Policy Research Working Paper 10759 A Global Incentive Scheme to Reduce Carbon Emissions Somik V. Lall Raghuram Rajan Christian Schoder Development Economics A verified reproducibility package for this paper is Development Policy Team available at http://reproducibility.worldbank.org, April 2024 click here for direct access. Policy Research Working Paper 10759 Abstract This paper proposes an objective way of estimating and allo- United States and China are the two biggest emitters and, cating “differentiated” responsibilities for carbon emissions assuming a Global Carbon Incentive of $10, they jointly across countries. These responsibilities translate into specific would contribute more than $70 billion to the fund, from obligations and incentives for future emission reductions which nations such as India, Nigeria, Pakistan, Bangladesh, and support for adaptation, mitigation, and development. and Indonesia would be the major recipients. An important The proposals in this paper should be seen as a starting point adjustment to the Global Carbon Reduction Incentive is to for an informed and productive debate. Under the Global focus on consumption rather than production—a country Carbon Reduction Incentive, every country that emits more should not avoid responsibility for the carbon it consumes than the per capita global average pays into a global incen- by outsourcing production to another country. The pro- tive fund. This annual payment will be calculated based on posal considers that countries that have used more of the the “excess” emissions per capita, the country’s population, collective carbon budget have benefited from the associated and a dollar amount called the Global Carbon Incentive. development and should pay for it. The proposal also con- Countries below the global per capita average would receive siders methane emissions as well as crediting countries for a payout commensurate with their “under-emission.” The their efforts toward preventing deforestation. This paper is a product of the Development Policy Team, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at raghuram.rajan@chicagobooth.edu and slall1@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click here for direct access. RESEA CY LI R CH PO TRANSPARENT ANALYSIS S W R R E O KI P NG PA The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team A Global Incentive Scheme to Reduce Carbon Emissions1 Somik V. Lall, Raghuram Rajan, and Christian Schoder JEL classification: F30, F55, Q56 Keywords: greenhouse gas emissions, global warming, international financial institutions 1 Somik Lall is an Economic Adviser at the World Bank, Raghuram Rajan is the Katherine Dusak Miller Distinguished Service Professor of Finance at the University of Chicago, and Christian Schoder is an Economist at the World Bank. The authors thank Baris Tercioglu for excellent research assistance, and Indermit Gill and Ayhan Kose for helpful discussions. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Author for correspondence: Rajan < raghuram.rajan@chicagobooth.edu> Motivation The 1992 UN Rio Summit concluded that countries had a common but differentiated responsibility to tackle greenhouse gas (GHG) emissions – common in that climate change affects everyone, and differentiated because countries have different responsibilities for creating the problem, as well as differing abilities to resolve it. Thirty years on, in its report released in April 2022 (IPCC 2022), the Intergovernmental Panel on Climate Change highlights the urgency of steep emissions reductions to keep global warming from reaching 1.5°C above pre-industrial levels.2 Ideally, the allocation of responsibilities would be within a framework that provides sufficient incentives to achieve this target. Unfortunately, there is no agreement on how to allocate responsibilities. Clearly, Uganda, which emits 0.1 ton per capita of carbon per year (in 2018), has much less responsibility both for the carbon that is already in the atmosphere and for what continues to be pumped out than the US, which emits 16 tons per capita per year.3 And the US has more responsibility than the EU, which emits 6.4 tons per capita. Yet the EU has committed to cut its 1990 emission levels by at least 55 percent by 2030, while the Biden administration wants only to halve its 2005 emissions by 2030. And of course, there are no penalties if a country fails to adhere to commitments. Without international agreements that set out clear rewards and penalties, policy commitments are not credible. This impedes the low-carbon transition, which is largely driven by private sector expectations about future carbon prices and technological change. Forward guidance and expectations management can be effective instruments to promote the low-carbon transition. By making “excess emissions” costly, the Global Carbon Reduction Incentive GCRI could serve as a 2 The report finds that limiting future emissions to 300 Gt CO2 will be required to ensure the 1.5° ceiling with high probability. 3 Hallegatte et al (2023) find that the global emissions increase associated with eradicating extreme poverty is small -- global energy emissions would need to be reduced by 2.08 GtCO2e per year, instead of 2.0 GtCO2e per year in the absence of any progress towards extreme poverty eradication. 2 simple institutional arrangement to improve the credibility of policy commitments. In fact, it can help mobilize the private sector in hastening mitigation of GHG emissions. Emission rights are a form of property right held against the planet. The weaker a country’s commitment to reduce emissions, the more rights it claims. Collectively, countries have claimed significantly more emission rights than is consistent with the 1.5°C ceiling, and there is no agreement on how to limit these self-claimed rights. Relatedly, in 2009 in Copenhagen, high-income countries promised to channel US$100 billion a year to less wealthy nations by 2020, to help them adapt to climate change and mitigate further rises in temperature. The promise was vague in that it was not clear whether these would be grants and subsidies, or simply financing at market rates. It was made vaguer still because it did not specify who would put up the money. In sum, an objective way of estimating and allocating “differentiated” responsibility is needed, which can then translate into specific obligations (as well as specific support for adaptation and mitigation) and policy incentives. Absent such an objective measure, action plans will tend to be based on domestic political compulsions and fiscal space rather than the planet’s needs, with substantial amounts of free-riding. Worse, it is likely that the principle of “common but differentiated” goes by the wayside as the imperative to avoid climatic catastrophe looms larger. This paper outlines the desirable characteristics of any scheme that allocates responsibility and provides incentives for future climate action. It continues by describing a few schemes that satisfy these characteristics and highlighting the key parameters about which international negotiations should be most concerned. These include the issue of consumption- versus production-based emissions, the balance between considering past and future emissions, and what type of emissions are included. Finally, the paper offers some preliminary calculations on how these schemes would affect different countries. 3 1. Desirable Characteristics of a Responsibility Allocation and Incentive Scheme Desirable characteristics of a responsibility allocation and incentive scheme include fairness, forward-looking orientation, efficiency, ease of operation and flexibility, and ease of decentralization. Fairness High-income countries have put much of the carbon that already exists into the air. And they are still emitting more per capita than many low-income countries. To the extent that the right to emit is a property right held by each individual on the planet,4 high-income countries have a greater responsibility to curtail emissions, both because they have used up more of their property right (assuming an overall budget of emissions rights that would take the world to 1.5°C), and they continue to emit more. Having become rich partly based on past emissions, they also have the wealth to pay for adaptation and mitigation. In sum, any scheme to allocate responsibility should do so based on emissions, past and present. It should also help raise the $100 billion annually that has been promised. Ahluwalia and Patel (2021) make a case to allocate the available carbon budget in a demonstrably fair manner into individual country budgets, with each country defining its own emission trajectory to stay within its carbon budget. Dasgupta, Lall, and Wheeler (2022) consider equity considerations from a historical perspective going back to 1900; they show that 60 percent of high- income countries have already exceeded their carbon budgets (based on population shares). The United States crossed its per capita allocation in 1945, the United Kingdom in 1947, and Germany in 1956. 4 Our focus on fairness based on individuals rather than nations is consistent with the treatment of climate equity by Stern (2007), Mattoo and Subramaniam (2013) and many others. 