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add_sdp_gdp() allows you to add estimated GDP and "surplus" domestic product data from a 2020 analysis published in International Studies Quarterly by Anders, Fariss, and Markowitz.

Usage

add_sdp_gdp(data)

Arguments

data

a data frame with appropriate peacesciencer attributes

Value

add_sdp_gdp() takes a (dyad-year, leader-year, leader-dyad-year, state-year) data frame and adds information about the estimated gross domestic product (in 2011 USD) for that year, the estimated population in that year, the GDP per capita in that year, and what Anders, Fariss and Markowitz term the "surplus domestic product" in that year. If the data are dyad-year (leader-dyad-year), the function adds eight total columns for the first state (i.e. ccode1) and the second state (i.e. ccode2) for all these estimates. If the data are state-year (or leader-year), the function returns four additional columns to the original data that contain that same information for a given state in a given year.

Details

The function leans on attributes of the data that are provided by one of the "create" functions. Make sure a recognized function (or data created by that function) appear at the top of the proverbial pipe. Users will also want to note that the underlying function access two different data sets. It appears that the results published in the International Studies Quarterly used Correlates of War classification, but a follow-up repository on Github uses Gleditsch-Ward classification. The extent to which these estimates are generated by simulation, it does mean the estimates will be slightly different across both data sets even for common observations (e.g. the United States in 1816).

Because these are large nominal numbers, the estimates have been log-transformed. Users can always exponentiate these if they choose. Researchers can use these data to construct reasonable estimates of surplus GDP per capita, but must exponentiate the underlying variables before doing this.

Be mindful that the data are fundamentally state-year and that extensions to leader-level data should be understood as approximations for leaders in a given state-year.

References

Anders, Therese, Christopher J. Fariss, and Jonathan N. Markowitz. 2020. "Bread Before Guns or Butter: Introducing Surplus Domestic Product (SDP)" International Studies Quarterly 64(2): 392--405.

Author

Steven V. Miller

Examples


# just call `library(tidyverse)` at the top of the your script
library(magrittr)

cow_ddy %>% add_sdp_gdp()
#> # A tibble: 2,101,440 × 11
#>    ccode1 ccode2  year wbgdp2011est1 wbpopest1 sdpest1 wbgdppc2011est1
#>     <dbl>  <dbl> <dbl>         <dbl>     <dbl>   <dbl>           <dbl>
#>  1      2     20  1920          27.6      18.4    27.5            9.19
#>  2      2     20  1921          27.6      18.5    27.5            9.18
#>  3      2     20  1922          27.7      18.5    27.6            9.21
#>  4      2     20  1923          27.8      18.5    27.7            9.26
#>  5      2     20  1924          27.8      18.5    27.7            9.30
#>  6      2     20  1925          27.9      18.5    27.8            9.32
#>  7      2     20  1926          27.9      18.5    27.8            9.34
#>  8      2     20  1927          27.9      18.6    27.8            9.35
#>  9      2     20  1928          27.9      18.6    27.8            9.36
#> 10      2     20  1929          27.9      18.6    27.8            9.35
#> # … with 2,101,430 more rows, and 4 more variables: wbgdp2011est2 <dbl>,
#> #   wbpopest2 <dbl>, sdpest2 <dbl>, wbgdppc2011est2 <dbl>

create_stateyears() %>% add_sdp_gdp()
#> Joining, by = c("ccode", "year")
#> # A tibble: 16,926 × 7
#>    ccode statenme                  year wbgdp2011est wbpopest sdpest wbgdppc2011est
#>    <dbl> <chr>                    <dbl>        <dbl>    <dbl>  <dbl>          <dbl>
#>  1     2 United States of America  1816         23.6     15.9   22.9           7.66
#>  2     2 United States of America  1817         23.6     16.0   22.9           7.64
#>  3     2 United States of America  1818         23.6     16.0   22.9           7.64
#>  4     2 United States of America  1819         23.7     16.0   23.0           7.66
#>  5     2 United States of America  1820         23.7     16.1   23.0           7.66
#>  6     2 United States of America  1821         23.8     16.1   23.1           7.68
#>  7     2 United States of America  1822         23.8     16.1   23.1           7.70
#>  8     2 United States of America  1823         23.8     16.1   23.1           7.69
#>  9     2 United States of America  1824         23.9     16.2   23.2           7.69
#> 10     2 United States of America  1825         23.9     16.2   23.3           7.72
#> # … with 16,916 more rows

create_stateyears(system = "gw") %>% add_sdp_gdp()
#> Joining, by = c("gwcode", "year")
#> # A tibble: 18,463 × 7
#>    gwcode statename                 year wbgdp2011est wbpopest sdpest wbgdppc2011est
#>     <dbl> <chr>                    <dbl>        <dbl>    <dbl>  <dbl>          <dbl>
#>  1      2 United States of America  1816         23.6     15.9   22.8           7.66
#>  2      2 United States of America  1817         23.6     16.0   22.8           7.64
#>  3      2 United States of America  1818         23.6     16.0   22.9           7.64
#>  4      2 United States of America  1819         23.7     16.0   22.9           7.66
#>  5      2 United States of America  1820         23.7     16.1   23.0           7.66
#>  6      2 United States of America  1821         23.8     16.1   23.0           7.68
#>  7      2 United States of America  1822         23.8     16.1   23.1           7.70
#>  8      2 United States of America  1823         23.8     16.1   23.1           7.69
#>  9      2 United States of America  1824         23.9     16.2   23.2           7.69
#> 10      2 United States of America  1825         23.9     16.2   23.2           7.72
#> # … with 18,453 more rows