cow_sdp_gdp: (Surplus and Gross) Domestic Product for Correlates of War...

cow_sdp_gdpR Documentation

(Surplus and Gross) Domestic Product for Correlates of War States

Description

These are state-year level data for surplus and gross domestic product for Correlates of War state system members. Data also include population estimates for per capita standardization.

Usage

cow_sdp_gdp

Format

A data frame with 27753 observations on the following five variables.

ccode

a numeric vector for the Correlates of War state code

year

a numeric vector for the year

wbgdp2011est

a numeric vector for the estimated natural log of GDP in 2011 USD (log-transformed)

wbpopest

a numeric vector for the estimated population size (log-transformed)

sdpest

a numeric vector for the estimated surplus domestic product (log-transformed)

wbgdppc2011est

a numeric vector for the estimated GDP per capita (log-transformed)

Details

These were extracted from the actual replication files from International Studies Quarterly. Because these data are ultimately being simulated, a user can expect some slight differences between the Correlates of War version of these data (which Anders et al. published) and the Gleditsch-Ward version of these data (which appear to be the one the authors will more vigorously support going forward).

Space considerations compel me to round these data to three decimal points. These "economic" data are routinely the biggest in the package, and it's because of the decimal points. The justification for this is these data are estimated/simulated anyways and the information loss is at the 1/1000th decimal point. This procedure basically cuts the size of the data to be less than 25% of its original size. The original simulations are available for remote download if you'd like. Type ?download_extdata() for more information.

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.


peacesciencer documentation built on March 24, 2022, 5:06 p.m.