add_rugged_terrain: Add rugged terrain information to a data frame

In peacesciencer: Tools and Data for Quantitative Peace Science Research

Add rugged terrain information to a data frame

Description

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.

Usage

add_rugged_terrain(data)

Arguments

data	a data frame with appropriate peacesciencer attributes

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.

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.

Author(s)

Steven V. Miller

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

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

cow_ddy %>% add_rugged_terrain()

create_stateyears() %>% add_rugged_terrain()

create_stateyears(system = "gw") %>% add_rugged_terrain()

peacesciencer documentation built on March 31, 2023, 8:37 p.m.