Resources for the Future Socioeconomic Projections (RFF-SPs)

RFF-SPs Monte Carlo output data:

This dataset includes the socioeconomic and emissions data generated by the Resources for the Future Socioeconomic Projections (RFF-SPs) model as discussed in Rennert et al. (forthcoming) (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 data take the form of a Monte Carlo simulation with n = 10,000 draws. File structure and column metadata are described here:

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death_rates/

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• rffsp_death_rates_run_1.feather
• rffsp_death_rates_run_2.feather
• rffsp_death_rates_run_2.feather

       ...

• rffsp_death_rates_run_999.feather
• rffsp_death_rates_run_1000.feather

This folder contains 1,000 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 in this folder contains 3 columns: ISO3, Year, and DeathRate. For each row:

- ISO3 contains the ISO numeric-3 code (https://www.iso.org/iso-3166-country-codes.html) of the country whose GDP and population are projected. - Year contains the calendar year of the predictions.

- year contains the calendar year of the prediction.

- DeathRate contains a death rate in average deaths per 1000 people.

Baseline mortality data found in data/mortality was derived from the death_rates.csv provided to the RFF team on October 7th from Hana Sevcikova.  In that source file, the column DeathRate is the annual deaths per 1000 people. PopAvg is the denominator (average between two time periods) and PopStart is population at the start of the time interval. Values are average deaths per 1000 people.

There is one mortality death rate trajectory for each population trajectory, and each RFF-SP is matched to one of these 1000 trajectories. The file sampled_pop_trajectory_numbers.csv described below maps each of the 10,000 RFF SP scenarios to the baseline mortality scenario (out of 1000) matched to its population draw.

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emissions/

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• rffsp_co2_emissions.csv
• rffsp_ch4_emissions.csv
• rffsp_n2o_emissions.csv

Each file in this folder contains 3 columns: sample, year, and value. For each row:

- sample contains the number identifying which draw a prediction belongs to (from 1 to 10,000).

- year contains the calendar year of the prediction.

- value contains the projected annual global emissions of the gas specified in the filename.

The units are as follows:

• rffsp_co2_emissions.csv is in gigatons C
• rffsp_ch4_emissions.csv is in megatons CH4
• rffsp_n2o_emissions.csv is in megatons N2

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pop_income/

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• rffsp_pop_income_run_1.feather
• rffsp_pop_income_run_2.feather
• rffsp_pop_income_run_3.feather

       ...

• rffsp_pop_income_run_9999.feather
• rffsp_pop_income_run_10000.feather

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:

- 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. - Year contains the calendar year of the predictions.

- Pop contains the projected population for a given country and year, in units of thousands of people.

- GDP contains the projected GDP for a given country and year, in units of millions of 2011 USD.

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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.

The probabilistic economic and emissions projections are from Rennert et al. (forthcoming), which in turn are based in part on Müller, Stock, and Watson (forthcoming).

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sample_numbers/

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• sampled_gdp_trajectory_numbers.csv
• sampled_pop_trajectory_numbers.csv

These two files hold the sample IDs corresponding to the 10,000 draws from the dataset described above in the pop_income/ section. For reproducibility, these sample sets are available as inputs to the scripts which created them and used when the script is run in deterministic mode.  More information on the weighting and specifications of such sampling is available in the code.

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ypc1990/

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• rffsp_ypc1990.csv

This CSV file is a matrix of 10,000 rows, pertaining to the 10,000 draws, and 184 columns, pertaining to the 184 countries in this analysis. The columns are labeled with the ISO Alpha-3 code (https://www.iso.org/iso-3166-country-codes.html). The values are the GDP for a given country and sample, in units of millions of 2011 USD.

References

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: https://direct.mit.edu/rest/article-abstract/doi/10.1162/rest_a_00997/97738/An-Econometric-Model-of-International-Growth

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: https://www.sciencedirect.com/science/article/pii/S0169207021001394

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: 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/