‘It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.’
Sherlock Holmes, A Scandal in Bohemia
Abstract: In recent days, immigration is at the centre of the political debate. Nevertheless, opinions about this topic are too often founded in emotional claims rather than in formal evidence. This blog post, therefore, follows a detective approach to uncover the effects of immigration on a particular area, international trade. First, the evidence is collected and exposed in detail, later different theories and mechanisms that drive the evidence are discussed. The conclusion is that immigration fosters international trade by reducing trade costs due to immigrants’ knowledge of home-country markets, language, preferences, and business contacts.
Immigration and its effects in host societies is one of the most candent topics in European politics these days. In contrast to this open debate in the political sphere, there exists a tremendous consensus among academics regarding the effects of immigration. According to this consensus the general concerns and fears about immigration are, in the best case, overrated and often baseless.
In general, immigrants generate a positive aggregate economic impact on the host country. Examples of studies providing evidence of these claims are numerous and for the sake of brevity, only some are reproduced here. Immigration has an almost negligible effect on host country salaries and a positive effect on employment (Card, 2001; Peri and Sparber, 2009; Ottaviano and Peri, 2012; Cattaneo, Fiorio and Peri, 2014; Foged and Peri, 2015). Migrants contribute more in taxes and social contributions than they receive in individual benefits (Liebig and Mo, 2013). Finally, more immigration implies, in the long run, more income per capita, less poverty and unemployment and better educational outcomes (Sequeira, Nunn and Qian 2017; Rodríguez-Pose and von Berlepsch 2019).
However, this blog post will examine the effect of immigration in a very particular area, namely, international trade. To do so, the reader is invited to follow the same approach as to solve a mystery and, therefore, to be guided by the greatest detective of all times, Sherlock Holmes.
Following closely the science of deduction, this post starts by providing evidence obtained in different immigration cases worldwide. Only after evidence is presented, one can start thinking about theories and mechanisms behind the data. Finally, the post concludes.
Evidence: Does immigration affect trade?
The body of modern literature on the relation between immigration and trade started to grow in 1994 with the seminal paper written by Gould (Gould, 1994). In this paper, the author is the first to use modern empirical methods to study the effect of immigration on trade flows. Based on the data from the United States and its 47 trading partners during the years 1970 to 1986, he found positive results of immigration in trade flows, especially on exports from the US to the immigrants’ home countries.
Building on Gould’s work, many others have later explored this topic. Although this post will focus on three of the most influential studies, a more complete review can be found in Felbermayr et al. (2015) and is also summarized in Figure 1.
Evidence 1: Rauch and Trindade (2002)
In this paper, the authors study the impact of Chinese networks on trade among 63 countries. To do so, they first split the traded goods into two categories: differentiated and homogenous goods. A homogenous good is the kind of good that is similar everywhere and, thus, it is easy to obtain information thereon and have reference prices; differentiated goods, on the other hand, are goods whose prices can hardly express all the characteristics of the product and are difficult to assess.
The authors find that Chinese networks affect positively international trade in both types of goods, however, the percentage increase in bilateral trade attributable to Chinese networks is 63%-102% greater for the differentiated than homogenous goods. More importantly, this increase in trade is not only significant vis-à-vis China but also between two other countries that both host Chinese immigrants.
Evidence 2: Dunlevy (2006)
Dunlevy studies the impact of immigrants on the bilateral exports of the 50 American States to 87 trading partners. His results confirm the previous aforementioned findings by showing a positive and significant effect of immigration on exports. Moreover, Dunlevy expands the analysis further by conditioning the results on two other factors: corruption level at the destination country and language similarity with the US.
As regards the corruption level, he finds that, in general, it deters trade. Nevertheless, interestingly, the pro-trade effect of immigration grows bigger the more corrupt is the home country of the immigrants. As regards the language, the results are reversed. If the home language of the destination country is either English or Spanish, overall trade is higher and, in this case, the pro-trade effect of immigration is negligible, meaning that immigrants do not add to the already existing flows.
Evidence 3: Parsons and Venzina (2018)
Although previous evidence is suggestive, it is not conclusive due to endogeneity concerns . “Probably the biggest single concern related to much of the papers mentioned above is that the network variable (the stock or share of migrants) may be correlated to trade shocks. When this is the case, [the models] lead to biased and inconsistent results” (Felbermayr et al., 2015). The same authors signal three main sources of endogeneity. First, there might be reverse causality concerns: greater trade flows might cause greater immigration flows. Secondly, there might be omitted variables; immigration may be correlated with unobserved factors that also affect trade (Hanson, 2010). Finally, there might be a measurement error.
Felbermayr et al. continue by stating, “The most convincing way to address the endogeneity concern is to look for some exogenous events that cause variation in bilateral migration stocks but have no direct effect on bilateral trade”. This is exactly what Parsons and Venzina do. In their paper, the authors use a wave of immigration from Vietnam to the US upon the fall of Saigon in 1975 to be the first to establish a formal causal link between immigration and trade.
The immigration wave from Vietnam to the US started in April 1975 when, after the fall of Saigon, the US military evacuated 130,000 refugees from South Vietnam. After this first wave, more followed, and by 1994 more than 1.4 million Vietnamese had arrived in the US. The resettlement process of these migrants was quite chaotic due to the large amounts of people arriving. However, the main objective of the policymakers was to avoid a concentration of Vietnamese in a single state like Cubans in Florida. This resulted in a quite random spread of refugees among different states. At the same time and in parallel with this exodus, the US imposed a trade embargo on Vietnam that lasted until 1994. Finally, the data shows that, by 1994, a vast majority of migrants (or their descendants) remained in the state where they were assigned, thus, creating a perfectly exogenous distribution of immigrants across states .
