Latent variable datasets for Gross Domestic Product (GDP), GDP per capita, Surplus Domestic Product, and population. The latent variable modeling framework that expands data coverage (1500 A.D--present) and, by making use of multiple indicators for each variable, provides a principled framework to estimate uncertainty for values for all country-year variables relative to one another. Surplus domestic product (SDP) decomposes subsistence income and surplus income from total GDP. Military expenditure latent variable estimates are also now available.
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Jan 30, 2024
Miriam Barnum; Christopher J. Fariss; Jonathan N. Markowitz; Gaea Morales, 2024, "Replication Data for: Measuring Arms: Introducing the Global Military Spending Dataset", https://doi.org/10.7910/DVN/RKJAKJ, Harvard Dataverse, V1
Agreement between observed country-year-variable values (orange boxes) and the posterior predicted point estimates for which the observed value is observed (light grey boxes). Dark grey boxes show the distribution for the full range of the posterior predicted point estimates (including estimates for which the original value is missing). Across all...
Adobe PDF - 8.9 MB - MD5: 483208e0ff4f1f20a555566c484ee2e1
Supplementary Appendix
Adobe PDF - 1.6 MB - MD5: c9a99c6b4f8ad9d17e8647c873bfa9f3
pre print of manuscript
ZIP Archive - 1.5 GB - MD5: a4cf3b675054fae84961bf5004937d7f
replication files
Gzip Archive - 16.9 MB - MD5: 2186bc80478db0aae2a62c8c94759c6b
Gzip Archive - 37.3 MB - MD5: 803b032c9e1b9de99be381787dabb1d1
Gzip Archive - 17.9 MB - MD5: b1faa8634a868929df024717bfcadf57
Gzip Archive - 39.6 MB - MD5: 18ab7f17469efaa55a53613578a1757c
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