4 Forward-Looking Orientation Making the payment scheme dependent only on past or present emissions addresses the objective of fairness, but penalizing past behavior may not provide strong incentives for future decarbonization. Hence, the payment scheme should have a forward-looking element which includes future emissions in the payment scheme. This would imply that the scheme is rolled out over time with periodic payments which depend on historic emissions and the recent performance. Balancing the historical-responsibility and incentive aspects of the scheme would be an important parameter subject to international negotiations. Efficiency It is important that the world economizes on costs. One way to get efficient outcomes is for all countries to be faced with the same price of emissions. So, Europe scrapes coal plants because the price of carbon emissions is high there, while Uganda builds them because the price of carbon emissions is low there. Unequal incentives can also breed resentment. Workers in coal-fired utilities in high-income countries that are being closed will not be happy if they see such utilities being opened in low- income countries. Unfortunately, emissions are still not priced in a consistent manner across as well as within countries (Agnolucci et al, forthcoming). Ease of Operation and Flexibility Any scheme has to be easy to operationalize and monitor. Overly complicated schemes can be hard to communicate to the public, whose buy-in is essential. Difficulties in measuring inputs and outputs can lead to gaming and evasion, reducing fairness and efficiency. It will also increase operational costs for the scheme, reducing the funds that can be devoted to adaptation and mitigation. The scheme should also be flexible. If the world is emitting much more than consistent with the 1.5°C ceiling, it should be easy to ramp up the incentive by increasing the price of “excess” emissions without detailed global renegotiation. Conversely, if technological change significantly reduces the costs of emissions, it should be possible to dial down incentives equally easily. Ideally, the scheme should be self-adjusting based on objective measures. 5 Ease of Decentralization Countries are not ready for a one-size-fits-all scheme. Some may want to impose a carbon tax, while a carbon tax may be politically impossible in other countries. Conversely, emissions regulation or a ban on coal use may be more easily implemented in those countries. At any rate, countries should have the flexibility, within the umbrella of the scheme, to experiment with what works best in their countries. Experimentation and innovation could result in better practices for mitigation that could spread across countries. 2. Possible Schemes A variety of schemes that satisfy these desired criteria are possible. These could be thought of as variations on a common theme, with extensions or alternatives addressing different concerns. Global Carbon Reduction Incentive The starting point is that every individual has the implicit right to emit at the world per capita emission level. Of course, “under-emitting” countries should not be incentivized to increase their emissions, while “excess emission” countries should reduce them. Hence, embedding incentives is key. Every country that emits more than the per capita world average (currently around 5 tons) would pay into a global incentive fund. This annual payment would be calculated by multiplying the excess emissions per capita by the country’s population and a dollar amount called the Global Carbon Incentive. So if the country’s population is 30 million, its per capita emission is 17 tons, and the Global Carbon Incentive (GCI) is set at $10, it would pay $30 million*(17-5)*10= $3.6 billion. Countries below the global per capita average would receive a payout commensurate with their “under-emission”. A country of 40 million emitting 2 tons per capita would receive $40 million*(5-2)*10= $1.2 billion. The fund is completely self-financing by design – what is paid in exactly equals what is paid out (assuming administrative costs are negligible). Note that the $10 GCI is set for illustrative purposes and future research should compute an optimal rate balancing political feasibility and sufficient incentives. 6 Importantly, every country would face a loss of $10 per capita for every ton by which they increase per capita emissions, whether they are at a high, low, or average level today. So Uganda has the same incentives to economize on emissions as the United States because the payment Uganda receives from the fund would fall commensurately if it increased per capita emissions. Moreover, this scheme addresses the equity problem. Low emitters, which are often the poorest countries and most endangered by climatic changes they did not cause, get a payment, which they can use to help their people adapt. The Global Carbon Reduction Incentive (GCRI) scheme also assigns responsibility for payments in a feasible way: the big emitters typically have the ability to pay. This approach is consistent with the broader principle of common but differentiated responsibilities (see also Mattoo and Subramaniam 2013). Of course, what a country does domestically is entirely its own business. Instead of levying a politically unpopular carbon tax, one country may impose prohibitive regulations on coal, while another may levy taxes on energy inputs and a third may incentivize renewables. Each one does it their own way, with the GCRI supplementing any moral incentives they already have to act at the country level. The GCRI does not snuff out domestic experimentation. Incentives can be enhanced, or softened, simply by changing the amount of the GCI. It could be increased if the urgency for action increases. It can be reduced if some miraculous technological breakthrough occurs on emission reduction. To avoid creating uncertainty, after an initial period of calibration, any change in the GCI could be contemplated only every 3 years or so. The process of adjustment can also be automated by allowing the GCI to depend on the available carbon budget in a transparent way. The annual payments/receipts by each country for a GCI of $10 are listed in Annex Table A. Table 1 presents the GCI payments and receipts for the top 10 countries. The biggest net payers are the United States and China, while the biggest net receivers are India, Nigeria, Pakistan, Bangladesh, and Indonesia. For a GCI of $10 per ton, the total payments are $133 billion (and, obviously, the receipts by carbon under-emitters are the same). Countries such as France and the UK, with per capita emissions close to the global average pay small amounts --- $0.29 billion and $0.84 billion, respectively. Countries such as Sweden, with per capita emissions below the global average, would in fact be a net recipient. To get a payment of $100 billion by the excess emitters, the GCI could be reduced to $7.5 per ton. 7 Tax or incentive US Deviation from global PRODUCTION CO2 POP 2019 Per Capita CO2 Billions (valuing COUNTRY average (per capita CO2 - (MIL TONS) (millions) (production) 'excess' emissions at 4.61 tons/person) USD 10 per ton) United States 5,291.77 325.03 16.28 11.67 37.92 China 10,053.86 1,420.67 7.08 2.46 34.96 Russian Federation 1,651.85 145.48 11.35 6.74 9.80 Japan 1,172.92 127.46 9.20 4.59 5.85 Saudi Arabia 639.54 33.05 19.35 14.74 4.87 Korea, Rep. 649.98 51.06 12.73 8.11 4.14 Canada 572.77 36.73 15.60 10.98 4.03 Germany 769.54 82.66 9.31 4.69 3.88 Iran, Islamic Rep. 683.75 80.69 8.47 3.86 3.11 Australia 412.90 24.58 16.80 12.19 2.99 Kazakhstan 299.67 18.07 16.58 11.97 2.16 Tanzania 11.35 54.70 0.21 -4.41 -2.41 Philippines 131.31 105.14 1.25 -3.37 -3.54 Congo, Dem. Rep. 2.55 81.46 0.03 -4.58 -3.73 Brazil 498.47 207.80 2.40 -2.22 -4.61 Ethiopia 14.96 106.43 0.14 -4.48 -4.76 Indonesia 592.60 264.58 2.24 -2.38 -6.29 Bangladesh 81.50 159.67 0.51 -4.11 -6.55 Pakistan 216.57 207.95 1.04 -3.57 -7.43 Nigeria 120.27 190.96 0.63 -3.99 -7.61 India 2,462.08 1,338.48 1.84 -2.78 -37.16 Table 1: The Global Carbon Reduction Incentive – payments and receipts for the top 10 countries Source: Author calculations based on ‘Our World in Data‘ (https://ourworldindata.org/). Modification 1: Consumption versus Production An important adjustment to the GCRI is to focus on consumption rather than production – a country should not avoid responsibility for the carbon it consumes by outsourcing production to another country. So, the proposal adds the carbon embedded in imported goods and subtracts the 8 carbon embedded in exported goods from the carbon produced by a country. For a country like China, CO2 emissions based on production are 10 billion tons and fall to 9 billion tons when a consumption-based measure is used. In the United States, 5.2 billion tons of CO2 are “produced” and 5.6 billion tons are “consumed”. This exercise is carried out for all countries where these data are available through Our World in Data (https://ourworldindata.org/). The results are presented in Annex Table A. With the consumption-based emissions, China’s payments decline significantly – from USD 35 billion to USD 20 billion. This adjustment does not materially impact other countries. Modification 2: Stock of Carbon Emitted The proposal has ignored the stock of emissions thus far. Some countries would argue that they should not be held responsible for emissions when there was little knowledge that emissions were damaging. Others would argue that regardless of foreknowledge, countries that have used more of the collective carbon budget have benefited from the associated development and should pay for it. A middle ground may be sensible here, backing out the stock of carbon emitted thus far, with 1990 as the start year. This is well into a timeframe where high- and low-income countries alike were aware of climate change; the Rio Earth Summit was held in 1992. One could follow the same principle as above and argue that every individual today has the right to have emitted the average stock of carbon between 1990 and today (again, the fund can consider either carbon production emissions or carbon consumption emissions). So excess emission countries will be those whose per capita average is more than the global per capita average stock emitted between 1990 and today.5 The last question is what rate the excess stock of emissions should attract. Given that this one-off payment will not change any incentive to act (since the emissions have already occurred), its value can be debated. Arguably, the cost of additional emissions should grow as the carbon budget shrinks, so emissions in the past ought to be costed at a lower rate than current emissions. What payments are required with a “moderate” rate of $0.3 /ton and how does