and-iea-publish-study-on-the-technical-conditions-necessary-for-a-power-system-with-a-high-share-of-renewables-in-france-towards-2050

    • Search Google Scholar
    • Export Citation
  • International Atomic Energy Agency, 2009. “Nuclear Technology and Economic Development in the Republic of Korea.” Vienna: IAEA.

  • International Energy Agency (IEA) and OECD Nuclear Energy Association (OECD-NEA), 2020. “Projected Costs of Generating Electricity: 2020 Edition”. https://www.iea.org/reports/projected-costs-of-generating-electricity-2020

    • Search Google Scholar
    • Export Citation
  • International Fund for Agricultural Development (IFAD), 2019. 2019 Climate Action Report. Rome: IFAD.

  • International Monetary Fund, 2019. “How to Mitigate Climate Change.” Fiscal Monitor, October 2019. (Washington D.C.: International Monetary Fund).

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2020. “Mitigating Climate Change,” World Economic Outlook, Chapter 3. (Washington D.C.: International Monetary Fund.)

    • Search Google Scholar
    • Export Citation
  • International Monetary Fund, 2021. Fiscal Monitor Update (January 2021). Washington D.C.: International Monetary Fund.

  • International Renewable Energy Agency (IRENA), 2016. Renewable Energy: Measuring the Economics. https://www.irena.org/media/Files/IRENA/Agency/Publication/2016/IRENA_Measuring-the-Economics_2016.pdf

    • Search Google Scholar
    • Export Citation
  • International Renewable Energy Agency (IRENA) 2019. “Renewable Energy Now Accounts for a Third of Global Power Capacity”. https://www.irena.org/newsroom/pressreleases/2019/Apr/Renewable-Energy-Now-Accounts-for-a-Third-of-Global-Power-Capacity

    • Search Google Scholar
    • Export Citation
  • International Renewable Energy Agency (IRENA), 2020. IRENA Renewable Costing Alliance Dataset. http://costing.irena.org/irena-renewable-costing-alliance.aspx.

    • Search Google Scholar
    • Export Citation
  • Keynes, J. M., 1936. The General Theory of Employment, Interest and Money. London: Palgrave-MacMillan.

  • Kennedy, E. and T. Marting, 2016. “Biomimicry: Streamlining the Front End of Innovation for Environmentally Sustainable Products,” Research-Technology Management, 59(4):4048.

    • Search Google Scholar
    • Export Citation
  • Lazard Asset Management, 2020. Levelized Cost of Energy and Levelized Cost of Storage – 2020.

  • Lovering, J. R., A. Yip, T. Nordhaus, 2016. “Historical construction costs of global nuclear power reactors.” Energy Policy, 91:371382.

    • Search Google Scholar
    • Export Citation
  • McElwee, P., E. Turnout, M. Chiroleu-Assouline, J. Clapp, C. Isenhour, T. Jackson, E. Kelemen, D. C. Miller, G. Rusch, J. H. Spangenberg, A. Waldron, 2020. “Ensuring a Post-COVID Economic Agenda Tackles Global Biodiversity Loss,” One Earth, Perspectives, 3(4):448461.

    • Search Google Scholar
    • Export Citation
  • McKinsey & Co., 2020a. “Valuing nature conservation: A methodology for quantifying the benefits of protecting the planet’s natural capitalhttps://www.mckinsey.com/~/media/McKinsey/Business%20Functions/Sustainability/Our%20Insights/Valuing%20nature%20conservation/Valuing-nature-conservation.pdf

    • Search Google Scholar
    • Export Citation
  • McKinsey & Co., 2020b. “How a post-pandemic stimulus can both create jobs and help the climate.” www.mckinsey.com/~/media/McKinsey/Business%20Functions/Sustainability/Our%20Insights/How%20a%20post-pandemic%20stimulus%20can%20both%20create%20jobs%20and%20help%20the%20climate/How-a-post-pandemic-stimulus-can-both-create-jobs-and-help-the-climate.pdf

    • Search Google Scholar
    • Export Citation
  • Miller, D. C., A. Agrawal, and J. Timmons Roberts, 2012. “Biodiversity, Governance, and the Allocation of International Aid for Conservation.” Conservation Letters, https://doi.org/10.1111/j.1755–263X.2012.00270.x

    • Search Google Scholar
    • Export Citation
  • Mohr, M., 2005. “A Trend-Cycle(-Season) Filter,” ECB Working Paper, Frankfurt: European Central Bank.

