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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Unknown - 3.4 MB - MD5: bd340a8b7c310c84b248a2555883711a
military burdens estimates
Gzip Archive - 17.1 MB - MD5: f289dba2a891de21881a9be85e6ee961
updated military expenditure estimates
Gzip Archive - 37.8 MB - MD5: b0c39226fe34c93e4771b402ce7db433
updated military expenditure estimates
Aug 1, 2024
Fariss, Christopher; Therese Anders; Jonathan Markowitz; Miriam Barnum, 2022, "Latent Estimates of Historic Gross Domestic Product, GDP per capita, Surplus Domestic Product, and Population Data Version 1", https://doi.org/10.7910/DVN/FALCGS, Harvard Dataverse, V2
Gross Domestic Product (GDP), GDP per capita, and population are central to the study of politics and economics broadly, and conflict processes in particular. Despite the prominence of these variables in empirical research, existing data lack historical coverage and are assumed to be measured without error. We develop a latent variable modeling fra...
Adobe PDF - 8.9 MB - MD5: 7d16ecba8537c04024afd7569efc42d2
Tabular Data - 57.5 MB - 12 Variables, 409680 Observations - UNF:6:W+2mlMI629Q8zjfzYLnQyg==
Tabular Data - 125.5 MB - 12 Variables, 904710 Observations - UNF:6:mQMI1oYSaB3fxEFBzDozMQ==
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