this compare to a GCI of $10/ton? Once again, this would be a one-off payment rather than a recurring payment, though it 5 An alternative would be to calculate country payments each year if the GCRI scheme were in operation since 1990 and cumulate the payments. This more detailed calculation takes into account the variation in population over time, as well as allows for possible variation in the GCI. 9 is also possible to consider amortizing the payment over say 20 years and adding it to the annual GCRI payments. Table 2 presents the payments and receipts for the top 10 countries; Annex Table Deviation from global Tax or incentive CO2 Stock (MIL Population Per Capita CO2 COUNTRY average (per capita CO2 (valued at 0.3 USD TONS) 2019 (millions) stock Stock) per ton) US Billions United States 167,927.36 329.06 510.32 400.17 39.50 Russian Federation 49,909.67 145.87 342.15 232.00 10.15 China 184,376.75 1,433.78 128.59 18.45 7.94 Japan 36,938.62 126.86 291.18 181.03 6.89 Germany 26,251.71 83.52 314.33 204.18 5.12 Canada 16,332.75 37.41 436.58 326.43 3.66 Korea, Rep. 14,869.02 51.23 290.27 180.12 2.77 Saudi Arabia 12,329.56 34.27 359.79 249.65 2.57 United Kingdom 15,728.91 67.53 232.92 122.77 2.49 Australia 10,982.38 25.20 435.75 325.61 2.46 Viet Nam 3,004.90 96.46 31.15 -78.99 -2.29 Congo, Dem. Rep. 64.39 86.79 0.74 -109.40 -2.85 Philippines 2,392.64 108.12 22.13 -88.01 -2.85 Brazil 11,339.75 211.05 53.73 -56.41 -3.57 Ethiopia 198.21 112.08 1.77 -108.38 -3.64 Bangladesh 1,273.65 163.05 7.81 -102.33 -5.01 Indonesia 11,061.53 270.63 40.87 -69.27 -5.62 Nigeria 2,530.88 200.96 12.59 -97.55 -5.88 Pakistan 4,005.61 216.57 18.50 -91.65 -5.95 India 41,536.37 1,366.42 30.40 -79.75 -32.69 B provides the full list. Table 2: The Global Carbon Reduction Incentive, modifying for carbon stocks– payments and receipts for the top 10 countries valued at 0.3 USD per ton Source: Author calculations based on ‘Our World in Data‘ (https://ourworldindata.org/). The key finding of the GCRI based on production-related carbon stocks is that the rankings for both payers and recipients do not change much compared to the GCRI based on annual emissions. The United States and the Russian Federation are the top contributors based on stock values. China is the third largest contributor. Yet, the net contributions of China decrease drastically from $35 billion to $8 billion. The cumulative emissions since the 1990s have been low in China compared to the US and Russia. These numbers are computed using a production-based approach. With the consumption-based approach (reported in the Annex), however, China moves from paying into the fund to becoming a recipient. 10 Modification 3: Accounting for Methane Methane is a major greenhouse gas. Following the same logic as with CO2, the deviation of the country (per capita) emissions and stocks from the global average can be calculated for each country. Excess emissions or deviations were multiplied by the country’s population and the GCI. The results are reported in Annex Table C. To the extent that methane is more problematic than carbon for climate change, the GCI could be set higher. Per capita methane emissions are over four times the global average in Australia, Canada, New Zealand, and Russia. Countries such as France, Germany, and the UK have per capita emissions lower than the global average. In addition, the price of the excess stock emitted since 1990 can be calculated. Annex Table D reports the results. In terms of methane emissions, Russia takes the lead as the main emitter. With a stock-based approach, emissions of Brazil and Australia become more significant. China is the second largest recipient following India if only methane emissions are considered. Modification 4: Forestry One large carbon sink is a country’s forests. Bastin et al. (2019) use spatially granular data to estimate forest restoration potential across the globe and find room for an additional 0.9 billion hectares of forest cover, which could store about 750 Gt of CO2 at maturity. To the extent that a country has protected its forests, given its stage of development and its population density, it should get some credit for it.6 To objectively compute a measure for ‘excess’ forest cover, the proposed framework predicts a baseline forest cover in a country given its natural environment and initial forest endowment (in 1990) as well as hard-to-control factors like its stage of development (e.g., more agriculture means less forest cover), and its population (larger population for a given terrain means less forest cover). The actual forest cover less the predicted forest cover is the ‘excess’ forest cover that the country should get credit for. Using a conversion rate for how much carbon is stored per square km of forest, the total tons of carbon stored in the 6 The point here is that countries with a natural propensity for forest cover should not receive credit for their natural endowments. 11 ‘excess’ forest can be obtained. It is important to note that the carbon absorption quality of forests varies across countries; the proposal accounts for these differences using the Global Forest Resources Assessment data of the FAO. 7 For example, a sq km of forest in India stores 4,100 tons of CO2. In Brazil, that figure is 12,100 tons; in Indonesia it is 13,800 tons. The CO2 equivalent of excess forest can be priced at the GCI to get an excess forestry benefit for a country. Of course, the specific model used to determine the predicted area of forests needs to be worked out. A potential first pass is in Annex 1 which computes the CO2 stored by the ‘excess’ forest in 2019 controlling for a country’s income level, population density, temperature and precipitation, land area, agricultural land, and forest endowment in 1990. Table 3 highlights the top 10 countries that could be credited for forestry based on our first approximation estimates.8 China leads the way. Its initial forest coverage was around 1.6 million sq km in 1990. Given its zChina to have around 1.8 million sq km of forest in 2019. Its actual forest cover in 2019, however, is around 2.2 million sq km. Hence it overperformed compared to the global average, making it eligible for USD 0.36 billion as credit using a GCI of USD 0.3 per ton. The key finding is that measures that protect forest cover, over and beyond a country’s development, natural endowment and demography, have only a limited impact in offsetting carbon emissions. The change in the stock of emissions since 1990 is mostly the result of rapidly increasing production and consumption of carbon. 7 http://countrystat.org/home.aspx?c=FOR. 8 Countries could also be credited at the GIC rate on a flow basis for the carbon absorbed annually by their “excess” forests. This would create an additional incentive to maintain, or even expand, forest cover. These calculations can be done using the methods already outlined. 12 Table 3: Forestry Credits for top 10 countries valued at 0.3 USD per ton Credit ($ Billions) Forest Forest performance Valuing Forest coverage coverage 2019 Predicted (deviations from excess stock 1990 (000's of sq (000's of sq forest (000s regression predictions - CO2 equivalents at $0.3 per Country km) km) Of sq km) 000's of sq km) (mil tons) ton China 1,571.41 2,180.99 1,779.76 401.23 1,203.68 0.36 India 639.38 718.94 595.92 123.01 504.36 0.15 Viet Nam 93.76 145.67 92.53 53.14 382.64 0.11 Mexico 705.92 658.20 605.16 53.04 169.73 0.05 Congo, Rep. 223.15 219.61 172.90 46.71 714.72 0.21 Gabon 237.62 235.42 189.51 45.91 564.71 0.17 Spain 139.05 185.68 141.08 44.60 102.57 0.03 Guyana 186.02 184.25 147.88 36.36 389.10 0.12 Thailand 193.61 199.09 164.29 34.80 160.08 0.05 Colombia 649.58 593.41 563.36 30.06 336.63 0.10 Implementation Once the broad contours of the framework are decided, some structures will have to be put in place. 1) The process of measuring actual carbon emissions by a country will have to be standardized. As with the calculation of any aggregates like GDP, there will have to be some assumptions as well as the use of rules of thumb. Since these decisions will imply actual money gained or lost by a country, it is best that these be set by a small independent technical group or secretariat. Further, advances in satellite image processing have made it possible to accurately measure carbon and methane in near real time. NASA’s OCO-2 and OCO-3 instruments, the European Space Agency’s METOP-A and TROPOMI (Sentinel-5P) platforms, China’s TANSAT, and the Japan Space Exploration Agency’s GOSAT and GOSAT-2 can be tapped for accurate and independent measurement (Dasgupta et al 2021). 2) There will be a debate about whether countries that are poorly governed should receive payments. In general, so long as there is a functioning government that is not kleptocratic, payments should not be withheld. If there is no government that meets these minimum conditions, payment could be held in trust by the World Bank for when such a government emerges. Furthermore, there should be no presumption that payments would be used for 13 climate adaptation or mitigation – some countries may decide to invest more in schooling or in poverty relief. 3) Parameters like the value of the GCI for carbon or methane could be decided periodically (say every 3-5 years). Better still, they could be tied to the remaining emission budget in a transparent way. 3. Political Feasibility Clearly, large emitters have a disincentive to bind themselves to make payments. They may also have little ability to bind successor governments. Yet, if the world is to make some collective headway on climate change, governments have to make costly commitments that may be unappealing to successor governments – this problem is not specific to the proposed schemes. While the political infeasibility of any climatic action is clear, the existential cost of inaction is equally clear. Furthermore, the issue of differentiated responsibility cannot be avoided. Fuzzy unenforceable long-term commitments need to be transformed into short-term specific obligations. The more these short-term obligations are obtained through simple transparent calculations, the more legitimacy the global community will have in requiring they be adhered to. The proposals in this paper should be seen as a starting point for an informed, and hopefully productive, debate. References Agnolucci, Paolo, Carolyn Fischer, Dirk Heine, Mariza Montes de Oca León, Kathleen Patroni, Joseph Pryor, and Stéphane Hallegatte. Forthcoming. “Measuring Total Carbon Pricing.” World Bank, Washington, DC. Ahluwalia, M. S., & Patel, U. 2022. Climate Change Policy for Developing Countries (CSEP Working Paper 23). New Delhi: Centre for Social and Economic Progress. Bastin, J-F., Y. Finegold, C. Garcia, D. Mollicone et al. 2019. The global tree restoration potential. Science, 365(6448): 76-79. 