  • MIT Energy Initiative (MITEI), 2018. The Future of Nuclear Energy in a Carbon-Constrained World. http://energy.mit.edu/news/mit-energy-initiative-study-reports-on-the-future-of-nuclear-energy/

    • Search Google Scholar
    • Export Citation
  • Muro, M., A. Tomer, R. Shivaram, J. Kane, 2019. “Advancing Inclusion Through Clean Energy Jobs,” Metropolitan Policy Program at Brookings.

    • Search Google Scholar
    • Export Citation
  • NERA, 2017. “Impacts of Greenhouse Gas Regulations on the Industrial Sector.” Report prepared for the American Council for Capital Formation Center for Policy Research. https://www.globalenergyinstitute.org/sites/default/files/NERA percent20Finalpercent20Reportpercent202.pdf

    • Search Google Scholar
    • Export Citation
  • Nuclear Energy Institute, 2014. White Paper on Nuclear Energy’s Economic Benefits — Current and Future. Washington D.C.: Nuclear Energy Institute.

    • Search Google Scholar
    • Export Citation
  • OECD, 2020. Biodiversity and the economic response to COVID-19: Ensuring a green and resilient recovery. https://www.oecd.org/coronavirus/policy-responses/biodiversity-and-the-economic-response-to-covid-19-ensuring-a-green-and-resilient-recovery-d98b5a09/

    • Search Google Scholar
    • Export Citation
  • OECD, 2020a. “A Comprehensive Overview of Global Biodiversity Finance”. https://www.oecd.org/environment/resources/biodiversity/report-a-comprehensive-overview-of-global-biodiversity-finance.pdf

    • Search Google Scholar
    • Export Citation
  • OECD Nuclear Energy Agency (OECD-NEA), 2019. “The Costs of Decarbonization: System Costs with High Shares of Nuclear and renewables.” https://www.oecd-nea.org/jcms/pl_15000/the-costs-of-decarbonisation-system-costs-with-high-shares-of-nuclear-and-renewables

    • Search Google Scholar
    • Export Citation
  • Oxford Economics, 2019. “Nuclear Power Pays—Assessing the Trends in Electric Power Generation Employment and Wages.”

  • Paulson Institute-The Nature Conservancy-Cornell University, 2020. Financing Nature: Closing the Global Biodiversity Financing Gap. Washington D.C.: The Paulson Institute.

    • Search Google Scholar
    • Export Citation
  • Pollin, R., J. Heintz, and H. Garrett-Peltier, 2009. “The Economic Benefits of Investing in Clean Energy.” Department of Economics and Political Economy Research Institute (PERI), University of Massachusetts, Amherst.

    • Search Google Scholar
    • Export Citation
  • Ramey, V.A. and S. Zubairy, 2018. “Government spending multipliers in good times and in bad: evidence from U.S. historical data.” Journal of Political Economy, 126 (2): 850901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rockström, R., J., Gaffeny, O. et al, 2017. A Roadmap for Rapid Decarbonization, Science, 355(6331): 12691271.

  • Searchinger, T. D., C. Malins; P. Dumas, D. Baldock, J. Glauber, T. Jayne, J. Huang, P. Marenya, 2020. “Revising Public Agricultural Support to Mitigate Climate Change. Development Knowledge and Learning.” Washington, DC: World Bank.

    • Search Google Scholar
    • Export Citation
  • Seddon N., E. Daniels, R. Davis, R. Harris, X. Hou-Jones, S. Huq, V. Kapos, G.M. Mace, A.R. Rizvi, H. Reid, D. Roe, S. Wicander, 2020. “Global recognition of the importance of nature-based solutions for climate change adaptation.” Global Sustainability 3 2020, e15.

