International Migration and Economic Integration
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International Migration and Economic Integration

Understanding the Immigrant–Trade Link

Roger White and Bedassa Tadesse

This essential volume examines the influence of immigrants on the process of international economic integration – specifically, their influences on bilateral and multilateral trade flows. It extends beyond the identification and explanation of the immigrant–trade link and offers a more expansive treatment of the subject matter, making it the most comprehensive volume of its kind. The authors present abundant evidence that confirms the positive influences of immigrants on trade between their home and host countries; however the immigrant–trade link may not be universal. The operability of the link is found to depend on a variety of factors related to immigrants’ home countries, their host countries, the types of goods and services being traded and the anthropogenic characteristics of the immigrants themselves.
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Roger White and Bedassa Tadesse


CHAPTER 3 1. 2. 3. 4. 5. Price (1996) notes that birthplace origins are not the same as ethnic origins. We acknowledge this and, due to data constraints, proceed cautiously employing country of birth as representative of ethnic origin. Section 3.5 provides a list of nations in the data set identified by White Australia Policy association. Section 3.5 lists the 1-digit SITC sectors. If j = k, internal distance is the square root of the country’s mass times 0.4 (Head and Mayer, 2000). We follow Wooldridge (2002) and test for autocorrelation and heteroskedasticity in the panel data. Both Wooldridge and Breusch-Pagan tests, respectively, reject (at p > 0.001) the null hypotheses of no autocorrelation and the homoskedastic panels assumption. Since we have time-invariant country characteristics, the use of fixed effects regression is ruled out. Thus, we select FGLS as our estimation strategy. We also use the panel-corrected standard errors (PCSE) technique for estimating variances as an alternative estimation strategy to check the robustness of our findings (see section 3.2.1 for details). The liberal classification lists 12.28 percent of industries as producing organized exchange goods, while the conservative classification identifies 17.83 percent. A test of difference in means yields a t-statistic of 3.79. No significant differences are found across classifications for differentiated or referenced-priced products. We chose to forego use of the Tobit specification in the primary estimations as it is possible that a level of zero imports and/or exports is natural for some countries; especially so for disaggregate trade values. For each...

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