well empirically and is better at developing an understanding where nations
are involved in conflict (Batchelor, Dunne and Lamb, 2002). Other studies have followed models which incorporate political, economic and military factors in determining military expenditure.
The latter models have, however, tended to perform well empirically for developing countries. This is especially true with more comprehensive analyses (Batchelor, Dunne and Lamb, 2002). Dunne and Perlo-Freeman (2003) found that in developing countries, significant variables varied markedly in importance across countries. The authors further suggest that a focus on panel analyses foregoes the benefit of understanding dynamic processes within countries. Nikolaidou (2008) found alack of uniformity in the determinants of military expenditure among 15 countries in the European Union. The author also notes that a distinction between short-term and long-term determinants could prove beneficial. Panel
approaches have mixed results, however, there does seem to be consensus on the importance and complexity of the country-specific elements that determine military expenditure. Country and region- specific literature will prove helpful in better understanding the South African context of military expenditure. However, there is still pertinent theory suggested in various panel approaches which may still generally applicable.
Abdelfattah
et al. (2014) examined the case study of Egypt and found a positive association with the Israel’s lagged military burden and negative associations with output and net exports. Tambudzai (2011) looked at the determinants of military expenditure in Zimbabwe and followed a qualitative analysis by integrating findings from informal interviews and document analysis. The author highlights the value of incorporating internal historical and political dynamics alongside econometric analyses of the topic and found that factors such as corruption and regime security greatly affected the demand for military spending (in the Zimbabwean context. In the South African context, Batchelor, Dunne and Lamb (2002) found South Africa’s military burden to bean autoregressive function and highlighted strategic factors as conditions. The authors found negative impacts in the UN embargo and the change in regime and positive impacts in South Africa’s involvement n the Angolan War and the early years of the republic. The general demand approach used in this study was later adapted by Oladotun (2019), also in the South African context but from 1970 to 2017. This author further specified the general model
to include GDP per capita, population growth rate, the trade balance as a share of GDP as well as other factors social, political and economic factors. It was
found that the trade balance, democracy index, external threats and inflations rates significantly determined South Africa’s military expenditure.
Dunne, Perlo-Freeman and Smith (2008) suggest that in panel and cross-sectional analyses, it maybe more beneficial to exclude the notion of an arms race. Rather, the authors suggest that the aggregate military spending of Potential Enemies and the aggregate military spending of the security web may serve as good variable proxies for threat perception. The security web is defined to include all neighbours and security- allies (Dunne,
Perlo-Freeman and Smith, 2008). Ina panel study of 120 countries, including South Africa, Gupta, de Mello and Sharan (2000) confirm that corruption is associated with increased military expenditure. Thus, it may prove beneficial to account fora measure
of corruption in the analysis, especially in the South African context. One should note that this can be difficult to account for, as the Corruption Perceptions Index (CPI) would be a reliable indicator but records only date back to 1995. Generally, Kumar (2017) suggests an extensive range of possible determinants
for defence spending, outlined in the Appendix. This includes many previously mentioned factors but may prove helpful in investigating further variable inclusions.
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