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download_extdata() leverages R's inst directory flexibility to allow you to download some extra data and store it in the package.

Usage

download_extdata(overwrite = FALSE)

Arguments

overwrite

logical, defaults to FALSE. If FALSE, the function checks to see if you've already downloaded the data and, if you already have, it does nothing. If TRUE, the function redownloads the data.

Value

download_extdata() downloads some extra data stored on my website (http://svmiller.com) and sticks them in the extdatadirectory in the package.

A Description of Various Data Sets This Will Download

Running download_extdata() returns the following data that will be stored in the package's extdata directory.

Correlates of War Dyadic Trade Data Set (v. 4.0)

These are directed dyad-year-level data for dyadic trade from the Correlates of War project. The trade values presented here have been rounded to three decimal points to conserve space. The data downloaded by this function are about 4.1 megabytes in size.

COLUMNDESCRIPTION
ccode1a numeric vector for the Correlates of War state code for the first state
ccode2a numeric vector for the Correlates of War state code for the second state
yearthe year
flow1imports of ccode1 from ccode2, in current million USD
flow2imports of ccode2 from ccode1, in current million USD
smoothflow1smoothed flow1 values
smoothflow2smoothed flow2 values

Directed Leader Dyad-Year Data, 1870-2015 (CoW States)

These are all directed leader dyad-year data from 1870-2015. Data come from the Archigos data (version 4.1). The data are standardized to just those observations where both leaders and states appear in the CoW state system data. The data downloaded by this function are about 2 megabytes in size.

COLUMNDESCRIPTION
yearthe year
obsid1the unique Archigos (v. 4.1) observation ID for the first leader
obsid2the unique Archigos (v. 4.1) observation ID for the second leader
ccode1a numeric vector for the Correlates of War state code for the first state
ccode2a numeric vector for the Correlates of War state code for the second state
gender1the gender of obsid1 ("M" or "F")
gender2the gender of obsid2 ("M" or "F")
leaderage1the approximate age (i.e. year - yrborn) for obsid1 in the year
leaderage2the approximate age (i.e. year - yrborn) for obsid2 in the year
yrinoffice1a running count for the tenure of obsid1, starting at 1.
yrinoffice2a running count for the tenure of obsid2, starting at 1.

Directed Leader Dyad-Year Data, 1870-2015 (Gleditsch-Ward States)

These are all directed leader dyad-year data from 1870-2015. Data come from the Archigos data (version 4.1). The data represent every possible dyadic leader-pairing in the Archigos data (which is denominated in the Gleditsch-Ward system), but standardizes leader dyad-years to Gleditsch-Ward state system dates. The data downloaded by this function are about 2.2 megabytes in size.

COLUMNDESCRIPTION
yearthe year
obsid1the unique Archigos (v. 4.1) observation ID for the first leader
obsid2the unique Archigos (v. 4.1) observation ID for the second leader
gwcode1a numeric vector for the Gleditsch-Ward state code for the first state
gwcode2a numeric vector for the Gleditsch-Ward state code for the second state
gender1the gender of obsid1 ("M" or "F")
gender2the gender of obsid2 ("M" or "F")
leaderage1the approximate age (i.e. year - yrborn) for obsid1 in the year
leaderage2the approximate age (i.e. year - yrborn) for obsid2 in the year
yrinoffice1a running count for the tenure of obsid1, starting at 1.
yrinoffice2a running count for the tenure of obsid2, starting at 1.

Chance-Corrected Measures of Foreign Policy Similarity (FPSIM, v. 2)

The FPSIM data set provides measures of foreign policy similarity of dyads based on alliance ties (Correlates of War, version 4.1) and UN General Assembly voting (Voeten, version 17) for all members of the Correlates of War state system. The alliance data cover the time period from 1816 to 2012, and the UN voting data from 1946 to 2015. The similarity measures include various versions of Ritter and Signorino's S (weighted/non-weighted by material capabilities; squared/absolute distance metrics) as well as the chance-corrected measures Cohen's (1960) kappa and Scott's (1955) pi. The measures based on alliance data come in two versions: one is based on valued alliance ties and the other is based on binary alliance ties. Data were last updated on December 7, 2017, and this description was effectively plagiarized (with his blessing) from Frank Haege's Dataverse.

These data are directed dyad-years with 17 columns and 1,872,198 observations. They will almost certainly be the largest data set I nudge/ask you to download remotely. The file containing this information is 18.6 MB in size. To reduce size further, these decimal points have also been rounded to three spots.

Haege generated all estimates of dyadic foreign policy similarity, except for the taub column. That was generated separately, by me.

COLUMNDESCRIPTION
yearthe year
ccode1the Correlates of War state code for the first state
ccode2the Correlates of War state code for the second state
taubTau-b (valued alliance data)
srsvasunweighted S (squared distances, valued alliance data)
srswvasweighted S (squared distances, valued alliance data)
srsvaaunweighted S (absolute distances, valued alliance data)
srswvaaweighted S (absolute distances, valued alliance data)
kappavaKappa (squared distances, valued alliance data)
pivaPi (squared distances, valued alliance data)
srsbaUnweighted S (binary alliance data)
srswbaWeighted S (binary alliance data)
kappabaKappa (binary alliance data)
pibaPi denominator (binary alliance data)
srsvvsUnweighted S (squared distances, valued UN voting data)
srsvvaUnweighted S (absolute distances, valued UN voting data)
kappavvKappa (squared distances, valued UN voting data)
pivvPi (squared distances, valued UN voting data)

