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The Elgar Companion to Public Economics

Empirical Public Economics

Edited by Attiat F. Ott and Richard J. Cebula

Attiat Ott and Richard Cebula have recognised the need to present, in an accessible and straightforward way, the voluminous literature in the public economics arena. Advances in econometric techniques and the spillover of knowledge from other disciplines made it difficult, not only for students but also for lecturers, to accurately find the information they need.
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Chapter 11: Defense Expenditure and Economic Growth: Evidence from Cross-Country Panel Data

Rati Ram


Rati Ram* Introduction The relation between defense (military) spending and economic growth has attracted the attention of numerous scholars since Benoit’s (1973) finding of a positive association between the two.1 Ram (1995, pp. 255–7) listed many studies up to the mid-1990s that sought to refine or extend Benoit’s work. He also indicated (p. 257) the main refinements and extensions undertaken by various scholars. Dunne (1996) provided another review of the literature. Of course, many studies have appeared since the reviews by Ram (1995) and Dunne (1996). These consist of single-country research using time-series methodology and a few multicountry studies in cross-section or panel-data format. Although it is difficult to make a simple summarizing statement about the relation between defense spending and economic growth indicated by this more recent research, it seems the predominant pattern does not suggest a significant positive or negative association between the two variables.2 The main motivation for the present chapter is provided by the consideration that while there are many recent single-country studies that indicate a somewhat ambiguous and variable pattern, and several cross-section estimates can also be found, there is a limited amount of panel-data research that includes a large number of countries and covers a substantial period after the Cold War. As is well known, single-country studies are constrained by a relatively small number of observations that limit the usefulness of timeseries procedures. Moreover, in the absence of a large number of such studies, it is difficult to...

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