Abstract
With a view toward two purposes, the article examines measures of United States military expenditure. It first discusses what types of data would be most suitable for the analysis of the economic burden of such expenditure and it explains, second, why existing databases with U.S. (and global) military expenditure coverage have limited validity, and therefore utility, for the first purpose. The article advances the concepts of minimal and maximal augmented military expenditure measures to better capture the full economic resource burden imposed on an economy than do the presently available measures. The difference of current measures to the proposed augmented measures is not primarily one of an intercept change but mostly of a slope change. The article claims that, by fiscal year 2018, the economic burden imposed by military expenditure on the U.S. economy when using the augmented measures is about double the size of the burden as measured by all of the currently available measures. Since, to date, most empirical work on the effects of military expenditure on economies tends to rely on inappropriate measures, misleading findings may have resulted.
Highlights
Extensive theoretical and statistical literatures have developed which theorize, measure, and analyze countries’ military expenditure and their economic causes and effects, if any
Inferential statistical analysis of any hypothesized relation between military spending and economic growth depends on a number of validity concepts among which are construct validity and content validity, the notions that (1) a measure used in an empirical setup should equal, or well correspond to, its theoretical companion construct and (2) that a measure should correspond to all facets of a given construct, not a selection thereof
Even the Bureau of Economic Analysis (BEA)’s National Income and Product Accounts (NIPA) numbers violate content validity as they still capture only a selection of the economic resources devoted to the U.S military sector so that further adjustments to the data are required before their use in empirical economic analysis
Summary
577.4 128.2 705.6 states’ self-submitted data, based on states’ agency budgets adjusted to fit UNODA’s rather than. NIPA’s NDCE number, Outlays (NDO) functional budget line item 050 is broader than that is, National Defense Consumption Expenditure, which for that of the DOD agency alone and exceeds the DOD- FY2017 comes in at USD555.8 billion, includes a depreciation related functional line item 051. BEA’s NIPA numbers include pensions and pension contributions (see Ludwick and Branklin, 2018, Table 4) but exclude the whole of the budget of the Department of Veterans Affairs (DVA) from the computation of national defense consumption and gross investment expenditure (NDCGIE). Later on I will comment on the size of the “add-in” when producing Augmented NIPA numbers.) if hiring a soldier in the year 1970 includes or implies a contractual promise to provide pension and health care benefits in the year 2018, the actual 2018 spending fulfills the promise made and is to be counted as military expenditure in terms of the use of total economic resources available to government in 2018.
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