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4 results for “social cost of carbon”
The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates
<p>This repository contains the socioeconomic and emissions projections generated by the Resources for the Future Socioeconomic Projections (RFF-SPs) model as discussed in Rennert et al., "<a href="https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/">The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates</a>" , forthcoming at the <em>Brookings Papers on Economic Activity</em>. The data take the form of a Monte Carlo simulation with n = 10,000 draws.</p> <p>File structure and column metadata are described here: </p> <p>--- <br> emissions/ <br> --- </p> <p>- rffsp_co2_emissions.csv <br> - rffsp_ch4_emissions.csv <br> - rffsp_n2o_emissions.csv </p> <p>Each file in this folder contains 3 columns: sample, year, and value. For each row: </p> <p>- sample contains the number identifying which draw a prediction belongs to (from 1 to 10,000). <br> - year contains the calendar year of the prediction. <br> - value contains the projected annual global emissions of the gas specified in the filename. IMPORTANT: Units are as follows: "rffsp_co2_emissions.csv" is in gigatons C (not CO2), "rffsp_ch4_emissions.csv " is in megatons CH4, and "rffsp_n2o_emissions.csv " is in megatons N2 (not N2O). </p> <p>--- <br> pop_income/ <br> --- </p> <p>- rffsp_pop_income_run_1.feather <br> - rffsp_pop_income_run_2.feather <br> - rffsp_pop_income_run_3.feather <br> . <br> . <br> . <br> - rffsp_pop_income_run_9999.feather <br> - rffsp_pop_income_run_10000.feather </p> <p>This folder contains 10,000 files in the .feather file format (https://arrow.apache.org/docs/python/feather.html), which is optimized for I/O speed and compressed to minimize storage requirements. Each file corresponds to one draw of our socioeconomic data, and contains 4 columns: Country, Year, Pop, and GDP. The number in each filename corresponds to the "sample" column in the emissions data. For each row:</p> <p>- Country contains the ISO Alpha-3 code (https://www.iso.org/iso-3166-country-codes.html) of the country whose GDP and population are projected. <br> - Year contains the calendar year of the predictions. <br> - Pop contains the projected population for a given country and year, in units of thousands of people. <br> - GDP contains the projected GDP for a given country and year, in units of millions of 2011 USD. </p> <p>--- </p> <p>The probabilistic population projections were produced by Adrian E. Raftery and Hana Ševčíková (University of Washington), using the methods described by Raftery and Ševčíková (2021). Please cite this reference in any publications using these projections. Their research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) under NIH grant number R01 HD-070936. </p> <p>The probabilistic economic and emissions projections are from Rennert et al. (forthcoming), based in part on those from Müller, Stock, and Watson (forthcoming). </p> <p>---</p> <p><strong>References </strong></p> <p>Müller, U.K, Stock, J.H., and Watson, M.W. (forthcoming). An Econometric Model of International Growth Dynamics for Long-Horizon Forecasting. The Review of Economics and Statistics, available online 30 October 2020. URL: <a href="https://direct.mit.edu/rest/article-abstract/doi/10.1162/rest_a_00997/97738/An-Econometric-Model-of-International-Growth">https://direct.mit.edu/rest/article-abstract/doi/10.1162/rest_a_00997/97738/An-Econometric-Model-of-International-Growth</a> </p> <p>Raftery, A.E. and Ševčíková, H. (2021). Probabilistic population forecasting: Short to very long-term. International Journal of Forecasting, available online 7 October 2021. URL: <a href="https://www.sciencedirect.com/science/article/pii/S0169207021001394">https://www.sciencedirect.com/science/article/pii/S0169207021001394</a> </p> <p>Rennert, K., Prest, B.C., Pizer, W., Newell, R.G., Anthoff, D., Kingdon, C., Rennels, L., Cooke, R., Raftery, A.E., Ševčíková, H, and Errickson, F. (forthcoming). The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates. Brookings Papers on Economic Activity. Available online 27 October 2021. URL: <a href="https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/">https://www.rff.org/publications/working-papers/the-social-cost-of-carbon-advances-in-long-term-probabilistic-projections-of-population-gdp-emissions-and-discount-rates/ </a></p>
