would income redistribution result in higher aggregate...

OutlineMotivation and Previous literature

Data and MethodologyResults

Discussion

Would income redistribution result in higheraggregate emissions?

(”Income Inequality and Carbon Consumption:Evidence from Environmental Engel Curves”)

Lutz Sager([email protected])

PhD Student in Environmental EconomicsGrantham Research Institute — Department of Geography & Environment

London School of Economics and Political Science

27 April 2017

Lutz Sager ([email protected]) Would income redistribution result in higher aggregate emissions?



Discussion

1 Motivation and Previous literature

2 Data and Methodology

3 ResultsIncome, consumption, technologyHousehold carbon inequalityQuantifying the ”equity-pollution” dilemmaPositional consumption (?)

4 Discussion




Discussion

Motivation: Greenhouse gas emissions and climate change

Source: IPCC, 2014 (AR5)




Discussion

Motivation: Greenhouse gas emissions and climate change

Global annual GHG emissions49Gt CO2e in 2010 (7t pp)

Limiting global warming to 2oC(relative to 1861-1880)..

..requires about 40-70 per centreduction in GHG emissions by2050.

about 2-3t per person

Source: IPCC, 2014 (AR5)




Discussion

Motivation: Income inequality on the rise

Source: Atkinson et al., JEL 2011

Rising incomeinequality since1980s(Atkinson et al.,2011)

Rising wealthinequality since1980s (Saez &Zucman, 2016)

Global convergenceof living standards(Lakner & Milanovic,2016)




Discussion

Motivation: Distribution matters

Distribution matters:

Welfare & distributional justice (Rawls, 1971; Cowell, 2011)

Social norms and cohesion (Wilkinson & Pickett, 2010)

Economic development (Alesina & Perotti, 1996)

Consumer behaviour (Stiglitz, 2008; Frank et al., 2014)

...

The environment (?)




Discussion

Motivation: Distribution and the environment

The environment as a source of inequalities:

Climate change and food security in LDC’s(Rosenweig & Parry, Nature 1994)

Exposure and vulnerability to air pollution(Currie & Neidell, QJE 2005)

...

Inequalities as a source of environmental degradation




Discussion

Motivation: The ”equity-pollution” dilemma

Existing literature: Income and carbon

Income is predictor for CO2 (e.g. Chancel & Piketty, 2015)

BUT Income elasticity < 1 (e.g. Chakravarty et al., 2009)

Necessities are carbon-intensive (Pearce, 1991)

Regulation / taxation can be regressive (Gough, 2013)

The ”equity-pollution” dilemma:

Given the higher pollution intensity of consumption per unit ofexpenditure by poorer households, progressive redistribution mayresult in higher aggregate pollution from consumption.




Discussion

Motivation: Research question(s)

Principal research question:

Will progressive income redistribution increase GHG emissionsembedded in household consumption? If yes, by how much?

Subsidiary research questions:

1 How does consumption-based carbon vary with income?

Budget constraint?Other correlated factors?

2 How has consumption-based carbon evolved over time?

Contribution of technology?Income growth? Distribution?

3 Inequality of consumption-based carbon?

Contribution of income, education, location, etc.?




Discussion

Previous literature: Inequality & carbon

Theory: How inequality may affect environmental outcomes

Political Economy (Boyce, 1994)

Consumer choice (Scruggs, 1998; Heerink et al., 2001)

Evidence: Association between inequality and emissions

Baek & Gweisah (2013): positive association(time-series, US, 1967-2008)

Heerink et al. (2001): negative association(panel, 180 countries, 1961-2001)

Others; BUT problems of identification for causal inference




Discussion

Previous literature: Inequality & carbon

Contribution of this draft:

Estimate household carbon in United States (1996-2009)

First to quantify the ”equity-pollution” dilemma

Decompose evolution of household carbon (1996 vs. 2009)

Decompose household carbon inequality (2009)

Using concept of Environmental Engel curves (EEC)introduced by Levinson & O’Brien (NBER, 2015)

Assess link between carbon intensity and ’visibility’ of goods




Discussion

Methodology: (Environmental) Engel curves

EEC for air pollution (Levinson & O’Brien, NBER 2015)Household-level Kuznets curve (Kahn, 1998)Allows for a number of analytical exercisesKey assumption: (Conditional) homogeneity of preferences




Discussion

Methodology: From consumption to emissions




Discussion

Consumer expenditure (CEX) - Data

Data source: U.S. Consumer Expenditure Survey (quarterly)(Bureau of Labor Statistics)

Population: U.S. Consumer Units (CU / Households)

Information: - Monthly expenditures (860 UCC) [MTBI]- CU Income & characteristics [FMLI]- Much more (potential use?)

Sample: 51,642 CU (1996 - 2009, yearly)[full information providers]




Discussion

Emission factors (WIOD) - Data

Data source: World Input-Output Database

Population: 35 Industry sectors (US, 1996-2009) List

Information: - Input-output tables [IO]- CO2 emissions per sector [Env. Acc.]

Output: Emission intensity (kg CO2 per USD)

Methodology: Leontief(1970)




Discussion

Emission factors (Direct)

Yearly avg. prices [U.S. EIA]:

1 Gasoline (retail)

2 Heating oil (residential)

3 Gas (residential)

4 Electricity (residential)

Air travel [U.S. BTS]:Avg. fuel use

Avg. pass. miles x Avg. pass. milesAvg. air fare

Emission factors [U.S. EPA]:

1 Gasoline

2 Heating oil/Diesel

3 Propane gas

4 Kerosene-type jet-fuel

Electricity [U.S. EPA eGRID]:Total CO2 emissions (kg)

Total energy output (kWh)




Discussion

Final sample




Discussion

Limitations

Limitations:

1 Product segments / quality

2 Trade (in progress)

3 Only CO2, not CH4/N2O (agriculture, waste disposal..)

4 CEX Survey: Sampling (tails), reporting bias, etc.

5 Sample: Full-information reporters only

6 Matching: 641 UCC codes to 34 WIOD sectors

7 Coverage: Deductions (e.g. medicine), debt / mortgage, etc.

8 Regional heterogeneity (electricity grid, rural/urban, etc.)




Discussion

Income, consumption, technologyHousehold carbon inequalityQuantifying the ”equity-pollution” dilemmaPositional consumption (?)

