Do immigrants import terrorism?

Abstract

The relationship between immigration and terrorism is an important public policy concern. Using bilateral migration data for 170 countries from 1990 to 2015, we estimate the relationship between levels of immigration and terrorism using an instrumental variables (IV) strategy based on the decades prior stocks of immigrants in destination countries. We specifically investigate rates of immigration from Muslim majority countries and countries involved in armed conflicts. We find no relationship between immigration and terrorism, whether measured by the number of attacks or victims, in destination countries.

Introduction

Greater immigration flows have the potential to significantly reduce global poverty and increase the size of the world’s economy (Clemens, 2011). Although many people in the public fear that gains to the immigrants come at the expense of the economic welfare of the native population, economists generally find these fears are mistaken (Powell, 2015). Global free trade in labor (immigration), like free trade in goods, enriches citizens from both countries engaged in the exchange. But, immigrants aren’t just workers, they are people too (Borjas, 2016). Thus, unlike goods that cross borders, they can make their own decisions outside of the labor market that impact destination countries in other ways. Does letting in more immigrant workers increase the risk of letting in terrorists? Might immigrant workers, who become dissatisfied with life in their new country, turn to terrorism? Thus, is securing the economic gains from greater immigration associated with also incurring the cost of higher rates of terrorism? If so, perhaps the economic benefits of greater immigration might not be worth the increased costs. This paper empirically investigates the relationship between immigration and terrorism and is thus tied to two evolving literatures: one literature on the non-narrowly defined economic impacts of immigration on destination countries and a second literature on the causes of terrorism.

Borjas, 2014, Borjas, 2015 challenged the literature claiming that liberalized immigration would boost global economic output by tens of trillions of dollars. He pointed out that the models economists used to estimate these gains all relied on the institutions and social norms that regulate economic exchange in destination countries remaining intact after immigrants arrive en masse. He writes, “What would happen to the institutions and social norms that govern economic exchanges in specific countries after the entry/exit of perhaps hundreds of millions of people” (Borjas, 2015, p. 961)? In his recent book he succinctly states the problem and the state of our knowledge about it:

For immigration to generate substantial global gains, it must be the case that billions of immigrants can move to the industrialized economies without importing the “bad” institutions that led to poor economic conditions in the source countries in the first place. It seems inconceivable that the North’s infrastructure would remain unchanged after the admission of billions of new workers. Unfortunately, remarkably little is known about the political and cultural impact of immigration on the receiving countries, and about how institutions in these receiving countries would adjust to the influx (Borjas, 2014, p. 169).

Borjas (2015) models a variety of scenarios showing how the economic gains from immigration can decrease or turn negative depending on how much they erode the productivity in destination countries by importing their inferior social capital, however, he offers no empirical evidence that this importation does, in fact, take place. A small but growing literature has developed attempting to empirically assess these fears.

Ortega and Peri (2014) and Clemens and Pritchett (2016) examine how immigration directly impacts productivity. Another series of papers examines whether immigration undermines formal institutions of economic freedoms that are correlated with greater productivity. Clark et al. (2015) examine how immigration impacted economic freedom in a cross section of countries and Padilla and Cachanosky (2018) examine the relationship across U.S. states. Powell et al. (2017) and Nowrasteh et al. (2019) take advantage of natural experiments in Israel and Jordan, respectively, and use a synthetic control methodology to study how exogenous mass influxes of immigrants impacted economic freedom and other institutions in destination countries. Finally, Bologna-Pavlik et al. (2019) examine how immigration has impacted corruption across a cross-section of countries. Overall, these papers find little support for Borjas’ fears and often, find evidence that immigration improves institutions in destination. However, there are alternative channels through which immigrants could reduce the expected gains from immigration in destination countries. The spread of terrorism is one such channel.

Terrorism is the intentional and indiscriminate use of violence by private actors that is intended to create terror in the public at large to achieve a political, religious, or ideological aim (Fortna, 2015). Terrorism is intrinsically difficult to study as the number of terrorist attacks is small, the common ideologies and political aims of terrorists change over time, and there are many potential factors that could convince a person to become a terrorist. To help deal with these challenges, we empirically examine the general relationship between immigration and terrorism from 1990 to 2015. This period of observation is obviously of the greatest policy relevance. We also narrow our focus to better examine immigration from Muslim majority countries and countries engaged in conflicts, both of which are relevant after President Trump imposed a temporary ban on Muslim immigrants and traveler from particular Muslim countries and those riven by conflict (Executive Order No. 13769, 82 Fed. Reg. 8977, Executive Order No. 13780, 82 Fed. Reg. 13209). Finally, we engage the literature on factors that are related to terrorism to establish our control variables.