Do Sanctions Constrain Military Spending of Iran?

ABSTRACT

Do sanctions reduce military spending in Iran? To answer this question, we use annual data from 1960 to 2017 and the autoregressive distributed lag (ARDL) model. We show that an increase in the intensity of sanctions is associated with a larger decrease in military spending in both the short and the long run. Each level of increase in the intensity of sanctions with respect to our coding approach decreases military spending in the long run by approximately 33%, ceteris paribus. We also find that only the multilateral sanctions, in which the United States acts in conjunction with other countries to sanction Iran, have a statistically significant and negative impact on military spending of Iran in both the short and the long run. Multilateral sanctions reduce Iran’s military spending by approximately 77% in the long run, ceteris paribus. The results remain robust when controlling for other determinants of military spending such as gross domestic product (GDP), oil rents, trade openness, population, quality of political institutions, military expenditure of the Middle East region, non-military spending of government and the war period with Iraq.

KEYWORDS:

• Sanctions
• military spending
• Iran
• ARDL
• JCPOA

JEL CLASSIFICATION:

• D74
• F51
• Q34
• H56
• N45

Acknowledgments

We thank helpful comments and suggestions of the Editor (Christos Kollias), two anonymous referees and participants at the Toyo-Marburg Workshop (Tokyo, 2018) and the 6th International Conference on the Iranian Economy (Naples, 2019).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The full transcript of Trump’s speech on the Iran Nuclear Deal is available at: https://www.nytimes.com/2018/05/08/us/politics/trump-speech-iran-deal.html .

2. For more details see https://www.bbc.com/news/world-middle-east-45634448 .

3. Farzanegan (2014b) shows that marginalized small business sector is characteristic of oil-based economies.

4. http://www.worldbank.org/en/news/feature/2014/06/23/theorist-eric-maskin-globalization-is-increasing-inequality .

5. For more details see government defense anti-corruption initiative of Transparency International: https://government.defenceindex.org/#intro .

6. http://unscr.com/en/resolutions/661 .

7. http://unscr.com/en/resolutions/687 .

8. http://unscr.com/en/resolutions/1483 .

9. http://unscr.com/en/resolutions/1546 .

10. The regression coefficient on a logarithmic variable can be interpreted as an elasticity, that is, as the rate of the percentage change in the dependent variable for each 1% change in the independent variable.

11. The World Bank reports the military expenditures (% of GDP) data from the Stockholm International Peace Research Institute (SIPRI). The SIPRI database is the most up-to-date database on global military spending refreshed annually, which are derived from the NATO definition. The reported military spending is not including civil defense and current expenditures for previous military activities, such as for veterans’ benefits, demobilization, conversion, and destruction of weapons.

12. We re-examined our estimations by including a dummy variable for the period when Iran’s army intervened in Dhafor war (from 1972 to 1975; see Hughes 2017). The coefficient for this dummy is insignificant both in the long and the short run. Indeed, one of the mentioned aims for Iran’s army to intervene in Dhafor war was to train its military forces and test its previously purchased advanced armaments on the ground (Pace 1976).

13. The first kinds of these post-revolution sanctions were the order of President Carter to freeze Iranian assets in US banks on 14 November 1979.

14. According to the ADF test, Lmx is stationary in its level also at 5% confidence level.

15. Our dependent variable in regression analysis is the log of military spending. The multilateral sanction is a dummy variable. It takes the value of 1 if sanctions are multilaterally imposed (period of 2006–2015) and zero otherwise. The estimated coefficient for the multilateral sanction dummy variable is −1.5. If we shift from unilateral sanction to multilateral one (from 0 to 1), then the negative effect on military spending is (exponential value of (−1.5) −1)*100 which is approximately 77%. See Dizaji (2018b) and Hufbauer and Oegg (2003) for similar perspectives regarding the interpretation of sanction dummy variables.

16. We have also applied the cumulative sum of recursive residuals (CUSUM) and the cumulative sum of squares of the recursive residuals (CUSUMSQ) tests to test for parameter constancy. The findings indicate that the estimated coefficients are stable. These results are available upon request.

17. Using the share of military spending in GDP is especially more common in cross-country estimations. It has a couple of advantages such as ‘comparability across countries, no need to deal with inflation and deflators or with exchange rate conversions into a common currency’ (for a detailed discussion on this issue, see Brauer 2002).

18. The regression for the underlying ARDL equations fits very well and passes the diagnostic tests against serial correlation, functional form misspecification, and non-normal errors. It failed the heteroscedasticity test at 5% in both models. However, according to Shrestha and Chowdhury (2005), ‘since the time series constituting the ARDL equation are potentially of mixed order of integration, i.e., I(0) and I(1), it is sometimes natural to detect heteroscedasticity’. In addition, when analyzing the stability of the long-run coefficients together with the short-run dynamics, the cumulative sum (CUSUM) and the cumulative sum of squares (CUSUMQ), point to the in-sample stability of both models. These results are available upon request.

19. We have also re-estimated the model using the post-revolution period (1980–2017). The results still show that economic sanctions have negative impacts on Iran’s military burden. Additionally, more comprehensive sanctions lead to higher contracting pressure put on Iran’s military burden. The US unilateral sanctions cannot reduce Iran’s military burden, yet they may motivate Iran’s government to pay more attention to strengthening its military forces. The sign of the coefficients for sanctions variables in the short run are similar to those in the long run. However, in the post-revolution estimation period, we cannot reject the existence of serial correlations among the residuals.

20. These results are available upon request.

Additional information

Funding

Sajjad F. Dizaji appreciates the Gerda Henkel Foundation financial support (Award Number AZ 05/KF/18; Project Title: Economic Sanctions and conflict Resolution within Special Program Security, Society and the State) during his visiting research at the CNMS, University of Marburg.