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1990-2019年:全球碳不平等.pdf
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1990-2019年:全球碳不平等.pdf
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Global carbon inequality over 1990-2019
Abstract
All humans contribute to climate change but not equally. Here I estimate the
global inequality of individual greenhouse gas (GHG) emissions between 1990
and 2019, using a newly assembled data set of income and wealth inequality,
Environmental Input-Output tables and a framework differentiating emissions
from consumption and investments. In my benchmark set of estimates, I find
that the bottom 50% of the world population emitted 12% of global emissions
in 2019, whereas the top 10% emitted 48% of the total. Since 1990, the bottom
50% of the world population has been responsible for only 16% of all emissions
whereas the top 1% for 23% of the total. While per capita emissions of the
global top 1% increased since 1990, emissions from low and middle income
groups within rich countries declined. Contrary to the situation in 1990, 63% of
the global inequality in individual emissions is now due to a gap between low
and high emitters within countries rather than between countries. Finally, the
bulk of total emissions from the global top 1% of the world population comes
from their investments rather than from their consumption. These findings have
implications for contemporary debates on fair climate policies and stress the
need for governments to develop better data on individual emissions to monitor
progress towards sustainable lifestyles: a lot remains to be learned about the
relationship between emissions and wealth.
1
I INTRODUCTION
Climate change and economic inequalities are among the most pressing chal-
lenges of our times, and they are interrelated: failure to contain climate change
is likely to exacerbate inequalities within and between countries [1, 2, 3, 4] and
economic inequalities within countries tend to slow the implementation of climate
policies [5, 6]. In order to properly understand the relationship between economic
inequality and climate change, sound and timely data is needed about the distribution
of greenhouse gases (GHG) emissions between individuals and across the globe.
Such information is currently missing. As a matter of fact, researchers, policymakers
and civil society struggle to establish even basic facts about which groups of the
population contributes to emissions growth, or mitigation. This jeopardize any
efforts towards sustainable lifestyles.
This paper seeks to address these issues by harnessing recent conceptual and
empirical progress in the measurement of income, wealth and GHG emissions.
Compared with previous work on global carbon inequality [7, 8, 9, 7, 10], this paper
presents three major developments in terms of data, methods and scope.
First, the paper uses novel income and wealth inequality data from the World
Inequality Database [11] to track inequality from the bottom to the top of the
distribution. This economic inequality data is combined with GHG footprints from
Input-Output models thanks to a newly assembled set of country-level information
on the link between individual emissions, consumption and income in more than 100
countries. The methodology therefore makes it possible to track individual GHG
emission levels with more precision than previous longitudinal carbon inequality
estimates[9]. Second, the method developed allows to distinguish explicitly between
emissions from private consumption and investments, making it possible to better
understand the drivers of emissions among wealthy groups. Third, the paper focuses
on the distribution of emissions over the 1990-2019 period, that is from the first
Intergovernmental Panel on Climate Change (IPCC) report to the eve of the Covid-19
pandemic. The three decades saw critical shifts in the distribution of world economic
growth [12], which have not been systematically studied from the point of view of
GHG emissions inequality.
2
There are two broad approaches to the measurement of global carbon inequality.
Bottom-up approaches use household-level micro data to produce macro estimates.
This is the approach taken by [8, 13, 14], who mobilize the large set of consumption
surveys available from the World Bank Global Consumption Database, as well as
additional consumer expenditure surveys done in rich countries. These surveys
are linked to Environmental Multi Regional Input Output models (EMRIOs) to
provide estimates of energy consumption or emissions per consumption group. To
the extent that micro-level data is available, this method is the best way to measure
global carbon inequality associated with individual consumption. Given the data-
intensive process, this approach has not looked at the evolution of global emissions.
Another limitation is that this approach tends to underestimate the consumption
levels of the richest groups, due to well documented misreporting and sampling
errors [15]. Top-down approaches to the measurement of global carbon inequality use
the regularities observed in micro-level data to provide modeled estimates based on
elasticity parameters and income or consumption inequality distributions. This is the
approach taken by [7, 9, 10, 16]. These studies typically use one single elasticity for
all countries, which limits the precision country-level estimates. Another limitation
of both top-down and the bottom-up approaches is that they do not treat investment-
related emissions particularly well.
