Climate, Economic Growth, and National Preferences for Geoengineering
Climate, Economic Growth, and National Preferences for Geoengineering Dr Malcolm Fairbrother Dr Adam Dixon School of Geographical Sciences University of Bristol 15 August 2012
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 economyQ1: How do climatic conditions affect the economy?
Context: Geoengineering/ClimatePreferences… 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 countriesQ2: 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?
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…
Costs (and Benefits?) of ClimateChange and/or GeoengineeringA. 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
Costs (and Benefits?) of ClimateChange 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’
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
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
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
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?
Climate and Economy: FinerScale 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,
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”
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
Nordhaus: A “Climate-Output Reversal” GDP/capita: declines monotonically with temperatureGDP/area:rises withtemperature, thendeclines past ~12°C
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
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
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?)
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
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
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)
CapitaCoefficient Estimate (* p < 0.05) Estimate (* p < 0.05)(Intercept) 8.57* 8.61* Fixedpoly(dprec,2)1 -4.28* -5.39* Effects Coefficientspoly(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 -0.00RE Gridcell 0.24 0.17 RandomRE Country-Year 0.05 0.04 Effects VariancesRE Country 3.01 2.69RE Residual 0.02 0.01# countries 173 (all) 152 (no big oil producers)
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
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