The Climate Equity Reference Calculator database

The database for the Climate Equity Reference Calculator includes 195 countries: 193 of the 195 members of the UNFCCC (except Andorra and South Sudan, both of which are missing from most databases), plus Taiwan and Palestine. Data for China, Macao and Hong Kong, which are typically reported separately in most income and emissions databases, are combined.

The Climate Equity Reference Calculator database is updated regularly with newly published data. The current calculator and published documentation are based primarily on data from 2015 (see details below). For archival purposes it is version 7.0.0.

Income

Recent historical income (GDP) data comes primarily from the World Bank’s World Development Indicators Online,[1] which contains data for national income from 1960 to 2014 for almost all of the 195 countries in the database. For most of the missing countries or territories, data comes from the CIA World Factbook.[2] For data prior to 1960 or other missing years, data comes from the Maddison data set.[3]
Data is reported in $2010 US, at market exchange rates (MER). Conversion to PPP (2005) is based on converting “Current US Dollars” for 2005 to PPP (Current International Dollars). The PPP conversion rate is held constant at this value.

Income (GDP) projections from 2015-2020 are from the IMF’s World Economic Outlook (April 2015).[4] Projected growth rates are applied to the most recent World Bank national GDP data (in most cases 2014); long term estimates (2021 to 2030) are based on the median GDP growth rates across the models in the EMF27Base-FullTech scenario as reported in the IPCC AR5 scenario database.[5]

CO2 emissions

CO2 data for the period from 1959 through to 2013 comes from the Global Carbon Project [6], which in turn is based on data from the Carbon Dioxide Information and Analysis Center (CDIAC), except for Annex I nations, where we take values of CO2 emissions from fossil fuel use and cement manufacturing for the period 1990 to 2012 directly from their mandatory National Inventory Reports as collated by the UNFCCC.[7] For all countries, CO2 data for 1850 through 1958 is taken from the World Resource Institute’s CAIT [8]. For a very small number of countries,[9] we use different, but equally well-respected data sources.

Baseline emissions are projected after 2013 based on the median carbon intensity changes modelled in the EMF27Base-FullTech scenario from the IPCC AR5 scenario database for each of the five regions of the scenario (see note 5), combined with the population and GDP projections as described above. These baselines are further calibrated for their total to match the median baseline scenario of the UNEP Emissions Gap Report 2015 [10].

Non-CO2 GHGs

Values for non-CO2 GHGs for Annex I countries are taken from the UNFCCC’s national reporting (see note 7). Estimates for non-Annex I countries and for Annex I countries for the pre-1990 period come from WRI’s CAIT (see note 8).

Baseline projections for 2014 to 2030 for all countries are based on the median intensity changes reported in the IPCC AR5 scenario database for the models of the EMF27-Base-FullTech scenario (see note 5).

CO2 from Land Use (LUCF)

Historical emissions (for the 1850 to 1989 period) from LUCF (Land Use Change and Forestry) in the Climate Equity Reference Calculator Database are generated from multiple sources, as no authoritative, country-level dataset exists. The total global LUCF budget is constrained to match the figures published by the Global Carbon Project (GCP) (see note 6). Regional values 1850-1989 are constrained to meet the ten regional budgets published by CDIAC, the so-called Houghton dataset;[11] that is the relative emissions in each region are scaled such that the sum of all regions matches the global total from GCP. National budgets are derived from the relative shares of regional totals in the MATCH database.[12]

Scaling from relative national values to match regional totals is not a simple linear transformation, as some countries have negative estimated LUCF emissions and linear scaling would actually implausibly adjust emissions in a region with both negative and positive emissions. Instead, where the constrained regional total is less than the sum of national estimates, countries with negative emissions are held at their reported negative emissions levels and countries with positive emissions are proportionally reduced; where the constrained regional total is larger than the sum of national estimates, countries with negative emissions are scaled towards zero (that is, their emissions become less negative) and countries with positive emissions are scaled upwards.

For the period from 1990 to 2012, data from the National Inventory Reports to the UNFCCC (see note 7) were used for Annex I countries, while WRI’s CAIT (see note 8) was used for non-Annex I countries for that period.

Baseline projections for 2013 through 2030 are held constant at the 10-year average of historical (2003-2012) emissions or removals.