Results: Non-parametric Engel curves

1 EECs areincreasing

2 EECs areconcave

3 EECs shift downover time




Discussion


Results: Non-parametric Engel curves




Discussion


Results: Technology, savings, composition

Detail




Discussion


Results: Parametric Engel curves

Further analyses require additional assumptions:

1 Inclusion of control variables

2 Specific functional form for EEC

3 Assume (conditional) homogeneity of preferences

Empirical specification:

yit = β1tmit + β2tm2it + x′itδt + εit (1)

Household carbon (yit); After tax income (mit); Controls (x′it)




Discussion


Results: Parametric Engel curves




Discussion


Results: Household carbon - Decomposition over time

Oaxaca-Blinder decomposition:

Increase of 10.9t inhousehold carbon between1996 (22.8t) and 2009(33.7t) [2009 technology]

Income (after tax)explains 3.4t (30 percent)

Expenditure explains 6.0t(55 per cent)

Other variables explain little




Discussion


Results: Households carbon inequality




Discussion


Results: Household carbon inequality - Decomposition

Factor decomposition:

Income explains30-41 per cent ofvariation in CO2

Family sizeexplains 11-13 percent

Other variablesexplain little

Large unexplainedvariation




Discussion


Results: Quantifying the ”equity-pollution” dilemma

Findings so far:

1 Environmental Engel curves

are upward-slopingare concaveshift down with time

2 Income appears to be main driver of household CO2

Across time (alongside technology)Within time

3 Other household characteristics explain little

4 Large unexplained variation remains

So, by how much would income redistribution increase CO2?




Discussion


Results: Quantifying the ”equity-pollution” dilemma

Example (2009): β2 = −0.27, Ψ = 57.1 (k USD) Math

Marginal redistribution :

The expected effect of a marginal redistribution of 1000 USD froma higher income to a lower income household is an increase of30.8kg in household CO2. That constitutes about 6 per cent ofaverage CO2 per 1000 USD expenditure (514kg).

Full redistribution:

Average household carbon in 2009 is predicted to increase by 0.9tfrom 33.7t to about 34.6t under full income equality, a rise ofabout 2.7 per cent.




Discussion


Results: Positional consumption (?)




Discussion

Discussion

Next steps:

1 Expand from 1996-2009 to 1996-2014 (WIOD)2 Improve measurement:

TradeCO2eRegional prices / emission-factors...

Future research:1 Motivations for consumption of specific goods

Status / positional consumptionEnvironmental awareness in consumption...

2 Wealth inequality and access to assets




Discussion

Appendix: WIOD sectors




Discussion

Appendix: WIOD sectors

Back to WIOD




Discussion

Appendix: Direct emission factors




Discussion

Appendix: Consumption categories




Discussion

Appendix: Emission factors (WIOD) - Methodology

Methodology as proposed by Leontief (1970)Output of n sectors (x); intermediate (Cx) and consumed (y).

x = Cx + y (2)

Direct Requirement matrix (C) to Total Requirement matrix (T).

x = [I− C]−1y = Ty (3)

Total emission-intensities (z) to total emission-intensities (z).

z = z′T (4)

Back to WIOD




Discussion

Appendix: Technology, savings, composition

Back




Discussion

Results: Quantifying the ”equity-pollution” dilemmaEstimated EEC: yit = β1tmit + β2tm

2it + x′itδt

Marginal change in consumption from income:∂yi∂mi

= β1 + 2β2mi

Marginal transfer from j to i :∂yi∂mi−

∂yj∂mj

= −2β2(mj − mi )

Expected effect of marginal transfer between two random households:

Eij(∂yi∂mi− ∂yj∂mj|mj > mi ) = −2β2Eij (mj −mi |mj > mi ) = −2β2Ψ(F (m))

Gini’s Mean Difference: Ψ(F (m)) =∫ ∫|y − z|dF (y)dF (z) or 1

N(N−1)

∑Ni=1

∑Nj=1 |mi − mj |, i 6= j

Difference in emissions when moving to ”full equality”:

β2

[m2 − 1

N

N∑i=1

m2i

]Back to Results




Discussion

Appendix: Positional consumption (?)


LSE Seminar series on Climate Change, Inequality and Social Policy27 April 2017

Would income redistribution result in higher aggregate emissions?Lutz Sager (Grantham Research Institute, LSE)

Discussants:

Ian GoughVisiting Professor CASE and Grantham Research Institute, LSE

Professor Angela DruckmanCentre for the Understanding of Sustainable Prosperity, University of Surrey

Ian Gough:Heat, Greed and Human Need:

Climate change, capitalism and sustainable wellbeing

Edward Elgar, Forthcoming autumn 2017

Selected slides

Categories of personal consumption by necessity and emission content, UK 2009

Source: Chitnis et al (2014): Tables 5, A.5

Summary of eco‐social policies in Chapter 7

Raworth, K. (2012) 'A safe and just space for humanity: can we live within the doughnut', Oxfam Policy and Practice: Climate Change and Resilience, 8(1), 1-26.

A Safe and Just Space for Humanity

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