14 Dasgupta, S., Lall, S, and Wheeler, D. 2021. Urban CO2 Emissions : A Global Analysis with New Satellite Data. Policy Research working paper,no. WPS 9845 Washington, D.C. : World Bank Group. Dasgupta, S., Lall, S, and Wheeler, D. 2022. Who is Accountable for Climate Change? History and Equity in Carbon Budget Allocation, mimeo, World Bank. Hallegatte, S., Wolburg, P., and Mahler, D. 2023. The Climate Implications of Ending Global Poverty. World Bank. Mattoo, A. and Subramanian, A. 2013. Greenprint: a new approach to cooperation on climate change. Center for Global Development. Stern, N. 2007. The Economics of Global Climate Change: The Stern Review. Cambridge University Press. 15 Annex: Forestry In considering country-specific efforts to protect, one needs to control for a country’s natural forest propensity, as well as account for forest ‘consumption’ as part of a country’s development trajectory. One also needs to consider economic geography in terms of the density of settlements. The regression model outlined here seeks to identify a measure of “excess forestation” for every country i. Excess forestation is the difference between the observed forest cover in 2019 (forest19i) (sq kms) and a hypothetical share in 2019 predicted by the regression model. Hence, excess forestation for country i is simply the residual, ui, of the regression model: forest19i = α + Xiβ + ui (1) where α is the intercept and β is a vector of coefficients for controls of interest. The key question is on the choice of control variables that should be included in Xi. What are the main drivers of (de)forestation? • Log of per-capita GDP (incomei): Richer countries are expected to have smaller forest shares if they exploited forests during earlier stages of development. Yet this relationship is non-linear with faster deforestation in low-income countries (which may rely on forest resources) than in high-income countries. Hence, the specification also includes this variable with a squared term. The variables are averages over the last 5 years to flatten out business cycle fluctuations. • Population density (population_densityi): Countries with higher population densities may need to expand into the forest frontier to accommodate its residents – the evidence from the urban literature suggests that cities around the world expand at the extensive margin as incomes and populations increase (Lall et al 2021). • Precipitation (Annual_precipi) and temperature (Annual_tempi): They both capture climatic properties. While it may be preferred to use measures reflecting agroclimatic zones, considerable heterogeneity within large countries makes it difficult to assign specific zones to a country. • Share of agricultural land (agricultural_landi): Agriculture is a main driver of deforestation. Variants of the specification have also considered urban density, education, real effective exchange rates, and the share of services as a proxy for structural change. Yet, these variables were statistically insignificant and did not change R2 considerably. Hence, they are excluded from the final specifications. All data have been obtained from the World Bank’s World Development Indicators. The regression model above seeks to explain the forest coverage by various explanatory variables. Yet, if countries are rich today, have a high population density, or have a high share of agriculture, they could have reduced their forest shares many decades, even centuries ago. While it may be useful to consider natural propensity for a country to have forest cover, such historic data are challenging to collect for a large sample of countries. Further, since much of the work in the paper 16 takes 1990 as a starting point and the interest lies in forestation ambitions in recent decades, 1990 is taken as the cut-off year. Hence, the specification includes an additional regressor: • Forest cover in 1990 (forest90i): This variable controls for both the country’s natural inclination to forests (jointly with precipitation and temperature) and the deforestation before 1990. In this case, the residuals can be interpreted as the change in forest over since 1990 above or below what the economic and climatic regression model would predict. Countries with a positive (negative) residual have increased (reduced) forest cover since 1990 relative to the model’s prediction, and excess forestation is positive (negative). After estimating countries’ excess forestation and deforestation, these values expressed in sq km of land area are converted to CO2 equivalents. The carbon stock in living forest biomass data of the FAO provides the conversion rates. These data express carbon stock per hectare of forest for each country. The reference year to convert forest area in square km to CO2 equivalent is 2010. Countries with forest cover less than 5 percent of land area are dropped from the analysis as their residuals were noisy. 17 18 Annex Table A: Annual payments/receipts by each country for a GCI of $10 and $7.5. Valuing 'excess' Valuing 'excess' emissions at $7.5 per ton emissions at $10 per -- compatible with a ton $100 B fund Deviation Payments Deviation from global Payments or Payments Per Per from global average or CO2 Receipts Payments or CO2 Capita Capita average (per (per capita Receipts consumpti (consump or Receipts Receipts ECONOMY production CO2 CO2 capita CO2 CO2 (producti on (mil tion (productio (consump (mil tons) (product (consum production - consumptio on based) tons) based) n based) tion ion) ption) 4.61 n 4.9 USD USD based) tons/person) tons/perso Billions Billions n) United States 5,291.77 5,635.92 16.28 17.34 11.67 12.44 37.92 40.42 28.44 30.31 China 10,053.86 8,999.52 7.08 6.33 2.46 1.43 34.96 20.32 26.22 15.24 Russian Federation 1,651.85 1,419.53 11.35 9.76 6.74 4.85 9.80 7.06 7.35 5.30 Japan 1,172.92 1,341.14 9.20 10.52 4.59 5.62 5.85 7.16 4.38 5.37 Saudi Arabia 639.54 663.66 19.35 20.08 14.74 15.18 4.87 5.02 3.65 3.76 Korea, Rep. 649.98 691.55 12.73 13.54 8.11 8.64 4.14 4.41 3.11 3.31 Canada 572.77 572.67 15.60 15.59 10.98 10.69 4.03 3.93 3.02 2.94 Germany 769.54 861.69 9.31 10.42 4.69 5.52 3.88 4.56 2.91 3.42 Iran, Islamic Rep. 683.75 638.57 8.47 7.91 3.86 3.01 3.11 2.43 2.33 1.82 Australia 412.90 385.69 16.80 15.69 12.19 10.79 2.99 2.65 2.25 1.99 Kazakhstan 299.67 238.79 16.58 13.21 11.97 8.31 2.16 1.50 1.62 1.13 South Africa 463.93 328.49 8.14 5.76 3.52 0.86 2.01 0.49 1.51 0.37 Taiwan, China 279.71 272.16 11.82 11.50 7.20 6.59 1.70 1.56 1.28 1.17 Poland 326.39 292.55 8.60 7.71 3.98 2.80 1.51 1.06 1.13 0.80 United Arab Emirates 181.69 212.70 19.12 22.38 14.50 17.48 1.38 1.66 1.03 1.25 Malaysia 256.77 249.98 8.25 8.04 3.64 3.13 1.13 0.97 0.85 0.73 Qatar 100.15 67.32 36.93 24.82 32.32 19.92 0.88 0.54 0.66 0.41 United Kingdom 392.03 542.39 5.88 8.13 1.26 3.23 0.84 2.15 0.63 1.61 Netherlands 160.87 151.39 9.45 8.90 4.84 3.99 0.82 0.68 0.62 0.51 Kuwait 95.92 89.91 23.75 22.26 19.13 17.36 0.77 0.70 0.58 0.53 Italy 352.20 458.56 5.81 7.56 1.19 2.66 0.72 1.61 0.54 1.21 Czechia 105.22 104.80 9.89 9.85 5.27 4.94 0.56 0.53 0.42 0.39 Spain 265.66 281.18 5.69 6.02 1.08 1.12 0.50 0.52 0.38 0.39 Belgium 100.07 173.10 8.77 15.16 4.15 10.26 0.47 1.17 0.36 0.88 Turkmenistan 71.48 12.42 7.80 0.45 0.34 Oman 61.89 64.91 13.33 13.98 8.71 9.07 0.40 0.42 0.30 0.32 Trinidad and Tobago 41.20 29.18 29.78 21.10 25.16 16.19 0.35 0.22 0.26 0.17 Türkiye 405.34 422.21 5.00 5.21 0.39 0.31 0.31 0.25 0.23 0.19 Mongolia 43.81 38.98 14.08 12.52 9.46 7.62 0.29 0.24 0.22 0.18 France 327.76 432.67 5.06 6.68 0.44 1.77 0.29 1.15 0.21 0.86 Iraq 201.21 5.37 0.75 0.28 0.21 19 Austria 67.54 92.84 7.66 10.53 3.04 5.62 0.27 0.50 0.20 0.37 Bahrain 32.70 18.17 21.79 12.11 17.18 7.20 0.26 0.11 0.19 0.08 Libya 54.79 8.31 3.70 0.24 0.18 Israel 61.20 78.36 7.42 9.50 2.81 4.60 0.23 0.38 0.17 0.28 Greece 71.75 59.61 6.79 5.64 2.17 0.74 0.23 0.08 0.17 0.06 Ukraine 227.11 207.78 5.11 4.67 0.49 -0.23 0.22 -0.10 0.16 -0.08 Singapore 46.64 110.84 8.18 19.43 3.56 14.53 0.20 0.83 0.15 0.62 Norway 44.42 48.92 8.39 9.24 3.78 4.34 0.20 0.23 0.15 0.17 Finland 44.88 64.96 8.15 11.79 3.53 6.89 0.19 0.38 0.15 0.28 Ireland 38.89 41.94 8.17 8.81 3.55 3.91 0.17 0.19 0.13 0.14 Belarus 60.00 62.67 6.35 6.63 1.73 1.73 0.16 0.16 0.12 0.12 New Zealand 35.90 38.91 7.64 8.28 3.02 3.37 0.14 0.16 0.11 0.12 Bulgaria 45.44 39.55 6.40 5.57 1.78 0.66 0.13 0.05 0.10 0.04 Venezuela, RB 146.10 162.84 4.98 5.55 0.36 0.64 0.11 0.19 0.08 0.14 Estonia 16.51 17.10 12.51 12.95 7.89 8.05 0.10 0.11 0.08 0.08 Slovak Republic 35.02 46.78 6.43 8.59 1.81 3.68 0.10 0.20 0.07 0.15 Hong Kong SAR, China 42.57 107.72 5.82 14.74 1.21 9.83 0.09 0.72 0.07 0.54 Denmark 34.51 50.41 6.02 8.80 1.40 3.89 0.08 0.22 0.06 0.17 Brunei Darussalam 8.72 9.33 20.55 21.99 15.94 17.09 0.07 0.07 0.05 0.05 Luxembourg 9.40 23.06 15.90 38.97 11.28 34.07 0.07 0.20 0.05 0.15 Bosnia and Herzegovina 21.79 6.49 1.87 0.06 0.05 Equatorial Guinea 11.20 8.87 4.26 0.05 0.04 Serbia 45.58 5.16 0.55 0.05 0.04 New Caledonia 5.98 21.58 16.96 0.05 0.04 Slovenia 14.23 18.50 6.85 8.91 2.24 4.01 0.05 0.08 0.03 0.06 Curacao 4.95 30.58 25.96 0.04 0.03 Portugal 51.42 55.86 5.00 5.43 0.38 0.52 0.04 0.05 0.03 0.04 Hungary 48.33 64.87 4.97 6.67 0.35 1.76 0.03 0.17 0.03 