    • Search Google Scholar
    • Export Citation
  • Stiglitz, J., 2020. Green Dealing – The Green Recovery Event, Project Syndicate, October 15, 2020. https://www.project-syndicate.org/videos/green-dealing-the-green-recovery-event?referral=d582d5

    • Search Google Scholar
    • Export Citation
  • Stock, J. H. and M. W. Watson, 2005. Implications of Dynamic Factor Models for VAR Analysis. NBER Working Papers 11467.

  • S&P Global Platts, 2020. World Electric Power Plants Database. Washington D.C.: Platts.

  • Turnhout, E., P. McElwee, M. Chiroleu-Assouline, J. Clapp, C. Isenhour, E. Kelemen, T. Jackson, D. C. Miller, G. M. Rusch, J. H. Spangenberg, A. Waldron, 2021. “Enabling Transformative Economic Change in the Post-2020 Biodiversity Agenda” (forthcoming).

    • Search Google Scholar
    • Export Citation
  • United Nations (UN), 2020a. Message by the Secretary General António Guterres on the occasion of the International Earth Day, April 22, 2020. https://www.un.org/en/observances/earth-day/message

    • Search Google Scholar
    • Export Citation
  • United Nations (UN) 2020b. Climate Action. “Biodiversity and Nature-Based Solutions”. https://www.un.org/en/climatechange/climate-solutions/biodiversity-and-nature-based-solutions

    • Search Google Scholar
    • Export Citation
  • United Nations Environment Programme (UNEP), 2020. “10 Things You Should Know About Industrial Farming.” Nairobi, Kenya: UNEP. https://www.unep.org/news-and-stories/story/10-things-you-should-know-about-industrial-farming

    • Search Google Scholar
    • Export Citation
  • United Nations Environment Programme-United Nations Development Programme-Food and Agriculture Organization (UNEP-UNDP-FAO), 2021. Global Report on Fiscal Reform for Sustainable Agriculture. Nairobi: UNEP.

    • Search Google Scholar
    • Export Citation
  • VividEconomics, 2020. The Greenness for Stimulus Index Report. https://www.vivideconomics.com/casestudy/greenness-for-stimulus-index/

  • Waldron, A. et al., 2013. “Targeting global conservation funding to limit immediate biodiversity declines.” Proceedings of the National Academy of Sciences USA 110: 1214412148.

    • Search Google Scholar
    • Export Citation
  • Waldron, A., Miller, D., Redding, D. et al., 2017. “Reductions in global biodiversity loss predicted from conservation spending.” Nature, 551: 364367.

    • Search Google Scholar
    • Export Citation
  • Waldron et al., 2020. “Working paper analyzing the economic implications of the proposed 30% target for areal protection in the draft post-2020 Global Biodiversity Framework”. https://www.conservation.cam.ac.uk/files/waldron_report_30_by_30_publish.pdf

    • Search Google Scholar
    • Export Citation
  • Walley, N. and B. Whitehead, 1994. “It’s Not Easy Being Green”, Harvard Business Review, May-June 1994.

  • Willett, W., Rockström, J., Loken, B., Springmann, M., et al, 2019. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems, EAT-Lancet EAT–Lancet Commission on healthy diets from sustainable food systems.

    • Search Google Scholar
    • Export Citation
  • Wiser, R., and M. Bolinger, 2017. 2016 Wind Technologies Market Report. U.S. Department of Energy.

  • World Economic Forum (WEF), 2020. “Nature Risk Rising:Why the Crisis Engulfing Nature Matters for Business and the Economy.” In collaboration with PwC. New Nature Economy series. Geneve, Switzerland: WEF.

    • Search Google Scholar
    • Export Citation
  • World Nuclear Association, 2020. “Employment in the Nuclear and Wind Electricity Generating Sectors.” WNA Report No. 2020/006.

