Skip to contents

Load GDP data

Source: R/load_gdp_data.R
load_gdp_data.Rd

Loads GDP data from one of two sources included with the package and returns a country-year dataset using either COW or Gleditsch-Ward country codes.

Usage

load_gdp_data(
  start_year = 1945,
  end_year = 2019,
  dataset = c("gapminder", "fariss"),
  coding_system = c("cow", "gw")
)

Source

Gapminder: GDP per capita data from Gapminder. Gapminder data are distributed under CC BY 4.0; please cite Gapminder and the original data providers.

Fariss: Fariss, C.J., Anders, T., Markowitz, J.N., & Barnum, M. (2022). New estimates of over 500 years of historic GDP and population data. Journal of Conflict Resolution, 66(3), 553-591.

Arguments

start_year

Integer. First year to include.

end_year

Integer. Last year to include.

dataset

Character. Dataset to load:

"gapminder"

Gapminder GDP per capita (v32). Coverage: 1945-2019 by default (full source coverage is wider).

"fariss"

Latent GDP and GDP per capita estimates (Fariss, Anders, Markowitz & Barnum 2022), combined from their fariss_gdp and fariss_gdppc replication files. Coverage: 1500-2019.

coding_system

Character. Country coding system to use. Either "cow" for Correlates of War codes or "gw" for Gleditsch-Ward codes.

Value

A data frame with country-year GDP indicators. If coding_system = "cow", the data frame contains a cow column. If coding_system = "gw", it contains a gw column. Columns differ by dataset:

gapminder: year, gdp_pcap, log_gdp_pcap, gdp_growth.

fariss: year, fariss_gdp, fariss_gdppc.

Details

gdp_growth (gapminder only) is NA unless the preceding row is genuinely one year earlier for the same country, the same gap-safety check add_lag() uses, so a missing year never silently produces a growth rate computed against the wrong base year.

fariss_gdp and fariss_gdppc are the model's own latent-scale estimates, taken directly from the "latent_gdp"/"latent_gdppc" rows of the replication files (as opposed to the underlying raw indicator series also present in those files). Their absolute units are not independently verified here; consult Fariss et al. (2022) before using them outside of relative/comparative analysis.

References

Gapminder. (2024). GDP per capita in constant PPP dollars. https://www.gapminder.org/gdp-per-capita/

Fariss, C. J., Anders, T., Markowitz, J. N., & Barnum, M. (2022). New estimates of over 500 years of historic GDP and population data. Journal of Conflict Resolution, 66(3), 553-591. doi:10.1177/00220027211054432

Examples

gdp_cow <- load_gdp_data(coding_system = "cow")

gdp_gw <- load_gdp_data(coding_system = "gw")

fariss_gdp <- load_gdp_data(1900, 2015, dataset = "fariss", coding_system = "cow")