Political instability and services of GCC banks: how important is the Yemen War?

Purpose - The purpose of this paper is to examine the impact of the Yemen War on banking services (deposits and loans) at the aggregate and at the level of conventional and Islamic banks in GCC countries. The author also tests hypotheses of direct and indirect impacts of the Yemen War on bank services. Design/methodology/approach - The sample comprises a total of 70 banks (45 conventional and 25 Islamic banks) over the period 2000–2018. The static and dynamic panel generalized methods of moments (GMM) estimation techniques are applied. Findings - Empirical results indicate that the Yemen War has a significant negative direct impact on deposits and loans of GCC banks. The results lend support for the direct channel hypothesis, but not for the indirect channel hypothesis. The negative direct impact is most prominent on banks in GCC countries that are directly involved in the Yemen War, although the war has an asymmetric effect on conventional and Islamic banks, the former being more vulnerable. The overall conclusion is that the Yemen War exerts an asymmetric impact on the GCC region, across both banks and countries. Practical implications - These results are a warning to policymakers to be cautious when formulating a strategy for macroeconomic stability. Originality/value - It is widely recognized that the Yemen War has a significant impact on the economies of the GCC countries. However, the possible impact of the war on GCC bank services has not so far been subjected to robust empirical analysis. This paper therefore seeks to fill this gap by providing an in-depth quantitative analysis of this impact. It distinguishes between direct and indirect channels through which the Yemen War may affect bank services. It is also the first to examine the asymmetric impact of the Yemen War on the GCC region, across both banks (Islamic and conventional banks) and countries (whether or not involved in the war). The study uses both static panel and dynamic panel GMM estimation techniques to analyze the data.