R/add_nmc.R

In peacesciencer: Tools and Data for Quantitative Peace Science Research

#' Add Correlates of War National Military Capabilities Data
#'
#' @description \code{add_nmc()} allows you to add the Correlates of War National Material Capabilities data to your data.
#'
#'
#' @return
#'
#' \code{add_nmc()} takes a (dyad-year, leader-year, leader-dyad-year, state-year) data frame and adds information
#' about the national material capabilities for the state or two states in the dyad in a given year.
#' If the data are dyad-year (or leader-dyad-year),
#' the function adds 12 total columns for the first state (i.e. \code{ccode1}) and the
#' second state (i.e. \code{ccode2}) for all estimates of national
#' military capabilities provided by the Correlates of War project. If the data are
#' state-year (or leader-year), the function returns six additional columns
#' to the original data that contain that same information for a given state in a given year.
#'
#' @details
#'
#'
#' 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.
#'
#' @author Steven V. Miller
#'
#' @param data a data frame with appropriate \pkg{peacesciencer} attributes
#'
#' @references
#'
#' Singer, J. David, Stuart Bremer, and John Stuckey. (1972).
#' "Capability Distribution, Uncertainty, and Major Power War, 1820-1965." in
#' Bruce Russett (ed) *Peace, War, and Numbers*, Beverly Hills: Sage, 19-48.
#'
#' Singer, J. David. 1987. "Reconstructing the Correlates of War Dataset on
#' Material Capabilities of States, 1816-1985."
#' *International Interactions* 14(1): 115-32.
#'
#'
#' @examples
#'
#' # just call `library(tidyverse)` at the top of the your script
#' library(magrittr)
#'
#' cow_ddy %>% add_nmc()
#'
#' create_stateyears() %>% add_nmc()
#'
#'
add_nmc <- function(data) {

  if (length(attributes(data)$ps_data_type) > 0 && attributes(data)$ps_data_type %in% c("dyad_year", "leader_dyad_year")) {

    if (!all(i <- c("ccode1", "ccode2") %in% colnames(data))) {

      stop("add_nmc() merges on two Correlates of War codes (ccode1, ccode2), which your data don't have right now. Make sure to run create_dyadyears() at the top of the pipe. You'll want the default option, which returns Correlates of War codes.")


    } else {

    data %>% left_join(., cow_nmc, by=c("ccode1"="ccode","year"="year")) %>%
      rename(milex1 = .data$milex,
             milper1 = .data$milper,
             irst1 = .data$irst,
             pec1 = .data$pec,
             tpop1 = .data$tpop,
             upop1 = .data$upop,
             cinc1 = .data$cinc) %>%
      left_join(., cow_nmc, by=c("ccode2"="ccode","year"="year")) %>%
      rename(milex2 = .data$milex,
             milper2 = .data$milper,
             irst2 = .data$irst,
             pec2 = .data$pec,
             tpop2 = .data$tpop,
             upop2 = .data$upop,
             cinc2 = .data$cinc) -> data

      return(data)

    }


  } else if (length(attributes(data)$ps_data_type) > 0 && attributes(data)$ps_data_type %in% c("state_year", "leader_year")) {

    if (!all(i <- c("ccode") %in% colnames(data))) {

      stop("add_nmc() merges on two Correlates of War codes (ccode1, ccode2), which your data don't have right now. Make sure to run create_dyadyears() at the top of the pipe. You'll want the default option, which returns Correlates of War codes.")


    } else {

    data %>%
      left_join(., cow_nmc) -> data

      return(data)

    }

  } else  {
    stop("add_nmc() requires a data/tibble with attributes$ps_data_type of state_year or dyad_year. Try running create_dyadyears() or create_stateyears() at the start of the pipe.")
  }



  return(data)
}