Publications
Peer-Reviewed Journal Articles
Measuring Arms: Introducing the Global Military Spending Dataset. (with Christopher J. Fariss, Jonathan N. Markowitz, and Gaea Morales). Journal of Conflict Resolution. OnlineFirst, February 2024.
Preprint --- Appendix --- Data
Military spending data measure key international relations concepts such as balancing, arms races, the distribution of power, and the severity of military burdens. Unfortunately, missing values and measurement error threaten the validity of existing findings. Addressing this challenge, we introduce the Global Military Spending Dataset (GMSD). GMSD collates new and existing expenditure variables from a comprehensive collection of sources, expands data coverage, and employs a latent variable model to estimate missing values and quantify measurement error. We validate the data and present new findings. First, correlations between economic surplus and military spending are currently higher than at any point in the last two-hundred years. Second, updating DiGiuseppe and Poast’s (2018) analysis, we find larger substantive effects. Specifically, we find that the (negative) effect of a democratic ally on military spending is three times larger, and the (positive) effect of an increase in GDP is five times larger than previously estimated.
New Estimates of Over 500 Years of Historic GDP and Population Data. (with Christopher J. Fariss, Therese Anders, and Jonathan N. Markowitz). Journal of Conflict Resolution, 66:3 (April 2022). p. 553 - 591.
Preprint --- Appendix --- Replication materials
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 framework that expands data coverage (1500 AD–2018 AD) 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. Expanded temporal coverage of estimates provides new insights about the relationship between development and democracy, conflict, repression, and health. We also demonstrate how to incorporate uncertainty in observational models. Results show that the relationship between repression and development is weaker than models that do not incorporate uncertainty suggest. Future extensions of the latent variable model can address other forms of systematic measurement error with new data, new measurement theory, or both.
Is the NPT Unravelling? Evidence from Text Analysis of Review Conference Statements. (with James Lo). Journal of Peace Research, 57:6 (December 2020), p. 740 - 751.
Preprint --- Appendix --- Replication materials
The Treaty on the Non-Proliferation of Nuclear Weapons (NPT) is a landmark international treaty that is widely regarded as a cornerstone of the global nuclear non-proliferation regime. However, pessimists point to a growing divergence of preferences between nuclear weapons states and non-nuclear weapons states as a precursor to the impending ‘unraveling of this vital piece of international law’. In this article, we test for evidence of preference divergence using statements from NPT review conferences, which are manifestos presenting each country’s position on the NPT. We measure preferences on the NPT using Wordfish, a method that is frequently used to estimate ideological preferences from election manifestos. Our measure estimates the latent positions of state actors along a ‘non-proliferation vs. disarmament’ dimension, and shows little evidence of growing preference divergence between the nuclear weapons states and non-nuclear weapons states. Thus, a significant premise underlying more pessimistic assessments of the NPT appears to be in doubt.