Aid in Modulating the Impact of Terrorism on FDI: No Positive Thresholds, No Policy

Abstract

We investigate how foreign aid dampens the effects of terrorism on FDI using interactive quantile regressions. The empirical evidence is based on 78 developing countries for the period 1984–2008. Bilateral and multilateral aid variables are used, while terrorism dynamics entail: domestic, unclear, transnational and total number of terrorist attacks. The main finding is that foreign aid cannot be used as a policy tool to effectively address a hypothetically negative effect of terrorism on FDI. The positive threshold we cannot establish is important for policy makers because it communicates a cut-off point at which foreign aid completely neutralizes the negative effect of terrorism on FDI. From the conditioning information set, we also establish for the most part that the effects of GDP growth, infrastructural development and trade openness are an increasing function of FDI. Policy implications are discussed.

Keywords:

• FDI
• foreign aid
• terrorism
• quantile regression

JEL Classification:

• C52
• D74
• F23
• F35
• O40

Acknowledgements

The authors are indebted to the editor and reviewers for constructive comments. The authors are also indebted to Bandyopadhyay Subhayu (Federal Reserve Bank, St.Louis); Sandler Todd (University of Texas, Dallas) and Javed Younas (American University of Sharjah) for their benevolence in sharing their original dataset.

Notes

¹ The panel includes the following developing countries : “Albania, Costa Rica, India, Namibia, Syria, Algeria, Cote d’Ivoire, Indonesia, Nicaragua, Tanzania, Angola, Dominican Republic, Iran, Niger, Thailand, Argentina, Ecuador, Jamaica, Nigeria, Togo, Bahrain, Egypt, Jordan, Pakistan, Trinidad and Tobago, Bangladesh, El Salvador, Kenya, Panama, Tunisia, Bolivia, Ethiopia, Lebanon, Papua New Guinea, Turkey, Botswana, Gabon, Libya, Paraguay, Uganda, Brazil, Gambia, Madagascar, Peru, Uruguay, Burkina Faso, Ghana, Malawi, Philippines, Venezuela, Cameroon, Guatemala, Malaysia, Saudi Arabia, Vietnam, Chile, Guinea, Mali, Senegal, Yemen, China, Guinea-Bissau, Malta, Sierra Leone, Zambia, Colombia, Guyana ,Mexico, South Africa, Zimbabwe, Congo, D. Republic, Haiti, Morocco, Sri Lanka, Congo Republic, Honduras, Mozambique and Sudan”. It is important to note that some countries may be more developed than others (e.g. Malta). Unfortunately, we are employing a data-set from Bandyopadhyay et al. (2014) and are leaving it unchanged for the purpose of comparing our findings with those of the underlying study.

² Asiedu and Nandwa (2007), Johnson and Quartey (2009), Asiedu (2014) and Efobi, Beecroft, and Asongu (2014) consistently articulate the need to integrate foreign aid heterogeneity.

³ This assertion is based on the assumption that, in interactive regressions, the unconditional effects have a sign that is opposite to the sign of the conditional effects.