Data files for "Estimating a Social Cost of Carbon for Global Energy Consumption"
<p>Data files for "Estimating a Social Cost of Carbon for Global Energy Consumption".</p> <p>Findings of the paper can be replicated using these data files, along with code at https://github.com/ClimateImpactLab/energy-code-release-2020/.</p> <p> </p>
Reproduction data and code for "The social cost of carbon dioxide under climate-economy feedbacks and temperature variability"
<p>### Data for Kikstra et al. 2021, ERL, The social cost of carbon dioxide under climate-economy feedbacks and temperature variability</p> <p>This repository contains data and scripts for the main text figures in the article Kikstra, J.S., Waidelich, P., Rising J., Yumashev, D., Hope, C., Brierley, C.M. (2021) The social cost of carbon dioxide under climate-economy feedbacks and temperature variability, Environmental Research Letters. DOI <a href="https://doi.org/10.1088/1748-9326/ac1d0b">https://doi.org/10.1088/1748-9326/ac1d0b</a></p> <p>##### Authors<br> - Jarmo S. Kikstra<br> - Paul Waidelich<br> - James Rising<br> - Dmitry Yumashev<br> - Chris Hope<br> - Chris M. Brierly</p> <p>Correspondence: kikstra@iiasa.ac.at</p> <p>##### Data repository structure<br> - data # hosts all data that is used to produce the main text figures<br> - growth-effects # hosts model data for results from model runs with persistent damages, for figure 3 and figure 4<br> - PAGE-ANN-Growth_ModelResults_PersistenceDistribution # annual PAGE version, empirical persistence distribution<br> - PAGE-arVAR-Growth_ModelResults_PersistenceDistribution # annual PAGE version with temperature variability, empirical persistence distribution<br> - PAGE-Growth_ModelResults_FixedPersistence # main version, with 10 time steps, fixed persistence levels<br> - PAGE-Growth_ModelResults_LowPassFilterPersistenceDistribution # main version, with 10 time steps, low pass filter persistence distribution<br> - PAGE-Growth_ModelResults_PersistenceDistribution # main version, with 10 time steps, empirical persistence distribution<br> - page-ice # model data for results from PAGE-ICE base model runs<br> - scco2-montecarlo # for figure 6 data<br> - update-page # for figure 2 data<br> - variability # for figure 5 data<br> - extended data # hosts other data used in the manuscript or which we simply want to publish alongside. Example for naming convention for each variable in […] behind the files.<br> - economic-impact # model output variables “EquityWeighting_ te_totaleffect{_ann_yr}.csv” [PAGE-ICE_SSP1-1.9_discountedimpacts.csv]<br> - montecarlo-draws # model output variable “trialdata.csv” [PAGE-ICE_SSP1-1.9_trialdata.csv]<br> - sensitivity # hosts selected sensitivity analysis data used in the appendix<br> - temperature # model output variable “ClimateTemperature_rt_g_globaltemperature.csv” [PAGE-ICE_SSP1-1.9_globaltemperature.csv]<br> - scripts # has one script for each main text figure,<br> - figures # hosts main text figures as they come out of the scripts<br> - README.md # explanation for the repository</p>
Data and code for "Persistent macroeconomic damages raise social cost of carbon"
<p>This repository contains data and code to reproduce findings and figures of the paper:</p> <p>"Persistent macroeconomic damages raise social cost of carbon"</p> <p>Maximilian Kotz, Christopher Callahan, Annika Stechemesser, Leonie Wenz</p> <p>Details are given in the README and the repository will likely be updated in coming months.</p> <p>For questions please contact: maxkotz@pik-potsdam.de</p> <p> </p>
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