Do Remittances Diminish Social Violence?

Abstract

This paper represents the first attempt to formalise the relationship between remittances and social violence by developing a model that predicts that migrants’ remittances lead to the reduction of social violence in the recipient economy under the condition that remittances increase the average product of labour. Using homicide data as an indicator of social violence, we tested our model’s prediction. Controlling for the endogeneity problem with appropriate instruments, we found that remittances tend to reduce social violence. We performed sensitivity analysis on remittances in the empirical specification and found it robust with an unchanged negative sign.

Disclosure statement

No potential conflict of interest was reported by the authors.

Acknowledgements

The replication data and codes can be obtained from the corresponding author. We thank Zulfan Tadjoeddin, Daniel Scheller and Steve Telless for useful comments on a previous version. We would like to acknowledge the helpful comments provided by two anonymous referees and participants at the 2014 Australasian Development Economics Workshop. Any remaining errors are our own.

Notes

1. Ratha (2009). Barajas, Chami, Fullenkamp, Gapen, and Montiel (2009) and Chami et al. (2008) have reported that during 2007, remittances through official channels were $300 billion in addition to unknown transfers through unofficial channels, which are estimated to be about 40 per cent of flows through the official channels.

2. Our comprehensive definition of social violence is provided in Section 2.

3. We have used the terms social violence and conflict interchangeably in the paper.

4. There is an ancient Bengali proverb ‘deprivation degrades human character and soul’.

5. Lindley (2009), using data from Somalia, showed that, compared to a peaceful setting, the sending of remittances is different in a conflict-afflicted area, although she did not formalise a connection between these two variables.

6. In terms of number of deaths, most countries have homicide rates that exceed the threshold of 1000 combat-related deaths during a year that is the standard criterion for civil war.

7. Krug, E., Dahlberg, L., Mercy J., Zwi A., & Lozano R, eds. (2002) World report on violence and health. Geneva: World Health Organisation.

8. Conflict here indicates high levels of violence and crime. According to data produced by the WHO, in 2002 there were approximately 170,000 war-related deaths but over 500,000 deaths due to interpersonal violence worldwide, while in 2004 the counts were 182,000 and 598,000, respectively (WHO, 2004, 2008).

9. Our study focuses on the W-158 sub-category labelled as ‘violence’ under ‘deaths caused by intentional injuries’, in WHO (2004, 2008), whereas there are two latest waves of WHO data (available for year 2000 and 2012), where ‘interpersonal violence’ is labelled as the second sub-category in ‘deaths caused by intentional injury’ and coded as GHE-162. We are unsure about the comparability of these two data sets, hence preferred to use the ‘violence’ data which have been reliably used in past studies. Our choice was also determined by data limitation on some of the control variables in our paper, mainly hybrid political regimes, which were unavailable beyond 2005.

10. Please refer to Online Appendix I for data definitions and sources.

11. Various studies have used different samples, estimation methods and specifications and identification strategies, which vary according to the data and objectives of the studies and their findings, are not strictly comparable. Given the nature of our data and research question, we have used the most appropriate instrumentation strategy. However, the instrumentation strategy that was adopted in this paper and in the remittances literature in general, differs from the same in related topics such as the aid and growth relationship explored in Rajan and Subramanian (2008). The main difference is that our data, being purely cross-sectional, enables the use of time-invariant geographic variables in addition to time varying economic variables as instruments. In Rajan and Subramanian (2008), the idea behind the instrumentation strategy was to exploit the noneconomic explanations for donor behaviour in giving aid to capture the exogenous variation, which was measured by the bilateral colonial relationship between donor and recipient countries. Remittances, on the other hand, involve a series of small private household-to-household transfers and do not possess any such donor-recipient relationship. With respect to the aid and corruption literature, Tavares (2003) instrumented aid by exploiting the bilateral characteristics of developing countries and OECD economies. This is a useful approach and the construction of our Instrument5 is similar to this method, but rather than using a specific group of OECD economies and bilateral data, we used the aggregate data.

12. Another potential instrument could have been the migration data compiled by Ozden, Parsons, Schiff, and Walmsley (2011) because remittances and migration tend to be highly correlated. Whilst this satisfies the ‘instrument relevance’ condition very well, it falls short of the ‘exclusion principle’ which requires migration to have no direct effect on violence except through remittances or other included regressors. This is clearly not so – emigration can directly lead to more or less violence being perpetrated, or can be caused by violence.

13. Please refer to Online Appendix II for descriptive statistics.

14. The death rate is given by: [(death/population)*100,000] = 2.06. Given that the average population in our sample is 38,979,770, the actual number of deaths is thus 802.98.

15. Please refer to Online Appendix IV to see the list of countries.

16. In order to check the robustness of the IV-LIML results we have obtained so far, we also took only a sub-set of instruments and carried out additional IV estimates by dropping individual instruments or sets of instruments. These results are reported in Table A1 of Online Appendix V. To make comparison easier, we first report the results with all six instruments, and then subsequently drop one or more instruments. The results with a sub-set of instruments are similar to those using all six instruments.

17. Please refer to the correlation matrix in Online Appendix III.

18. For a detailed technical discussion on extreme bounds analysis (EBA), please refer to Online Appendix VI.

19. EBA is one way to test for robustness. Robustness can also be checked by running one regression only, employing the general-to-simple (GETS) approach a obtain a parsimonious representation of the general unrestricted model (GUM), which is an approximation to the data generation process (DGP), where only the robust regressors are retained (Hendry & Krolzig, 2004). However, this methodology requires the use of the specialised software PcGETS to run the GETS algorithm from GUM to the specific model.

20. bKash – a company using mobile phone-based digital technology in Bangladesh – provides banking services such as paying bills or transferring money, to customers who do not have access to formal financial services (http://online.wsj.com/articles/gates-links-technology-banking-services-for-poor-1412299200).