The results of the paper show that US exports to Vietnam during the years after the embargo (1995-2010) were higher and more diversified in those states with a higher population of Vietnamese refugees. Furthermore, the data suggest that a 10% increase in the Vietnamese network raises exports to Vietnam by between 4.5% and 14%. These results are especially relevant for differentiated goods.
Mechanism: How does immigration foster trade?
Although every evidence presented can only be interpreted in its very own context and results are, in general, non-universal. Nevertheless, due to the amount and variety of literature, it seems quite clear that immigration helps to increase international trade. According to the literature, immigrants influence trade in two basic ways. The first mechanism is through preferences: immigrants like home-country goods and products, thus, they incentivize the host country imports of these goods (this mechanism can be seen in the black dots of figure 1). The second mechanism is through foreign market information: immigrants know better their home country, which helps to avoid some trade costs between host and home country related to a lack of reliable data.
There are different ways immigrants can help improve foreign market information. Firstly, immigrants have a better understanding of the particularities of doing business in their home markets, therefore, they bring useful information to better assess differentiated goods. A second channel is related to language costs, as learned from Dunlevy (2006), exports to countries that have similar languages are not affected by immigration, whereas, immigrants play an important role in trading with countries with high communication barriers. Finally, the last channel is through trust building. Very often, international trade is based on contracts for delivery and payment. These contracts, normally, are unable to cover every eventuality (known as partial contractibility issues). In this framework, immigrants who have ties with their homeland may help to reduce the cost for negotiating and enforcing these contracts. As Weidenbaum and Hughes (1996) argue, “if a business owner violates an agreement, he is blacklisted. This is far worse than being sued because the entire Chinese network will refrain from doing business with the guilty party”. Also, following Dunlevy’s (Dunlevy 2006) findings, this channel plays a crucial role when home and host country institutions are very different, as well as when immigrants’ home country is more corrupt.
Costs of immigration are too often exaggerated and benefits are often ignored. Nevertheless, when looking at the economic data, we find support for immigration in many areas, including international trade, which is often characterized by asymmetric information and partial contractibility issues. It is in this framework where importing and exporting businesses can make the best use of immigrants’ information and trust networks in their home countries to overcome these challenges.
Card, D. (2001), “Immigrant inflows native outflows, and the local labor market impacts of higher immigration” J. Labor Econ. 19, 22–64.
Cattaneo, D., et al. (2014), “What Happens to the Careers of European Workers When Immigrants “Take Their Jobs”?” Fondazione Eni Enrico Mattei (FEEM).
Dunlevy, J.A. (2006), “The influence of corruption and language on the pro-trade effect of immigrants: Evidence from the American states” Rev. Econ. Stat. 88 (1), 182–186.
Felbermayr, G., Grossmann, V. and Kohler, W. (2015). “Migration, international trade, and capital formation: cause or effect?” Handbook of the Economics of International Migration, vol. 1, pp. 913–1025.
Foged, M. and Peri, G. (2015), “Immigrants’ Effect on Native Workers: New Analysis on Longitudinal Data” IZA Discussion Paper No. 8961.
Gould, D.M. (1994) “Immigrant links to the home country: Empirical implications for U.S. bilateral trade flows” Rev. Econ. Stat. 76 (2), 302–316.
Hanson, G.H. (2010) “International migration and the developing world” Handbook of Development Economics, pp. 4363–4414, Chapter 66.
Liebig,T. and Mo, J. (2013), “The Fiscal Impact of Immigration in OECD Countries” International Migration Outlook 2013, OECD Publishing.
Ottaviano, G.I.P., Peri, G. (2012), “Rethinking the effect of immigration on wages” J. Eur. Econ. Assoc. 10 (1), 152–197.
Parsons, C and P L Vézina (2018), “Migrant Network and Trade: The Vietnamese Boat People as a Natural Experiment”Economic Journal 128(612).
Peri, G. and Chad, S. (2009) “Task Specialization, Immigration and Wages.” American Economic Journal: Applied Economics, 1(3): 135–169.
Rauch, J.E., Trindade, V. (2002) “Ethnic Chinese networks in international trade” Rev. Econ. Stat. 84 (1), 116–130.
Rodríguez-Pose, A. and von Berlepsch, V. (2019) “The missing ingredient: Distance. Internal migration and its long-term economic impact in the United States” Centre for Economic Policy Research.
Sequeira, S., Nunn N., Qian N. (2017) “Migrants and the Making of America: The Shortand Long-Run Effects of Immigration During the Age of Mass Migration,” ifo DICE Report, ifo Institute – Leibniz Institute for Economic Research at the University of Munich, vol. 15(3), pages 30-34.
Weidenbaum, M. and Samuel H. (1996) “The Bamboo Network” New York: The Free Press.
 Endogeneity arise when it is impossible or extremely difficult to assess the flow of causality. As an example, if a study wants to disentangle the effect of A (immigration) on B (trade flows) there are three cases: A causes B; B causes A; C causes both A and B. If cases 2 or 3 are plausible, it is said that the study suffers of endogeneity issues.
 Exogeneity is the reverse of endogeneity. In this paper, as refugees were resettled randomly among the US States, it is possible to rule out cases 2 and 3 (see Endnote 1) because immigration is a product of luck.