  • World Resource Institute (WRI), 2020a. “4 Charts Explaining Greenhouse Gas Emissions by Country and Sector.” Blogpost by Mengpinge and Johannes Fredrich. https://www.wri.org/blog/2020/02/greenhouse-gas-emissions-by-country-sector

    • Search Google Scholar
    • Export Citation
  • World Resource Institute (WRI), 2020b. “10 Charts Show the Economic Benefits of US Climate Action.” Blogpost by Joel Jaeger and Devashree Saha. https://www.wri.org/blog/2020/07/economic-benefits-climate-action-us

    • Search Google Scholar
    • Export Citation
  • Zhu L., P. Ciais, Z. Deng, R. Lei, S. J. Davis, S. Feng, B. Zheng, D. Cui, X. Dou, B. Zhu, et al. 2020. “Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.” Nature Communications,, 11 (1).

    • Search Google Scholar
    • Export Citation

Appendix

A. Data

A.1 Endogenous Variables

Our variables of interest are gross domestic product and, depending on the specification, total investments, renewable energy investments, non-eco-friendly energy investments, nuclear energy investments, green land use spending, non-eco-friendly land use spending.

Data on clean renewable energy and non-eco-friendly energy investments come from the International Energy Agency. Data on nuclear energy investments were assembled specifically for this project by the OECD’s Nuclear Energy Agency in collaboration with the World Nuclear Association and the International Atomic Energy Agency. Green land use spending data were updated starting from the work of Waldron et al (2013, 2017). Non-eco-friendly land use spending data are based on an elaboration of OECD producer support estimates (PSE) and assembled by Searchinger et al. in 2020 for the World Bank Group. Gross domestic product and total investments are downloaded from the IMF’s World Economic Outlook database.

All series are transformed in real terms using the implicit GDP price deflator. Then, they are normalized by diving by real potential GDP.

The time span and the set of countries included in the analysis depend on the availability of data. Specifically:

  • for clean renewable energy and non-eco-friendly energy investments specifications, dataset includes China, Japan, Korea, Canada, United States, Brazil, Indonesia, Mexico, Russia, Oceania group (Australia and New Zealand) and EA group (France, Germany and Italy), for a time span that goes from 2003 to 2019;

  • for nuclear energy investments specification dataset includes China, France, Japan, Korea, Canada and United States, for a time span that goes from 1991 to 2017;

  • for green land use spending specification dataset includes Burkina Faso, Burundi, Cambodia, Cameroon, Central African Republic, Chad, Ghana, Guatemala, Malawi, Mozambique, Niger, Senegal, Sierra Leone, Madagascar, Tanzania and Uganda, for a time span that goes from 1994 to 2008;

  • for non-eco-friendly land use spending specification dataset includes China, Japan, Korea, Canada, United States, Australia, Chile, Indonesia, Mexico, New Zealand, Russia, South Africa, Colombia, Iceland, Israel, Kazakhstan, Norway, Switzerland, Turkey and Ukraine, for a time span that goes from 1997 to 2016.

A.2 Exogenous Variables

Regarding specifications that include clean renewable energy investments, non-eco-friendly energy investments and nuclear energy investments, we use as exogenous variables the forecast of the total investments made at time t-1 for time t, provided by IMF’s World Economic Outlook.

A.3. Informational Dataset

The informational dataset used to extract common factors consists of 12 series for each country downloaded from IMF’s World Economic Outlook and Thomson Reuters Datastream Economics databases. The choice of the time series to include in the informational dataset is dictated by their availability for all countries and for all periods included in the analysis.

The following variables were downloaded for each country considered:

  • National Account: Government Consumption Expenditure; Total Government Revenue; Export of Goods and Services; Imports of Goods and Services; Final Consumption Expenditure of Households; Gross National Saving.

  • Output: Industrial Production Index (not available for Green Land Use Dataset); Change in Inventories.

  • Employment: Employees Domestic Concept.

  • Exchange rates: Real Effective Exchange Rates (not available for Green Land Use Dataset).

  • Money and credit quantity aggregates: Broad Money or Money Supply M0, M1, M2, M3 (depending on the availability).

  • Price indexes: Consumer Price Index.

Where appropriate we transform variables to guarantee stationarity tested by the Phillips and Perron (1986) and Kwiatkowski et al. (1992) tests.

