R/rd-african_coups.R

In stevedata: Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics

#' @importFrom tibble tibble
NULL

#' Modeling Coups in Africa, 1960 to 1975 (1982)
#'
#' A data set on modeling coups in Africa using data from the period between
#' 1960 and 1975 (1982). These data offer a partial replication of Jackman
#' (1978).
#'
#' @format A data frame with the following 11 variables.
#' \describe{
#' \item{\code{iso3c}}{a three-character ISO code for state identification}
#' \item{\code{country}}{an English country name}
#' \item{\code{jci}}{Jackman's (1978) coup index from 1960 to 1975}
#' \item{\code{tmis}}{Johnson et al.'s (1984) total military involvement score}
#' \item{\code{agperc}}{an estimate of the percentage of the country's labor force in agriculture and animal husbandry}
#' \item{\code{indperc}}{an estimate of the percentage of the country's labor force in industry}
#' \item{\code{literacy_cnts}}{an estimate of countrywide literacy from around 1965}
#' \item{\code{literacy_ba}}{another estimate of countrywide literacy from around 1965}
#' \item{\code{leperc}}{an estimate of the size of the largest ethnic group, as a percentage}
#' \item{\code{partydom}}{the percentage of the vote received by the largest party in the country prior to independence}
#' \item{\code{turnout}}{the turnout (as a percentage) at the independence referendum}
#' }
#'
#' @details
#'
#' Data exist for instructional purposes, especially about modeling interactions.
#' Reading Jackman (1978) and Johnson et al. (1984) will provide more information
#' about the data and hypotheses. There was a follow-up symposium on this in
#' 1986 in \emph{American Political Science Review} that may be an interesting
#' read and provide even more context about what's at stake in this debate.
#'
#' English country names are country names from around the time of publication.
#' Take note of older names of "Dahomey", "Swaziland", "Upper Volta", and "Zaire."
#' The three-character ISO codes are current, mostly for ease of doing other
#' things with the data. However, this comes with the acknowledgment that
#' Dahomey and Zaire used to have different ISO codes under their older names.
#' Both codes for Dahomey (`DHY`) and Zaire (`ZAR`) were retired in 1977 and
#' 1997, respectively.
#'
#' Ideally, I'd have Morrison's (1972) \emph{Black Africa}, but I do not. I have
#' a copy of a 1989 update, though. That's what I consulted in constructing
#' this data set.
#'
#' Jackman (1978) is deceptively opaque on what he's doing for the ethnic group
#' variable and arguably misleads on what his turnout variable is actually from.
#' In the case of the ethnic group variable, it's the difference between saying
#' the largest ethnic group in Rwanda is 98% of the population versus 80% of
#' the population. In short, it's the difference of saying whether there are
#' any Tutsi at all in the country. Basically, I'm uncertain with what he's
#' doing with what Morrison et al. (1989) define as "ethnic clusters".
#'
#' Related: the agricultural variable is a midway point between columns B and
#' columns C in Table 3.11 of Morrison et al. (1989). I do not think this is too
#' far removed from what Jackman was looking at in an older version of the same
#' data, but there will be slight differences. It's the difference of "these
#' variables came from 1966" versus "this is an interpolation of 1960 to 1970".
#' The latter is what I offer here. I can only do so much.
#'
#' To continue this theme of the opacity in trying to reconstruct the data,
#' Jackman (1978, p. 1265) says his social mobilization index incorporates the
#' percentage of the labor force that is not employed in agriculture. The
#' summary statistics he provides in fn. 4 on p. 1265 are consistent with this,
#' at least (for the most part) in this reconstruction of the data. However,
#' other statistical results and other language from Jackman are consistent with
#' him using the percentage of the labor force that is employed in industry.
#' This is not a trivial distinction either. Using the percentage of the
#' country's labor force in industry would, in a literal sense, not strictly
#' be "the simple sum of the percentage of the labor force in nonagricultural
#' occupations". It would exclude those working in service industries. The
#' data provide the opportunity to use either the industrial percentage variable
#' or to manually create a non-agricultural labor force percentage variable as
#' the difference between 100 and the agricultural labor force percentage
#' variable. It makes the most sense to do the latter. The industry percentage
#' variable comes from Table 3.14 in Morrison et al. (1989) and is likewise a
#' midway point between 1960 and 1970.
#'
#' Mercifully, the coup variables come from a replication by Johnson et al.
#' (1984). Based on Morrison et al.'s (1989) updated data, it's not clear how
#' Jackman could've derived some of these estimates using the formula he said
#' he used. For example, Benin should have a score of 39 based on the
#' information in Table 2.10 (p. 373 in Morrison et al. (1989)). Cameroon should
#' have a 1 and not a 2, per Table 5.10 (p. 399). My comments here work under
#' the assumption that Morrison et al. are adding information and not revising
#' information in the second edition of the \emph{Black Africa} handbook.
#'
#' To be more precise, both the Jackman coup index and total military involvement
#' variables are directly copied from Table 2 in Johnson et al. (1984) on p. 627.
#' Missingness in the Jackman coup index variable communicates the country was
#' not included in his original study, but was included in the Johnson et al.
#' replication.
#'
#' The literacy variables have suffices communicating where I obtained them. The
#' Cross-National Time Series Database has a variable effectively communicating
#' this information that I was using first in trying to recreate these data.
#' These data come from 1965 in that data set. Jackman and Johnson et al. are
#' assuredly using Morrison's almanac. That information is in Table 4.11 of
#' Morrison et al. (1989), though it's possible the estimates contained therein
#' are slightly different than what was reported in the first edition. I cannot
#' know for sure.
#'
#' Ethiopia is conspicuously missing in the party dominance variable. That's by
#' design, and apparently its omission warranted ample discussion both by
#' Jackman (1978) and Johnson et al. (1984). Johnson et al. (1984, fns. 4,5)
#' argue it's a curious choice that can situationally influence the results that
#' Jackman reports, but there are also lots of other choices made by Jackman
#' (1978) that can influence these results.
#'
#' I am 99.9% sure the turnout variable is Table 5.9 in Morrison et al. (1989).
#' Jackman (1978) says this is from *before* independence but I'm confident he
#' meant it was the turnout at the independence referendum.
#'
#' @references
#'
#' Jackman, Robert W. 1978. "The Predictability of Coups d'etat: A Model with
#' African Data." \emph{American Political Science Review} 72(4): 1262-75.
#'
#' Jackman, Robert W., Rosemary H. T. O'Kane, Thomas H. Johnson, Pat McGowan,
#' and Robert O. Slater. 1986. "Explaining African Coups d'Etat."
#' \emph{American Political Science Review} 80(1): 225-49.
#'
#' Johnson, Thomas H., Robert O. Slater, and Pat McGowan. 1984. "Explaining
#' African Military Coups d'Etat, 1960-1982." \emph{American Political Science
#' Review} 78(3): 622-40.
#'
#' Morrison, Donald George, Robert Cameron Mitchell, and John Naber Paden. 1989.
#' \emph{Black Africa: A Comparative Handbook} (2nd ed.). New York, NY: The Free
#' Press.

"african_coups"