“Armaments and Economic Performance”. The literature on military expenditure (milex) is scrutinized with respect to five areas. Investment is reduced when milex increases. Most studies have found economic growth hindered by higher milex. No clear association between milex and employment is found. However, the same amount of other public expenditure creates more jobs. There is some evidence for milex as counter-cyclical instrument in the US. The result for studies if milex is used in electoral cycles in the US is contradictory. Disaggregated data are emphasized as a possible solution to get more definite results.
“The Economic Costs of Civil Wars”. The empirical studies of the economic costs of internal armed conflicts are divided into accounting and modelling methods. Cost is seen as the difference between the counterfactual production without conflict and the actual production. The average economic cost of internal armed conflict is a 3.7% yearly reduction of GDP. There are large differences between the estimates. One of the reasons for pursuing such studies is to give improved basis for more cost-effective post-conflict reconstruction, which is better achieved with an accounting method.
“War and Economic Performance – Different Data, Different Conclusions?” This article studies the importance of armed conflict for economic growth by replicating an earlier analysis with new data on conflicts. The basic model investigates how conflicts in 1960-1974 affect economic growth in 1975-1989. Koubi finds that “wars are conducive to higher growth”. Koubi’s finding is confirmed when different conflict data is used in a similar research design.
“The Role of External Factors in Economic Growth: A Comparative Analysis of Thailand and the Philippines 1950-1990”. Can differences in economic performance be explained by external factors? Both historical and regression analyses are utilised to answer the question. Three external factors are analysed: International trade, foreign direct investment, and external debt. In the regression analysis none of the external factors qualify as statistically significant. The historical analysis finds two external factors discriminating between the two countries. Thus, they might explain the differing growth rates of Thailand and the Philippines: Manufactured exports and external debt.