By Malcolm Fairbrother

1. Climate, Economic Growth, and
National Preferences for
Geoengineering
Dr Malcolm Fairbrother
Dr Adam Dixon
School of Geographical Sciences
University of Bristol
15 August 2012

2. Context
 If you could choose a climate for your country
(especially temperature) what would you choose?
 choice may soon no longer be amusingly
hypothetical, because of geoengineering
 even without geoengineering, questions about the
consequences of future climate change for the
economy
Q1: How do climatic conditions affect the economy?

3. Context: Geoengineering/Climate
Preferences… and Conflicts?
 climate consequences of geoengineering (and of
climate change generally) are likely to vary cross-
nationally
 the economic benefits versus costs of
geoengineering (including compared to
uncontrolled climate change) may therefore be
distributed unequally across countries
Q2: Based on a model of the consequences for the
climate of different geoengineering scenarios, and
a model of climate’s consequences for economic
growth, what geoengineering options will different
national governments prefer?

4. Economics of Geoengineering
 few people prefer geoengineering to mitigation,
but…
 technical feasibility (of various geoengineering
options) is under investigation, and appears to be
not far off
 financial costs of geoengineering may be lower
than those of greenhouse gas emission
reductions
 mitigation through emissions reductions requires
multilateral (collective) action, while
geoengineering may be possible for even just one
actor unilaterally…

6. Costs (and Benefits?) of Climate
Change and/or Geoengineering
A. ecological
 status quo best (also for ecosystem services)
B. economic
1. costs of geoengineering
2. costs of transition/adaptation to new climate
3. sea level rise
4. weather (fluctuations from climate)
5. impacts of climate on growth

7. Costs (and Benefits?) of Climate
Change and/or Geoengineering
1. costs of geoengineering
2. costs of transition/adaptation to new climate
3. sea level rise
4. weather (annual/briefer fluctuations from
climate)
5. impacts of climate on growth
 financial implications of 4-5 potentially largest
 unless SLR is really substantial…
 4 and 5 could have benefits for some regions,
not just costs
 we focus here on 5, and the question of how
different climates would affect countries’

13. Climate and Economy
 standard (old) observation: cold countries tend to
be rich, and hot countries tend to be poor
 e.g., Montesquieu 1748, Huntington 1915
 a few exceptions:
 North Korea, post-socialist nations (e.g.,
Mongolia)
 Singapore, small oil-rich nations (e.g., Qatar)
 renewed interest in the impacts of climate/natural
geography on economic growth and incomes
 partly, but not only, because of climate change
 new datasets, methods
 policy implications (e.g., aid for African

15. Climate and Economy: Literature
 Jeffrey Sachs and collaborators:
 Africa (e.g.) is poor partly because of
climate/natural geog
 proximity to coast/navigable rivers
 health burden of tropical disease (especially
malaria)
 also parasitic, disease, etc., impacts on plants,
livestock
 policy implication: foreign aid for specific climate-
counteracting measures (e.g., mosquito nets,
agricultural productivity-enhancing technology)
 method: cross-sectional regressions with

17. Climate and Economy: A Caveat
 so is “colder always better”? maybe, but maybe
not…
 historically, climate/natural geography led to
cross-national differences in key economic,
political, and social institutions
 institutions have been a (some say the) primary
source of cross-national income differences (see
Rodrik, etc.)
 absence of corruption
 capable public administration, law
enforcement
 effective public education and health services

18. Climate and Economy: A Caveat
 implication: climatic differences across nations
are collinear with national-level conditions that
could be the real determinants of (growth rates in)
living standards
 risk of naïve interpretations of regressions of
income on climatic variables
 how then to control for potentially confounding
national-level variables?

19. Climate and Economy: Finer
Scale
 one solution: draw contrasts within countries
 and within-country analyses have two other
advantages:
1. climatic averages for large countries are
dubious
 exploit disaggregated data
2. if we want to know, counterfactually, how a
region would be affected by a different
climate, comparing it to another in the same
country controls for lots of things
 even if the climate were to change, many
other things probably wouldn’t (culture,

20. Climate and Economy: Literature
 Dell, Jones, and Olken (DJO) 2009:
 cross-sectionally, warmer temperatures are
correlated with lower per capita incomes…
 not just across countries (-8.5% per 1°C rise),
 but also within them,
 and even within regions within countries
 data: municipal-level, from 12 countries in the
Americas
 all this “suggests that omitted country
characteristics are not wholly driving the cross-
sectional relationship between temperature and
income”

21. Climate and Economy:
From GDP/capita to GDP/km2
 Nordhaus 2006 (etc.):
 produced a “G-Econ” dataset with estimates of
economic activity for 1° by 1° land gridcells in
1990 (N = ~20,000)
 “Gross Cell Product” (GCP), not per capita
 key findings:
 temperature again the most important climatic
variable
 per area instead of per capita, higher
temperatures are correlated with more output,
not less, and non-linearly
 output/area peaks at about 12°C