1

We thank Michel Berthélemy (OECD-Nuclear Energy Agency) for providing nuclear energy investment data. We are deeply indebted to Greg Kaser, Philippe Costes and King Lee (all World Nuclear Association), as well as to Victoria Alexeeva Bertrand Magné, Henri Paillere and Aliki Van Heek (all International Atomic Energy Agency) for the illuminating discussions on nuclear energy data and the sector more generally. We are indebted to Joshua Goldstein and Steffan Qvist who helped us contact them. We also thank Michael Waldron and Pablo Gonzalez at the International Energy Agency for providing us with data on supply and power generation of both clean and fossil fuel energy. In addition, we are grateful to Tim Searchinger and Chris Malins for providing broken down data from their 2020 World bank paper on agricultural subsidies and explaining methodologies to us. Dan Miller kindly agreed that we used the global dataset that he originally produced on conservation spending and was later used for publications in Nature and PNAS. Conversations with Frank Hawkins, Thomas Lovejoy, Juha Siikamaki, John Tobin, Andrew Karolij, Michael Jenkins, Patrick McGuire and Charlotte Kaiser helped us navigate in the ‘jungle’ of global conservation finance. Hanbo Hi provided excellent research assistance in collecting macroeconomic data. Financial support by UK’s FCDO is gratefully acknowledged. We are grateful also to Roberto Buizza, Andrea Roventini, the Dasgupta Review team, and many IMF and World Bank colleagues for their useful comments. All errors are our own.

3

See Seddon et a l. (2020) for a definition of NBSs.

4

Some have argued that because it produces radioactive waste, nuclear power should be excluded from a ny green spending concept. However, past IMF studies on green energy, including the recent 2019 Fiscal Monitor have included investment in nuclear power among sources of green energy because, like here, the definition of what constitutes ‘green’ energy has been based on the impact of the investment on gas emissions. See also Eyraud et a l. (2011).

5

As part of the Paris Agreement in 2015 countries agreed to a common goal of limiting the rise in global temperatures this century to “well below” 2 degrees Celsius, with an aim of keeping the increase at 1.5 degrees.

6

Estimates by the IPCC indicate that when all is accounted for, the agri-food sector is potentially responsible for well over a third of greenhouse gas emissions (IPCC, 2019).

7

Most biodiversity is found in lower-income tropical countries where international aid, given almost entirely by OECD countries, forms the majority of funding for biodiversity conservation. Average a id to biodiversity for 2013–17 was US$6.3 billion per year, representing just 0.01% of the OECD’s GDP of US$47 billion (Turnhout et a l., 2021).

8

Note that spending on energy and land use differ because the former involves considerably more infrastructure spending, whereas the latter relies almost entirely on operational capital and smaller infrastructure/machinery investment, generally. Subsidies to land use/agriculture involve some support to the purchase of investment goods but also other categories of spending like price support, support for the purchase of seeds, insurance, etc. In addition, subsidies to land use (green or brown) tend to be spent by the public sector, which is not the case for spending on green or brown energy which is largely private.

9

Geothermal energy is heat derived within the sub-surface of the earth. Water and/or steam carry the geothermal energy to the Earth's surface. Depending on its characteristics, geothermal energy can be used for heating and cooling purposes or be harnessed to generate clean electricity.

10

Marine energy or marine power (also sometimes referred to as ocean energy, ocean power, or marine and hydrokinetic energy) refers to the energy carried by ocean waves, tides, salinity, and ocean temperature differences.

11

The IEA indicates for example, in the case of wind farms, that by leveraging upon latest technological advances, repowering allows not only to “increment the nameplate capacity of an existing wind farm, but also to enhance load factors and to reduce operation and maintenance costs. This is mainly driven by larger turbines and increased hub heights that allow production of a greater amount of power with a smaller number of turbines” (IEA, 2020b).

12

Investment estimates draw on IEA analysis on annual capacity additions and unit investment costs, partly derived from surveys with industry, IEA (2019a), S&P Global Platts (2020), BNEF (2020), IRENA (2020) and other organizations. More details can be found in IEA’s methodological annex to the IEA’s 2020 World Energy Report.