Gini Coefficients

Gini coefficients for the majority of countries in the Equity Calculator database are taken from the World Income Inequality Database.[13] For countries which have reliable national or supranational sources (e.g., US Census Bureau, EU Europa database) newer Ginis are used where available. For some countries other sources are used, and for those for which no published figures are available, Gini coefficients are estimated on the basis of comparable countries.

Population

Current, historical and projected population for most countries are taken from the United Nations Population Division’s medium variant.[14]

Calculating the RCI from the Equity Calculator dataset

The Climate Equity Reference Calculator sets a country’s fair share of the global climate effort in proportion to its Responsibility and Capacity Index, or RCI, which in turn is calculated from a country’s capacity and responsibility. Capacity for a given year is defined as the sum of the income of all individuals in the country, excluding the total income of everyone under a user-specified income level referred to as the development threshold. (Central to the calculation is the commonly used assumption that national income distributions can be modeled as lognormal distributions.[15] The lognormal distribution has been shown to provide a reasonable approximation of measured income distributions.[16] With this assumption, any national income distribution can be modeled with just a Gini Coefficient and the per-capita income.) The Calculator’s initial setting of for development threshold is $7500 per capita, PPP adjusted; so we will use that number in the following example. For people making more than $7500 annually, only their income above that threshold counts towards the national measure of capacity. Responsibility is calculated in a similar manner. Emissions are calculated from income based on a user-specified elasticity, which is initially set to one (i.e., all individuals in a country have emissions proportional to income); thus, all emissions are excluded for those whose incomes are under the development threshold, and emissions equivalent to $7500 of consumption at the national average carbon intensity are excluded for those with income over the threshold. Unlike the calculation of capacity, however, responsibility is calculated on a cumulative basis, starting at a user-specified initial year, so that responsibility in (say) 2015 is the sum of responsibility calculated in this way for each year from the specified start year to 2015. Capacity and responsibility are then expressed as a percentage of the global total, and combined into a single “Responsibility and Capacity Index” by taking a weighted average. In the Calculator, the Responsibility and Capacity weightings are initially set to be equal, but the calculator allows this to be user-specified, all the way from 100% Responsibility to 100% capacity.


[1] http://databank.worldbank.org/data/home.aspx
[2] https://www.cia.gov/library/publications/the-world-factbook
[3] Statistics on World Population, GDP and Per Capita GDP, 1-2008 AD, available at http://www.ggdc.net/MADDISON/oriindex.htm
[4] http://www.imf.org/external/pubs/ft/weo/2015/01/index.htm
[5] https://secure.iiasa.ac.at/web-apps/ene/AR5DB
[6] The data file used in this version of the Calculator database is Global_Carbon_Budget_2014_v1.1_finalMay2015.xlsx, available at http://www.globalcarbonproject.org/carbonbudget/archive.htm#CB2014
[7] http://unfccc.int/ghg_data/ghg_data_unfccc/time_series_annex_i/items/3814.php
[8] http://cait.wri.org/historical
[9] Liechtenstein, Marshall Islands, Federated States of Micronesia, Palestine, Somalia, Taiwan, and Timor-Leste taken from CDIAC; Monaco from UNFCCC; Tuvalu from EDGAR.
[10] United Nations Environment Programme. 2015. The Emissions Gap Report 2015. Nairobi: UNEP. Available at http://uneplive.unep.org/media/docs/theme/13/EGR_2015_Technical_Report_final_version.pdf; Our calibration algorithm takes account of the different treatment of Annex I LULUCF emissions and emissions from international aviation and shipping in our database compared to the UNEP report.
[11] Houghton, R.A. 2008. Carbon Flux to the Atmosphere from Land-Use Changes: 1850-2005. In TRENDS: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. Available at http://cdiac.ornl.gov/trends/landuse/houghton/houghton.html
[12] The MATCH dataset is available as supplemental online material published with Höhne, Blum, Fuglestvedt, Skeie, Kurosawa, Hu, Lowe, Gohar, Matthews, Nioac de Salles, Ellermann 2011: Contributions of individual countries’ emissions to climate change and their uncertainty, Climatic Change 106:359-391
[13] http://www.wider.unu.edu/research/Database/en_GB/database/
[14] http://esa.un.org/unpd/wpp/unpp/panel_population.htm
[15] A good technical description of the lognormal distribution is given on Wikipedia. https://en.wikipedia.org/wiki/Log-normal_distribution
[16] Lopez, J.H, and L. Servén. 2006. A Normal Relationship? Poverty, Growth and Inequality: World Bank Policy Research Paper #3814. Available at http://econ.worldbank.org