22. Nordhaus: A “Climate-Output
Reversal”
GDP/capita:
declines
monotonically with
temperature
GDP/area:
rises with
temperature, then
declines past ~12°C

25. GDP/capita and GDP/km2
 at the national level, GDP/capita is probably the
greater concern
 but within countries, differences in the
concentration of GDP in different areas may tell
us something about where people want to live
 population movements may reflect human
security, economic opportunities, climate-
related quality of life
 national climate/geoengineering preferences
could therefore reflect impacts on either
GDP/capita or GDP/km2
 we consider both

26. Weather and the Economy
 other studies look not at climate, but the effects of
weather (year-on-year fluctuations, drought, etc.)
 some studies say precipitation matters more than
temperature, others the opposite
 e.g., DJO 2012: +/-1°C fluctuations
increase/reduce GDP growth by 1.3% (not just
the level of GDP)
 though only for poor countries, not rich
 and by many means, not just through effects on
agriculture
 e.g., political instability

27. Existing Models: Summary
 Sachs, Nordhaus, DJO 2009, others: cross-
sectional
 limitation: growth over time ≠ cross-sectional
differences
 also limitations of many studies because only
national-level
 DJO 2012, others: fluctuations from the norm
over time
 limitation: dismisses the norm (what if the norm
changes?)

28. Our Modelling Strategy
 we investigate how economic production changes
(grows) over time, and varies cross-sectionally,
treating production as a function of time-invariant
climate characteristics
1. at the national level (differences among
nations)
2. at the sub-national level (differences within
nations)
 model GDP growth using a multilevel “growth
curve”
 interact time-invariant X variable of interest with
time

29. Multilevel Modelling
 four-level multilevel model, with cell-years (i)
cross-classified in cells (c) and country-times (t),
and cells and country-times in turn both nested
within countries (j):
 mean-centre each covariate by country
 produces (e.g.) mean temperature by country,
and difference between gridcell temperature

30. Data
 climate data from Irvine et al.
 based on HadCM3L, a Met Office Hadley
Centre atmosphere-ocean general circulation
model used in the IPCC’s Third and Fourth
Assessments
 geoengineered climate scenarios
 national-level economic data from the Penn World
Table 7.0
 gridcell data from G-Econ project (Nordhaus et
al.)
 four waves: 1990, 1995, 2000, 2005
 billions of current USD (market exchange rates)

33. Outcome: Gross Cell Product
Coefficient Estimate (* p < 0.05) Estimate (* p < 0.05)
(Intercept) 17.4* 18.0* Fixed
poly(dprec,2)1 58.2* 48.0* Effects
Coefficients
poly(dprec,2)2 -63.1* -74.1*
time 0.110* 0.129*
poly(dtemp,2)1 367* 173*
poly(dtemp,2)2 18.8* -44.7*
poly(cm.temp,2)1 249* 98.3
poly(cm.temp,2)2 -393* -344*
time:poly(dtemp,2)1 6.38* 2.59*
time:poly(dtemp,2)2 -1.75* -4.81*
time:poly(cm.temp,2) 19.3* 8.17*
1
time:poly(cm.temp,2) -1.86 -0.726
2
RE Gridcell 8.66 7.07 Random
RE Country-Year 0.05 0.04 Effects
Variances
RE Country 4.69 4.33
RE Residual 0.15 0.17
# countries 173 (all) 152 (no big oil producers)

34. Capita
Coefficient Estimate (* p < 0.05) Estimate (* p < 0.05)
(Intercept) 8.57* 8.61* Fixed
poly(dprec,2)1 -4.28* -5.39* Effects
Coefficients
poly(dprec,2)2 4.31* 4.46*
time 0.08* 0.09*
poly(dtemp,2)1 -28.26* -5.43*
poly(dtemp,2)2 -14.49* 2.87*
cm.temp -0.06* -0.07*
time:poly(dtemp, 2)1 1.95* 1.56*
time:poly(dtemp, 2)2 -0.57* -1.21*
time:cm.temp 0.00 -0.00
RE Gridcell 0.24 0.17 Random
RE Country-Year 0.05 0.04 Effects
Variances
RE Country 3.01 2.69
RE Residual 0.02 0.01
# countries 173 (all) 152 (no big oil producers)

39. Conclusions/Implications
 growth within countries may be… like Goldilocks?
 appears to hold either per capita, or in absolute
terms
 for some countries, the economic implications of
“predictable” climate change may be… positive
 many countries are better off (in terms of
predicted growth in human standards of living)
in a “warmed” scenario
 does imply potential international conflicts over
interest over geoengineering

40. A Final Caveat
 this analysis addresses the economic implications
of changes in the typical climate of a place… not
the weather
 sea level rise, extreme weather events (droughts,
storms, etc.), and increased year-on-year climate
variability all have potentially huge costs
 those potential costs, compared to the small
relative costs of greenhouse gas emission
reductions, still imply an aggressive climate
mitigation strategy (e.g., a $30/tonne price for
CO2)
 EU Emissions Trading System, British Columbia
carbon tax