(Non-Directed) Dyadic Minimum Distance Data Plus (CoW States)

These are non-directed dyadic minimum distance data from Schvitz et al. (2022) for all Correlates of War states from the start of 1886 to the end of 2019. Note that I call these "data plus", with the idea of informally branding these as a kind of augmentation of what you might otherwise do with the cshapes package. This data set has over 4.4 million rows for each dyadic minimum distance for all available years. Within each year, there is a recorded minimum distance for Jan. 1, June 30, Dec. 31 and, in addition, any day within the year where the composition of the international system (or shape of a state) changed, as recorded in cshapes. Sometimes these changes concern the dyadic minimum distance; sometimes they don't. For example, the League of Nations is responsible for a lot shape changes (i.e. system entry) in the CoW state system data in the year 1920. That obviously won't change the dyadic minimum distance between the U.S. and Canada, which will always be zero. Sometimes the start of the year (Jan. 1), the midpoint of the year (June 30), or the end of the year (Dec. 31) coincides with a system change. Often it doesn't. Note that a referent day (Jan. 1, June 30, Dec. 31) may not appear in a given year for a given dyad if that date exists outside CoW state system membership. For example, Canada doesn't appear as a state system member until Jan. 10, 1920. The goal of this data set is allow you to more quickly generate dyadic minimum distances within peacesciencer's functionality if you are proficient in tidyverse verbs. You could also use it to highlight how often the dyadic minimum distance may vary within a year for a given dyad.

Despite the dimensions of the data set, it's not too big of a download. The data are about 1.7 MB in size.

COLUMNDESCRIPTION
ccode1the Correlates of War state code for the first state
ccode2the Correlates of War state code for the second state
yearthe year
datea date, coinciding with either a system change date or a referent day (i.e. Jan. 1, June 30, Dec. 31)
change_datea date that, when present, indicates the shape of the system changed on that day
mindistthe dyadic minimum distance (in kilometers)

(Non-Directed) Dyadic Minimum Distance Data Plus (G-W States)

These are non-directed dyadic minimum distance data from Schvitz et al. (2022) for all Gleditsch-Ward states from the start of 1886 to the end of 2019. Note that I call these "data plus", with the idea of informally branding these as a kind of augmentation of what you might otherwise do with the cshapes package. This data set has over 3.7 million rows for each dyadic minimum distance for all available years. Within each year, there is a recorded minimum distance for Jan. 1, June 30, Dec. 31 and, in addition, any day within the year where the composition of the international system (or shape of a state) changed, as recorded in cshapes. Sometimes these changes concern the dyadic minimum distance; sometimes they don't. For example, the dissolution of the Soviet Union is responsible for a lot shape changes (i.e. system entry) in 1991. That obviously won't change the dyadic minimum distance between the U.S. and Canada, which will always be zero. Sometimes the start of the year (Jan. 1), the midpoint of the year (June 30), or the end of the year (Dec. 31) coincides with a system change. Often it doesn't. Note that a referent day (Jan. 1, June 30, Dec. 31) may not appear in a given year for a given dyad if that date exists outside G-W state system membership. For example, Haiti disappears from the state system on July 4, 1915 and reappears on Aug. 15, 1934. That means there won't be any dyadic minimum distance observations with the U.S., for example, on Dec. 31, 1915 or June 30, 1934. The goal of this data set is allow you to more quickly generate dyadic minimum distances within peacesciencer's functionality if you are proficient in tidyverse verbs. You could also use it to highlight how often the dyadic minimum distance may vary within a year for a given dyad.

Despite the dimensions of the data set, it's not too big of a download. The data are about 1.4 MB in size.

COLUMNDESCRIPTION
gwcode1the Gleditsch-Ward state code for the first state
gwcode2the Gleditsch-Ward state code for the second state
yearthe year
datea date, coinciding with either a system change date or a referent day (i.e. Jan. 1, June 30, Dec. 31)
change_datea date that, when present, indicates the shape of the system changed on that day
mindistthe dyadic minimum distance (in kilometers)

References

Barbieri, Katherine, Omar M. G. Keshk, and Brian Pollins. 2009. "TRADING DATA: Evaluating our Assumptions and Coding Rules." Conflict Management and Peace Science. 26(5): 471-491.

Goemans, Henk E., Kristian Skrede Gleditsch, and Giacomo Chiozza. 2009. "Introducing Archigos: A Dataset of Political Leaders" Journal of Peace Research 46(2): 269--83.

Haege, Frank. 2011. "Choice or Circumstance? Adjusting Measures of Foreign Policy Similarity for Chance Agreement." Political Analysis 19(3): 287-305.

Schvitz, Guy, Luc Girardin, Seraina Ruegger, Nils B. Weidmann, Lars-Erik Cederman, and Kristian Skrede Gleditsch. 2022. "Mapping The International System, 1886-2017: The CShapes 2.0 Dataset." Journal of Conflict Resolution. 66(1): 144-161.

Weidmann, Nils B. and Kristian Skrede Gleditsch. 2010. "Mapping and Measuring Country Shapes: The cshapes Package." The R Journal 2(1): 18-24.

Author

Steven V. Miller

Examples


if (FALSE) {
# Here's where the data are going to be downloaded.
system.file("extdata", package="peacesciencer")
# Now, let's download the data.
download_extdata()
}