Immigration and GDP nexus: is the association asymmetric?

The association between economic growth and immigration has been a long-time debatable area among economists. Yet, the asymmetric connection stays somewhat ignored area in this strand of the literature. The investigation of a nonlinear and asymmetric relationship between economic growth and immigration is motivated by empirical insights. The structural change and resulted nonlinear behavior in the real GDP per capita and immigration series is due to idiosyncratic shocks in data. Events such as the global financial crisis (2008–2009), Asian currency crisis (1997–98), Dot-com bubble burst (2001), and sudden extreme events (terrorist attack on September 11, 2001) can cause structural breaks in the series and exhibit nonlinear behavior. Thus, in this paper we examine the asymmetric association of the immigration-GDP per capita nexus via utilizing the nonlinear autoregressive distributed lag model (NARDL). The asymmetric influence of GDP was generated by the disintegrations of GDP into positive and negative changes. The paper finds evidence of long-run relationship (cointegration), using annual data from 1947- 2018. The empirical analysis presents verification of long- and short-run asymmetric effect. The paper finds that positive shocks of real GDP per capita affects immigration, while no such effect is found for the negative changes, both in the short- and long-run. Finally, the vector error correction model (VECM) illustrates significant long-and short-run unidirectional causality running from positive change of GDP per capita to immigration. However, the VECM model suggests a significant long-run bidirectional causality between immigration and GDP per capita decrease.