0.13 Iceland 3.57 10.67 6.05 0.02 0.00 0.02 Cyprus 7.31 7.66 6.20 6.50 1.58 1.59 0.02 0.02 0.01 0.01 Guadeloupe 2.50 6.25 1.63 0.01 0.00 Martinique 2.29 6.08 1.47 0.01 0.00 Bahamas, The 2.31 6.05 1.43 0.01 0.00 Sint Maarten (Dutch part) 0.74 17.89 13.27 0.01 0.00 Faeroe Islands 0.68 14.09 9.47 0.00 0.00 Lithuania 13.57 21.77 4.77 7.65 0.15 2.75 0.00 0.08 0.00 0.06 Aruba 0.88 8.34 3.73 0.00 0.00 Bermuda 0.64 10.14 5.52 0.00 0.00 Greenland 0.54 9.53 4.92 0.00 0.00 Bonaire Sint Eustatius and Saba 0.34 13.41 8.80 0.00 0.00 Palau 0.21 11.96 7.35 0.00 0.00 Andorra 0.48 6.20 1.58 0.00 0.00 Seychelles 0.54 5.62 1.01 0.00 0.00 20 Anguilla 0.15 10.05 5.44 0.00 0.00 Turks and Caicos Islands 0.22 6.01 1.39 0.00 0.00 Antigua and Barbuda 0.49 5.13 0.51 0.00 0.00 British Virgin Islands 0.18 6.17 1.56 0.00 0.00 Saint Pierre and Miquelon 0.06 10.65 6.04 0.00 0.00 Montserrat 0.04 7.02 2.41 0.00 0.00 Nauru 0.05 5.16 0.55 0.00 0.00 Niue 0.01 5.34 0.72 0.00 0.00 Saint Kitts and Nevis 0.24 4.61 -0.01 0.00 0.00 Cook Islands 0.07 4.25 -0.36 0.00 0.00 Saint Helena 0.01 1.97 -2.64 0.00 0.00 Liechtenstein 0.15 4.00 -0.62 0.00 0.00 Tuvalu 0.01 0.63 -3.98 0.00 0.00 Barbados 1.23 4.31 -0.31 0.00 0.00 Marshall Islands 0.15 2.52 -2.10 0.00 0.00 Suriname 2.50 4.38 -0.24 0.00 0.00 Dominica 0.17 2.34 -2.28 0.00 0.00 Grenada 0.29 2.61 -2.01 0.00 0.00 Saint Vincent and the Grenadines 0.23 2.13 -2.49 0.00 0.00 Tonga 0.14 1.35 -3.27 0.00 0.00 Saint Lucia 0.50 2.74 -1.88 0.00 0.00 Malta 1.58 5.16 3.62 11.79 -1.00 6.88 0.00 0.03 0.00 0.02 Kiribati 0.06 0.54 -4.07 0.00 0.00 French Polynesia 0.79 2.85 -1.76 0.00 0.00 French Guiana 0.71 2.58 -2.04 -0.01 0.00 Montenegro 2.28 3.63 -0.98 -0.01 0.00 Samoa 0.24 1.22 -3.39 -0.01 0.00 Maldives 1.56 3.15 -1.46 -0.01 -0.01 São Tomé and Príncipe 0.13 0.61 -4.01 -0.01 -0.01 Mayotte 0.30 1.18 -3.44 -0.01 0.00 -0.01 Switzerland 37.94 118.28 4.49 14.00 -0.13 9.09 -0.01 0.77 -0.01 0.58 Chile 84.16 91.87 4.56 4.97 -0.06 0.07 -0.01 0.01 -0.01 0.01 Belize 0.63 1.67 -2.94 -0.01 -0.01 Vanuatu 0.16 0.54 -4.07 -0.01 -0.01 Guyana 2.33 3.00 -1.61 -0.01 -0.01 Croatia 18.02 21.30 4.31 5.09 -0.31 0.19 -0.01 0.01 -0.01 0.01 Mauritius 4.40 5.51 3.48 4.36 -1.14 -0.55 -0.01 -0.01 -0.01 -0.01 Latvia 7.44 12.52 3.81 6.41 -0.80 1.51 -0.02 0.03 -0.01 0.02 Cabo Verde 0.56 1.05 -3.57 -0.02 -0.01 Bhutan 1.34 1.80 -2.81 -0.02 -0.02 North Macedonia 7.30 3.51 -1.11 -0.02 -0.02 Solomon Islands 0.29 0.46 -4.16 -0.03 -0.02 21 Fiji 1.33 1.52 -3.10 -0.03 -0.02 Sweden 42.50 70.03 4.29 7.07 -0.32 2.17 -0.03 0.21 -0.02 0.16 Comoros 0.25 0.31 -4.31 -0.04 0.00 -0.03 Botswana 6.66 17.46 3.02 7.91 -1.60 3.00 -0.04 0.07 -0.03 0.05 Djibouti 0.41 0.43 -4.18 -0.04 -0.03 Eswatini 0.99 0.88 -3.74 -0.04 -0.03 Lebanon 26.68 3.95 -0.67 -0.05 -0.03 Gabon 4.91 2.38 -2.23 -0.05 -0.03 Timor-Leste 0.53 0.42 -4.19 -0.05 -0.04 Jamaica 8.01 8.83 2.74 3.02 -1.87 -1.88 -0.05 -0.05 -0.04 -0.04 Namibia 4.06 8.99 1.69 3.74 -2.93 -1.16 -0.07 -0.03 -0.05 -0.02 Lesotho 2.36 1.13 -3.49 -0.07 -0.05 Panama 11.13 23.94 2.71 5.83 -1.90 0.92 -0.08 0.04 -0.06 0.03 Armenia 5.51 5.76 1.87 1.96 -2.74 -2.95 -0.08 -0.09 -0.06 -0.07 Guinea-Bissau 0.30 0.17 -4.45 -0.08 -0.06 Azerbaijan 37.27 39.72 3.79 4.04 -0.83 -0.87 -0.08 -0.09 -0.06 -0.06 Georgia 10.12 11.27 2.52 2.81 -2.09 -2.09 -0.08 -0.08 -0.06 -0.06 Albania 4.78 5.79 1.66 2.01 -2.96 -2.90 -0.09 -0.08 -0.06 -0.06 Uruguay 6.51 11.41 1.89 3.32 -2.72 -1.59 -0.09 -0.05 -0.07 -0.04 Gambia, The 0.54 0.24 -4.37 -0.10 -0.07 Lao PDR 19.23 18.95 2.77 2.73 -1.85 -2.18 -0.13 -0.15 -0.10 -0.11 Moldova 5.10 1.26 -3.36 -0.14 -0.10 Romania 76.03 76.83 3.87 3.91 -0.75 -0.99 -0.15 -0.20 -0.11 -0.15 Costa Rica 8.14 12.83 1.64 2.59 -2.97 -2.31 -0.15 -0.11 -0.11 -0.09 Eritrea 0.72 0.21 -4.40 -0.15 -0.11 Mauritania 3.28 0.77 -3.85 -0.16 -0.12 Kyrgyzstan 10.40 16.23 1.68 2.62 -2.94 -2.28 -0.18 -0.14 -0.14 -0.11 Argentina 183.97 188.83 4.19 4.30 -0.43 -0.61 -0.19 -0.27 -0.14 -0.20 West Bank and Gaza 3.09 0.65 -3.97 -0.19 -0.14 Jordan 25.29 33.84 2.60 3.48 -2.02 -1.43 -0.20 -0.14 -0.15 -0.10 Congo, Rep. 3.53 0.69 -3.93 -0.20 -0.15 Liberia 1.19 0.25 -4.36 -0.21 -0.15 Central African Republic 0.20 0.04 -4.57 -0.21 -0.16 El Salvador 6.51 8.41 1.02 1.32 -3.60 -3.59 -0.23 -0.23 -0.17 -0.17 Tunisia 29.38 27.81 2.57 2.43 -2.05 -2.47 -0.23 -0.28 -0.18 -0.21 Dominican Republic 25.08 26.61 2.39 2.53 -2.23 -2.37 -0.23 -0.25 -0.18 -0.19 Nicaragua 5.45 6.44 0.85 1.01 -3.76 -3.90 -0.24 -0.25 -0.18 -0.19 Paraguay 7.67 11.06 1.12 1.61 -3.50 -3.29 -0.24 -0.23 -0.18 -0.17 Cuba 25.57 2.26 -2.36 -0.27 -0.20 Bolivia 23.07 22.46 2.06 2.01 -2.55 -2.90 -0.29 -0.32 -0.21 -0.24 Papua New Guinea 6.48 0.77 -3.85 -0.32 -0.24 Togo 2.20 7.09 0.29 0.92 -4.33 -3.98 -0.33 -0.31 -0.25 -0.23 Tajikistan 7.47 0.84 -3.77 -0.34 -0.25 22 Sierra Leone 0.92 0.12 -4.49 -0.34 -0.25 Honduras 9.76 11.91 1.03 1.26 -3.58 -3.64 -0.34 -0.34 -0.25 -0.26 Algeria 156.34 3.78 -0.84 -0.35 -0.26 Uzbekistan 109.13 3.41 -1.20 -0.38 -0.29 Ecuador 38.84 46.60 2.31 2.78 -2.30 -2.13 -0.39 -0.36 -0.29 -0.27 Thailand 280.58 277.88 4.06 4.02 -0.56 -0.89 -0.39 -0.61 -0.29 -0.46 Benin 6.69 8.70 0.60 0.78 -4.02 -4.13 -0.45 -0.46 -0.34 -0.35 Haiti 3.08 0.28 -4.34 -0.48 -0.36 South Sudan 1.56 0.14 -4.47 -0.49 -0.37 Burundi 0.55 0.05 -4.56 -0.49 -0.37 Syrian Arab Republic 30.13 1.74 -2.88 -0.50 -0.37 Guinea 3.17 3.17 0.26 0.26 -4.35 -4.64 -0.53 -0.56 -0.39 -0.42 Rwanda 1.07 1.07 0.09 0.09 -4.53 -4.82 -0.54 -0.58 -0.41 -0.43 Zimbabwe 11.07 12.47 0.78 0.88 -3.84 -4.03 -0.55 -0.57 -0.41 -0.43 Guatemala 18.12 22.84 1.07 1.35 -3.54 -3.55 -0.60 -0.60 -0.45 -0.45 Senegal 10.64 11.05 0.69 0.72 -3.93 -4.19 -0.61 -0.65 -0.45 -0.48 Cambodia 12.03 17.34 0.75 1.08 -3.86 -3.82 -0.62 -0.61 -0.46 -0.46 Somalia 0.64 0.04 -4.57 -0.67 -0.50 Chad 0.96 0.06 -4.55 -0.68 -0.51 Zambia 6.33 9.58 0.38 0.57 -4.24 -4.34 -0.72 -0.73 -0.54 -0.55 Sri Lanka 21.94 31.58 1.04 1.50 -3.58 -3.41 -0.76 -0.72 -0.57 -0.54 Malawi 1.39 3.12 0.08 0.18 -4.54 -4.73 -0.80 -0.84 -0.60 -0.63 Mali 3.50 0.19 -4.43 -0.82 -0.62 Burkina Faso 3.85 4.94 0.20 0.26 -4.42 -4.65 -0.85 -0.89 -0.64 -0.67 Peru 53.03 61.78 1.69 1.96 -2.93 -2.94 -0.92 -0.93 -0.69 -0.69 Korea, Dem. People’s Rep. 24.57 0.97 -3.65 -0.93 -0.70 Niger 1.96 0.09 -4.52 -0.98 -0.73 Côte d'Ivoire 10.76 15.55 0.44 0.64 -4.18 -4.27 -1.02 -1.04 -0.77 -0.78 Morocco 61.83 64.33 1.74 1.81 -2.88 -3.10 -1.02 -1.10 -0.77 -0.83 Cameroon 7.72 10.51 0.31 0.43 -4.30 -4.48 -1.06 -1.10 -0.79 -0.83 Angola 28.26 0.95 -3.67 -1.09 -0.82 Mexico 463.09 484.10 3.71 3.88 -0.90 -1.02 -1.13 -1.28 -0.85 -0.96 Madagascar 3.76 5.02 0.15 0.20 -4.47 -4.71 -1.14 -1.20 -0.86 -0.90 Nepal 11.78 17.30 0.42 0.62 -4.19 -4.28 -1.16 -1.19 -0.87 -0.89 Yemen, Rep. 10.64 0.38 -4.23 -1.18 -0.88 Ghana 16.00 20.18 0.55 0.69 -4.07 -4.21 -1.18 -1.23 -0.89 -0.92 Mozambique 7.39 16.86 0.26 0.59 -4.36 -4.32 -1.25 -1.24 -0.94 -0.93 Colombia 89.36 100.48 1.83 2.05 -2.79 -2.85 -1.36 -1.39 -1.02 -1.05 Afghanistan 8.40 0.23 -4.38 -1.59 -1.19 Sudan 20.88 0.51 -4.10 -1.68 -1.26 Uganda 5.18 7.57 0.13 0.18 -4.49 -4.72 -1.85 -1.95 -1.39 -1.46 Egypt, Arab Rep. 231.50 236.27 2.40 2.45 -2.22 -2.45 -2.14 -2.37 -1.60 -1.77 Kenya 17.23 26.69 0.34 0.53 -4.27 -4.37 -2.15 -2.20 -1.61 -1.65 Myanmar 28.21 0.53 -4.09 -2.18 0.00 -1.64 23 Viet Nam 213.01 210.08 2.25 2.22 -2.36 -2.68 -2.24 -2.54 -1.68 -1.90 Tanzania 11.35 20.07 0.21 0.37 -4.41 -4.54 -2.41 -2.48 -1.81 -1.86 Philippines 131.31 151.47 1.25 1.44 -3.37 -3.46 -3.54 -3.64 -2.66 -2.73 Congo, Dem. Rep. 2.55 0.03 -4.58 -3.73 -2.80 Brazil 498.47 518.93 2.40 2.50 -2.22 -2.41 -4.61 -5.00 -3.46 -3.75 Ethiopia 14.96 20.24 0.14 0.19 -4.48 -4.71 -4.76 -5.02 -3.57 -3.76 Indonesia 592.60 607.82 2.24 2.30 -2.38 -2.61 -6.29 -6.90 -4.71 -5.17 Bangladesh 81.50 102.88 0.51 0.64 -4.11 -4.26 -6.55 -6.80 -4.92 -5.10 Pakistan 216.57 224.50 1.04 1.08 -3.57 -3.82 -7.43 -7.95 -5.57 -5.97 Nigeria 120.27 125.56 0.63 0.66 -3.99 -4.25 -7.61 -8.11 -5.71 -6.08 India 2,462.08 2,254.74 1.84 1.68 -2.78 -3.22 -37.16 -43.09 -27.87 -32.32 24 Annex Table B: Annual payments/receipts by each country for the stock of historical emissions. Global Global average average 110.14 117.33 Note: stock values take 1990 as tons/pers tons/pers Valuing 'excess' stock at Valuing 'excess' stock at $10 initial year on on $0.3 per ton per ton Deviation Deviation Payments from from or Payments CO2 Per Per global global Payments or Receipts or Receipts Payments or CO2 STOCK STOCK Capita Capita average average Receipts (prod. (cons. Receipts ECONOMY prod. cons. CO2 CO2 (per (per (prod. STOCK STOCK (cons. STOCK (MIL TONS) (MIL STOCK STOCK capita capita STOCK based) based) USD based) TONS) (prod.) (cons.) CO2 CO2 based) USD Billions STOCK STOCK Billions prod.) cons.) United States 167,927.36 174,897.27 510.32 531.50 400.17 414.16 39.50 40.89 1,316.83 1,362.86 Russian Federation 49,909.67 39,171.85 342.15 268.54 232.00 151.20 10.15 6.62 338.43 220.56 China 184,376.75 159,742.45 128.59 111.41 18.45 -5.92 7.94 -2.55 264.55 -84.91 Japan 36,938.62 43,373.05 291.18 341.90 181.03 224.56 6.89 8.55 229.66 284.88 Germany 26,251.71 30,768.19 314.33 368.41 204.18 251.07 5.12 6.29 170.53 209.69 Canada 16,332.75 16,581.75 436.58 443.23 326.43 325.90 3.66 3.66 122.12 121.92 Korea, Rep. 14,869.02 16,500.10 290.27 322.11 180.12 204.77 2.77 3.15 92.27 104.90 Saudi Arabia 12,329.56 11,839.89 359.79 345.50 249.65 228.17 2.57 2.35 85.55 78.19 United Kingdom 15,728.91 19,731.77 232.92 292.19 122.77 174.86 2.49 3.54 82.91 118.08 Australia 10,982.38 9,996.75 435.75 396.65 325.61 279.31 2.46 2.11 82.06 70.40 Italy 13,001.65 16,469.68 214.73 272.00 104.58 154.67 1.90 2.81 63.32 93.65 South Africa 12,404.14 8,800.90 211.83 150.29 101.68 32.96 1.79 0.58 59.54 19.30 Poland 10,105.69 9,230.14 266.73 243.62 156.58 126.28 1.78 1.44 59.33 47.85 Ukraine 10,248.41 8,047.84 232.95 182.93 122.81 65.60 1.62 0.87 54.03 28.86 Kazakhstan 6,667.81 5,144.53 359.42 277.31 249.28 159.98 1.39 0.89 46.24 29.68 Iran, Islamic Rep. 13,670.99 12,775.33 164.88 154.08 54.74 36.74 1.36 0.91 45.39 30.47 Taiwan, China 6,969.11 7,380.76 293.14 310.46 183.00 193.12 1.31 1.38 43.51 45.91 France 11,424.20 