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Economics and the Geosciences

Economics and the Geosciences. William D. Nordhaus AAAS Annual Meetings Yale University February 18, 2011.

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Economics and the Geosciences

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  1. Economics and the Geosciences William D. Nordhaus AAAS Annual Meetings Yale University February 18, 2011

  2. Outline of presentation • Economics and geography (GEcon) • Economics and luminosity • Integrated modeling of economics of climate change (DICE/RICE)

  3. The GEcon project • Purpose is to develop matched geophysical and economic data at geophysically scaling • Purposes: • Many processes are geophysically based (e.g., climate) • Much higher resolution (circa 100x): like Hubble telescope • Can be matched with geophysical, environmental data (climate, elevation, distance from coast or market, pollution, etc.) Nordhaus, Macroeconomics and Geography, PNAS, 2007; Nordhaus and Chen,

  4. Derivation of Data Set GPW grid cell estimates of population, area, RIG National or regional gross output, population data National and provincial GIS grid data (RIG, area, boundaries) Regional (e.g., county) estimates of output per capita Proportional allocation from political to geophysical boundaries GEcon gross cell product (GCP) data

  5. Countries and grid cells for Europe

  6. Europe in 3D

  7. Australia in 3D

  8. Luminosity as a Proxy for Output Xi Chen William Nordhaus

  9. Combining socioeconomic and luminosity data Economic data on developing countries is very weak. Question for this project: Can we use luminosity (nighttime lights) data as a proxy for standard accounting data for low-quality regions? Allows use of regional GEcon data for rich regional data set.

  10. Key elements in evaluating luminosity as a proxy The key elements in determining the value of a proxy are: • The quality of the luminosity data • The errors of measurement of the standard GDP data • The statistical relationship between luminosity and GDP The background paper shows the optimal weighting as a signal-extraction statistical problem. Chen and Nordhaus, The Value of Luminosity Data as a Proxy for Economic Statistics, NBER Working Paper, 2010

  11. Problems illustrated for southern New England Bleeding Saturation 11

  12. Stable lights and output by 1° x 1° grid cell (n = 14,287)

  13. Results on optimal weight on luminosity Chen and Nordhaus, in process.

  14. Main Results • For most countries, luminosity is essentially useless as a proxy for GDP and output measures. • Possible information value in statistical basket cases.

  15. Economic Integrated Assessment (IA) Models in Climate Change

  16. Integrated Assessment (IA) Models in Climate Change What are IA models? These are models that include the full range of cause and effect in climate change (“end to end” modeling). Major goals of IA models: Project trends in consistent manner Assess costs and benefits of climate policies Estimate the carbon price and efficient emissions reductions for different goals Nordhaus, “Copenhagen Accord,” PNAS, 2010.

  17. The emissions-climate-impacts-policy nexus: The RICE-2010model Fossil fuel use generates CO2 emissions Carbon cycle: redistributes around atmosphere, oceans, etc. Climate system: change in radiative warming, precip, ocean currents, sea level rise,… Impacts on ecosystems, agriculture, diseases, skiing, golfing, … Measures to control emissions (limits, taxes, subsidies, …)

  18. RICE-2010 model structure* Economic module: • Standard economic production structure • GHG emissions are global externality • 12 regions, multiple periods CO2/Climate module: • Emissions = f(Q, carbon price, time) • Concentrations = g(emissions, diffusion) • Temperature change = h(GHG forcings, time lag) • Economic damage = F(output, T, CO2, sea level rise) * Nordhaus, “Economics of Copenhagen Accord,” PNAS (US), 2010.

  19. Policy Scenarios for Analysis using the RICE-2010 model • 1. Baseline. • 2. Economic cost-benefit “optimum.” • 3. Limit to 2 °C. • 4. Copenhagen Accord, all countries. • 5. Copenhagen Accord, rich only.

  20. Temperature profiles: RICE -2010 Source: Nordhaus, “Economics of Copenhagen Accord,” PNAS (US), 2010.

  21. An interesting byproduct: CO2 shadow prices Shadow prices (social costs) were discovered by developers of linear programming techniques (Kantorovich and Koopmans, Nobel 1974). Originally thought useful for central planning prices. Today, useful because they reflect the marginal cost, or prices, of a constraint when efficiently imposed. For example, IA models can calculate the price associated with the 2 °C temperature target as a byproduct of the economic models. Can be used as guidelines for setting CO2 taxes or prices.

  22. Carbon prices for major scenarios from RICE-2010 model Source: Nordhaus, “Economics of Copenhagen Accord,” PNAS (US), 2010.

  23. Where are we today? Actual equivalent global carbon price = $1 / tCO2 Source: Nordhaus, “Economics of Copenhagen Accord,” PNAS (US), 2010. 23

  24. A new scientific renaissance of social and natural sciences?

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