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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31 to 38 of 38 Results
Sep 24, 2021
Christopher Fariss; Therese Anders; Jonathan Markowitz; Miriam Barnum, 2021, "Replication Data for: New Estimates of Over 500 Years of Historic GDP and Population Data", https://doi.org/10.7910/DVN/DC0ING, Harvard Dataverse, V4
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...
Sep 22, 2021
Therese Anders; Jonathan Markowitz; Christopher Fariss, 2021, "Replication Data for: Bread before guns or butter: Introducing Surplus Domestic Product (SDP)", https://doi.org/10.7910/DVN/U8RVMU, Harvard Dataverse, V2
Scholars systematically mismeasure power-resources and military burdens by using GDP (Gross Domestic Product) as a proxy for the income states can devote to arming. The core problem is that GDP confounds two conceptually distinct forms of income into one additive indicator. Subsistence income represents resources needed to provide the “bread” neces...
ZIP Archive - 4.4 MB - MD5: bf82cc32a7fdeac29c80ee5cbd1c2cc0
Adobe PDF - 3.7 MB - MD5: 6799f4ac68f1297f81780e8a0728c485
Supplementary Appendix
ZIP Archive - 1.5 GB - MD5: 12cf9615a7f805986d145276047b0490
Replication files
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