14,915.20 175.41 229.01 65.26 111.67 1.28 2.18 42.51 72.73 Spain 8,649.46 9,600.33 185.07 205.41 74.92 88.08 1.05 1.23 35.02 41.16 Netherlands 5,105.98 5,441.35 298.65 318.26 188.50 200.93 0.97 1.03 32.23 34.35 United Arab Emirates 3,771.82 4,479.95 386.04 458.52 275.90 341.18 0.81 1.00 26.96 33.34 Czechia 3,701.09 3,538.02 346.25 330.99 236.10 213.65 0.76 0.69 25.24 22.84 Belgium 3,503.16 5,515.31 303.58 477.96 193.44 360.62 0.67 1.25 22.32 41.61 Greece 2,780.07 2,734.50 265.44 261.09 155.30 143.75 0.49 0.45 16.26 15.06 Kuwait 2,043.93 1,801.20 485.83 428.14 375.69 310.80 0.47 0.39 15.81 13.08 Venezuela, RB 4,662.38 3,993.38 163.50 140.04 53.36 22.71 0.46 0.19 15.22 6.47 Malaysia 5,029.87 4,659.72 157.43 145.85 47.29 28.51 0.45 0.27 15.11 9.11 Qatar 1,706.13 1,070.36 602.43 377.94 492.29 260.61 0.42 0.22 13.94 7.38 Finland 1,716.50 2,314.04 310.28 418.29 200.13 300.95 0.33 0.50 11.07 16.65 Austria 2,053.78 2,878.38 229.34 321.42 119.20 204.09 0.32 0.55 10.67 18.28 Denmark 1,555.30 1,891.43 269.46 327.70 159.32 210.36 0.28 0.36 9.20 12.14 Belarus 1,923.29 1,761.68 203.47 186.37 93.33 69.04 0.26 0.20 8.82 6.53 25 Romania 2,998.02 2,842.04 154.82 146.76 44.68 29.43 0.26 0.17 8.65 5.70 Singapore 1,480.34 3,244.81 255.04 559.03 144.90 441.70 0.25 0.77 8.41 25.64 Trinidad and Tobago 982.33 591.04 704.19 423.70 594.05 306.36 0.25 0.13 8.29 4.27 Turkmenistan 1,464.05 246.39 136.24 0.24 8.10 Israel 1,730.61 2,161.42 203.14 253.71 92.99 136.37 0.24 0.35 7.92 11.62 Bulgaria 1,545.68 1,344.07 220.81 192.01 110.66 74.67 0.23 0.16 7.75 5.23 Libya 1,485.15 219.13 108.99 0.22 7.39 Ireland 1,214.48 1,513.28 248.74 309.94 138.60 192.61 0.20 0.28 6.77 9.40 Norway 1,268.00 828.61 235.74 154.05 125.59 36.71 0.20 0.06 6.76 1.97 Slovak Republic 1,246.41 1,450.34 228.41 265.78 118.26 148.44 0.19 0.24 6.45 8.10 Hungary 1,703.34 2,199.36 175.88 227.10 65.74 109.76 0.19 0.32 6.37 10.63 Portugal 1,685.86 1,966.24 164.86 192.28 54.71 74.94 0.17 0.23 5.60 7.66 Oman 1,058.20 1,040.26 212.70 209.10 102.56 91.76 0.15 0.14 5.10 4.57 Bahrain 665.55 429.93 405.54 261.97 295.39 144.63 0.15 0.07 4.85 2.37 New Zealand 1,000.58 1,070.98 209.19 223.91 99.05 106.58 0.14 0.15 4.74 5.10 Sweden 1,575.29 2,446.66 156.96 243.78 46.81 126.44 0.14 0.38 4.70 12.69 Serbia 1,404.73 160.13 49.99 0.13 4.39 Estonia 568.53 570.89 428.87 430.65 318.73 313.32 0.13 0.12 4.23 4.15 Hong Kong SAR, China 1,171.08 3,172.13 157.48 426.58 47.34 309.25 0.11 0.69 3.52 23.00 Switzerland 1,287.44 3,240.89 149.85 377.23 39.71 259.89 0.10 0.67 3.41 22.33 Luxembourg 310.77 471.58 504.72 765.88 394.58 648.55 0.07 0.12 2.43 3.99 Slovenia 465.95 568.46 224.16 273.48 114.02 156.14 0.07 0.10 2.37 3.25 Mongolia 546.86 505.56 169.56 156.75 59.42 39.42 0.06 0.04 1.92 1.27 Lithuania 475.26 731.53 172.22 265.08 62.07 147.75 0.05 0.12 1.71 4.08 Brunei Darussalam 194.26 178.29 448.34 411.47 338.19 294.13 0.04 0.04 1.47 1.27 Croatia 593.53 694.85 143.70 168.23 33.56 50.90 0.04 0.06 1.39 2.10 Curacao 137.76 842.94 732.79 0.04 1.20 0.00 Bosnia and Herzegovina 480.10 145.44 35.30 0.03 1.17 0.00 Cyprus 210.68 273.80 175.77 228.44 65.63 111.11 0.02 0.04 0.79 1.33 North Macedonia 297.58 142.83 32.69 0.02 0.68 0.00 New Caledonia 93.94 332.22 222.08 0.02 0.63 0.00 Latvia 270.70 420.19 141.97 220.37 31.83 103.04 0.02 0.06 0.61 1.96 Iceland 91.90 271.07 160.93 0.02 0.55 0.00 Aruba 45.09 424.13 313.98 0.01 0.33 0.00 Malta 73.14 140.46 166.08 318.95 55.94 201.62 0.01 0.03 0.25 0.89 Martinique 63.21 168.31 58.17 0.01 0.22 Guadeloupe 65.70 164.22 54.07 0.01 0.22 Bahamas 61.32 157.44 47.30 0.01 0.18 Equatorial Guinea 167.26 123.35 13.21 0.01 0.18 Faeroe Islands 19.57 402.08 291.94 0.00 0.14 Sint Maarten (Dutch part) 17.20 405.84 295.69 0.00 0.13 Greenland 17.96 316.91 206.76 0.00 0.12 26 Bermuda 16.84 269.47 159.33 0.00 0.10 Andorra 14.61 189.33 79.19 0.00 0.06 Bonaire Sint Eustatius and Saba 7.74 297.81 187.67 0.00 0.05 Barbados 36.45 127.01 16.86 0.00 0.05 Palau 6.38 354.65 244.50 0.00 0.04 Liechtenstein 5.97 156.97 46.83 0.00 0.02 Anguilla 3.30 221.76 111.62 0.00 0.02 Saint Pierre and Miquelon 1.99 342.04 231.89 0.00 0.01 British Virgin Islands 4.56 151.67 41.52 0.00 0.01 Nauru 2.21 204.94 94.80 0.00 0.01 Montserrat 1.14 227.41 117.27 0.00 0.01 Antigua and Barbuda 10.74 110.54 0.40 0.00 0.00 Niue 0.20 124.54 14.39 0.00 0.00 Seychelles 10.78 110.30 0.16 0.00 0.00 Saint Kitts and Nevis 5.61 106.16 -3.98 0.00 0.00 Suriname 63.82 109.77 -0.37 0.00 0.00 Cook Islands 1.61 91.75 -18.39 0.00 0.00 Saint Helena 0.32 53.13 -57.02 0.00 0.00 Turks and Caicos Islands 3.73 97.63 -12.51 0.00 0.00 Tuvalu 0.27 22.99 -87.15 0.00 -0.01 Marshall Islands 3.27 55.59 -54.56 0.00 -0.03 Dominica 3.74 52.08 -58.06 0.00 -0.04 Grenada 6.41 57.22 -52.92 0.00 -0.06 Saint Vincent and the Grenadines 5.60 50.65 -59.50 0.00 -0.07 Tonga 3.25 31.13 -79.01 0.00 -0.08 Saint Lucia 11.42 62.50 -47.65 0.00 -0.09 French Polynesia 19.62 70.25 -39.89 0.00 -0.11 Kiribati 1.36 11.54 -98.61 0.00 -0.12 French Guiana 19.90 68.44 -41.70 0.00 -0.12 Montenegro 56.57 90.08 -20.07 0.00 -0.13 Samoa 4.91 24.89 -85.26 -0.01 -0.17 São Tomé and Príncipe 2.38 11.08 -99.06 -0.01 -0.21 Mayotte 6.21 23.34 -86.80 -0.01 -0.23 Azerbaijan 1,081.52 939.72 107.64 93.53 -2.51 -23.81 -0.01 -0.07 -0.25 -2.39 Belize 13.60 34.85 -75.30 -0.01 -0.29 Vanuatu 2.94 9.80 -100.34 -0.01 -0.30 Guyana 53.30 68.09 -42.05 -0.01 -0.33 Maldives 22.32 42.04 -68.11 -0.01 -0.36 Mauritius 93.17 134.68 73.38 106.08 -36.76 -11.26 -0.01 0.00 -0.47 -0.14 Cabo Verde 10.51 19.11 -91.03 -0.02 -0.50 27 Jamaica 271.62 289.37 92.13 98.15 -18.01 -19.19 -0.02 -0.02 -0.53 -0.57 Solomon Islands 7.76 11.59 -98.56 -0.02 -0.66 Bhutan 16.65 21.81 -88.33 -0.02 -0.67 Fiji 30.11 33.84 -76.31 -0.02 -0.68 Comoros 4.10 4.82 -105.33 -0.03 -0.90 Djibouti 11.82 12.14 -98.00 -0.03 -0.95 Eswatini 30.69 26.73 -83.42 -0.03 -0.96 Gabon 141.79 65.26 -44.88 -0.03 -0.98 Botswana 129.03 249.47 56.01 108.29 -54.14 -9.05 -0.04 -0.01 -1.25 -0.21 Timor-Leste 6.02 4.65 -105.49 -0.04 -1.36 Lesotho 61.80 29.08 -81.07 -0.05 -1.72 Armenia 137.88 146.46 46.62 49.52 -63.53 -67.82 -0.06 -0.06 -1.88 -2.01 Moldova 251.84 62.29 -47.86 -0.06 -1.93 Namibia 72.16 137.99 28.93 55.32 -81.22 -62.02 -0.06 -0.05 -2.03 -1.55 Uruguay 178.56 269.73 51.58 77.92 -58.56 -39.42 -0.06 -0.04 -2.03 -1.36 Albania 114.00 143.57 39.57 49.84 -70.57 -67.50 -0.06 -0.06 -2.03 -1.94 Guinea-Bissau 6.54 3.40 -106.74 -0.06 -2.05 Argentina 4,714.87 4,551.44 105.29 101.64 -4.86 -15.70 -0.07 -0.21 -2.17 -7.03 Georgia 221.40 252.81 55.40 63.25 -54.75 -54.08 -0.07 -0.06 -2.19 -2.16 Lebanon 529.59 77.25 -32.90 -0.07 -2.26 Chile 1,849.60 1,949.11 97.59 102.84 -12.55 -14.49 -0.07 -0.08 -2.38 -2.75 Uzbekistan 3,393.62 102.89 -7.25 -0.07 -2.39 Gambia, The 10.42 4.44 -105.71 -0.07 -2.48 Panama 215.84 317.66 50.83 74.81 -59.32 -42.53 -0.08 -0.05 -2.52 -1.81 Costa Rica 190.39 320.36 37.72 63.47 -72.42 -53.87 -0.11 -0.08 -3.66 -2.72 Eritrea 17.10 4.89 -105.25 -0.11 -3.68 Mauritania 51.61 11.40 -98.74 -0.13 -4.47 Kyrgyzstan 239.33 343.47 37.30 53.53 -72.84 -63.80 -0.14 -0.12 -4.67 -4.09 Cuba 772.58 68.17 -41.98 -0.14 -4.76 West Bank and Gaza 56.54 11.35 -98.79 -0.15 -4.92 Central African Republic 6.04 1.27 -108.87 -0.15 -5.17 Syrian Arab Republic 1,363.03 79.85 -30.29 -0.16 -5.17 Liberia 20.16 4.08 -106.06 -0.16 -5.24 Congo, Rep. 52.72 9.80 -100.34 -0.16 -5.40 El Salvador 170.55 235.97 26.43 36.56 -83.72 -80.77 -0.16 -0.16 -5.40 -5.21 Jordan 556.20 728.91 55.06 72.16 -55.08 -45.18 -0.17 -0.14 -5.56 -4.56 Nicaragua 119.77 150.04 18.30 22.92 -91.85 -94.41 -0.18 -0.19 -6.01 -6.18 Dominican Republic 562.86 624.22 52.41 58.13 -57.73 -59.21 -0.19 -0.19 -6.20 -6.36 Tunisia 661.73 673.41 56.58 57.58 -53.56 -59.75 -0.19 -0.21 -6.26 -6.99 Paraguay 137.84 210.92 19.57 29.94 -90.58 -87.39 -0.19 -0.18 -6.38 -6.16 Lao PDR 136.63 160.19 19.06 22.34 -91.09 -94.99 -0.20 -0.20 -6.53 -6.81 Togo 49.44 112.77 6.12 13.95 -104.03 -103.38 -0.25 -0.25 -8.41 -8.36 Papua New Guinea 124.12 14.14 -96.00 -0.25 -8.43 0.00 28 Sierra Leone 16.92 2.17 -107.98 -0.25 -8.44 0.00 Bolivia 401.82 379.91 34.90 33.00 -75.24 -84.34 -0.26 -0.29 -8.66 -9.71 Honduras 196.77 254.78 20.19 26.14 -89.95 -91.19 -0.26 -0.27 -8.77 -8.89 Tajikistan 126.48 13.57 -96.57 -0.27 -9.00 0.00 Korea, Dem. People’s Rep. 1,859.09 72.43 -37.71 -0.29 -9.68 0.00 Türkiye 8,193.71 9,180.14 98.21 110.03 -11.93 -7.30 -0.30 -0.18 -9.96 -6.09 Iraq 3,289.27 83.68 -26.47 -0.31 -10.40 0.00 Ecuador 865.38 983.55 49.81 56.61 -60.33 -60.72 -0.31 -0.32 -10.48 -10.55 Haiti 54.11 4.80 -105.34 -0.36 -11.86 0.00 South Sudan 27.46 2.48 -107.66 -0.36 -11.91 0.00 Benin 94.78 144.32 8.03 12.23 -102.11 -105.11 -0.36 -0.37 -12.05 -12.40 Zimbabwe 361.87 385.58 24.71 26.33 -85.44 -91.01 -0.38 -0.40 -12.51 -13.33 Burundi 8.89 0.77 -109.37 -0.38 -12.61 0.00 Mexico 12,709.96 13,446.17 99.63 105.40 -10.52 -11.94 -0.40 -0.46 -13.42 -15.23 Guinea 57.33 57.33 4.49 4.49 -105.65 -112.85 -0.40 -0.43 -13.49 -14.41 Rwanda 18.93 18.93 1.50 1.50 -108.64 -115.84 -0.41 -0.44 -13.72 -14.63 Thailand 6,235.59 6,229.33 89.56 89.47 -20.58 -27.87 -0.43 -0.58 -14.33 -19.40 Algeria 3,281.56 76.22 -33.92 -0.44 -14.60 0.00 Guatemala 328.95 446.77 18.71 25.41 -91.43 -91.92 -0.48 -0.48 -16.08 -16.16 Senegal 173.94 205.00 10.67 12.58 -99.47 -104.76 -0.49 -0.51 -16.21 -17.07 Somalia 18.14 1.17 -108.97 -0.50 -16.83 0.00 Cambodia 131.87 221.80 8.00 13.45 -102.15 -103.88 -0.51 -0.51 -16.84 -17.13 Chad 20.66 1.30 -108.85 -0.52 -17.36 0.00 Zambia 96.12 164.37 5.38 9.20 -104.76 -108.13 -0.56 -0.58 -18.71 -19.31 Sri Lanka 361.18 559.22 16.94 26.23 -93.21 -91.11 -0.60 -0.58 -19.87 -19.43 Malawi 30.42 67.17 1.63 3.61 -108.51 -113.73 -0.61 -0.64 -20.21 -21.19 Mali 51.07 2.60 -107.55 -0.63 -21.14 0.00 Burkina Faso 51.66 72.29 2.54 3.56 -107.60 -113.78 -0.66 -0.69 -21.87 -23.12 Peru 1,095.70 1,251.44 33.70 38.49 -76.44 -78.84 -0.75 -0.77 -24.85 -25.63 Niger 31.63 1.36 -108.79 -0.76 -25.36 0.00 Côte d'Ivoire 215.19 270.57 8.37 10.52 -101.78 -106.81 -0.79 -0.82 -26.17 -27.47 Cameroon 142.24 186.33 5.50 7.20 -104.65 -110.13 -0.81 -0.85 -27.08 -28.50 Morocco 1,294.02 1,475.08 35.48 40.44 -74.66 -76.89 -0.82 -0.84 -27.23 -28.04 Yemen, Rep. 457.75 15.70 -94.45 -0.83 -27.54 0.00 Madagascar 62.07 92.04 2.30 3.41 -107.84 -113.92 -0.87 -0.92 -29.08 -30.72 Angola 549.49 17.27 -92.88 -0.89 -29.56 0.00 Nepal 136.67 217.84 4.78 7.61 -105.37 -109.72 -0.90 -0.94 -30.14 -31.39 Ghana 271.36 385.78 8.92 12.68 -101.22 -104.65 -0.92 -0.95 -30.79 -31.83 Mozambique 86.69 236.24 2.85 7.78 -107.29 -109.56 -0.98 -1.00 -32.58 -33.27 Colombia 2,063.90 2,300.09 41.00 45.69 -69.14 -71.64 -1.04 -1.08 -34.81 -36.06 Afghanistan 124.11 3.26 -106.88 -1.22 -40.66 Sudan 320.52 7.49 -102.66 -1.32 -43.95 Uganda 74.32 124.35 1.68 2.81 -108.46 -114.53 -1.44 -1.52 -48.02 -50.70 Kenya 312.95 454.59 5.95 8.65 -104.19 -108.69 -1.64 -1.71 -54.78 -57.14 29 Myanmar 380.44 7.04 -103.10 -1.67 -55.72 Tanzania 169.72 298.68 2.93 5.15 -107.22 -112.19 -1.87 -1.95 -62.19 -65.07 Egypt, Arab Rep. 4,770.86 4,778.06 47.52 47.60 -62.62 -69.74 -1.89 -2.10 -62.86 -70.01 Viet Nam 3,004.90 3,201.71 31.15 33.19 -78.99 -84.14 -2.29 -2.44 -76.20 -81.17 Congo, Dem. Rep. 64.39 0.74 -109.40 -2.85 -94.95 Philippines 2,392.64 3,007.47 22.13 27.82 -88.01 -89.52 -2.85 -2.90 -95.16 -96.78 Brazil 11,339.75 11,895.08 53.73 56.36 -56.41 -60.97 -3.57 -3.86 -119.06 -128.68 Ethiopia 198.21 286.84 1.77 2.56 -108.38 -114.78 -3.64 -3.86 -121.47 -128.64 Bangladesh 1,273.65 1,635.21 7.81 10.03 -102.33 -107.31 -5.01 -5.25 -166.85 -174.96 Indonesia 11,061.53 10,723.20 40.87 39.62 -69.27 -77.71 -5.62 -6.31 -187.46 -210.31 Nigeria 2,530.88 2,307.89 12.59 11.48 -97.55 -105.85 -5.88 -6.38 -196.04 -212.72 Pakistan 4,005.61 4,220.89 18.50 19.49 -91.65 -97.84 -5.95 -6.36 -198.48 -211.90 India 41,536.37 38,611.39 30.40 28.26 -79.75 -89.08 -32.69 -36.52 -1,089.66 -1,217.17 30 Annex Table C: Annual payments/receipts by each country for a GCI on methane flows of $10 and $7.5. Payments or Receipts Payments or Deviation USD Billions Receipts Methane Methane from Global ($7.5 per USD Billions Economy (mil tons) Population per person Average ton) ($10per ton) Russian Federation 881.39 145.48 6.06 4.92 5.37 7.16 United States 638.97 325.03 1.97 0.83 2.02 2.69 Brazil 445.97 207.80 2.15 1.01 1.57 2.09 Australia 129.59 24.58 5.27 4.13 0.76 1.02 Zambia 116.95 16.86 6.94 5.80 0.73 0.98 Canada 118.86 36.73 3.24 2.10 0.58 0.77 Argentina 119.46 43.93 2.72 1.58 0.52 0.69 Uzbekistan 105.42 31.96 3.30 2.16 0.52 0.69 Indonesia 357.96 264.58 1.35 0.21 0.43 0.57 Iran, Islamic Rep. 141.16 80.69 1.75 0.61 0.37 0.49 Venezuela, RB 81.85 29.35 2.79 1.65 0.36 0.48 Turkmenistan 50.49 5.76 8.77 7.63 0.33 0.44 United Arab Emirates 50.11 9.50 5.27 4.14 0.29 0.39 Afghanistan 77.40 36.26 2.13 1.00 0.27 0.36 Azerbaijan 45.13 9.84 4.59 3.45 0.25 0.34 Chad 49.98 15.02 3.33 2.19 0.25 0.33 New Zealand 32.81 4.70 6.98 5.84 0.21 0.27 Paraguay 33.23 6.87 4.84 3.70 0.19 0.25 Angola 54.79 29.84 1.84 0.70 0.16 0.21 Central African Republic 25.66 4.61 5.57 4.43 0.15 0.20 Libya 27.88 6.59 4.23 3.09 0.15 0.20 Colombia 75.88 48.92 1.55 0.41 0.15 0.20 Kazakhstan 40.40 18.07 2.24 1.10 0.15 0.20 Botswana 22.27 2.21 10.08 8.94 0.15 0.20 Myanmar 79.64 53.37 1.49 0.35 0.14 0.19 Uruguay 21.65 3.44 6.30 5.16 0.13 0.18 Bolivia 30.37 11.19 2.71 1.58 0.13 0.18 Ukraine 66.18 44.47 1.49 0.35 0.12 0.16 Tanzania 75.99 54.70 1.39 0.25 0.10 0.14 Papua New Guinea 23.28 8.44 2.76 1.62 0.10 0.14 Mongolia 17.09 3.11 5.49 4.35 0.10 0.14 Malaysia 48.43 31.11 1.56 0.42 0.10 0.13 Bahrain 14.09 1.50 9.39 8.25 0.09 0.12 Equatorial Guinea 13.50 1.26 10.69 9.55 0.09 0.12 Ireland 16.20 4.76 3.40 2.26 0.08 0.11 Sudan 55.73 40.84 1.36 0.23 0.07 0.09 Brunei 9.40 0.42 22.14 21.00 0.07 0.09 Congo, Rep. 12.44 5.11 2.43 1.29 0.05 0.07 31 Cambodia 24.66 16.01 1.54 0.40 0.05 0.06 Belarus 17.17 9.45 1.82 0.68 0.05 0.06 Guyana 6.86 0.78 8.85 7.71 0.04 0.06 Lao PDR 13.78 6.95 1.98 0.84 0.04 0.06 Thailand 83.89 69.19 1.21 0.07 0.04 0.05 Qatar 7.69 2.71 2.83 1.70 0.03 0.05 Saudi Arabia 42.17 33.05 1.28 0.14 0.03 0.05 Guinea 18.23 12.08 1.51 0.37 0.03 0.04 Poland 47.15 37.96 1.24 0.10 0.03 0.04 Nicaragua 10.35 6.38 1.62 0.48 0.02 0.03 Somalia 19.46 14.60 1.33 0.19 0.02 0.03 Liberia 7.96 4.70 1.69 0.55 0.02 0.03 Romania 24.85 19.65 1.26 0.13 0.02 0.02 Niger 27.05 21.63 1.25 0.11 0.02 0.02 Serbia 12.45 8.83 1.41 0.27 0.02 0.02 Israel 11.66 8.25 1.41 0.28 0.02 0.02 Algeria 49.38 41.39 1.19 0.05 0.02 0.02 Namibia 4.81 2.40 2.00 0.86 0.02 0.02 Barbados 2.33 0.29 8.14 7.00 0.02 0.02 Mauritania 6.83 4.28 1.59 0.45 0.01 0.02 Grenada 2.01 0.11 18.09 16.95 0.01 0.02 Mexico 143.81 124.75 1.15 0.01 0.01 0.02 Ecuador 20.51 16.79 1.22 0.08 0.01 0.01 Suriname 1.87 0.57 3.28 2.14 0.01 0.01 Kuwait 5.82 4.04 1.44 0.30 0.01 0.01 Nepal 32.70 27.72 1.18 0.04 0.01 0.01 Georgia 5.42 4.01 1.35 0.21 0.01 0.01 Panama 5.36 4.11 1.30 0.17 0.01 0.01 Denmark 7.18 5.73 1.25 0.11 0.00 0.01 Belize 1.06 0.38 2.81 1.67 0.00 0.01 Czechia 12.59 10.64 1.18 0.04 0.00 0.00 Mauritius 1.87 1.26 1.48 0.34 0.00 0.00 Mali 21.35 18.53 1.15 0.01 0.00 0.00 Eswatini 1.49 1.13 1.32 0.18 0.00 0.00 Iceland 0.56 0.33 1.66 0.52 0.00 0.00 Vanuatu 0.50 0.29 1.73 0.60 0.00 0.00 Lithuania 3.37 2.85 1.18 0.05 0.00 0.00 Montenegro 0.84 0.63 1.34 0.20 0.00 0.00 Fiji 1.11 0.88 1.26 0.13 0.00 0.00 North Macedonia 2.48 2.08 1.19 0.05 0.00 0.00 Cuba 13.00 11.33 1.15 0.01 0.00 0.00 Antigua and Barbuda 0.20 0.10 2.10 0.96 0.00 0.00 Samoa 0.31 0.20 1.56 0.42 0.00 0.00 Saint Lucia 0.27 0.18 1.49 0.35 0.00 0.00 Bhutan 0.91 0.75 1.22 0.08 0.00 0.00 32 Oman 5.31 4.64 1.14 0.01 0.00 0.00 Saint Kitts and Nevis 0.08 0.05 1.54 0.40 0.00 0.00 Palau 0.02 0.02 1.12 -0.02 0.00 0.00 Tuvalu 0.01 0.01 0.88 -0.26 0.00 0.00 Cook Islands 0.01 0.02 0.57 -0.57 0.00 0.00 Tonga 0.10 0.10 0.98 -0.16 0.00 0.00 Seychelles 0.09 0.10 0.93 -0.20 0.00 0.00 Liechtenstein 0.02 0.04 0.53 -0.61 0.00 0.00 Albania 3.26 2.88 1.13 -0.01 0.00 0.00 Marshall Islands 0.03 0.06 0.52 -0.62 0.00 0.00 Dominica 0.05 0.07 0.63 -0.51 0.00 0.00 Andorra 0.05 0.08 0.65 -0.49 0.00 0.00 Saint Vincent and the Grenadines 0.07 0.11 0.64 -0.50 0.00 0.00 Kiribati 0.02 0.11 0.18 -0.96 0.00 0.00 Bahamas 0.32 0.38 0.83 -0.31 0.00 0.00 Luxembourg 0.55 0.59 0.93 -0.21 0.00 0.00 Lesotho 2.25 2.09 1.08 -0.06 0.00 0.00 Portugal 11.58 10.29 1.13 -0.01 0.00 0.00 São Tomé and Príncipe 0.03 0.21 0.14 -0.99 0.00 0.00 Eritrea 3.66 3.42 1.07 -0.07 0.00 0.00 Latvia 1.99 1.95 1.02 -0.12 0.00 0.00 Malta 0.22 0.44 0.49 -0.65 0.00 0.00 Trinidad and Tobago 1.26 1.38 0.91 -0.23 0.00 0.00 Solomon Islands 0.40 0.64 0.62 -0.52 0.00 0.00 Bosnia and Herzegovina 3.49 3.36 1.04 -0.10 0.00 0.00 Slovenia 1.99 2.08 0.96 -0.18 0.00 0.00 Estonia 1.11 1.32 0.84 -0.30 0.00 0.00 Djibouti 0.68 0.94 0.72 -0.42 0.00 0.00 Maldives 0.12 0.49 0.24 -0.90 0.00 0.00 Netherlands 18.92 17.02 1.11 -0.03 0.00 0.00 Cabo Verde 0.13 0.54 0.24 -0.90 0.00 0.00 Guinea-Bissau 1.46 1.83 0.80 -0.34 0.00 -0.01 Cyprus 0.71 1.18 0.60 -0.54 0.00 -0.01 Comoros 0.28 0.81 0.34 -0.79 0.00 -0.01 Costa Rica 4.88 4.95 0.99 -0.15 -0.01 -0.01 Armenia 2.57 2.94 0.87 -0.27 -0.01 -0.01 Bulgaria 7.25 7.10 1.02 -0.12 -0.01 -0.01 Gambia, The 1.65 2.22 0.74 -0.39 -0.01 -0.01 Gabon 1.46 2.06 0.71 -0.43 -0.01 -0.01 Norway 5.03 5.29 0.95 -0.19 -0.01 -0.01 Croatia 3.74 4.18 0.89 -0.25 -0.01 -0.01 Moldova 3.39 4.06 0.84 -0.30 -0.01 -0.01 Finland 4.55 5.51 0.83 -0.31 -0.01 -0.02 Honduras 8.90 9.43 0.94 -0.19 -0.01 -0.02 33 Slovak Republic 4.35 5.45 0.80 -0.34 -0.01 -0.02 Kyrgyzstan 4.76 6.19 0.77 -0.37 -0.02 -0.02 Greece 9.61 10.57 0.91 -0.23 -0.02 -0.02 Jamaica 0.83 2.92 0.28 -0.85 -0.02 -0.02 Sierra Leone 6.02 7.49 0.80 -0.33 -0.02 -0.03 Singapore 3.89 5.70 0.68 -0.46 -0.02 -0.03 Dominican Republic 9.06 10.51 0.86 -0.28 -0.02 -0.03 El Salvador 4.11 6.39 0.64 -0.49 -0.02 -0.03 Austria 6.84 8.82 0.78 -0.36 -0.02 -0.03 Hungary 7.21 9.73 0.74 -0.40 -0.03 -0.04 Zimbabwe 11.90 14.23 0.84 -0.30 -0.03 -0.04 Belgium 8.50 11.42 0.74 -0.39 -0.03 -0.04 Peru 31.21 31.47 0.99 -0.15 -0.03 -0.05 Lebanon 3.07 6.76 0.45 -0.68 -0.03 -0.05 Switzerland 4.88 8.45 0.58 -0.56 -0.04 -0.05 Tajikistan 5.32 8.88 0.60 -0.54 -0.04 -0.05 Jordan 5.92 9.73 0.61 -0.53 -0.04 -0.05 Togo 3.49 7.70 0.45 -0.69 -0.04 -0.05 Sweden 4.81 9.90 0.49 -0.65 -0.05 -0.06 Tunisia 6.30 11.44 0.55 -0.59 -0.05 -0.07 Guatemala 12.53 16.92 0.74 -0.40 -0.05 -0.07 Syrian Arab Republic 12.98 17.31 0.75 -0.39 -0.05 -0.07 Burkina Faso 15.09 19.20 0.79 -0.35 -0.05 -0.07 Senegal 10.74 15.43 0.70 -0.44 -0.05 -0.07 Benin 5.63 11.18 0.50 -0.64 -0.05 -0.07 Chile 13.44 18.47 0.73 -0.41 -0.06 -0.08 Haiti 4.63 10.98 0.42 -0.72 -0.06 -0.08 Madagascar 20.51 25.59 0.80 -0.34 -0.06 -0.09 Malawi 10.91 17.68 0.62 -0.52 -0.07 -0.09 Cameroon 17.97 24.58 0.73 -0.41 -0.08 -0.10 Rwanda 3.32 11.99 0.28 -0.86 -0.08 -0.10 Burundi 1.97 10.84 0.18 -0.96 -0.08 -0.10 Korea, Dem. People’s Rep. 18.55 25.43 0.73 -0.41 -0.08 -0.10 Ghana 20.81 29.13 0.71 -0.42 -0.09 -0.12 France 60.47 64.82 0.93 -0.21 -0.10 -0.13 Mozambique 18.92 28.68 0.66 -0.48 -0.10 -0.14 Spain 39.33 46.68 0.84 -0.30 -0.10 -0.14 Uganda 32.87 41.21 0.80 -0.34 -0.11 -0.14 Sri Lanka 9.42 21.12 0.45 -0.69 -0.11 -0.15 Viet Nam 91.31 94.59 0.97 -0.17 -0.12 -0.16 Ethiopia 103.97 106.43 0.98 -0.16 -0.13 -0.17 Kenya 39.39 50.22 0.78 -0.35 -0.13 -0.18 South Africa 45.14 56.99 0.79 -0.35 -0.15 -0.20 Côte d'Ivoire 7.05 24.45 0.29 -0.85 -0.16 -0.21 Morocco 17.09 35.57 0.48 -0.66 -0.18 -0.23 34 Yemen, Rep. 8.18 27.83 0.29 -0.84 -0.18 -0.24 United Kingdom 52.18 66.71 0.78 -0.36 -0.18 -0.24 Italy 44.88 60.62 0.74 -0.40 -0.18 -0.24 Iraq 15.69 37.50 0.42 -0.72 -0.20 -0.27 Korea, Rep. 25.87 51.06 0.51 -0.63 -0.24 -0.32 Germany 56.17 82.66 0.68 -0.46 -0.28 -0.38 Congo, Dem. Rep. 51.20 81.46 0.63 -0.51 -0.31 -0.42 Türkiye 43.53 81.05 0.54 -0.60 -0.37 -0.49 Egypt, Arab Rep. 55.94 96.43 0.58 -0.56 -0.40 -0.54 Philippines 65.61 105.14 0.62 -0.51 -0.41 -0.54 Nigeria 128.95 190.96 0.68 -0.46 -0.66 -0.88 Pakistan 141.53 207.95 0.68 -0.46 -0.71 -0.95 Bangladesh 80.77 159.67 0.51 -0.63 -0.76 -1.01 Japan 21.69 127.46 0.17 -0.97 -0.93 -1.23 China 1261.56 1420.67 0.89 -0.25 -2.67 -3.55 India 659.96 1338.48 0.49 -0.65 -6.48 -8.64 Taiwan, China 23.67 Hong Kong SAR, China 7.31 New Caledonia 0.28 