The present paper builds on the strengths of top-down and bottom-up approaches
and offers novel developments. By mobilizing country-level elasticities from over a
hundred countries, the paper departs from previous top-down approaches. By focus-
ing on the 1990-2019 period, the paper adds historical depth to single year bottom-up
studies and by distinguishing between emissions from personal consumption and
from investments, it is possible to shed new light on the dynamics of emissions in
particular among top groups.
The general approach followed here can be summarized as follows: using EM-
RIOs, I obtain country-level GHG emissions for the household sector, the investment
sector and the government sector across countries (emissions are net of imports and
exports embedded in goods and services traded with the rest of the world). These
emissions are distributed to individuals in each country using country-level data
on the elasticity of emissions and consumption, income and wealth. A variety of
3
alternative estimation strategies are tested and it appears that the key results are
robust to a large range of parametric assumptions on the relationship between emis-
sions, income, consumption and wealth. To be clear, a lot remains to be learned and
debated about the link between individual emissions and wealth. As in any exercise
of this sort, the statistical reconstructions presented below should be analyzed with
caution.
II RESULTS
Carbon emission inequalities within regions
Global average per capita emissions reached about 6tCO
2
e in 2019. To have high
chances of staying below +1.5°C global temperature increase, average per capita
emissions should be 1.9tCO
2
e between now and 2050 (that is the equivalent of an
economy-class round-trip flight between London and New-York) and zero afterwards
(see SI section 3).
Inequality in average per capita emissions between world regions remain large,
as shown in Extended Data Figure 1. On top of these gaps, significant inequalities in
carbon footprints are observed within regions. Figure 1 presents the carbon footprints
of the bottom 50% of emitters, the middle 40% and the top 10% of the population
within regions according to my benchmark estimates. Emission levels and shares for
other groups are presented in the SI (section 7).
In East Asia, it is found that the poorest 50% emit on average 2.9 tCO
2
e per
annum while the middle 40% emit nearly eight tonnes, and the top 10% almost 40
tonnes. This contrasts sharply with North America, where the bottom 50% emit
fewer than 10 tonnes, the middle 40% around 22 tonnes, and the top 10% around
69 tCO
2
e. This in turn can be contrasted with the emissions in Europe, where the
bottom 50% emit five tonnes, the middle 40% around 10.5 tCO
2
e, and the top 10%
around 30 tCO
2
e. Emissions levels in South and Southeast Asia are significantly
lower than in the these regions, from around 1 tCO
2
e for the bottom 50% to 11
tonnes on average for the top 10%.
It is striking that the poorest half of the population in the US has emission levels
comparable with the European middle 40%, despite being almost twice as poor
4
as this group in purchasing power parity terms [17]. Conversely, the top 10% of
the population in East Asia emits significantly more than its European counterpart
(40tCO
2
e vs. 29tCO
2
e, respectively). It also appears that Russia & Central Asia
have an emissions distribution broadly similar to that of Europe, but with higher top
10% emissions (due to higher income and wealth inequalities in Russia & Central
Asia) and lower bottom 50% emissions. Sub-Saharan Africa lags behind, with the
bottom 50% emitting around 0.5 tonnes per capita and per year, and the top 10%
emitting around 7.5 tonnes.
Global carbon inequality between individuals
Figure 2 presents the inequality of carbon emissions between individuals at
the world level. The global bottom 50% emit on average 1.4 tCO
2
e per year and
contribute to 11.5% of the total. The middle 40% emit 6.1 tonnes on average, making
up 40.5% of the total. The top 10% emit 28.7 tonnes (48% of the total). The top
1% emits 101 tonnes (16.9% of the total). Global carbon emissions inequality thus
appears to be great: close to half of all emissions are released by one tenth of
the global population, and just one hundredth of the world population (77 million
individuals) emits about 50% more than the entire bottom half of the population (3.8
billion individuals).
The evolution of individual carbon emissions inequalities
How has global emissions inequality changed over the past few decades? In
Figure 3A, global polluters are ranked from the least emitting to the highest on
the X axis, and their per capita emissions growth rate between 1990 and 2019 is
presented on the Y axis. (Figure 4B shows where each global percentile of emitters
live as discussed below.) Since 1990, average global emissions per capita grew by
2.3% (and overall emissions grew by about 50%, see SI Table 6.1). The per capita
emissions of the bottom 50% grew faster than the average (26%), while those of the
middle 40% as a whole was negative (-1.2%), and some percentiles of the global
distribution actually saw a reduction in their emissions of between 5 and 25%. Per
capita emissions of the top 1% emissions grew by 26% and top 0.01% emissions by
5
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