13

Where possible, past investments in transmission and distribution assets, are based in publicly available data from utilities, regulators and other domestic entities.

14

OCC should not be confused with another popular measure of “cost” namely the Levelized Cost of Electricity (LCOE). It is the total cost to build and operate a power plant over its lifetime divided by the total electricity output dispatched from the plant over that period, hence typically cost per megawatt hour. It takes into account the financing costs of the capital component (not just the ‘overnight’ cost). This other metric reflects the ‘total average cost per KWh’ but does not reflect the total cost of electricity/services provided. Importantly, note that when comparing nuclear and renewables such as solar and wind, system costs should also be considered, as discussed in recent studies from the OECD-NEA (2019) and MITEI (2018) because when the share of wind/solar grows above approximately 1/3 of the electricity mix, the system costs grows exponentially and outweigh the advantage of cheap solar/wind.

15

Investment estimates reflect IEA analysis on annual capacity additions and u nit investment costs, derived in part from surveys with industry, IEA (2019), S&P Global Platts (2020), BNEF (2020), IRENA (2019) and other organizations.

16

The way the IEA measures investment across various energy sectors varies reflecting differences in the availability of data and the nature of expenditures. More details can be found in the World Energy Investment 2020 Methodology Annex.

17

These countries include Australia, Canada, Chile, China, Colombia, Iceland, Indonesia, Israel, Japan, Kazakhstan, Korea, Mexico, New Zealand, Norway, Russia, South Africa, Switzerland, Turkey, Ukraine, and the United States.

18

More details on the methodology employed by the OECD to produce PSE data can be found here: http://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/documents/producer-support-estimates-manual.pdf

19

Since we cannot derive analytical solutions for the impulse responses, we perform Monte Carlo simulation considering 20,000 parameters draw and discarding the first 10000 draw as burn-in.

20

For the sake of simplicity, we prefer to use the terminology of statistical significance, in analogy to the frequentist approach to inference. However, the Bayesian approach formally leads to credible intervals around the estimates. We consider “significant” those multipliers with credible intervals, delimited by the 16th and the 84th percentiles, that exclude zero.

21

For example this includes the construction and the maintenance of infrastructure such as fences, boardwalks, observation platforms, and other durable machinery such as communication equipment and optical devices for distant viewing, vehicles or satellite monitoring and GPS tracking devices necessary to perform conservation services.

22

Input/output models link various sectors of the economy—agriculture, construction, government, households, manufacturing, services and trade—and trace how spending flows among those various sectors. An input/output model also includes geographic linkages, and shows how spending flows at national, state and county levels.

23

GDP and GVA multipliers differ in derivation. The GDP multiplier describes the total output generated as a result of $1 of output in the target industry; the GVA multipliers instead describes the additional value added generated in the economy by spending $1 of direct value added . Gross value added provides a dollar value for the amount of goods and services that have been produced in a country, minus the cost of a ll inputs and raw materials that are directly attributable to that production. It thus corresponds to the difference between gross and net output.

24

The analysis focuses on four broad categories of clean energy spending, namely: Industry (improve industrial energy efficiency; build carbon-capture-and-storage infrastructure); Buildings (retrofit houses for energy efficiency; install smart-building systems; Energy (reinforce the electricity-distribution grid; expand energy storage; accelerate build-out of wind and solar power; accelerate rollout of LED street lighting); Transport (expand electric-vehicle charging networks; create bus rapid transit and urban rail schemes; scale up electric-vehicle manufacturing; develop active-transport infrastructure).

25

Labor income is a subset of the total economic value or output.

26

The estimates are calculated per megawatt of installed capacity and reflect a nominal 1,000-megawatt plant size. In practice, new nuclear plants are larger than 1,000 megawatts, so the economic benefits understate the benefits that new nuclear plants will produce.

Building Back Better: How Big Are Green Spending Multipliers?
Author: Nicoletta Batini, Mario di Serio, Matteo Fragetta, and Mr. Giovanni Melina