Curacao 0.16 Guadeloupe 0.40 Martinique 0.38 Sint Maarten (Dutch part) 0.04 Faeroe Islands 0.05 Aruba 0.11 Bermuda 0.06 Greenland 0.06 Bonaire Sint Eustatius and Saba 0.03 Anguilla 0.01 Turks and Caicos Islands 0.04 British Virgin Islands 0.03 Saint Pierre and Miquelon 0.01 Montserrat 0.00 Nauru 0.01 Niue 0.00 Saint Helena 0.01 French Polynesia 0.28 French Guiana 0.28 Mayotte 0.25 Timor-Leste 1.24 West Bank and Gaza 4.75 South Sudan 10.90 35 Annex Table D: Annual payments/receipts by each country for a GCI on historical methane stocks of $10 and $7.5. Payments or Payments or Receipts ($ Receipts ($ Billions) Cumulative Population Cumulative Deviation Billions) Valuing Valuing excess Methane (mil 2019 methane per from Global excess stock at stock at $10 Economy ton) (millions) capita Average $0.3 per ton per ton Russian Federation 21,225.52 145.87 145.51 118.54 5.19 172.92 United States 19,142.54 329.06 58.17 31.21 3.08 102.70 Brazil 10,191.58 211.05 48.29 21.33 1.35 45.01 Australia 4,106.56 25.20 162.94 135.97 1.03 34.27 Indonesia 9,858.37 270.63 36.43 9.46 0.77 25.61 Zambia 2,815.89 17.86 157.66 130.69 0.70 23.34 Canada 3,116.75 37.41 83.31 56.35 0.63 21.08 Argentina 3,240.60 44.78 72.37 45.40 0.61 20.33 Ukraine 3,099.93 43.99 70.46 43.50 0.57 19.14 Uzbekistan 2,605.15 32.98 78.99 52.02 0.51 17.16 Libya 1,834.70 6.78 270.71 243.74 0.50 16.52 Venezuela, RB 2,066.12 28.52 72.46 45.49 0.39 12.97 United Kingdom 2,626.73 67.53 38.90 11.93 0.24 8.06 New Zealand 893.99 4.78 186.91 159.94 0.23 7.65 Turkmenistan 913.45 5.94 153.73 126.76 0.23 7.53 Iran, Islamic Rep. 2,923.52 82.91 35.26 8.30 0.21 6.88 United Arab Emirates 789.08 9.77 80.76 53.80 0.16 5.26 Kazakhstan 1,020.55 18.55 55.01 28.05 0.16 5.20 Paraguay 700.57 7.04 99.45 72.48 0.15 5.11 Azerbaijan 765.45 10.05 76.18 49.22 0.15 4.95 Uruguay 570.20 3.46 164.72 137.75 0.14 4.77 Angola 1,320.63 31.83 41.50 14.53 0.14 4.62 Colombia 1,804.98 50.34 35.86 8.89 0.13 4.48 Central African Republic 565.69 4.75 119.21 92.25 0.13 4.38 Poland 1,427.63 37.89 37.68 10.72 0.12 4.06 Botswana 443.41 2.30 192.48 165.51 0.11 3.81 Bolivia 684.64 11.51 59.47 32.50 0.11 3.74 Romania 886.36 19.36 45.77 18.81 0.11 3.64 Myanmar 1,799.27 54.05 33.29 6.33 0.10 3.42 Syrian Arab Republic 776.02 17.07 45.46 18.50 0.09 3.16 Ireland 429.66 4.88 88.00 61.04 0.09 2.98 Brunei 295.49 0.43 681.96 654.99 0.09 2.84 Equatorial Guinea 263.32 1.36 194.19 167.23 0.07 2.27 Malaysia 1,085.38 31.95 33.97 7.01 0.07 2.24 Mongolia 303.13 3.23 93.99 67.03 0.06 2.16 Thailand 2,082.47 69.63 29.91 2.95 0.06 2.05 36 Netherlands 641.94 17.10 37.55 10.58 0.05 1.81 Bahrain 224.45 1.64 136.76 109.80 0.05 1.80 Belarus 429.64 9.45 45.45 18.49 0.05 1.75 France 1,905.37 65.13 29.26 2.29 0.04 1.49 Czechia 425.31 10.69 39.79 12.82 0.04 1.37 Papua New Guinea 367.61 8.78 41.89 14.92 0.04 1.31 Serbia 339.82 8.77 38.74 11.77 0.03 1.03 Chad 527.58 15.95 33.08 6.12 0.03 0.98 Georgia 199.72 4.00 49.97 23.01 0.03 0.92 Lao PDR 280.42 7.17 39.11 12.15 0.03 0.87 Bulgaria 274.23 7.00 39.18 12.21 0.03 0.85 Somalia 496.17 15.44 32.13 5.17 0.02 0.80 Guyana 98.72 0.78 126.12 99.15 0.02 0.78 Congo, Rep. 221.49 5.38 41.17 14.20 0.02 0.76 Cambodia 519.02 16.49 31.48 4.52 0.02 0.74 Namibia 140.87 2.49 56.47 29.51 0.02 0.74 Sudan 1,223.68 42.81 28.58 1.62 0.02 0.69 Denmark 224.01 5.77 38.81 11.85 0.02 0.68 Belize 71.68 0.39 183.63 156.67 0.02 0.61 Barbados 60.95 0.29 212.35 185.39 0.02 0.53 Lithuania 124.80 2.76 45.22 18.26 0.02 0.50 Portugal 326.04 10.23 31.88 4.92 0.02 0.50 Grenada 50.65 0.11 452.22 425.26 0.01 0.48 Ecuador 509.50 17.37 29.33 2.36 0.01 0.41 Germany 2,288.75 83.52 27.40 0.44 0.01 0.37 Cuba 341.94 11.33 30.17 3.21 0.01 0.36 Nicaragua 202.28 6.55 30.90 3.94 0.01 0.26 Mauritania 145.65 4.53 32.18 5.22 0.01 0.24 Suriname 38.93 0.58 66.96 40.00 0.01 0.23 Qatar 98.55 2.83 34.80 7.83 0.01 0.22 Finland 170.54 5.53 30.83 3.86 0.01 0.21 Albania 95.54 2.88 33.16 6.20 0.01 0.18 Israel 246.14 8.52 28.89 1.93 0.00 0.16 Latvia 66.53 1.91 34.89 7.93 0.00 0.15 Panama 123.66 4.25 29.12 2.16 0.00 0.09 Saudi Arabia 933.12 34.27 27.23 0.27 0.00 0.09 North Macedonia 64.43 2.08 30.92 3.96 0.00 0.08 Eswatini 39.22 1.15 34.16 7.20 0.00 0.08 Slovenia 64.16 2.08 30.87 3.90 0.00 0.08 Greece 290.22 10.47 27.71 0.75 0.00 0.08 Norway 152.13 5.38 28.28 1.32 0.00 0.07 Iceland 15.23 0.34 44.92 17.96 0.00 0.06 Bosnia and Herzegovina 94.61 3.30 28.66 1.70 0.00 0.06 Saint Lucia 10.08 0.18 55.14 28.18 0.00 0.05 Montenegro 21.79 0.63 34.70 7.73 0.00 0.05 37 Estonia 40.34 1.33 30.43 3.47 0.00 0.05 Mauritius 38.24 1.27 30.12 3.15 0.00 0.04 Bhutan 24.21 0.76 31.73 4.76 0.00 0.04 Vanuatu 11.05 0.30 36.85 9.88 0.00 0.03 Antigua and Barbuda 4.77 0.10 49.12 22.15 0.00 0.02 Samoa 6.99 0.20 35.47 8.50 0.00 0.02 Kuwait 114.51 4.21 27.22 0.25 0.00 0.01 Saint Kitts and Nevis 2.02 0.05 38.23 11.27 0.00 0.01 Fiji 23.99 0.89 26.96 -0.01 0.00 0.00 Palau 0.45 0.02 25.00 -1.97 0.00 0.00 Tuvalu 0.27 0.01 23.17 -3.80 0.00 0.00 Tonga 2.71 0.10 25.93 -1.03 0.00 0.00 Slovak Republic 146.99 5.46 26.94 -0.03 0.00 0.00 Cook Islands 0.30 0.02 17.10 -9.87 0.00 0.00 Dominica 1.55 0.07 21.59 -5.38 0.00 0.00 Liechtenstein 0.54 0.04 14.20 -12.76 0.00 0.00 Seychelles 2.04 0.10 20.87 -6.09 0.00 -0.01 Moldova 108.34 4.04 26.80 -0.17 0.00 -0.01 Marshall Islands 0.75 0.06 12.76 -14.21 0.00 -0.01 Andorra 1.03 0.08 13.35 -13.61 0.00 -0.01 Saint Vincent and the Grenadines 1.89 0.11 17.09 -9.87 0.00 -0.01 Luxembourg 15.39 0.62 24.99 -1.97 0.00 -0.01 Kiribati 0.48 0.12 4.08 -22.88 0.00 -0.03 Bahamas 7.29 0.39 18.72 -8.25 0.00 -0.03 Austria 237.05 8.96 26.47 -0.49 0.00 -0.04 São Tomé and Príncipe 0.84 0.22 3.91 -23.06 0.00 -0.05 Malta 5.60 0.44 12.72 -14.25 0.00 -0.06 Gambia, The 55.11 2.35 23.47 -3.49 0.00 -0.08 Djibouti 16.47 0.97 16.92 -10.05 0.00 -0.10 Solomon Islands 8.27 0.67 12.35 -14.62 0.00 -0.10 Trinidad and Tobago 26.09 1.39 18.70 -8.26 0.00 -0.12 Cabo Verde 2.91 0.55 5.29 -21.67 0.00 -0.12 Maldives 2.01 0.53 3.79 -23.18 0.00 -0.12 Lesotho 44.21 2.13 20.80 -6.16 0.00 -0.13 Croatia 98.21 4.13 23.78 -3.19 0.00 -0.13 Armenia 65.39 2.96 22.11 -4.86 0.00 -0.14 Cyprus 17.37 1.20 14.49 -12.47 0.00 -0.15 Belgium 294.70 11.54 25.54 -1.43 0.00 -0.16 Gabon 41.76 2.17 19.22 -7.74 -0.01 -0.17 Comoros 5.62 0.85 6.60 -20.36 -0.01 -0.17 Eritrea 76.76 3.50 21.95 -5.01 -0.01 -0.18 Guinea-Bissau 33.17 1.92 17.27 -9.70 -0.01 -0.19 Costa Rica 115.15 5.05 22.81 -4.15 -0.01 -0.21 Hungary 235.59 9.68 24.33 -2.64 -0.01 -0.26 38 Oman 104.60 4.97 21.03 -5.94 -0.01 -0.30 Liberia 100.32 4.94 20.32 -6.65 -0.01 -0.33 Guinea 303.48 12.77 23.76 -3.20 -0.01 -0.41 Honduras 214.91 9.75 22.05 -4.91 -0.01 -0.48 Jamaica 27.44 2.95 9.31 -17.66 -0.02 -0.52 Kyrgyzstan 120.72 6.42 18.82 -8.15 -0.02 -0.52 El Salvador 109.85 6.45 17.02 -9.94 -0.02 -0.64 Dominican Republic 208.06 10.74 19.37 -7.59 -0.02 -0.82 Switzerland 148.74 8.59 17.31 -9.65 -0.02 -0.83 Sweden 185.20 10.04 18.45 -8.51 -0.03 -0.85 Algeria 1,071.50 43.05 24.89 -2.08 -0.03 -0.89 Singapore 62.18 5.80 10.71 -16.25 -0.03 -0.94 Zimbabwe 296.52 14.65 20.25 -6.72 -0.03 -0.98 Sierra Leone 108.28 7.81 13.86 -13.11 -0.03 -1.02 Tanzania 1,461.31 58.01 25.19 -1.77 -0.03 -1.03 Jordan 160.20 10.10 15.86 -11.11 -0.03 -1.12 Nepal 654.85 28.61 22.89 -4.07 -0.03 -1.17 Mali 405.93 19.66 20.65 -6.31 -0.04 -1.24 Lebanon 59.97 6.86 8.75 -18.22 -0.04 -1.25 Chile 373.40 18.95 19.70 -7.26 -0.04 -1.38 Togo 73.02 8.08 9.03 -17.93 -0.04 -1.45 Tajikistan 105.89 9.32 11.36 -15.60 -0.04 -1.45 Tunisia 157.79 11.69 13.49 -13.47 -0.05 -1.58 Korea, Dem. People’s Rep. 526.68 25.67 20.52 -6.44 -0.05 -1.65 Madagascar 543.18 26.97 20.14 -6.82 -0.06 -1.84 Peru 690.94 32.51 21.25 -5.71 -0.06 -1.86 Senegal 251.63 16.30 15.44 -11.52 -0.06 -1.88 Niger 440.50 23.31 18.90 -8.07 -0.06 -1.88 Haiti 109.63 11.26 9.73 -17.23 -0.06 -1.94 Benin 114.28 11.80 9.68 -17.28 -0.06 -2.04 Guatemala 263.70 17.58 15.00 -11.97 -0.06 -2.10 Spain 1,038.81 46.74 22.23 -4.74 -0.07 -2.21 Burkina Faso 296.53 20.32 14.59 -12.37 -0.08 -2.51 Sri Lanka 317.01 21.32 14.87 -12.10 -0.08 -2.58 Burundi 52.83 11.53 4.58 -22.38 -0.08 -2.58 Italy 1,366.74 60.55 22.57 -4.39 -0.08 -2.66 Rwanda 70.82 12.63 5.61 -21.36 -0.08 -2.70 Côte d'Ivoire 413.08 25.72 16.06 -10.90 -0.08 -2.80 Malawi 205.00 18.63 11.00 -15.96 -0.09 -2.97 Cameroon 387.18 25.88 14.96 -12.00 -0.09 -3.11 Mexico 3,096.15 127.58 24.27 -2.69 -0.10 -3.44 Afghanistan 643.03 38.04 16.90 -10.06 -0.11 -3.83 Mozambique 425.87 30.37 14.02 -12.94 -0.12 -3.93 South Africa 1,159.01 58.56 19.79 -7.17 -0.13 -4.20 Ghana 317.93 30.42 10.45 -16.51 -0.15 -5.02 39 Yemen, Rep. 167.18 29.16 5.73 -21.23 -0.19 -6.19 Morocco 353.56 36.47 9.69 -17.27 -0.19 -6.30 Korea, Rep. 729.24 51.23 14.24 -12.73 -0.20 -6.52 Uganda 528.35 44.27 11.93 -15.03 -0.20 -6.65 Kenya 738.98 52.57 14.06 -12.91 -0.20 -6.79 Viet Nam 1,914.41 96.46 19.85 -7.12 -0.21 -6.87 Iraq 325.33 39.31 8.28 -18.69 -0.22 -7.35 Ethiopia 1,871.49 112.08 16.70 -10.27 -0.35 -11.51 Türkiye 1,088.42 83.43 13.05 -13.92 -0.35 -11.61 Congo, Dem. Rep. 1,137.67 86.79 13.11 -13.86 -0.36 -12.03 Philippines 1,559.56 108.12 14.42 -12.54 -0.41 -13.56 Egypt, Arab Rep. 1,254.98 100.39 12.50 -14.46 -0.44 -14.52 Bangladesh 1,949.11 163.05 11.95 -15.01 -0.73 -24.47 Nigeria 2,959.27 200.96 14.73 -12.24 -0.74 -24.59 Japan 783.14 126.86 6.17 -20.79 -0.79 -26.37 Pakistan 2,739.57 216.57 12.65 -14.31 -0.93 -31.00 China 24,919.18 1,433.78 17.38 -9.58 -4.12 -137.41 India 16,380.03 1,366.42 11.99 -14.98 -6.14 -204.64 Taiwan, China 23.77 0.00 Hong Kong SAR, China 7.44 0.00 Curacao 0.16 0.00 New Caledonia 0.28 0.00 Aruba 0.11 0.00 Martinique 0.38 0.00 Guadeloupe 0.40 0.00 Faeroe Islands 0.05 0.00 Sint Maarten (Dutch part) 0.04 0.00 Greenland 0.06 0.00 Bermuda 0.06 0.00 Bonaire Sint Eustatius and Saba 0.03 0.00 Anguilla 0.01 0.00 Saint Pierre and Miquelon 0.01 0.00 British Virgin Islands 0.03 0.00 Nauru 0.01 0.00 Montserrat 0.00 0.00 Niue 0.00 0.00 Saint Helena 0.01 0.00 Turks and Caicos Islands 0.04 0.00 French Polynesia 0.28 0.00 French Guiana 0.29 0.00 Mayotte 0.27 0.00 Timor-Leste 1.29 0.00 West Bank and Gaza 4.98 0.00 South Sudan 11.06 0.00 40