Remittance and financial inclusion in refugee migrants: inverse probability of treatment weighting using the propensity score

ABSTRACT

This paper investigates the impact on remittances on financial inclusion of refugee migrants. While financial inclusion is gaining traction in the humanitarian and development literature, the linkage with the potential to improve the wellbeing of refugees, who are part of an upward spiral in numbers, has not been tackled. We examine World Bank survey data of 1041 Syrian refugees, using the inverse probability of treatment weighting propensity score analysis (IPTW). The method minimises the influence of outliers and addresses unobservable and missing data biases, which can plague survey based data. We observe that common indicators of financial inclusion when applied to refugees, given their limited access to formal financial services, may introduce a bias as the informal financial sector and excluded formal financial sector services do contribute to inclusiveness. We adopt a broader protocol for our data, measuring financial inclusion through six metrics stemming from G20 proposals. Overall, there is an opportunity to deepen financial inclusion for refugees who receive or send remittances. The possibility of expanding the financial inclusion options, and for this to percolate through to greater social inclusion, proffers practical commercial steps and policy enabling actions.

KEYWORDS:

• Financial inclusion
• remittance
• refugees
• propensity score analysis
• inverse probability of treatment weighting

JEL CLASSIFICATION:

• G00
• G2
• G28
• F22

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ ‘The core essence of financial inclusion lies in its non-discriminatory principle that everyone, everywhere, should have access to essential financial services that are affordable and that meet their needs’ (Pistelli 2017).

² In statistical literature, four methods used for propensity score are: Covariate adjustment using propensity score; stratification or sub-classification on the propensity score, matching on the propensity score, and inverse probability of weighing.

³ Apart from that reverse causality or simultaneity can create endogeneity problem in the remittances and financial inclusion relationship. In the robustness section, using IV probit model we control reverse causality/simultaneity.

⁴ International tech firm Iris Guard has developed Iris Scanning technology. Once asylum seekers arrive in Jordan, their biometric data are collected, securely stored and encoded. The information can be used to give refugees an identity that is internationally recognised, and which can be used to access aid, banking, healthcare and other services.

⁵ In here, reported rebalance summary for significant outcome variables only.