add_rugged_terrain() allows you to add information, however crude,
about the "ruggedness" of a state's terrain to your (dyad-year, leader-year, leader-dyad-year, state-year) data.
Value
add_rugged_terrain() takes a (dyad-year, leader-year, leader-dyad-year, state-year)
data frame, whether the primary state identifiers are from the Correlates of War
system or the Gleditsch-Ward system, and returns information about the
"ruggedness" of the state's terrain. The two indicators returned are the
"terrain ruggedness index" calculated by Nunn and Puga (2012) and a logarithmic
transformation of how mountainous the state is (as calculated by Gibler and Miller, 2014).
The dyad-year (leader-dyad-year) data get four additional columns (i.e. both indicators for both states
in the dyad) whereas the state-year data get just the two additional columns.
Details
Please see the information for the underlying data rugged, and the
associated R script in the data-raw directory, to see how these data are generated.
Importantly, these data are time-agnostic and move slowly. We're talking about geography here.
Both data sets benchmark around 1999-2000 and it's a leap of faith to use these data for comparisons
across the entirety of the Correlates of War or Gleditsch-Ward system membership. Every use of data
of these types have been either cross-sectional snapshots or for making state-to-state comparisons
after World War II (think of your prominent civil war studies here). Be mindful about what you expect
to get from these data.
The underlying data have both Gleditsch-Ward codes and Correlates of War codes. The merge it makes depends
on what you declare as the "master" system at the top of the pipe (e.g.. in create_dyadyears() or
create_stateyears()). If, for example, you run create_stateyears(system="cow") and follow
it with add_gwcode_to_cow(), the merge will be on the Correlates of War codes and not the Gleditsch-Ward
codes. You can see the script mechanics to see how this is achieved.
References
Fearon, James D., and David Laitin, "Ethnicity, Insurgency, and Civil War" American Political Science Review 97: 75–90.
Gibler, Douglas M. and Steven V. Miller. 2014. "External Territorial Threat, State Capacity, and Civil War." Journal of Peace Research 51(5): 634-646.
Nunn, Nathan and Diego Puga. 2012. "Ruggedness: The Blessing of Bad Geography in Africa." Review of Economics and Statistics. 94(1): 20-36.
Riley, Shawn J., Stephen D. DeGloria, and Robert Elliot. 1999. "A Terrain Ruggedness Index That Quantifies Topographic Heterogeneity,” Intermountain Journal of Sciences 5: 23–27.
Examples
# \donttest{
# just call `library(tidyverse)` at the top of the your script
library(magrittr)
cow_ddy %>% add_rugged_terrain()
#> # A tibble: 2,139,270 × 7
#> ccode1 ccode2 year rugged1 newlmtnest1 rugged2 newlmtnest2
#> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 2 20 1920 1.07 3.21 0.775 2.80
#> 2 2 20 1921 1.07 3.21 0.775 2.80
#> 3 2 20 1922 1.07 3.21 0.775 2.80
#> 4 2 20 1923 1.07 3.21 0.775 2.80
#> 5 2 20 1924 1.07 3.21 0.775 2.80
#> 6 2 20 1925 1.07 3.21 0.775 2.80
#> 7 2 20 1926 1.07 3.21 0.775 2.80
#> 8 2 20 1927 1.07 3.21 0.775 2.80
#> 9 2 20 1928 1.07 3.21 0.775 2.80
#> 10 2 20 1929 1.07 3.21 0.775 2.80
#> # ℹ 2,139,260 more rows
create_stateyears() %>% add_rugged_terrain()
#> Joining with `by = join_by(ccode)`
#> # A tibble: 17,121 × 5
#> ccode statenme year rugged newlmtnest
#> <dbl> <chr> <int> <dbl> <dbl>
#> 1 2 United States of America 1816 1.07 3.21
#> 2 2 United States of America 1817 1.07 3.21
#> 3 2 United States of America 1818 1.07 3.21
#> 4 2 United States of America 1819 1.07 3.21
#> 5 2 United States of America 1820 1.07 3.21
#> 6 2 United States of America 1821 1.07 3.21
#> 7 2 United States of America 1822 1.07 3.21
#> 8 2 United States of America 1823 1.07 3.21
#> 9 2 United States of America 1824 1.07 3.21
#> 10 2 United States of America 1825 1.07 3.21
#> # ℹ 17,111 more rows
create_stateyears(system = "gw") %>% add_rugged_terrain()
#> Joining with `by = join_by(gwcode)`
#> # A tibble: 18,637 × 5
#> gwcode statename year rugged newlmtnest
#> <dbl> <chr> <int> <dbl> <dbl>
#> 1 2 United States of America 1816 1.07 3.21
#> 2 2 United States of America 1817 1.07 3.21
#> 3 2 United States of America 1818 1.07 3.21
#> 4 2 United States of America 1819 1.07 3.21
#> 5 2 United States of America 1820 1.07 3.21
#> 6 2 United States of America 1821 1.07 3.21
#> 7 2 United States of America 1822 1.07 3.21
#> 8 2 United States of America 1823 1.07 3.21
#> 9 2 United States of America 1824 1.07 3.21
#> 10 2 United States of America 1825 1.07 3.21
#> # ℹ 18,627 more rows
# }